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Sample records for surface emg signal

  1. Identification of contaminant type in surface electromyography (EMG) signals.

    PubMed

    McCool, Paul; Fraser, Graham D; Chan, Adrian D C; Petropoulakis, Lykourgos; Soraghan, John J

    2014-07-01

    The ability to recognize various forms of contaminants in surface electromyography (EMG) signals and to ascertain the overall quality of such signals is important in many EMG-enabled rehabilitation systems. In this paper, new methods for the automatic identification of commonly occurring contaminant types in surface EMG signals are presented. Such methods are advantageous because the contaminant type is typically not known in advance. The presented approach uses support vector machines as the main classification system. Both simulated and real EMG signals are used to assess the performance of the methods. The contaminants considered include: 1) electrocardiogram interference; 2) motion artifact; 3) power line interference; 4) amplifier saturation; and 5) additive white Gaussian noise. Results show that the contaminants can readily be distinguished at lower signal to noise ratios, with a growing degree of confusion at higher signal to noise ratios, where their effects on signal quality are less significant.

  2. Active Finger Recognition from Surface EMG Signal Using Bayesian Filter

    NASA Astrophysics Data System (ADS)

    Araki, Nozomu; Hoashi, Yuki; Konishi, Yasuo; Mabuchi, Kunihiko; Ishigaki, Hiroyuki

    This paper proposed an active finger recognition method using Bayesian filter in order to control a myoelectric hand. We have previously proposed a finger joint angle estimation method based on measured surface electromyography (EMG) signals and a linear model. However, when we estimate 2 or more finger angles by this estimation method, the estimation angle of the inactive finger is not accurate. This is caused by interference of surface EMG signal. To solve this interference problem, we proposed active finger recognition method from the amplitude spectrum of surface EMG signal using Bayesian filter. To confirm the effectiveness of this recognition method, we developed a myoelectric hand simulator that implements proposed recognition algorithm and carried out real-time recognition experiment.

  3. Nonstationary harmonic modeling for ECG removal in surface EMG signals.

    PubMed

    Zivanovic, Miroslav; González-Izal, Miriam

    2012-06-01

    We present a compact approach for mitigating the presence of electrocardiograms (ECG) in surface electromyographic (EMG) signals by means of time-variant harmonic modeling of the cardiac artifact. Heart rate and QRS complex variability, which often account for amplitude and frequency time variations of the ECG, are simultaneously captured by a set of third-order constant-coefficient polynomials modulating a stationary harmonic basis in the analysis window. Such a characterization allows us to significantly suppress ECG from the mixture by preserving most of the EMG signal content at low frequencies (less than 20 Hz). Moreover, the resulting model is linear in parameters and the least-squares solution to the corresponding linear system of equations efficiently provides model parameter estimates. The comparative results suggest that the proposed method outperforms two reference methods in terms of the EMG preservation at low frequencies. PMID:22453600

  4. ECG Artifact Removal from Surface EMG Signal Using an Automated Method Based on Wavelet-ICA.

    PubMed

    Abbaspour, Sara; Lindén, Maria; Gholamhosseini, Hamid

    2015-01-01

    This study aims at proposing an efficient method for automated electrocardiography (ECG) artifact removal from surface electromyography (EMG) signals recorded from upper trunk muscles. Wavelet transform is applied to the simulated data set of corrupted surface EMG signals to create multidimensional signal. Afterward, independent component analysis (ICA) is used to separate ECG artifact components from the original EMG signal. Components that correspond to the ECG artifact are then identified by an automated detection algorithm and are subsequently removed using a conventional high pass filter. Finally, the results of the proposed method are compared with wavelet transform, ICA, adaptive filter and empirical mode decomposition-ICA methods. The automated artifact removal method proposed in this study successfully removes the ECG artifacts from EMG signals with a signal to noise ratio value of 9.38 while keeping the distortion of original EMG to a minimum. PMID:25980853

  5. Simulation of surface EMG signals generated by muscle tissues with inhomogeneity due to fiber pinnation.

    PubMed

    Mesin, Luca; Farina, Dario

    2004-09-01

    Surface electromyographic (EMG) signal modeling has important applications in the interpretation of experimental EMG data. Most models of surface EMG generation considered volume conductors homogeneous in the direction of propagation of the action potentials. However, this may not be the case in practice due to local tissue inhomogeneities or to the fact that there may be groups of muscle fibers with different orientations. This study addresses the issue of analytically describing surface EMG signals generated by bi-pinnate muscles, i.e., muscles which have two groups of fibers with two orientations. The approach will also be adapted to the case of a muscle with fibers inclined in the depth direction. Such muscle anatomies are inhomogeneous in the direction of propagation of the action potentials with the consequence that the system can not be described as space invariant in the direction of source propagation. In these conditions, the potentials detected at the skin surface do not travel without shape changes. This determines numerical issues in the implementation of the model which are addressed in this work. The study provides the solution of the nonhomogenous, anisotropic problem, proposes an implementation of the results in complete surface EMG generation models (including finite-length fibers), and shows representative results of the application of the models proposed.

  6. Discrimination of Combined Motions for Prosthetic Hands Using Surface EMG Signals

    NASA Astrophysics Data System (ADS)

    Ibe, Ayuko; Gouko, Manabu; Ito, Koji

    The present paper proposes a multiple step discrimination method to determine single and combined movements intended by an amputee from surface electromyogram (EMG) signals. Most previous approaches to the discrimination of movement using EMG signals have been restricted to single joint movements. Our approach enables the amputee's intended movement to be determined from among four single and two combined limb functions using an initial rise zone 125 msec long. Experiments with ten subjects and four electrodes demonstrated that our proposal determines six forearm movements at a discrimination rate exceeding than 90%.

  7. Real-time intelligent pattern recognition algorithm for surface EMG signals

    PubMed Central

    Khezri, Mahdi; Jahed, Mehran

    2007-01-01

    Background Electromyography (EMG) is the study of muscle function through the inquiry of electrical signals that the muscles emanate. EMG signals collected from the surface of the skin (Surface Electromyogram: sEMG) can be used in different applications such as recognizing musculoskeletal neural based patterns intercepted for hand prosthesis movements. Current systems designed for controlling the prosthetic hands either have limited functions or can only be used to perform simple movements or use excessive amount of electrodes in order to achieve acceptable results. In an attempt to overcome these problems we have proposed an intelligent system to recognize hand movements and have provided a user assessment routine to evaluate the correctness of executed movements. Methods We propose to use an intelligent approach based on adaptive neuro-fuzzy inference system (ANFIS) integrated with a real-time learning scheme to identify hand motion commands. For this purpose and to consider the effect of user evaluation on recognizing hand movements, vision feedback is applied to increase the capability of our system. By using this scheme the user may assess the correctness of the performed hand movement. In this work a hybrid method for training fuzzy system, consisting of back-propagation (BP) and least mean square (LMS) is utilized. Also in order to optimize the number of fuzzy rules, a subtractive clustering algorithm has been developed. To design an effective system, we consider a conventional scheme of EMG pattern recognition system. To design this system we propose to use two different sets of EMG features, namely time domain (TD) and time-frequency representation (TFR). Also in order to decrease the undesirable effects of the dimension of these feature sets, principle component analysis (PCA) is utilized. Results In this study, the myoelectric signals considered for classification consists of six unique hand movements. Features chosen for EMG signal are time and time

  8. A novel approach for removing ECG interferences from surface EMG signals using a combined ANFIS and wavelet.

    PubMed

    Abbaspour, Sara; Fallah, Ali; Lindén, Maria; Gholamhosseini, Hamid

    2016-02-01

    In recent years, the removal of electrocardiogram (ECG) interferences from electromyogram (EMG) signals has been given large consideration. Where the quality of EMG signal is of interest, it is important to remove ECG interferences from EMG signals. In this paper, an efficient method based on a combination of adaptive neuro-fuzzy inference system (ANFIS) and wavelet transform is proposed to effectively eliminate ECG interferences from surface EMG signals. The proposed approach is compared with other common methods such as high-pass filter, artificial neural network, adaptive noise canceller, wavelet transform, subtraction method and ANFIS. It is found that the performance of the proposed ANFIS-wavelet method is superior to the other methods with the signal to noise ratio and relative error of 14.97dB and 0.02 respectively and a significantly higher correlation coefficient (p<0.05). PMID:26643795

  9. Fast generation model of high density surface EMG signals in a cylindrical conductor volume.

    PubMed

    Carriou, Vincent; Boudaoud, Sofiane; Laforet, Jeremy; Ayachi, Fouaz Sofiane

    2016-07-01

    In the course of the last decade, fast and qualitative computing power developments have undoubtedly permitted for a better and more realistic modeling of complex physiological processes. Due to this favorable environment, a fast, generic and reliable model for high density surface electromyographic (HD-sEMG) signal generation with a multilayered cylindrical description of the volume conductor is presented in this study. Its main peculiarity lies in the generation of a high resolution potential map over the skin related to active Motor Units (MUs). Indeed, the analytical calculus is fully performed in the frequency domain. HD-sEMG signals are obtained by surfacic numerical integration of the generated high resolution potential map following a variety of electrode shapes. The suggested model is implemented using parallel computing techniques as well as by using an object-oriented approach which is comprehensive enough to be fairly quickly understood, used and potentially upgraded. To illustrate the model abilities, several simulation analyses are put forward in the results section. These simulations have been performed on the same muscle anatomy while varying the number of processes in order to show significant speed improvement. Accuracy of the numerical integration method, illustrating electrode shape diversity, is also investigated in comparison to analytical transfer functions definition. An additional section provides an insight on the volume detection of a circular electrode according to its radius. Furthermore, a large scale simulation is introduced with 300MUs in the muscle and a HD-sEMG electrode grid composed of 16×16 electrodes for three constant isometric contractions in 12s. Finally, advantages and limitations of the proposed model are discussed with a focus on perspective works. PMID:27183535

  10. Fast generation model of high density surface EMG signals in a cylindrical conductor volume.

    PubMed

    Carriou, Vincent; Boudaoud, Sofiane; Laforet, Jeremy; Ayachi, Fouaz Sofiane

    2016-07-01

    In the course of the last decade, fast and qualitative computing power developments have undoubtedly permitted for a better and more realistic modeling of complex physiological processes. Due to this favorable environment, a fast, generic and reliable model for high density surface electromyographic (HD-sEMG) signal generation with a multilayered cylindrical description of the volume conductor is presented in this study. Its main peculiarity lies in the generation of a high resolution potential map over the skin related to active Motor Units (MUs). Indeed, the analytical calculus is fully performed in the frequency domain. HD-sEMG signals are obtained by surfacic numerical integration of the generated high resolution potential map following a variety of electrode shapes. The suggested model is implemented using parallel computing techniques as well as by using an object-oriented approach which is comprehensive enough to be fairly quickly understood, used and potentially upgraded. To illustrate the model abilities, several simulation analyses are put forward in the results section. These simulations have been performed on the same muscle anatomy while varying the number of processes in order to show significant speed improvement. Accuracy of the numerical integration method, illustrating electrode shape diversity, is also investigated in comparison to analytical transfer functions definition. An additional section provides an insight on the volume detection of a circular electrode according to its radius. Furthermore, a large scale simulation is introduced with 300MUs in the muscle and a HD-sEMG electrode grid composed of 16×16 electrodes for three constant isometric contractions in 12s. Finally, advantages and limitations of the proposed model are discussed with a focus on perspective works.

  11. Muscle-fiber conduction velocity estimated from surface EMG signals during explosive dynamic contractions.

    PubMed

    Pozzo, M; Merlo, E; Farina, D; Antonutto, G; Merletti, R; Di Prampero, P E

    2004-06-01

    Muscle-fiber conduction velocity (CV) was estimated from surface electromyographic (EMG) signals during isometric contractions and during short (150-200 ms), explosive, dynamic exercises. Surface EMG signals were recorded with four linear adhesive arrays from the vastus lateralis and medialis muscles of 12 healthy subjects. Isometric contractions were at linearly increasing force from 0% to 100% of the maximum. The dynamic contractions consisted of explosive efforts of the lower limb on a sledge ergometer. For the explosive contractions, muscle-fiber CV was estimated in seven time-windows located along the ascending time interval of the force. There was a significant correlation between CV values during the isometric ramp and explosive contractions (R = 0.75). Moreover, CV estimates increased significantly from (mean +/- SD) 4.32 +/- 0.46 m/s to 4.97 +/- 0.45 m/s during the increasing-force explosive task. It was concluded that CV can be estimated reliably during dynamic tasks involving fast limb movements and that, in these contractions, it may provide important information on motor-unit control properties.

  12. Neural network committees for finger joint angle estimation from surface EMG signals

    PubMed Central

    Shrirao, Nikhil A; Reddy, Narender P; Kosuri, Durga R

    2009-01-01

    Background In virtual reality (VR) systems, the user's finger and hand positions are sensed and used to control the virtual environments. Direct biocontrol of VR environments using surface electromyography (SEMG) signals may be more synergistic and unconstraining to the user. The purpose of the present investigation was to develop a technique to predict the finger joint angle from the surface EMG measurements of the extensor muscle using neural network models. Methodology SEMG together with the actual joint angle measurements were obtained while the subject was performing flexion-extension rotation of the index finger at three speeds. Several neural networks were trained to predict the joint angle from the parameters extracted from the SEMG signals. The best networks were selected to form six committees. The neural network committees were evaluated using data from new subjects. Results There was hysteresis in the measured SMEG signals during the flexion-extension cycle. However, neural network committees were able to predict the joint angle with reasonable accuracy. RMS errors ranged from 0.085 ± 0.036 for fast speed finger-extension to 0.147 ± 0.026 for slow speed finger extension, and from 0.098 ± 0.023 for the fast speed finger flexion to 0.163 ± 0.054 for slow speed finger flexion. Conclusion Although hysteresis was observed in the measured SEMG signals, the committees of neural networks were able to predict the finger joint angle from SEMG signals. PMID:19154615

  13. Arm Orthosis/Prosthesis Movement Control Based on Surface EMG Signal Extraction.

    PubMed

    Suberbiola, Aaron; Zulueta, Ekaitz; Lopez-Guede, Jose Manuel; Etxeberria-Agiriano, Ismael; Graña, Manuel

    2015-05-01

    This paper shows experimental results on electromyography (EMG)-based system control applied to motorized orthoses. Biceps and triceps EMG signals are captured through two biometrical sensors, which are then filtered and processed by an acquisition system. Finally an output/control signal is produced and sent to the actuators, which will then perform the actual movement, using algorithms based on autoregressive (AR) models and neural networks, among others. The research goal is to predict the desired movement of the lower arm through the analysis of EMG signals, so that the movement can be reproduced by an arm orthosis, powered by two linear actuators. In this experiment, best accuracy has achieved values up to 91%, using a fourth-order AR-model and 100ms block length.

  14. A new method for the extraction and classification of single motor unit action potentials from surface EMG signals.

    PubMed

    Gazzoni, Marco; Farina, Dario; Merletti, Roberto

    2004-07-30

    It has been shown that multi-channel surface EMG allows assessment of anatomical and physiological single motor unit (MU) properties. To get this information, the action potentials of single MUs should be extracted from the interference EMG signals. This study describes an automatic system for the detection and classification of MU action potentials from multi-channel surface EMG signals. The methods for the identification and extraction of action potentials from the raw signals and for their clustering into the MUs to which they belong are described. The segmentation phase is based on the matched Continuous Wavelet Transform (CWT) while the classification is performed by a multi-channel neural network that is a modified version of the multi-channel Adaptive Resonance Theory networks. The neural network can adapt to slow changes in the shape of the MU action potentials. The method does not require any interaction of the operator. The technique proposed was validated on simulated signals, at different levels of force, generated by a structure based surface EMG model. The MUs identified from the simulated signals covered almost the entire recruitment curve. Thus, the proposed algorithm was able to identify a MU sample representative of the muscle. Results on experimental signals recorded from different muscles and conditions are reported, showing the possibility of investigating anatomical and physiological properties of the detected MUs in a variety of practical cases. The main limitation of the approach is that complete firing patterns can be obtained only in specific cases due to MU action potential superpositions.

  15. Age Related Differences in the Surface EMG Signals on Adolescent's Muscle during Contraction

    NASA Astrophysics Data System (ADS)

    Uddin Ahamed, Nizam; Taha, Zahari; Alqahtani, Mahdi; Altwijri, Omar; Rahman, Matiur; Deboucha, Abdelhakim

    2016-02-01

    The aim of this study was to investigate whether there are differences in the amplitude of the EMG signal among five different age groups of adolescent's muscle. Fifteen healthy adolescents participated in this study and they were divided into five age groups (13, 14, 15, 16 and 17 years). Subjects were performed dynamic contraction during lifting a standard weight (3-kg dumbbell) and EMG signals were recorded from their Biceps Brachii (BB) muscle. Two common EMG analysis techniques namely root mean square (RMS) and mean absolute values (MAV) were used to find the differences. The statistical analysis was included: linear regression to examine the relationships between EMG amplitude and age, repeated measures ANOVA to assess differences among the variables, and finally Coefficient of Variation (CoV) for signal steadiness among the groups of subjects during contraction. The result from RMS and MAV analysis shows that the 17-years age groups exhibited higher activity (0.28 and 0.19 mV respectively) compare to other groups (13-Years: 0.26 and 0.17 mV, 14-years: 0.25 and 0.23 mV, 15-Years: 0.23 and 0.16 mV, 16-years: 0.23 and 0.16 mV respectively). Also, this study shows modest correlation between age and signal activities among all age group's muscle. The experiential results can play a pivotal role for developing EMG prosthetic hand controller, neuromuscular system, EMG based rehabilitation aid and movement biomechanics, which may help to separate age groups among the adolescents.

  16. Simulation of surface EMG signals for a multilayer volume conductor with a superficial bone or blood vessel.

    PubMed

    Mesin, Luca

    2008-06-01

    This study analytically describes surface electromyogram (EMG) signals generated by a planar multilayer volume conductor constituted by different subdomains modeling muscle, bone (or blood vessel), fat, and skin tissues. The bone is cylindrical in shape, with a semicircular section. The flat portion of the boundary of the bone subdomain is interfaced with the fat layer tissue, the remaining part of the boundary is in contact with the muscle layer. The volume conductor is a model of physiological tissues in which the bone is superficial, as in the case of the tibia bone, backbone, and bones of the forearm. The muscle fibers are considered parallel to the axes of the bone, so that the model is space invariant in the direction of propagation of the action potential. The proposed model, being analytical, allows faster simulations of surface EMG with respect to previously developed models including bone or blood vessels based on the finite-element method. Surface EMG signals are studied by simulating a library of single-fiber action potentials (SFAP) of fibers in different locations within the muscle domain, simulating the generation, propagation, and extinction of the action potential. The decay of the amplitude of the SFAPs in the direction transversal to the fibers is assessed. The decay in the direction of the bone has a lower rate with respect to the opposite direction. Similar results are obtained by simulating motor unit action potentials (MUAPs) constituted by 100 fibers with territory 5 mm2. M waves and interference EMG signals are also simulated based on the library of SFAPs. Again, the decay of the amplitude of the simulated interference EMG signals is lower approaching the bone with respect to going farther from it. The findings of this study indicate the effect of a superficial bone in enhancing the EMG signals in the transversal direction with respect to the fibers of the considered muscle. This increases the effect of crosstalk. The same mathematical

  17. An optimized method for tremor detection and temporal tracking through repeated second order moment calculations on the surface EMG signal.

    PubMed

    De Marchis, Cristiano; Schmid, Maurizio; Conforto, Silvia

    2012-11-01

    In this study, the problem of detecting and tracking tremor from the surface myoelectric signal is addressed. A method based on the calculation of a Second Order Moment Function (SOMF) inside a window W sliding over the sEMG signal is here presented. An analytical formulation of the detector allows the extraction of the optimal parameters characterizing the algorithm. Performance of the optimized method is assessed on a set of synthetic tremor sEMG signals in terms of sensitivity, precision and accuracy through the use of a properly defined cost function able to explain the overall detector performance. The obtained results are compared to those emerging from the application of optimized versions of traditional detection techniques. Once tested on a database of synthetic tremor sEMG data, a quantitative assessment of the SOMF algorithm performance is carried out on experimental tremor sEMG signals recorded from two patients affected by Essential Tremor and from two patients affected by Parkinson's Disease. The SOMF algorithm outperforms the traditional techniques both in detecting (sensitivity and positive predictive value >99% for SNR higher than 3dB) and in estimating timings of muscular tremor bursts (bias and standard deviation on the estimation of the onset and offset time instants lower than 8ms). Its independence from the SNR level and its low computational cost make it suitable for real-time implementation and clinical use. PMID:22257701

  18. Dynamical characteristics of surface EMG signals of hand grasps via recurrence plot.

    PubMed

    Ouyang, Gaoxiang; Zhu, Xiangyang; Ju, Zhaojie; Liu, Honghai

    2014-01-01

    Recognizing human hand grasp movements through surface electromyogram (sEMG) is a challenging task. In this paper, we investigated nonlinear measures based on recurrence plot, as a tool to evaluate the hidden dynamical characteristics of sEMG during four different hand movements. A series of experimental tests in this study show that the dynamical characteristics of sEMG data with recurrence quantification analysis (RQA) can distinguish different hand grasp movements. Meanwhile, adaptive neuro-fuzzy inference system (ANFIS) is applied to evaluate the performance of the aforementioned measures to identify the grasp movements. The experimental results show that the recognition rate (99.1%) based on the combination of linear and nonlinear measures is much higher than those with only linear measures (93.4%) or nonlinear measures (88.1%). These results suggest that the RQA measures might be a potential tool to reveal the sEMG hidden characteristics of hand grasp movements and an effective supplement for the traditional linear grasp recognition methods. PMID:24403424

  19. Estimation of motor unit conduction velocity from surface EMG recordings by signal-based selection of the spatial filters.

    PubMed

    Mesin, Luca; Tizzani, Francesca; Farina, Dario

    2006-10-01

    Muscle fiber conduction velocity (CV) can be estimated by the application of a pair of spatial filters to surface electromagnetic (EMG) signals and compensation of the spatial filter transfer function with equivalent temporal filters. This method integrates the selection of the spatial filters for signal detection to the estimation of CV. Using this approach, in this paper, we propose a novel technique for signal-based selection of the spatial filter pair that minimizes the effect of nonpropagating signal components (end-of-fiber effects) on CV estimates (optimal filters). The technique is applicable to signals with one propagating and one nonpropagating component, such as single motor unit action potentials. It is shown that the determination of the optimal filters also allows the identification of the propagating and nonpropagating signal components. The new method was applied to simulated and experimental EMG signals. Simulated signals were generated by a cylindrical, layered volume conductor model. Experimental signals were recorded from the abductor pollicis brevis with a linear array of 16 electrodes. In the simulations, the proposed approach provided CV estimates with lower bias due to nonpropagating signal components than previously proposed methods based on the entire signal waveform. In the experimental signals, the technique separated propagating and nonpropagating signal components with an average reconstruction error of 2.9 +/- 0.9% of the signal energy. The technique may find application in single motor unit studies for decreasing the variability and bias of CV estimates due to the presence and different weights of the nonpropagating components.

  20. Decomposition of indwelling EMG signals

    PubMed Central

    Nawab, S. Hamid; Wotiz, Robert P.; De Luca, Carlo J.

    2008-01-01

    Decomposition of indwelling electromyographic (EMG) signals is challenging in view of the complex and often unpredictable behaviors and interactions of the action potential trains of different motor units that constitute the indwelling EMG signal. These phenomena create a myriad of problem situations that a decomposition technique needs to address to attain completeness and accuracy levels required for various scientific and clinical applications. Starting with the maximum a posteriori probability classifier adapted from the original precision decomposition system (PD I) of LeFever and De Luca (25, 26), an artificial intelligence approach has been used to develop a multiclassifier system (PD II) for addressing some of the experimentally identified problem situations. On a database of indwelling EMG signals reflecting such conditions, the fully automatic PD II system is found to achieve a decomposition accuracy of 86.0% despite the fact that its results include low-amplitude action potential trains that are not decomposable at all via systems such as PD I. Accuracy was established by comparing the decompositions of indwelling EMG signals obtained from two sensors. At the end of the automatic PD II decomposition procedure, the accuracy may be enhanced to nearly 100% via an interactive editor, a particularly significant fact for the previously indecomposable trains. PMID:18483170

  1. Error reduction in EMG signal decomposition.

    PubMed

    Kline, Joshua C; De Luca, Carlo J

    2014-12-01

    Decomposition of the electromyographic (EMG) signal into constituent action potentials and the identification of individual firing instances of each motor unit in the presence of ambient noise are inherently probabilistic processes, whether performed manually or with automated algorithms. Consequently, they are subject to errors. We set out to classify and reduce these errors by analyzing 1,061 motor-unit action-potential trains (MUAPTs), obtained by decomposing surface EMG (sEMG) signals recorded during human voluntary contractions. Decomposition errors were classified into two general categories: location errors representing variability in the temporal localization of each motor-unit firing instance and identification errors consisting of falsely detected or missed firing instances. To mitigate these errors, we developed an error-reduction algorithm that combines multiple decomposition estimates to determine a more probable estimate of motor-unit firing instances with fewer errors. The performance of the algorithm is governed by a trade-off between the yield of MUAPTs obtained above a given accuracy level and the time required to perform the decomposition. When applied to a set of sEMG signals synthesized from real MUAPTs, the identification error was reduced by an average of 1.78%, improving the accuracy to 97.0%, and the location error was reduced by an average of 1.66 ms. The error-reduction algorithm in this study is not limited to any specific decomposition strategy. Rather, we propose it be used for other decomposition methods, especially when analyzing precise motor-unit firing instances, as occurs when measuring synchronization.

  2. A threshold-based approach for muscle contraction detection from surface EMG signals

    NASA Astrophysics Data System (ADS)

    Morantes, Gaudi; Fernández, Gerardo; Altuve, Miguel

    2013-11-01

    Surface electromyographic (SEMG) signals are commonly used as control signals in prosthetic and orthotic devices. Super cial electrodes are placed on the skin of the subject to acquire its muscular activity through this signal. The muscle contraction episode is then in charge of activating and deactivating these devices. Nevertheless, there is no gold standard" to detect muscle contraction, leading to delayed responses and false and missed detections. This fact motivated us to propose a new approach that compares a smoothed version of the SEMG signal with a xed threshold, in order to detect muscle contraction episodes. After preprocessing the SEMG signal, the smoothed version is obtained using a moving average lter, where three di erent window lengths has been evaluated. The detector was tuned by maximizing sensitivity and speci city and evaluated using SEMG signals obtained from the anterior tibial and gastrocnemius muscles, taken during the walking of ve subjects. Compared with traditional detection methods, we obtain a reduction of 3 ms in the detection delay, an increase of 8% in sensitivity but a decrease of 15% in speci city. Future work is directed to the inclusion of a temporal threshold (a double-threshold approach) to minimize false detections and reduce detection delays.

  3. Classification of surface EMG signals using optimal wavelet packet method based on Davies-Bouldin criterion.

    PubMed

    Wang, Gang; Wang, Zhizhong; Chen, Weiting; Zhuang, Jun

    2006-10-01

    In this paper we present an optimal wavelet packet (OWP) method based on Davies-Bouldin criterion for the classification of surface electromyographic signals. To reduce the feature dimensionality of the outputs of the OWP decomposition, the principle components analysis was employed. Then we chose a neural network classifier to discriminate four types of prosthesis movements. The proposed method achieved a mean classification accuracy of 93.75%, which outperformed the method using the energy of wavelet packet coefficients (with mean classification accuracy 86.25%) and the fuzzy wavelet packet method (87.5%).

  4. A segmentation approach to long duration surface EMG recordings.

    PubMed

    El Falou, Wassim; Duchêne, Jacques; Hewson, David; Khalil, Mohamad; Grabisch, Michel; Lino, Frédéric

    2005-02-01

    The purpose of this study was to develop an automatic segmentation method in order to identify postural surface EMG segments in long-duration recordings. Surface EMG signals were collected from the cervical erector spinae (CES), erector spinae (ES), external oblique (EO), and tibialis anterior (TA) muscles of 11 subjects using a bipolar electrode configuration. Subjects remained seated in a car seat over the 150-min data-collection period. The modified dynamic cumulative sum (MDCS) algorithm was used to automatically segment the surface EMG signals. Signals were rejected by comparison with an exponential mathematical model of the spectrum of a surface EMG signal. The average power ratio computed between two successive retained segments was used to classify segments as postural or surface EMG. The presence of a negative slope of a regression line fitted to the median frequency values of postural surface EMG segments was taken as an indication of fatigue. Alpha level was set at 0.05. The overall classification error rate was 8%, and could be performed in 25 min for a 150-min signal using a custom-built software program written in C (Borland Software Corporation, CA, USA). This error rate could be enhanced by concentrating on the rejection method, which caused most of the misclassification (6%). Furthermore, the elimination of non-postural surface EMG segments by the use of a segmentation approach enabled muscular fatigue to be identified in signals that contained no evidence of fatigue when analysed using traditional methods.

  5. Fatigue compensation during FES using surface EMG.

    PubMed

    Winslow, Jeffrey; Jacobs, Patrick L; Tepavac, Dejan

    2003-12-01

    Muscle fatigue limits the effectiveness of FES when applied to regain functional movements in spinal cord injured (SCI) individuals. The stimulation intensity must be manually increased to provide more force output to compensate for the decreasing muscle force due to fatigue. An artificial neural network (ANN) system was designed to compensate for muscle fatigue during functional electrical stimulation (FES) by maintaining a constant joint angle. Surface electromyography signals (EMG) from electrically stimulated muscles were used to determine when to increase the stimulation intensity when the muscle's output started to drop. In two separate experiments on able-bodied subjects seated in hard back chairs, electrical stimulation was continuously applied to fatigue either the biceps (during elbow flexion) or the quadriceps muscle (during leg extension) while recording the surface EMG. An ANN system was created using processed surface EMG as the input, and a discrete fatigue compensation control signal, indicating when to increase the stimulation current, as the output. In order to provide training examples and test the systems' performance, the stimulation current amplitude was manually increased to maintain constant joint angles. Manual stimulation amplitude increases were required upon observing a significant decrease in the joint angle. The goal of the ANN system was to generate fatigue compensation control signals in an attempt to maintain a constant joint angle. On average, the systems could correctly predict 78.5% of the instances at which a stimulation increase was required to maintain the joint angle. The performance of these ANN systems demonstrates the feasibility of using surface EMG feedback in an FES control system.

  6. Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique

    PubMed Central

    Abbaspour, S; Fallah, A

    2014-01-01

    Background: The electrocardiogram artifact is a major contamination in the electromyogram signals when electromyogram signal is recorded from upper trunk muscles and because of that the contaminated electromyogram is not useful. Objective: Removing electrocardiogram contamination from electromyogram signals. Methods: In this paper, the clean electromyogram signal, electrocardiogram artifact and electrocardiogram signal were recorded from leg muscles, the pectoralis major muscle of the left side and V4, respectively. After the pre-processing, contaminated electromyogram signal is simulated with a combination of clean electromyogram and electrocardiogram artifact. Then, contaminated electromyogram is cleaned using adaptive subtraction method. This method contains some steps; (1) QRS detection, (2) formation of electrocardiogram template by averaging the electrocardiogram complexes, (3) using low pass filter to remove undesirable artifacts, (4) subtraction. Results: Performance of our method is evaluated using qualitative criteria, power spectrum density and coherence and quantitative criteria signal to noise ratio, relative error and cross correlation. The result of signal to noise ratio, relative error and cross correlation is equal to 10.493, 0.04 and %97 respectively. Finally, there is a comparison between proposed method and some existing methods. Conclusion: The result indicates that adaptive subtraction method is somewhat effective to remove electrocardiogram artifact from contaminated electromyogram signal and has an acceptable result. PMID:25505766

  7. Accurate identification of motor unit discharge patterns from high-density surface EMG and validation with a novel signal-based performance metric

    NASA Astrophysics Data System (ADS)

    Holobar, A.; Minetto, M. A.; Farina, D.

    2014-02-01

    Objective. A signal-based metric for assessment of accuracy of motor unit (MU) identification from high-density surface electromyograms (EMG) is introduced. This metric, so-called pulse-to-noise-ratio (PNR), is computationally efficient, does not require any additional experimental costs and can be applied to every MU that is identified by the previously developed convolution kernel compensation technique. Approach. The analytical derivation of the newly introduced metric is provided, along with its extensive experimental validation on both synthetic and experimental surface EMG signals with signal-to-noise ratios ranging from 0 to 20 dB and muscle contraction forces from 5% to 70% of the maximum voluntary contraction. Main results. In all the experimental and simulated signals, the newly introduced metric correlated significantly with both sensitivity and false alarm rate in identification of MU discharges. Practically all the MUs with PNR > 30 dB exhibited sensitivity >90% and false alarm rates <2%. Therefore, a threshold of 30 dB in PNR can be used as a simple method for selecting only reliably decomposed units. Significance. The newly introduced metric is considered a robust and reliable indicator of accuracy of MU identification. The study also shows that high-density surface EMG can be reliably decomposed at contraction forces as high as 70% of the maximum.

  8. Adaptive filtering for ECG rejection from surface EMG recordings.

    PubMed

    Marque, C; Bisch, C; Dantas, R; Elayoubi, S; Brosse, V; Pérot, C

    2005-06-01

    Surface electromyograms (EMG) of back muscles are often corrupted by electrocardiogram (ECG) signals. This noise in the EMG signals does not allow to appreciate correctly the spectral content of the EMG signals and to follow its evolution during, for example, a fatigue process. Several methods have been proposed to reject the ECG noise from EMG recordings, but seldom taking into account the eventual changes in ECG characteristics during the experiment. In this paper we propose an adaptive filtering algorithm specifically developed for the rejection of the electrocardiogram corrupting surface electromyograms (SEMG). The first step of the study was to choose the ECG electrode position in order to record the ECG with a shape similar to that found in the noised SEMGs. Then, the efficiency of different algorithms were tested on 28 erector spinae SEMG recordings. The best algorithm belongs to the fast recursive least square family (FRLS). More precisely, the best results were obtained with the simplified formulation of a FRLS algorithm. As an application of the adaptive filtering, the paper compares the evolutions of spectral parameters of noised or denoised (after adaptive filtering) surface EMGs recorded on erector spinae muscles during a trunk extension. The fatigue test was analyzed on 16 EMG recordings. After adaptive filtering, mean initial values of energy and of mean power frequency (MPF) were significantly lower and higher respectively. The differences corresponded to the removal of the ECG components. Furthermore, classical fatigue criteria (increase in energy and decrease in MPF values over time during the fatigue test) were better observed on the denoised EMGs. The mean values of the slopes of the energy-time and MPF-time linear relationships differed significantly when established before and after adaptive filtering. These results account for the efficacy of the adaptive filtering method proposed here to denoise electrophysiological signals.

  9. Techniques of EMG signal analysis: detection, processing, classification and applications

    PubMed Central

    Hussain, M.S.; Mohd-Yasin, F.

    2006-01-01

    Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications. PMID:16799694

  10. Comparative study of PCA in classification of multichannel EMG signals.

    PubMed

    Geethanjali, P

    2015-06-01

    Electromyographic (EMG) signals are abundantly used in the field of rehabilitation engineering in controlling the prosthetic device and significantly essential to find fast and accurate EMG pattern recognition system, to avoid intrusive delay. The main objective of this paper is to study the influence of Principal component analysis (PCA), a transformation technique, in pattern recognition of six hand movements using four channel surface EMG signals from ten healthy subjects. For this reason, time domain (TD) statistical as well as auto regression (AR) coefficients are extracted from the four channel EMG signals. The extracted statistical features as well as AR coefficients are transformed using PCA to 25, 50 and 75 % of corresponding original feature vector space. The classification accuracy of PCA transformed and non-PCA transformed TD statistical features as well as AR coefficients are studied with simple logistic regression (SLR), decision tree (DT) with J48 algorithm, logistic model tree (LMT), k nearest neighbor (kNN) and neural network (NN) classifiers in the identification of six different movements. The Kruskal-Wallis (KW) statistical test shows that there is a significant reduction (P < 0.05) in classification accuracy with PCA transformed features compared to non-PCA transformed features. SLR with non-PCA transformed time domain (TD) statistical features performs better in accuracy and computational power compared to other features considered in this study. In addition, the motion control of three drives for six movements of the hand is implemented with SLR using TD statistical features in off-line with TMSLF2407 digital signal controller (DSC). PMID:25860845

  11. Voiceless Bangla vowel recognition using sEMG signal.

    PubMed

    Mostafa, S S; Awal, M A; Ahmad, M; Rashid, M A

    2016-01-01

    Some people cannot produce sound although their facial muscles work properly due to having problem in their vocal cords. Therefore, recognition of alphabets as well as sentences uttered by these voiceless people is a complex task. This paper proposes a novel method to solve this problem using non-invasive surface Electromyogram (sEMG). Firstly, eleven Bangla vowels are pronounced and sEMG signals are recorded at the same time. Different features are extracted and mRMR feature selection algorithm is then applied to select prominent feature subset from the large feature vector. After that, these prominent features subset is applied in the Artificial Neural Network for vowel classification. This novel Bangla vowel classification method can offer a significant contribution in voice synthesis as well as in speech communication. The result of this experiment shows an overall accuracy of 82.3 % with fewer features compared to other studies in different languages. PMID:27652095

  12. siGnum: graphical user interface for EMG signal analysis.

    PubMed

    Kaur, Manvinder; Mathur, Shilpi; Bhatia, Dinesh; Verma, Suresh

    2015-01-01

    Electromyography (EMG) signals that represent the electrical activity of muscles can be used for various clinical and biomedical applications. These are complicated and highly varying signals that are dependent on anatomical location and physiological properties of the muscles. EMG signals acquired from the muscles require advanced methods for detection, decomposition and processing. This paper proposes a novel Graphical User Interface (GUI) siGnum developed in MATLAB that will apply efficient and effective techniques on processing of the raw EMG signals and decompose it in a simpler manner. It could be used independent of MATLAB software by employing a deploy tool. This would enable researcher's to gain good understanding of EMG signal and its analysis procedures that can be utilized for more powerful, flexible and efficient applications in near future.

  13. Comparison of surface EMG signals between electrode types, interelectrode distances and electrode orientations in isometric exercise of the erector spinae muscle.

    PubMed

    Zedka, M; Kumar, S; Narayan, Y

    1997-10-01

    The influence of electrode type, interelectrode distance (IED) and electrode orientation on EMG signals from the paraspinal muscles was investigated. Bipolar electrodes were placed at distances 2, 3, 4, 6 and 8 cm over the erector spinae in the cranio-caudal direction ("in series") as well as in the direction perpendicular to it ("in parallel"). Ten subjects performed 5 s isometric contractions of the erector spinae at 20, 40, 60, 80 and 100% MVC by pulling upward on a handlebar attached to the floor. RMS EMG signals were analyzed for mean average amplitude (AA). Mean total power (TP) and mean median frequency (MF) of the raw EMG signal were determined using fast Fourier transform. In addition to graded loading, sustained fatiguing contractions were performed from which TP and MF were obtained. With increasing IED the AA and TP increased while MF decreased. Although a trend towards higher AA, TP and MF was found for electrodes "in series", as compared to those "in parallel", the difference never reached significance. It is concluded that consistent information about muscle activity was obtained with Miniature Biopotential Skin Electrodes and 14445C Hewlett-Packard electrodes independently from IED or orientation. Orientation "in parallel" prevented the electrodes from sliding during muscle contraction. The third tested type, electrodes developed in the Neuromuscular Research Center, Boston, proved extremely sensitive to movement.

  14. Teager–Kaiser energy operator signal conditioning improves EMG onset detection

    PubMed Central

    Rider, Patrick; Steinweg, Ken; DeVita, Paul; Hortobágyi, Tibor

    2010-01-01

    Accurate identification of the onset of muscle activity is an important element in the biomechanical analysis of human movement. The purpose of this study was to determine if inclusion of the Teager–Kaiser energy operator (TKEO) in signal conditioning would increase the accuracy of popular electromyography (EMG) onset detection methods. Three methods, visual determination, threshold-based method, and approximated generalized likelihood ratio were used to estimate the onset of EMG burst with and without TKEO conditioning. Reference signals, with known onset times, were constructed from EMG signals collected during isometric contraction of the vastus lateralis (n = 17). Additionally, vastus lateralis EMG signals (n = 255) recorded during gait were used to evaluate a clinical application of the TKEO conditioning. Inclusion of TKEO in signal conditioning significantly reduced mean detection error of all three methods compared with signal conditioning without TKEO, using artificially generated reference data (13 vs. 98 ms, p < 0.001) and also compared with experimental data collected during gait (55 vs. 124 ms, p < 0.001). In conclusion, addition of TKEO as a step in conditioning surface EMG signals increases the detection accuracy of EMG burst boundaries. PMID:20526612

  15. Long-term surface EMG monitoring using K-means clustering and compressive sensing

    NASA Astrophysics Data System (ADS)

    Balouchestani, Mohammadreza; Krishnan, Sridhar

    2015-05-01

    In this work, we present an advanced K-means clustering algorithm based on Compressed Sensing theory (CS) in combination with the K-Singular Value Decomposition (K-SVD) method for Clustering of long-term recording of surface Electromyography (sEMG) signals. The long-term monitoring of sEMG signals aims at recording of the electrical activity produced by muscles which are very useful procedure for treatment and diagnostic purposes as well as for detection of various pathologies. The proposed algorithm is examined for three scenarios of sEMG signals including healthy person (sEMG-Healthy), a patient with myopathy (sEMG-Myopathy), and a patient with neuropathy (sEMG-Neuropathr), respectively. The proposed algorithm can easily scan large sEMG datasets of long-term sEMG recording. We test the proposed algorithm with Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) dimensionality reduction methods. Then, the output of the proposed algorithm is fed to K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers in order to calclute the clustering performance. The proposed algorithm achieves a classification accuracy of 99.22%. This ability allows reducing 17% of Average Classification Error (ACE), 9% of Training Error (TE), and 18% of Root Mean Square Error (RMSE). The proposed algorithm also reduces 14% clustering energy consumption compared to the existing K-Means clustering algorithm.

  16. Individual finger classification from surface EMG: Influence of electrode set.

    PubMed

    Celadon, Nicolo; Dosen, Strahinja; Paleari, Marco; Farina, Dario; Ariano, Paolo

    2015-01-01

    The aim of this work was to minimize the number of channels, determining acceptable electrode locations and optimizing electrode-recording configurations to decode isometric flexion and extension of individual fingers. Nine healthy subjects performed cyclical isometric contractions activating individual fingers. During the experiment they tracked a moving visual marker indicating the contraction type (flexion/extension), desired activation level and the finger that should be employed. Surface electromyography (sEMG) signals were detected from the forearm muscles using a matrix of 192 channels (24 longitudinal columns and 8 transversal rows, 10 mm inter-electrode distance). The classification was evaluated in the context of a linear discriminant analysis (LDA) with different sets of EMG electrodes: A) one linear array of 8 electrodes, B) two arrays of 8 electrodes each, C) a set with one electrode on the barycenter of each sEMG activity area, D) all the recorded channels. The results showed that the classification accuracy depended on the electrode set (F=14.67, p<;0.001). The best reduction approaches were the barycenter calculation and the use of two linear arrays of electrodes, which performed similarly to each other (both > 82% of average success rate). Considering the computation time and electrode positioning, it is concluded that two arrays of 8 electrodes provide an optimal configuration to classify the isometric flexion and extension of individual fingers.

  17. Driving Electric Vehicle by EMG Signal Considering Frequency Components

    NASA Astrophysics Data System (ADS)

    Aso, Shinichi; Sasaki, Akinori; Hashimoto, Hiroshi; Ishii, Chiharu

    This paper proposes a useful method driving the electric vehicle by EMG signals (Electromyographic signals) which are filtered on the basis of frequency components which change with muscle contraction. This method estimates strength of muscular tension by a single EMG signal. By our method, user is able to control speed of the electric vehicle by strength of muscular tension. The method of speed control may give user good or bad operation feeling in the meaning of SD (Semantic Differential) method and factor analysis. The operation feeling is evaluated by experiment on EMG interface in cases of using filters or not. As a result, it is shown that operation feeling is influenced by this method.

  18. Surface EMG measurements during fMRI at 3T: accurate EMG recordings after artifact correction.

    PubMed

    van Duinen, Hiske; Zijdewind, Inge; Hoogduin, Hans; Maurits, Natasha

    2005-08-01

    In this experiment, we have measured surface EMG of the first dorsal interosseus during predefined submaximal isometric contractions (5, 15, 30, 50, and 70% of maximal force) of the index finger simultaneously with fMRI measurements. Since we have used sparse sampling fMRI (3-s scanning; 2-s non-scanning), we were able to compare the mean amplitude of the undisturbed EMG (non-scanning) intervals with the mean amplitude of the EMG intervals during scanning, after MRI artifact correction. The agreement between the mean amplitudes of the corrected and the undisturbed EMG was excellent and the mean difference between the two amplitudes was not significantly different. Furthermore, there was no significant difference between the corrected and undisturbed amplitude at different force levels. In conclusion, we have shown that it is feasible to record surface EMG during scanning and that, after MRI artifact correction, the EMG recordings can be used to quantify isometric muscle activity, even at very low activation intensities.

  19. Features extraction of EMG signal using time domain analysis for arm rehabilitation device

    NASA Astrophysics Data System (ADS)

    Jali, Mohd Hafiz; Ibrahim, Iffah Masturah; Sulaima, Mohamad Fani; Bukhari, W. M.; Izzuddin, Tarmizi Ahmad; Nasir, Mohamad Na'im

    2015-05-01

    Rehabilitation device is used as an exoskeleton for people who had failure of their limb. Arm rehabilitation device may help the rehab program whom suffers from arm disability. The device that is used to facilitate the tasks of the program should improve the electrical activity in the motor unit and minimize the mental effort of the user. Electromyography (EMG) is the techniques to analyze the presence of electrical activity in musculoskeletal systems. The electrical activity in muscles of disable person is failed to contract the muscle for movements. In order to prevent the muscles from paralysis becomes spasticity, the force of movements should minimize the mental efforts. Therefore, the rehabilitation device should analyze the surface EMG signal of normal people that can be implemented to the device. The signal is collected according to procedure of surface electromyography for non-invasive assessment of muscles (SENIAM). The EMG signal is implemented to set the movements' pattern of the arm rehabilitation device. The filtered EMG signal was extracted for features of Standard Deviation (STD), Mean Absolute Value (MAV) and Root Mean Square (RMS) in time-domain. The extraction of EMG data is important to have the reduced vector in the signal features with less of error. In order to determine the best features for any movements, several trials of extraction methods are used by determining the features with less of errors. The accurate features can be use for future works of rehabilitation control in real-time.

  20. Surface EMG decomposition based on K-means clustering and convolution kernel compensation.

    PubMed

    Ning, Yong; Zhu, Xiangjun; Zhu, Shanan; Zhang, Yingchun

    2015-03-01

    A new approach has been developed by combining the K-mean clustering (KMC) method and a modified convolution kernel compensation (CKC) method for multichannel surface electromyogram (EMG) decomposition. The KMC method was first utilized to cluster vectors of observations at different time instants and then estimate the initial innervation pulse train (IPT). The CKC method, modified with a novel multistep iterative process, was conducted to update the estimated IPT. The performance of the proposed K-means clustering-Modified CKC (KmCKC) approach was evaluated by reconstructing IPTs from both simulated and experimental surface EMG signals. The KmCKC approach successfully reconstructed all 10 IPTs from the simulated surface EMG signals with true positive rates (TPR) of over 90% with a low signal-to-noise ratio (SNR) of -10 dB. More than 10 motor units were also successfully extracted from the 64-channel experimental surface EMG signals of the first dorsal interosseous (FDI) muscles when a contraction force was held at 8 N by using the KmCKC approach. A "two-source" test was further conducted with 64-channel surface EMG signals. The high percentage of common MUs and common pulses (over 92% at all force levels) between the IPTs reconstructed from the two independent groups of surface EMG signals demonstrates the reliability and capability of the proposed KmCKC approach in multichannel surface EMG decomposition. Results from both simulated and experimental data are consistent and confirm that the proposed KmCKC approach can successfully reconstruct IPTs with high accuracy at different levels of contraction.

  1. Subspace based adaptive denoising of surface EMG from neurological injury patients

    NASA Astrophysics Data System (ADS)

    Liu, Jie; Ying, Dongwen; Zev Rymer, William; Zhou, Ping

    2014-10-01

    Objective: After neurological injuries such as spinal cord injury, voluntary surface electromyogram (EMG) signals recorded from affected muscles are often corrupted by interferences, such as spurious involuntary spikes and background noises produced by physiological and extrinsic/accidental origins, imposing difficulties for signal processing. Conventional methods did not well address the problem caused by interferences. It is difficult to mitigate such interferences using conventional methods. The aim of this study was to develop a subspace-based denoising method to suppress involuntary background spikes contaminating voluntary surface EMG recordings. Approach: The Karhunen-Loeve transform was utilized to decompose a noisy signal into a signal subspace and a noise subspace. An optimal estimate of EMG signal is derived from the signal subspace and the noise power. Specifically, this estimator is capable of making a tradeoff between interference reduction and signal distortion. Since the estimator partially relies on the estimate of noise power, an adaptive method was presented to sequentially track the variation of interference power. The proposed method was evaluated using both semi-synthetic and real surface EMG signals. Main results: The experiments confirmed that the proposed method can effectively suppress interferences while keep the distortion of voluntary EMG signal in a low level. The proposed method can greatly facilitate further signal processing, such as onset detection of voluntary muscle activity. Significance: The proposed method can provide a powerful tool for suppressing background spikes and noise contaminating voluntary surface EMG signals of paretic muscles after neurological injuries, which is of great importance for their multi-purpose applications.

  2. Analysis of surface EMG baseline for detection of hidden muscle activity

    NASA Astrophysics Data System (ADS)

    Zhang, Xu; Zhou, Ping

    2014-02-01

    Objective. This study explored the feasibility of detecting hidden muscle activity in surface electromyogram (EMG) baseline. Approach. Power spectral density (PSD) analysis and multi-scale entropy (MSE) analysis were used. Both analyses were applied to computer simulations of surface EMG baseline with the presence (representing activity data) or absence (representing reference data) of hidden muscle activity, as well as surface electrode array EMG baseline recordings of healthy control and amyotrophic lateral sclerosis (ALS) subjects. Main results. Although the simulated reference data and the activity data yielded no distinguishable difference in the time domain, they demonstrated a significant difference in the frequency and signal complexity domains with the PSD and MSE analyses. For a comparison using pooled data, such a difference was also observed when the PSD and MSE analyses were applied to surface electrode array EMG baseline recordings of healthy control and ALS subjects, which demonstrated no distinguishable difference in the time domain. Compared with the PSD analysis, the MSE analysis appeared to be more sensitive for detecting the difference in surface EMG baselines between the two groups. Significance. The findings implied the presence of a hidden muscle activity in surface EMG baseline recordings from the ALS subjects. To promote the presented analysis as a useful diagnostic or investigatory tool, future studies are necessary to assess the pathophysiological nature or origins of the hidden muscle activity, as well as the baseline difference at the individual subject level.

  3. Forearm motion discrimination technique using real-time EMG signals.

    PubMed

    Mizuno, Haruaki; Tsujiuchi, Nobutaka; Koizumi, Takayuki

    2011-01-01

    The objective of this study is to develop a method of discriminating real-time motion from electromyogram (EMG) signals. We previously proposed a motion discrimination method. This method could discriminate five motions (hand opening, hand closing, hand chucking, wrist extension, and wrist flexion) at a rate of above 90 percent from four channel EMG signals in the forearm. The method prevents elbow motions from interfering with hand motion discrimination. However, discrimination processing time of this method is more than 300 ms, and the shortest delay time that is perceivable by the user is generally regarded to be roughly 300 ms. Furthermore, a robot hand has a mechanical delay time. Thus, the discrimination time should be less than 300 ms. Here, we propose a real-time motion discrimination method using a hyper-sphere model. In comparison with the old model, the hyper-sphere models can make more complex decision regions which can discriminate at the state of the motion. Furthermore, this model can learn EMG signals in real-time. We experimentally verified that the discrimination accuracies of this method were above 90 percent. Moreover, elbow motions did not interfere with the hand motion discrimination. The discrimination processing time was less than 300 ms, and was about 30 percent shorter than that of the old method. PMID:22255323

  4. Subauditory Speech Recognition based on EMG/EPG Signals

    NASA Technical Reports Server (NTRS)

    Jorgensen, Charles; Lee, Diana Dee; Agabon, Shane; Lau, Sonie (Technical Monitor)

    2003-01-01

    Sub-vocal electromyogram/electro palatogram (EMG/EPG) signal classification is demonstrated as a method for silent speech recognition. Recorded electrode signals from the larynx and sublingual areas below the jaw are noise filtered and transformed into features using complex dual quad tree wavelet transforms. Feature sets for six sub-vocally pronounced words are trained using a trust region scaled conjugate gradient neural network. Real time signals for previously unseen patterns are classified into categories suitable for primitive control of graphic objects. Feature construction, recognition accuracy and an approach for extension of the technique to a variety of real world application areas are presented.

  5. Surface EMG pattern recognition for real-time control of a wrist exoskeleton

    PubMed Central

    2010-01-01

    Background Surface electromyography (sEMG) signals have been used in numerous studies for the classification of hand gestures and movements and successfully implemented in the position control of different prosthetic hands for amputees. sEMG could also potentially be used for controlling wearable devices which could assist persons with reduced muscle mass, such as those suffering from sarcopenia. While using sEMG for position control, estimation of the intended torque of the user could also provide sufficient information for an effective force control of the hand prosthesis or assistive device. This paper presents the use of pattern recognition to estimate the torque applied by a human wrist and its real-time implementation to control a novel two degree of freedom wrist exoskeleton prototype (WEP), which was specifically developed for this work. Methods Both sEMG data from four muscles of the forearm and wrist torque were collected from eight volunteers by using a custom-made testing rig. The features that were extracted from the sEMG signals included root mean square (rms) EMG amplitude, autoregressive (AR) model coefficients and waveform length. Support Vector Machines (SVM) was employed to extract classes of different force intensity from the sEMG signals. After assessing the off-line performance of the used classification technique, the WEP was used to validate in real-time the proposed classification scheme. Results The data gathered from the volunteers were divided into two sets, one with nineteen classes and the second with thirteen classes. Each set of data was further divided into training and testing data. It was observed that the average testing accuracy in the case of nineteen classes was about 88% whereas the average accuracy in the case of thirteen classes reached about 96%. Classification and control algorithm implemented in the WEP was executed in less than 125 ms. Conclusions The results of this study showed that classification of EMG signals by

  6. S-EMG signal compression based on domain transformation and spectral shape dynamic bit allocation

    PubMed Central

    2014-01-01

    Background Surface electromyographic (S-EMG) signal processing has been emerging in the past few years due to its non-invasive assessment of muscle function and structure and because of the fast growing rate of digital technology which brings about new solutions and applications. Factors such as sampling rate, quantization word length, number of channels and experiment duration can lead to a potentially large volume of data. Efficient transmission and/or storage of S-EMG signals are actually a research issue. That is the aim of this work. Methods This paper presents an algorithm for the data compression of surface electromyographic (S-EMG) signals recorded during isometric contractions protocol and during dynamic experimental protocols such as the cycling activity. The proposed algorithm is based on discrete wavelet transform to proceed spectral decomposition and de-correlation, on a dynamic bit allocation procedure to code the wavelets transformed coefficients, and on an entropy coding to minimize the remaining redundancy and to pack all data. The bit allocation scheme is based on mathematical decreasing spectral shape models, which indicates a shorter digital word length to code high frequency wavelets transformed coefficients. Four bit allocation spectral shape methods were implemented and compared: decreasing exponential spectral shape, decreasing linear spectral shape, decreasing square-root spectral shape and rotated hyperbolic tangent spectral shape. Results The proposed method is demonstrated and evaluated for an isometric protocol and for a dynamic protocol using a real S-EMG signal data bank. Objective performance evaluations metrics are presented. In addition, comparisons with other encoders proposed in scientific literature are shown. Conclusions The decreasing bit allocation shape applied to the quantized wavelet coefficients combined with arithmetic coding results is an efficient procedure. The performance comparisons of the proposed S-EMG data

  7. Examination of motor unit control properties in stroke survivors using surface EMG decomposition: a preliminary report.

    PubMed

    Suresh, Nina; Li, Xiaoyan; Zhou, Ping; Rymer, William Zev

    2011-01-01

    The objective of this pilot study was to examine alterations in motor unit (MU) control properties, (i.e. MU recruitment and firing rate) after stroke utilizing a recently developed high-yield surface electromyogram (EMG) decomposition technique. Two stroke subjects participated in this study. A sensor array was used to record surface EMG signals from the first dorsal interosseous (FDI) muscle during voluntary isometric contraction at varying force levels. The recording was performed in both paretic and contralateral muscles using a matched force protocol. Single motor unit activity was extracted using the surface EMG decomposition software from Delsys Inc. The results from the two stroke subjects indicate a reduction in the mean motor unit firing rate and a compression of motor unit recruitment range in paretic muscle as compared with the contralateral muscles. These findings provide further evidence of spinal motoneuron involvement after a hemispheric brain lesion, and help us to understand the complex origins of stroke induced muscle weakness.

  8. Effectiveness of the Wavelet Transform on the Surface EMG to Understand the Muscle Fatigue During Walk

    NASA Astrophysics Data System (ADS)

    Hussain, M. S.; Mamun, Md.

    2012-01-01

    Muscle fatigue is the decline in ability of a muscle to create force. Electromyography (EMG) is a medical technique for measuring muscle response to nervous stimulation. During a sustained muscle contraction, the power spectrum of the EMG shifts towards lower frequencies. These effects are due to muscle fatigue. Muscle fatigue is often a result of unhealthy work practice. In this research, the effectiveness of the wavelet transform applied to the surface EMG (SEMG) signal as a means of understanding muscle fatigue during walk is presented. Power spectrum and bispectrum analysis on the EMG signal getting from right rectus femoris muscle is executed utilizing various wavelet functions (WFs). It is possible to recognize muscle fatigue appreciably with the proper choice of the WF. The outcome proves that the most momentous changes in the EMG power spectrum are symbolized by WF Daubechies45. Moreover, this research has compared bispectrum properties to the other WFs. To determine muscle fatigue during gait, Daubechies45 is used in this research to analyze the SEMG signal.

  9. Examination of Poststroke Alteration in Motor Unit Firing Behavior Using High-Density Surface EMG Decomposition.

    PubMed

    Li, Xiaoyan; Holobar, Ales; Gazzoni, Marco; Merletti, Roberto; Rymer, William Zev; Zhou, Ping

    2015-05-01

    Recent advances in high-density surface electromyogram (EMG) decomposition have made it a feasible task to discriminate single motor unit activity from surface EMG interference patterns, thus providing a noninvasive approach for examination of motor unit control properties. In the current study, we applied high-density surface EMG recording and decomposition techniques to assess motor unit firing behavior alterations poststroke. Surface EMG signals were collected using a 64-channel 2-D electrode array from the paretic and contralateral first dorsal interosseous (FDI) muscles of nine hemiparetic stroke subjects at different isometric discrete contraction levels between 2 to 10 N with a 2 N increment step. Motor unit firing rates were extracted through decomposition of the high-density surface EMG signals and compared between paretic and contralateral muscles. Across the nine tested subjects, paretic FDI muscles showed decreased motor unit firing rates compared with contralateral muscles at different contraction levels. Regression analysis indicated a linear relation between the mean motor unit firing rate and the muscle contraction level for both paretic and contralateral muscles (p < 0.001), with the former demonstrating a lower increment rate (0.32 pulses per second (pps)/N) compared with the latter (0.67 pps/N). The coefficient of variation (averaged over the contraction levels) of the motor unit firing rates for the paretic muscles (0.21 ± 0.012) was significantly higher than for the contralateral muscles (0.17 ± 0.014) (p < 0.05). This study provides direct evidence of motor unit firing behavior alterations poststroke using surface EMG, which can be an important factor contributing to hemiparetic muscle weakness.

  10. Wiener filtering of surface EMG with a priori SNR estimation toward myoelectric control for neurological injury patients.

    PubMed

    Liu, Jie; Ying, Dongwen; Zhou, Ping

    2014-12-01

    Voluntary surface electromyogram (EMG) signals from neurological injury patients are often corrupted by involuntary background interference or spikes, imposing difficulties for myoelectric control. We present a novel framework to suppress involuntary background spikes during voluntary surface EMG recordings. The framework applies a Wiener filter to restore voluntary surface EMG signals based on tracking a priori signal to noise ratio (SNR) by using the decision-directed method. Semi-synthetic surface EMG signals contaminated by different levels of involuntary background spikes were constructed from a database of surface EMG recordings in a group of spinal cord injury subjects. After the processing, the onset detection of voluntary muscle activity was significantly improved against involuntary background spikes. The magnitude of voluntary surface EMG signals can also be reliably estimated for myoelectric control purpose. Compared with the previous sample entropy analysis for suppressing involuntary background spikes, the proposed framework is characterized by quick and simple implementation, making it more suitable for application in a myoelectric control system toward neurological injury rehabilitation. PMID:25443536

  11. Wiener Filtering of Surface EMG with a priori SNR Estimation Toward Myoelectric Control for Neurological Injury Patients

    PubMed Central

    Liu, Jie; Ying, Dongwen; Zhou, Ping

    2014-01-01

    Voluntary surface electromyogram (EMG) signals from neurological injury patients are often corrupted by involuntary background interference or spikes, imposing difficulties for myoelectric control. We present a novel framework to suppress involuntary background spikes during voluntary surface EMG recordings. The framework applies a Wiener filter to restore voluntary surface EMG signals based on tracking a priori signal to noise ratio (SNR) by using the decision-directed method. Semi-synthetic surface EMG signals contaminated by different levels of involuntary background spikes were constructed from a database of surface EMG recordings in a group of spinal cord injury subjects. After the processing, the onset detection of voluntary muscle activity was significantly improved against involuntary background spikes. The magnitude of voluntary surface EMG signals can also be reliably estimated for myoelectric control purpose. Compared with the previous sample entropy analysis for suppressing involuntary background spikes, the proposed framework is characterized by quick and simple implementation, making it more suitable for application in a myoelectric control system toward neurological injury rehabilitation. PMID:25443536

  12. A novel biometric authentication approach using ECG and EMG signals.

    PubMed

    Belgacem, Noureddine; Fournier, Régis; Nait-Ali, Amine; Bereksi-Reguig, Fethi

    2015-05-01

    Security biometrics is a secure alternative to traditional methods of identity verification of individuals, such as authentication systems based on user name and password. Recently, it has been found that the electrocardiogram (ECG) signal formed by five successive waves (P, Q, R, S and T) is unique to each individual. In fact, better than any other biometrics' measures, it delivers proof of subject's being alive as extra information which other biometrics cannot deliver. The main purpose of this work is to present a low-cost method for online acquisition and processing of ECG signals for person authentication and to study the possibility of providing additional information and retrieve personal data from an electrocardiogram signal to yield a reliable decision. This study explores the effectiveness of a novel biometric system resulting from the fusion of information and knowledge provided by ECG and EMG (Electromyogram) physiological recordings. It is shown that biometrics based on these ECG/EMG signals offers a novel way to robustly authenticate subjects. Five ECG databases (MIT-BIH, ST-T, NSR, PTB and ECG-ID) and several ECG signals collected in-house from volunteers were exploited. A palm-based ECG biometric system was developed where the signals are collected from the palm of the subject through a minimally intrusive one-lead ECG set-up. A total of 3750 ECG beats were used in this work. Feature extraction was performed on ECG signals using Fourier descriptors (spectral coefficients). Optimum-Path Forest classifier was used to calculate the degree of similarity between individuals. The obtained results from the proposed approach look promising for individuals' authentication. PMID:25836061

  13. A novel biometric authentication approach using ECG and EMG signals.

    PubMed

    Belgacem, Noureddine; Fournier, Régis; Nait-Ali, Amine; Bereksi-Reguig, Fethi

    2015-05-01

    Security biometrics is a secure alternative to traditional methods of identity verification of individuals, such as authentication systems based on user name and password. Recently, it has been found that the electrocardiogram (ECG) signal formed by five successive waves (P, Q, R, S and T) is unique to each individual. In fact, better than any other biometrics' measures, it delivers proof of subject's being alive as extra information which other biometrics cannot deliver. The main purpose of this work is to present a low-cost method for online acquisition and processing of ECG signals for person authentication and to study the possibility of providing additional information and retrieve personal data from an electrocardiogram signal to yield a reliable decision. This study explores the effectiveness of a novel biometric system resulting from the fusion of information and knowledge provided by ECG and EMG (Electromyogram) physiological recordings. It is shown that biometrics based on these ECG/EMG signals offers a novel way to robustly authenticate subjects. Five ECG databases (MIT-BIH, ST-T, NSR, PTB and ECG-ID) and several ECG signals collected in-house from volunteers were exploited. A palm-based ECG biometric system was developed where the signals are collected from the palm of the subject through a minimally intrusive one-lead ECG set-up. A total of 3750 ECG beats were used in this work. Feature extraction was performed on ECG signals using Fourier descriptors (spectral coefficients). Optimum-Path Forest classifier was used to calculate the degree of similarity between individuals. The obtained results from the proposed approach look promising for individuals' authentication.

  14. Detection of driving fatigue by using noncontact EMG and ECG signals measurement system.

    PubMed

    Fu, Rongrong; Wang, Hong

    2014-05-01

    Driver fatigue can be detected by constructing a discriminant mode using some features obtained from physiological signals. There exist two major challenges of this kind of methods. One is how to collect physiological signals from subjects while they are driving without any interruption. The other is to find features of physiological signals that are of corresponding change with the loss of attention caused by driver fatigue. Driving fatigue is detected based on the study of surface electromyography (EMG) and electrocardiograph (ECG) during the driving period. The noncontact data acquisition system was used to collect physiological signals from the biceps femoris of each subject to tackle the first challenge. Fast independent component analysis (FastICA) and digital filter were utilized to process the original signals. Based on the statistical analysis results given by Kolmogorov-Smirnov Z test, the peak factor of EMG (p < 0.001) and the maximum of the cross-relation curve of EMG and ECG (p < 0.001) were selected as the combined characteristic to detect fatigue of drivers. The discriminant criterion of fatigue was obtained from the training samples by using Mahalanobis distance, and then the average classification accuracy was given by 10-fold cross-validation. The results showed that the method proposed in this paper can give well performance in distinguishing the normal state and fatigue state. The noncontact, onboard vehicle drivers' fatigue detection system was developed to reduce fatigue-related risks.

  15. Surface EMG system for use in long-term vigorous activities

    NASA Astrophysics Data System (ADS)

    de Luca, G.; Bergman, P.; de Luca, C.

    The purpose of the project was to develop an advanced surface electromyographic (EMG) system that is portable, un-tethered, and able to detect high-fidelity EMG signals from multiple channels. The innovation was specifically designed to extend NASA's capability to perform neurological status monitoring for long-term, vigorous activities. These features are a necessary requirement of ground-based and in-flight studies planned for the International Space Station and human expeditions to Mars. The project consisted of developing 1) a portable EMG digital data logger using a handheld PC for acquiring the signal and storing the data from as many as 8 channels, and 2) an EMG electrode/skin interface to improve signal fidelity and skin adhesion in the presence of sweat and mechanical disturbances encountered during vigorous activities. The system, referred to as a MyoMonitor, was configured with a communication port for downloading the data from the data logger to the PC computer workstation. Software specifications were developed and implemented for programming of acquisition protocols, power management, and transferring data to the PC for processing and graphical display. The prototype MyoMonitor was implemented using a handheld PC that features a color LCD screen, enhanced keyboard, extended Lithium Ion battery and recharger, and 128 Mbytes of F ash Memory. The system was designed to be belt-worn,l thereby allowing its use under vigorous activities. The Monitor utilizes up to 8 differential surface EMG sensors. The prototype allowed greater than 2 hours of continuous 8-channel EMG data to be collected, or 17.2 hours of continuous single channel EMG data. Standardized tests in human subjects were conducted to develop the mechanical and electrical properties of the prototype electrode/interface system. Tests conducted during treadmill running and repetitive lifting demonstrated that the prototype interface significantly reduced the detrimental effects of sweat

  16. Mean frequency derived via Hilbert-Huang transform with application to fatigue EMG signal analysis.

    PubMed

    Xie, Hongbo; Wang, Zhizhong

    2006-05-01

    The mean frequency (MNF) of surface electromyography (EMG) signal is an important index of local muscle fatigue. The purpose of this study is to improve the mean frequency (MNF) estimation. Three methods to estimate the MNF of non-stationary EMG are compared. A novel approach based on Hilbert-Huang transform (HHT), which comprises the empirical mode decomposition (EMD) and Hilbert transform, is proposed to estimate the mean frequency of non-stationary signal. The performance of this method is compared with the two existing methods, i.e. autoregressive (AR) spectrum estimation and wavelet transform method. It is observed that our method shows low variability in terms of robustness to the length of the analysis window. The time-varying characteristic of the proposed approach also enables us to accommodate other non-stationary biomedical data analysis.

  17. Nonlinear Analysis of Surface EMG Time Series

    NASA Astrophysics Data System (ADS)

    Zurcher, Ulrich; Kaufman, Miron; Sung, Paul

    2004-04-01

    Applications of nonlinear analysis of surface electromyography time series of patients with and without low back pain are presented. Limitations of the standard methods based on the power spectrum are discussed.

  18. A mechatronics platform to study prosthetic hand control using EMG signals.

    PubMed

    Geethanjali, P

    2016-09-01

    In this paper, a low-cost mechatronics platform for the design and development of robotic hands as well as a surface electromyogram (EMG) pattern recognition system is proposed. This paper also explores various EMG classification techniques using a low-cost electronics system in prosthetic hand applications. The proposed platform involves the development of a four channel EMG signal acquisition system; pattern recognition of acquired EMG signals; and development of a digital controller for a robotic hand. Four-channel surface EMG signals, acquired from ten healthy subjects for six different movements of the hand, were used to analyse pattern recognition in prosthetic hand control. Various time domain features were extracted and grouped into five ensembles to compare the influence of features in feature-selective classifiers (SLR) with widely considered non-feature-selective classifiers, such as neural networks (NN), linear discriminant analysis (LDA) and support vector machines (SVM) applied with different kernels. The results divulged that the average classification accuracy of the SVM, with a linear kernel function, outperforms other classifiers with feature ensembles, Hudgin's feature set and auto regression (AR) coefficients. However, the slight improvement in classification accuracy of SVM incurs more processing time and memory space in the low-level controller. The Kruskal-Wallis (KW) test also shows that there is no significant difference in the classification performance of SLR with Hudgin's feature set to that of SVM with Hudgin's features along with AR coefficients. In addition, the KW test shows that SLR was found to be better in respect to computation time and memory space, which is vital in a low-level controller. Similar to SVM, with a linear kernel function, other non-feature selective LDA and NN classifiers also show a slight improvement in performance using twice the features but with the drawback of increased memory space requirement and time

  19. A mechatronics platform to study prosthetic hand control using EMG signals.

    PubMed

    Geethanjali, P

    2016-09-01

    In this paper, a low-cost mechatronics platform for the design and development of robotic hands as well as a surface electromyogram (EMG) pattern recognition system is proposed. This paper also explores various EMG classification techniques using a low-cost electronics system in prosthetic hand applications. The proposed platform involves the development of a four channel EMG signal acquisition system; pattern recognition of acquired EMG signals; and development of a digital controller for a robotic hand. Four-channel surface EMG signals, acquired from ten healthy subjects for six different movements of the hand, were used to analyse pattern recognition in prosthetic hand control. Various time domain features were extracted and grouped into five ensembles to compare the influence of features in feature-selective classifiers (SLR) with widely considered non-feature-selective classifiers, such as neural networks (NN), linear discriminant analysis (LDA) and support vector machines (SVM) applied with different kernels. The results divulged that the average classification accuracy of the SVM, with a linear kernel function, outperforms other classifiers with feature ensembles, Hudgin's feature set and auto regression (AR) coefficients. However, the slight improvement in classification accuracy of SVM incurs more processing time and memory space in the low-level controller. The Kruskal-Wallis (KW) test also shows that there is no significant difference in the classification performance of SLR with Hudgin's feature set to that of SVM with Hudgin's features along with AR coefficients. In addition, the KW test shows that SLR was found to be better in respect to computation time and memory space, which is vital in a low-level controller. Similar to SVM, with a linear kernel function, other non-feature selective LDA and NN classifiers also show a slight improvement in performance using twice the features but with the drawback of increased memory space requirement and time

  20. Supralaryngeal muscle activity during sustained vibrato in four sopranos: surface EMG findings.

    PubMed

    Sapir, S; Larson, K K

    1993-09-01

    Four classically trained sopranos, aged 22-41 years, sustained a vibrato at a comfortable loudness level, and at different vowels (/u/, /i/, or /a/) and pitch levels (220, 277, 349, 440, 554, 698, or 880 Hz). Pairs of surface electrodes were placed on each singer's right side over the submandibular region, the thyroid cartilage, mandibular ramus, and upper lip to record electromyographic (EMG) activity from the anterior suprahyoid (ASH), extralaryngeal (ELAR), massetter (MAS), and perioral (PER) muscles, respectively. A headset-mounted miniature microphone transduced the voice, and a Kay Visi-Pitch extracted the voice fundamental frequency (F0). The output of the Visi-Pitch, a voltage analog of the F0 (VF0), and the EMG signals were digitized, the EMG signals rectified and smoothed, and the VF0 and smoothed EMG signals were subjected to Fast Fourier Transform (FFT) analysis. Spectral peaks in the FFT records indicated vibrato-related activity in the ASH and ELAR muscles, with occasional vibrato-related activity in the MAS and PER muscles. The role of supralaryngeal muscles in vibrato is discussed. PMID:8353638

  1. Real-time motion discrimination considering variation of EMG signals associated with lapse of time.

    PubMed

    Shiraki, Masashi; Tsujiuchi, Nobutaka; Akihito, Ito; Yamamoto, Tetsushi

    2015-08-01

    This study proposes a motion discrimination method that considers the variation of electromyogram (EMG) signals associated with a lapse of time. In a previous study, we proposed a real-time discrimination method based on EMG signals of the forearm. Our method uses a hypersphere model as a discriminator. In motion discrimination using EMG signals, one problem is to maintain high discrimination accuracy over time because EMG signals change with a lapse of time. This study analyzed the effect of changes in EMG signals on our method. Based on analysis results, adding a relearning system of the decision criteria to the discrimination system was expected to be effective. We created a new motion discrimination method that contains the relearning system and experimentally verified its effectiveness. The motion discrimination system discriminated three hand motions, open, grasp, and pinch with discrimination accuracy above 90% in real-time (processing time below 300 ms) even after time elapsed. PMID:26736306

  2. Applications of ICA and fractal dimension in sEMG signal processing for subtle movement analysis: a review.

    PubMed

    Naik, Ganesh R; Arjunan, Sridhar; Kumar, Dinesh

    2011-06-01

    The surface electromyography (sEMG) signal separation and decphompositions has always been an interesting research topic in the field of rehabilitation and medical research. Subtle myoelectric control is an advanced technique concerned with the detection, processing, classification, and application of myoelectric signals to control human-assisting robots or rehabilitation devices. This paper reviews recent research and development in independent component analysis and Fractal dimensional analysis for sEMG pattern recognition, and presents state-of-the-art achievements in terms of their type, structure, and potential application. Directions for future research are also briefly outlined.

  3. Surface EMG in advanced hand prosthetics.

    PubMed

    Castellini, Claudio; van der Smagt, Patrick

    2009-01-01

    One of the major problems when dealing with highly dexterous, active hand prostheses is their control by the patient wearing them. With the advances in mechatronics, building prosthetic hands with multiple active degrees of freedom is realisable, but actively controlling the position and especially the exerted force of each finger cannot yet be done naturally. This paper deals with advanced robotic hand control via surface electromyography. Building upon recent results, we show that machine learning, together with a simple downsampling algorithm, can be effectively used to control on-line, in real time, finger position as well as finger force of a highly dexterous robotic hand. The system determines the type of grasp a human subject is willing to use, and the required amount of force involved, with a high degree of accuracy. This represents a remarkable improvement with respect to the state-of-the-art of feed-forward control of dexterous mechanical hands, and opens up a scenario in which amputees will be able to control hand prostheses in a much finer way than it has so far been possible.

  4. Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition

    PubMed Central

    Chen, Maoqi

    2016-01-01

    Decomposition of electromyograms (EMG) is a key approach to investigating motor unit plasticity. Various signal processing techniques have been developed for high density surface EMG decomposition, among which the convolution kernel compensation (CKC) has achieved high decomposition yield with extensive validation. Very recently, a progressive FastICA peel-off (PFP) framework has also been developed for high density surface EMG decomposition. In this study, the CKC and PFP methods were independently applied to decompose the same sets of high density surface EMG signals. Across 91 trials of 64-channel surface EMG signals recorded from the first dorsal interosseous (FDI) muscle of 9 neurologically intact subjects, there were a total of 1477 motor units identified from the two methods, including 969 common motor units. On average, 10.6 ± 4.3 common motor units were identified from each trial, which showed a very high matching rate of 97.85 ± 1.85% in their discharge instants. The high degree of agreement of common motor units from the CKC and the PFP processing provides supportive evidence of the decomposition accuracy for both methods. The different motor units obtained from each method also suggest that combination of the two methods may have the potential to further increase the decomposition yield.

  5. Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition.

    PubMed

    Chen, Maoqi; Holobar, Ales; Zhang, Xu; Zhou, Ping

    2016-01-01

    Decomposition of electromyograms (EMG) is a key approach to investigating motor unit plasticity. Various signal processing techniques have been developed for high density surface EMG decomposition, among which the convolution kernel compensation (CKC) has achieved high decomposition yield with extensive validation. Very recently, a progressive FastICA peel-off (PFP) framework has also been developed for high density surface EMG decomposition. In this study, the CKC and PFP methods were independently applied to decompose the same sets of high density surface EMG signals. Across 91 trials of 64-channel surface EMG signals recorded from the first dorsal interosseous (FDI) muscle of 9 neurologically intact subjects, there were a total of 1477 motor units identified from the two methods, including 969 common motor units. On average, 10.6 ± 4.3 common motor units were identified from each trial, which showed a very high matching rate of 97.85 ± 1.85% in their discharge instants. The high degree of agreement of common motor units from the CKC and the PFP processing provides supportive evidence of the decomposition accuracy for both methods. The different motor units obtained from each method also suggest that combination of the two methods may have the potential to further increase the decomposition yield.

  6. Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition

    PubMed Central

    Chen, Maoqi

    2016-01-01

    Decomposition of electromyograms (EMG) is a key approach to investigating motor unit plasticity. Various signal processing techniques have been developed for high density surface EMG decomposition, among which the convolution kernel compensation (CKC) has achieved high decomposition yield with extensive validation. Very recently, a progressive FastICA peel-off (PFP) framework has also been developed for high density surface EMG decomposition. In this study, the CKC and PFP methods were independently applied to decompose the same sets of high density surface EMG signals. Across 91 trials of 64-channel surface EMG signals recorded from the first dorsal interosseous (FDI) muscle of 9 neurologically intact subjects, there were a total of 1477 motor units identified from the two methods, including 969 common motor units. On average, 10.6 ± 4.3 common motor units were identified from each trial, which showed a very high matching rate of 97.85 ± 1.85% in their discharge instants. The high degree of agreement of common motor units from the CKC and the PFP processing provides supportive evidence of the decomposition accuracy for both methods. The different motor units obtained from each method also suggest that combination of the two methods may have the potential to further increase the decomposition yield. PMID:27642525

  7. Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition.

    PubMed

    Chen, Maoqi; Holobar, Ales; Zhang, Xu; Zhou, Ping

    2016-01-01

    Decomposition of electromyograms (EMG) is a key approach to investigating motor unit plasticity. Various signal processing techniques have been developed for high density surface EMG decomposition, among which the convolution kernel compensation (CKC) has achieved high decomposition yield with extensive validation. Very recently, a progressive FastICA peel-off (PFP) framework has also been developed for high density surface EMG decomposition. In this study, the CKC and PFP methods were independently applied to decompose the same sets of high density surface EMG signals. Across 91 trials of 64-channel surface EMG signals recorded from the first dorsal interosseous (FDI) muscle of 9 neurologically intact subjects, there were a total of 1477 motor units identified from the two methods, including 969 common motor units. On average, 10.6 ± 4.3 common motor units were identified from each trial, which showed a very high matching rate of 97.85 ± 1.85% in their discharge instants. The high degree of agreement of common motor units from the CKC and the PFP processing provides supportive evidence of the decomposition accuracy for both methods. The different motor units obtained from each method also suggest that combination of the two methods may have the potential to further increase the decomposition yield. PMID:27642525

  8. Amplitude and frequency changes in surface EMG of biceps femoris during five days Bruce Protocol treadmill test.

    PubMed

    Jamaluddin, Fauzani N; Ahmad, Siti A; Noor, Samsul Bahari Mohd; Hassan, Wan Zuha Wan; Yaakob, Azhar; Adam, Yunus; Ali, Sawal H M

    2015-08-01

    Electromyography (EMG) is one of the indirect tools in indexing fatigue. Fatigue can be detected when there are changes on amplitude and frequency. However, various outcomes from literature make researchers conclude that EMG is not a reliable tool to measure fatigue. This paper investigates EMG behavior of biceps femoris in median frequency and mean absolute value during five days of Bruce Protocol treadmill test. Before that, surface EMG signals are filtered using band pass filter cut-off at 20-500Hz and are de-noised using db45 1-decimated wavelet transform. Five participants achieved more than 85% of their maximal heart rate during the running activity. The authors also consider other markers of fatigue such as performance, muscle soreness and lethargy as indicators to adaptation and maladaptation conditions. Result shows that turning points of median frequency and mean absolute value are very significant in indexing fatigue and indicators to adaptation of resistive training. PMID:26737713

  9. Effect of spatial filtering on crosstalk reduction in surface EMG recordings.

    PubMed

    Mesin, Luca; Smith, Stuart; Hugo, Suzanne; Viljoen, Suretha; Hanekom, Tania

    2009-04-01

    Increasing the selectivity of the detection system in surface electromyography (EMG) is beneficial in the collection of information of a specific portion of the investigated muscle and to reduce the contribution of undesired components, such as non-propagating components (due to generation or end-of-fibre effects) or crosstalk from nearby muscles. A comparison of the ability of different spatial filters to reduce the amount of crosstalk in surface EMG measurements was conducted in this paper using simulated signals. It focused on the influence of different properties of the muscle anatomy (changing subcutaneous layer thickness, skin conductivity, fibre length) and detection system (single, double and normal double differential, with two inter-electrode distances - IED) on the amount of crosstalk present in the measurements. A cylindrical multilayer (skin, subcutaneous tissue, muscle, bone) analytical model was used to simulate single fibre action potentials (SFAPs). Fibres were grouped together in motor units (MUs) and motor unit action potentials (MUAPs) were obtained by adding the SFAPs of the corresponding fibres. Interference surface EMG signals were obtained, modelling the recruitment of MUs and rate coding. The average rectified value (ARV) and mean frequency (MNF) content of the EMG signals were studied and used as a basis for determining the selectivity of each spatial filter. From these results it was found that the selectivity of each spatial filter varies depending on the transversal location of the measurement electrodes and on the anatomy. An increase in skin conductivity favourably affects the selectivity of normal double differential filters as does an increase in subcutaneous layer thickness. An increase in IED decreases the selectivity of all the analysed filters.

  10. Intra-session and inter-day reliability of forearm surface EMG during varying hand grip forces.

    PubMed

    Hashemi Oskouei, Alireza; Paulin, Michael G; Carman, Allan B

    2013-02-01

    Surface electromyography (EMG) is widely used to evaluate forearm muscle function and predict hand grip forces; however, there is a lack of literature on its intra-session and inter-day reliability. The aim of this study was to determine reliability of surface EMG of finger and wrist flexor muscles across varying grip forces. Surface EMG was measured from six forearm flexor muscles of 23 healthy adults. Eleven of these subjects undertook inter-day test-retest. Six repetitions of five randomized isometric grip forces between 0% and 80% of maximum force (MVC) were recorded and normalized to MVC. Intra- and inter-day reliability were calculated through the intraclass correlation coefficient (ICC) and standard error of measurement (SEM). Normalized EMG produced excellent intra-session ICC of 0.90 when repeated measurements were averaged. Intra-session SEM was low at low grip forces, however, corresponding normalized SEM was high (23-45%) due to the small magnitude of EMG signals. This may limit the ability to evaluate finer forearm muscle function and hand grip forces in daily tasks. Combining EMG of functionally related muscles improved intra-session SEM, improving within-subject reliability without taking multiple measurements. Removing and replacing electrodes inter-day produced poor ICC (ICC < 0.50) but did not substantially affect SEM.

  11. Examination of Hand Muscle Activation and Motor Unit Indices Derived from Surface EMG in Chronic Stroke

    PubMed Central

    Li, Xiaoyan; Liu, Jie; Li, Sheng; Wang, Ying-Chih

    2014-01-01

    In this study, we used muscle and motor unit indices, derived from convenient surface electromyography (EMG) measurements, for examination of paretic muscle changes post stroke. For 12 stroke subjects, compound muscle action potential and voluntary surface EMG signals were recorded from paretic and contralateral first dorsal interosseous, abductor pollicis brevis, and abductor digiti minimi muscles. Muscle activation index (AI), motor unit number index (MUNIX), and motor unit size index (MUSIX) were then calculated for each muscle. There was a significant AI reduction for all the three muscles in paretic side compared with contralateral side, providing an evidence of muscle activation deficiency after stroke. The hand MUNIX (defined by summing the values from the three muscles) was significantly reduced in paretic side compared with contralateral side, whereas the hand MUSIX was not significantly different. Furthermore, diverse changes in MUNIX and MUSIX were observed from the three muscles. A major feature of the present examinations is the primary reliance on surface EMG, which offers practical benefits because it is noninvasive, induces minimal discomfort and can be performed quickly. PMID:24967982

  12. Bilinear modeling of EMG signals to extract user-independent features for multiuser myoelectric interface.

    PubMed

    Matsubara, Takamitsu; Morimoto, Jun

    2013-08-01

    In this study, we propose a multiuser myoelectric interface that can easily adapt to novel users. When a user performs different motions (e.g., grasping and pinching), different electromyography (EMG) signals are measured. When different users perform the same motion (e.g., grasping), different EMG signals are also measured. Therefore, designing a myoelectric interface that can be used by multiple users to perform multiple motions is difficult. To cope with this problem, we propose for EMG signals a bilinear model that is composed of two linear factors: 1) user dependent and 2) motion dependent. By decomposing the EMG signals into these two factors, the extracted motion-dependent factors can be used as user-independent features. We can construct a motion classifier on the extracted feature space to develop the multiuser interface. For novel users, the proposed adaptation method estimates the user-dependent factor through only a few interactions. The bilinear EMG model with the estimated user-dependent factor can extract the user-independent features from the novel user data. We applied our proposed method to a recognition task of five hand gestures for robotic hand control using four-channel EMG signals measured from subject forearms. Our method resulted in 73% accuracy, which was statistically significantly different from the accuracy of standard nonmultiuser interfaces, as the result of a two-sample t -test at a significance level of 1%.

  13. Experimental analysis of accuracy in the identification of motor unit spike trains from high-density surface EMG.

    PubMed

    Holobar, Ales; Minetto, Marco Alessandro; Botter, Alberto; Negro, Francesco; Farina, Dario

    2010-06-01

    The aim of this study was to compare the decomposition results obtained from high-density surface electromyography (EMG) and concurrently recorded intramuscular EMG. Surface EMG signals were recorded with electrode grids from the tibialis anterior, biceps brachii, and abductor digiti minimi muscles of twelve healthy men during isometric contractions ranging between 5% and 20% of the maximal force. Bipolar intramuscular EMG signals were recorded with pairs of wire electrodes. Surface and intramuscular EMG were independently decomposed into motor unit spike trains. When averaged over all the contractions of the same contraction force, the percentage of discharge times of motor units identified by both decompositions varied in the ranges 84%-87% (tibialis anterior), 84%-86% (biceps brachii), and 87%-92% (abductor digiti minimi) across the force levels analyzed. This index of agreement between the two decompositions was linearly correlated with a self-consistency measure of motor unit discharge pattern that was based on coefficient of variation for the interspike interval (R(2) = 0.68 for tibialis anterior, R(2) = 0.56 for biceps brachii, and R(2) = 0.38 for abductor digiti minimi). These results constitute an important contribution to the validation of the noninvasive approach for the investigation of motor unit behavior in isometric low-force tasks.

  14. Characterization of stroke- and aging-related changes in the complexity of EMG signals during tracking tasks.

    PubMed

    Ao, Di; Sun, Rui; Tong, Kai-Yu; Song, Rong

    2015-04-01

    To explore the stroke- and aging-induced neurological changes in paretic muscles from an entropy point of view, fuzzy approximate entropy (fApEn) was utilized to represent the complexity of EMG signals in elbow-tracking tasks. In the experiment, 11 patients after stroke and 20 healthy control subjects (10 young and 10 age-matched adults) were recruited and asked to perform elbow sinusoidal trajectory tracking tasks. During the tests, the elbow angle and electromyographic (EMG) signals of the biceps brachii and triceps brachii were recorded simultaneously. The results showed significant differences in fApEn values of both biceps and triceps EMG among four groups at six velocities (p < 0.01), with fApEn values in the following order: affected sides of stroke patients < unaffected sides of stroke patients < age-matched controls < young controls. A possible mechanism underlying the smaller fApEn values in the affected sides in comparison with aged-matched controls and in the aged individuals in comparison with young controls might be the reduction in the number and firing rate of active motor units. This method and index provide evidence of neurological changes after stroke and aging by complexity analysis of the surface EMG signals. Further studies are needed to validate and facilitate the application in clinic.

  15. Basic reporting and interpretation of surface EMG amplitude and mean power frequency: a reply to Vitgotsky, Ogborn, and Phillips.

    PubMed

    Jenkins, Nathaniel D M; Housh, Terry J; Bergstrom, Haley C; Cochrane, Kristen C; Hill, Ethan C; Smith, Cory M; Johnson, Glen O; Schmidt, Richard J; Cramer, Joel T

    2016-03-01

    In this response, we addressed the specific issues raised by Vigotsky et al. and clarified (1) our methods and adherence to electromyographic signal reporting standards, (2) our interpretation of EMG amplitude, and (3) our interpretation of EMG mean power frequency.

  16. Effect of Vibration Training on Anaerobic Power and Quardroceps Surface EMG in Long Jumpers

    ERIC Educational Resources Information Center

    Liu, Bin; Luo, Jiong

    2015-01-01

    Objective: To explore the anaerobic power and surface EMG (sEMG) of quardrocep muscle in lower extremities after single vibration training intervention. Methods: 8 excellent male long jumpers voluntarily participated in this study. Four intervention modes were devised, including high frequency high amplitude (HFHA,30Hz,6mm), low frequency low…

  17. Effective low-power wearable wireless surface EMG sensor design based on analog-compressed sensing.

    PubMed

    Balouchestani, Mohammadreza; Krishnan, Sridhar

    2014-12-17

    Surface Electromyography (sEMG) is a non-invasive measurement process that does not involve tools and instruments to break the skin or physically enter the body to investigate and evaluate the muscular activities produced by skeletal muscles. The main drawbacks of existing sEMG systems are: (1) they are not able to provide real-time monitoring; (2) they suffer from long processing time and low speed; (3) they are not effective for wireless healthcare systems because they consume huge power. In this work, we present an analog-based Compressed Sensing (CS) architecture, which consists of three novel algorithms for design and implementation of wearable wireless sEMG bio-sensor. At the transmitter side, two new algorithms are presented in order to apply the analog-CS theory before Analog to Digital Converter (ADC). At the receiver side, a robust reconstruction algorithm based on a combination of ℓ1-ℓ1-optimization and Block Sparse Bayesian Learning (BSBL) framework is presented to reconstruct the original bio-signals from the compressed bio-signals. The proposed architecture allows reducing the sampling rate to 25% of Nyquist Rate (NR). In addition, the proposed architecture reduces the power consumption to 40%, Percentage Residual Difference (PRD) to 24%, Root Mean Squared Error (RMSE) to 2%, and the computation time from 22 s to 9.01 s, which provide good background for establishing wearable wireless healthcare systems. The proposed architecture achieves robust performance in low Signal-to-Noise Ratio (SNR) for the reconstruction process.

  18. Surface EMG-based Sketching Recognition Using Two Analysis Windows and Gene Expression Programming

    PubMed Central

    Yang, Zhongliang; Chen, Yumiao

    2016-01-01

    Sketching is one of the most important processes in the conceptual stage of design. Previous studies have relied largely on the analyses of sketching process and outcomes; whereas surface electromyographic (sEMG) signals associated with sketching have received little attention. In this study, we propose a method in which 11 basic one-stroke sketching shapes are identified from the sEMG signals generated by the forearm and upper arm muscles from 4 subjects. Time domain features such as integrated electromyography, root mean square and mean absolute value were extracted with analysis windows of two length conditions for pattern recognition. After reducing data dimensionality using principal component analysis, the shapes were classified using Gene Expression Programming (GEP). The performance of the GEP classifier was compared to the Back Propagation neural network (BPNN) and the Elman neural network (ENN). Feature extraction with the short analysis window (250 ms with a 250 ms increment) improved the recognition rate by around 6.4% averagely compared with the long analysis window (2500 ms with a 2500 ms increment). The average recognition rate for the eleven basic one-stroke sketching patterns achieved by the GEP classifier was 96.26% in the training set and 95.62% in the test set, which was superior to the performance of the BPNN and ENN classifiers. The results show that the GEP classifier is able to perform well with either length of the analysis window. Thus, the proposed GEP model show promise for recognizing sketching based on sEMG signals. PMID:27790083

  19. Effective Low-Power Wearable Wireless Surface EMG Sensor Design Based on Analog-Compressed Sensing

    PubMed Central

    Balouchestani, Mohammadreza; Krishnan, Sridhar

    2014-01-01

    Surface Electromyography (sEMG) is a non-invasive measurement process that does not involve tools and instruments to break the skin or physically enter the body to investigate and evaluate the muscular activities produced by skeletal muscles. The main drawbacks of existing sEMG systems are: (1) they are not able to provide real-time monitoring; (2) they suffer from long processing time and low speed; (3) they are not effective for wireless healthcare systems because they consume huge power. In this work, we present an analog-based Compressed Sensing (CS) architecture, which consists of three novel algorithms for design and implementation of wearable wireless sEMG bio-sensor. At the transmitter side, two new algorithms are presented in order to apply the analog-CS theory before Analog to Digital Converter (ADC). At the receiver side, a robust reconstruction algorithm based on a combination of ℓ1-ℓ1-optimization and Block Sparse Bayesian Learning (BSBL) framework is presented to reconstruct the original bio-signals from the compressed bio-signals. The proposed architecture allows reducing the sampling rate to 25% of Nyquist Rate (NR). In addition, the proposed architecture reduces the power consumption to 40%, Percentage Residual Difference (PRD) to 24%, Root Mean Squared Error (RMSE) to 2%, and the computation time from 22 s to 9.01 s, which provide good background for establishing wearable wireless healthcare systems. The proposed architecture achieves robust performance in low Signal-to-Noise Ratio (SNR) for the reconstruction process. PMID:25526357

  20. Physiological modules for generating discrete and rhythmic movements: component analysis of EMG signals.

    PubMed

    Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana Maria; Dan, Bernard; Cheron, Guy; McIntyre, Joseph

    2014-01-01

    A central question in Neuroscience is that of how the nervous system generates the spatiotemporal commands needed to realize complex gestures, such as handwriting. A key postulate is that the central nervous system (CNS) builds up complex movements from a set of simpler motor primitives or control modules. In this study we examined the control modules underlying the generation of muscle activations when performing different types of movement: discrete, point-to-point movements in eight different directions and continuous figure-eight movements in both the normal, upright orientation and rotated 90°. To test for the effects of biomechanical constraints, movements were performed in the frontal-parallel or sagittal planes, corresponding to two different nominal flexion/abduction postures of the shoulder. In all cases we measured limb kinematics and surface electromyographic activity (EMG) signals for seven different muscles acting around the shoulder. We first performed principal component analysis (PCA) of the EMG signals on a movement-by-movement basis. We found a surprisingly consistent pattern of muscle groupings across movement types and movement planes, although we could detect systematic differences between the PCs derived from movements performed in each shoulder posture and between the principal components associated with the different orientations of the figure. Unexpectedly we found no systematic differences between the figure eights and the point-to-point movements. The first three principal components could be associated with a general co-contraction of all seven muscles plus two patterns of reciprocal activation. From these results, we surmise that both "discrete-rhythmic movements" such as the figure eight, and discrete point-to-point movement may be constructed from three different fundamental modules, one regulating the impedance of the limb over the time span of the movement and two others operating to generate movement, one aligned with the

  1. Physiological modules for generating discrete and rhythmic movements: component analysis of EMG signals

    PubMed Central

    Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana Maria; Dan, Bernard; Cheron, Guy; McIntyre, Joseph

    2015-01-01

    A central question in Neuroscience is that of how the nervous system generates the spatiotemporal commands needed to realize complex gestures, such as handwriting. A key postulate is that the central nervous system (CNS) builds up complex movements from a set of simpler motor primitives or control modules. In this study we examined the control modules underlying the generation of muscle activations when performing different types of movement: discrete, point-to-point movements in eight different directions and continuous figure-eight movements in both the normal, upright orientation and rotated 90°. To test for the effects of biomechanical constraints, movements were performed in the frontal-parallel or sagittal planes, corresponding to two different nominal flexion/abduction postures of the shoulder. In all cases we measured limb kinematics and surface electromyographic activity (EMG) signals for seven different muscles acting around the shoulder. We first performed principal component analysis (PCA) of the EMG signals on a movement-by-movement basis. We found a surprisingly consistent pattern of muscle groupings across movement types and movement planes, although we could detect systematic differences between the PCs derived from movements performed in each shoulder posture and between the principal components associated with the different orientations of the figure. Unexpectedly we found no systematic differences between the figure eights and the point-to-point movements. The first three principal components could be associated with a general co-contraction of all seven muscles plus two patterns of reciprocal activation. From these results, we surmise that both “discrete-rhythmic movements” such as the figure eight, and discrete point-to-point movement may be constructed from three different fundamental modules, one regulating the impedance of the limb over the time span of the movement and two others operating to generate movement, one aligned with the

  2. Rectification is required to extract oscillatory envelope modulation from surface electromyographic signals.

    PubMed

    Dakin, Christopher J; Dalton, Brian H; Luu, Billy L; Blouin, Jean-Sébastien

    2014-10-01

    Rectification of surface electromyographic (EMG) recordings prior to their correlation with other signals is a widely used form of preprocessing. Recently this practice has come into question, elevating the subject of EMG rectification to a topic of much debate. Proponents for rectifying suggest it accentuates the EMG spike timing information, whereas opponents indicate it is unnecessary and its nonlinear distortion of data is potentially destructive. Here we examine the necessity of rectification on the extraction of muscle responses, but for the first time using a known oscillatory input to the muscle in the form of electrical vestibular stimulation. Participants were exposed to sinusoidal vestibular stimuli while surface and intramuscular EMG were recorded from the left medial gastrocnemius. We compared the unrectified and rectified surface EMG to single motor units to determine which method best identified stimulus-EMG coherence and phase at the single-motor unit level. Surface EMG modulation at the stimulus frequency was obvious in the unrectified surface EMG. However, this modulation was not identified by the fast Fourier transform, and therefore stimulus coherence with the unrectified EMG signal failed to capture this covariance. Both the rectified surface EMG and single motor units displayed significant coherence over the entire stimulus bandwidth (1-20 Hz). Furthermore, the stimulus-phase relationship for the rectified EMG and motor units shared a moderate correlation (r = 0.56). These data indicate that rectification of surface EMG is a necessary step to extract EMG envelope modulation due to motor unit entrainment to a known stimulus.

  3. Nonlinear Analysis of Surface EMG Time Series of Back Muscles

    NASA Astrophysics Data System (ADS)

    Dolton, Donald C.; Zurcher, Ulrich; Kaufman, Miron; Sung, Paul

    2004-10-01

    A nonlinear analysis of surface electromyography time series of subjects with and without low back pain is presented. The mean-square displacement and entropy shows anomalous diffusive behavior on intermediate time range 10 ms < t < 1 s. This behavior implies the presence of correlations in the signal. We discuss the shape of the power spectrum of the signal.

  4. A Review of Classification Techniques of EMG Signals during Isotonic and Isometric Contractions

    PubMed Central

    Nazmi, Nurhazimah; Abdul Rahman, Mohd Azizi; Yamamoto, Shin-Ichiroh; Ahmad, Siti Anom; Zamzuri, Hairi; Mazlan, Saiful Amri

    2016-01-01

    In recent years, there has been major interest in the exposure to physical therapy during rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and human machine interface (HMI) applications. An automated system will guide the user to perform the training during rehabilitation independently. Advances in engineering have extended electromyography (EMG) beyond the traditional diagnostic applications to also include applications in diverse areas such as movement analysis. This paper gives an overview of the numerous methods available to recognize motion patterns of EMG signals for both isotonic and isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who would like to select the most appropriate methodology in classifying motion patterns, especially during different types of contractions. For feature extraction, the probability density function (PDF) of EMG signals will be the main interest of this study. Following that, a brief explanation of the different methods for pre-processing, feature extraction and classifying EMG signals will be compared in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above. PMID:27548165

  5. A Review of Classification Techniques of EMG Signals during Isotonic and Isometric Contractions.

    PubMed

    Nazmi, Nurhazimah; Abdul Rahman, Mohd Azizi; Yamamoto, Shin-Ichiroh; Ahmad, Siti Anom; Zamzuri, Hairi; Mazlan, Saiful Amri

    2016-01-01

    In recent years, there has been major interest in the exposure to physical therapy during rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and human machine interface (HMI) applications. An automated system will guide the user to perform the training during rehabilitation independently. Advances in engineering have extended electromyography (EMG) beyond the traditional diagnostic applications to also include applications in diverse areas such as movement analysis. This paper gives an overview of the numerous methods available to recognize motion patterns of EMG signals for both isotonic and isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who would like to select the most appropriate methodology in classifying motion patterns, especially during different types of contractions. For feature extraction, the probability density function (PDF) of EMG signals will be the main interest of this study. Following that, a brief explanation of the different methods for pre-processing, feature extraction and classifying EMG signals will be compared in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above. PMID:27548165

  6. A comparative study of surface EMG classification by fuzzy relevance vector machine and fuzzy support vector machine.

    PubMed

    Xie, Hong-Bo; Huang, Hu; Wu, Jianhua; Liu, Lei

    2015-02-01

    We present a multiclass fuzzy relevance vector machine (FRVM) learning mechanism and evaluate its performance to classify multiple hand motions using surface electromyographic (sEMG) signals. The relevance vector machine (RVM) is a sparse Bayesian kernel method which avoids some limitations of the support vector machine (SVM). However, RVM still suffers the difficulty of possible unclassifiable regions in multiclass problems. We propose two fuzzy membership function-based FRVM algorithms to solve such problems, based on experiments conducted on seven healthy subjects and two amputees with six hand motions. Two feature sets, namely, AR model coefficients and room mean square value (AR-RMS), and wavelet transform (WT) features, are extracted from the recorded sEMG signals. Fuzzy support vector machine (FSVM) analysis was also conducted for wide comparison in terms of accuracy, sparsity, training and testing time, as well as the effect of training sample sizes. FRVM yielded comparable classification accuracy with dramatically fewer support vectors in comparison with FSVM. Furthermore, the processing delay of FRVM was much less than that of FSVM, whilst training time of FSVM much faster than FRVM. The results indicate that FRVM classifier trained using sufficient samples can achieve comparable generalization capability as FSVM with significant sparsity in multi-channel sEMG classification, which is more suitable for sEMG-based real-time control applications.

  7. The linear synchronization measures of uterine EMG signals: Evidence of synchronized action potentials during propagation.

    PubMed

    Domino, Malgorzata; Pawlinski, Bartosz; Gajewski, Zdzislaw

    2016-11-01

    Evaluation of synchronization between myoelectric signals can give new insights into the functioning of the complex system of porcine myometrium. We propose a model of uterine contractions according to the hypothesis of action potentials similarity which is possible to detect during propagation in the uterine wall. We introduce similarity measures based on the concept of synchronization as used in matching linear signals such as electromyographic (EMG) time series data. The aim was to present linear measures to assess synchronization between contractions in different topographic regions of the uterus. We use the cross-correlation function (ƒx,y[l], ƒy,z[l]) and the cross-coherence function (Cxy[ƒ], Cyz[ƒ]) to assess synchronization between three data series of a diestral uterine EMG bundles in porcine reproductive tract. Spontaneous uterine activity was recorded using telemetry method directly by three-channel transmitter and three silver bipolar needle electrodes sutured on different topographic regions of the reproductive tract in the sow. The results show the usefulness of the cross-coherence function in that synchronization between uterine horn and corpus uteri for multiple action potentials (bundles) could be observed. The EMG bundles synchronization may be used to investigate the direction and velocity of EMG signals propagation in porcine reproductive tract. PMID:27570104

  8. Relation between isometric muscle force and surface EMG in intrinsic hand muscles as function of the arm geometry.

    PubMed

    Del Santo, Francesco; Gelli, Francesca; Ginanneschi, Federica; Popa, Traian; Rossi, Alessandro

    2007-08-13

    Evidence exists that shoulder joint geometry influences recruitment efficiency and force-generating capacity of hand muscles [Ginanneschi, F., Del Santo, F., Dominici, F., Gelli, F., Mazzocchio, R., Rossi, A., 2005. Changes in corticomotor excitability of hand muscles in relation to static shoulder positions. Exp. Brain Res. 161 (3), 374-382; Dominici, F., Popa, T., Ginanneschi, F., Mazzocchio, R., Rossi, A., 2005. Cortico-motoneural output to intrinsic hand muscles is differentially influenced by static changes in shoulder positions. Exp. Brain Res. 164 (4), 500-504]. The present study was designed to examine the impact of changing shoulder joint position on the relation between surface EMG amplitude and isometric force production of the abductor digiti minimi muscle (ADM). EMG-force relation of ADM was examined in two shoulder positions: 30 degrees adduction (ANT) and 30 degrees abduction (POST) on the horizontal plane, i.e. under higher and lower force-generating capacity, respectively. The relation was studied over the full range isometric force (10-100% of maximum force in 10% increments, 3 s duration) by analysing root mean square (RMS), median frequency (Mf) of the power spectrum and non-linear recurrence quantification analysis (percentage of determinism: %DET) of the surface EMG signals. We found that in POST, the slope of the RMS-force relation was significantly higher than in ANT, while its general shape (strictly linear) was preserved. Averaged Mf of the EMG power spectrum was significantly higher in POST that in ANT, while no difference in %DET was observed between the two shoulder positions. The higher slope of the EMG-force relation in POST than in ANT is interpreted in terms of increased gain of the excitatory drive-firing rate relation. It is concluded that discharge from sensory receptors signalling shoulder position may act to regulate the gain of the excitatory drive-firing rate relation of motoneurones in order to compensate for reduced

  9. Differences in Contraction-Induced Hemodynamics and Surface EMG in Duchenne Muscular Dystrophy.

    PubMed

    Van Ginderdeuren, Eva; Caicedo, Alexander; Taelmans, Joachim; Goemans, Nathalie; van den Hauwe, Marlen; Naulaers, Gunnar; Van Huffel, Sabine; Buyse, Gunnar

    2016-01-01

    Duchenne muscular dystrophy (DMD) is the most common and devastating type of muscular dystrophy worldwide. In this study we have investigated the potential of the combined use of non-invasive near-infrared spectroscopy (NIRS) and surface electromyography (sEMG) to assess contraction-induced changes in oxygenation and myoelectrical activity, respectively in the biceps brachii of eight DMD patients aged 9-12 years and 11 age-matched healthy controls. Muscle tissue oxygenation index (TOI), oxyhemoglobin (HbO2), and sEMG signals were continuously measured during a sustained submaximal contraction of 60% maximal voluntary isometric contraction, and post-exercise recovery period. Compared to controls, DMD subjects showed significantly smaller changes in TOI during the contraction. In addition, during the reoxygenation phase some dynamic parameters extracted from the HbO2 measurements were significantly different between the two groups, some of which were correlated with functional performances on a 6-min walking test. In conclusion, non-invasive continuous monitoring of skeletal muscle oxygenation by NIRS is feasible in young children, and significant differences in contraction-induced deoxygenation and reoxygenation patterns were observed between healthy controls and DMD children.

  10. Novel Methods for Surface EMG Analysis and Exploration Based on Multi-Modal Gaussian Mixture Models.

    PubMed

    Vögele, Anna Magdalena; Zsoldos, Rebeka R; Krüger, Björn; Licka, Theresia

    2016-01-01

    This paper introduces a new method for data analysis of animal muscle activation during locomotion. It is based on fitting Gaussian mixture models (GMMs) to surface EMG data (sEMG). This approach enables researchers/users to isolate parts of the overall muscle activation within locomotion EMG data. Furthermore, it provides new opportunities for analysis and exploration of sEMG data by using the resulting Gaussian modes as atomic building blocks for a hierarchical clustering. In our experiments, composite peak models representing the general activation pattern per sensor location (one sensor on the long back muscle, three sensors on the gluteus muscle on each body side) were identified per individual for all 14 horses during walk and trot in the present study. Hereby we show the applicability of the method to identify composite peak models, which describe activation of different muscles throughout cycles of locomotion. PMID:27362752

  11. Novel Methods for Surface EMG Analysis and Exploration Based on Multi-Modal Gaussian Mixture Models

    PubMed Central

    Vögele, Anna Magdalena; Zsoldos, Rebeka R.; Krüger, Björn; Licka, Theresia

    2016-01-01

    This paper introduces a new method for data analysis of animal muscle activation during locomotion. It is based on fitting Gaussian mixture models (GMMs) to surface EMG data (sEMG). This approach enables researchers/users to isolate parts of the overall muscle activation within locomotion EMG data. Furthermore, it provides new opportunities for analysis and exploration of sEMG data by using the resulting Gaussian modes as atomic building blocks for a hierarchical clustering. In our experiments, composite peak models representing the general activation pattern per sensor location (one sensor on the long back muscle, three sensors on the gluteus muscle on each body side) were identified per individual for all 14 horses during walk and trot in the present study. Hereby we show the applicability of the method to identify composite peak models, which describe activation of different muscles throughout cycles of locomotion. PMID:27362752

  12. Processing of surface EMG through pattern recognition techniques aimed at classifying shoulder joint movements.

    PubMed

    Rivela, Diletta; Scannella, Alessia; Pavan, Esteban E; Frigo, Carlo A; Belluco, Paolo; Gini, Giuseppina

    2015-01-01

    Artificial arms for shoulder disarticulation need a high number of degrees of freedom to be controlled. In order to control a prosthetic shoulder joint, an intention detection system based on surface electromyography (sEMG) pattern recognition methods was proposed and experimentally investigated. Signals from eight trunk muscles that are generally preserved after shoulder disarticulation were recorded from a group of eight normal subjects in nine shoulder positions. After data segmentation, four different features were extracted (sample entropy, cepstral coefficients of the 4th order, root mean square and waveform length) and classified by means of linear discriminant analysis. The classification accuracy was 92.1% and this performance reached 97.9% after reducing the positions considered to five classes. To reduce the computational cost, the two channels with the least discriminating information were neglected yielding to a classification accuracy diminished by just 4.08%. PMID:26736704

  13. Cross-correlation analysis of multichannel uterine EMG signals.

    PubMed

    Halabi, R; Diab, M O; Moslem, B; Khalil, M; Marque, C

    2012-01-01

    The prevention of preterm labor remains one of the primary goals of obstetric research. One way to achieve this goal effectively is to understand the mechanisms regulating the uterine contractility. Herein, we evaluate the correlation between uterine electrical activities recorded from spatially-distributed regions by calculating the nonlinear regression coefficient. Results have shown that, during pregnancy, the degree of interdependence between signals is very high whereas, at labor, the correlation between the signals decreases remarkably. We conclude that pregnancy is characterized by the presence of few local potential sources dominating the other sources while at the onset of labor, the number of these sources increases remarkably which affects therefore the correlation between the signals.

  14. Comparison study of EMG signals compression by methods transform using vector quantization, SPIHT and arithmetic coding.

    PubMed

    Ntsama, Eloundou Pascal; Colince, Welba; Ele, Pierre

    2016-01-01

    In this article, we make a comparative study for a new approach compression between discrete cosine transform (DCT) and discrete wavelet transform (DWT). We seek the transform proper to vector quantization to compress the EMG signals. To do this, we initially associated vector quantization and DCT, then vector quantization and DWT. The coding phase is made by the SPIHT coding (set partitioning in hierarchical trees coding) associated with the arithmetic coding. The method is demonstrated and evaluated on actual EMG data. Objective performance evaluations metrics are presented: compression factor, percentage root mean square difference and signal to noise ratio. The results show that method based on the DWT is more efficient than the method based on the DCT.

  15. Nonlinear parameters of surface EMG in schizophrenia patients depend on kind of antipsychotic therapy

    PubMed Central

    Meigal, Alexander Yu.; Miroshnichenko, German G.; Kuzmina, Anna P.; Rissanen, Saara M.; Georgiadis, Stefanos D.; Karjalainen, Pasi A.

    2015-01-01

    We compared a set of surface EMG (sEMG) parameters in several groups of schizophrenia (SZ, n = 74) patients and healthy controls (n = 11) and coupled them with the clinical data. sEMG records were quantified with spectral, mutual information (MI) based and recurrence quantification analysis (RQA) parameters, and with approximate and sample entropies (ApEn and SampEn). Psychotic deterioration was estimated with Positive and Negative Syndrome Scale (PANSS) and with the positive subscale of PANSS. Neuroleptic-induced parkinsonism (NIP) motor symptoms were estimated with Simpson-Angus Scale (SAS). Dyskinesia was measured with Abnormal Involuntary Movement Scale (AIMS). We found that there was no difference in values of sEMG parameters between healthy controls and drug-naïve SZ patients. The most specific group was formed of SZ patients who were administered both typical and atypical antipsychotics (AP). Their sEMG parameters were significantly different from those of SZ patients taking either typical or atypical AP or taking no AP. This may represent a kind of synergistic effect of these two classes of AP. For the clinical data we found that PANSS, SAS, and AIMS were not correlated to any of the sEMG parameters. Conclusion: with nonlinear parameters of sEMG it is possible to reveal NIP in SZ patients, and it may help to discriminate between different clinical groups of SZ patients. Combined typical and atypical AP therapy has stronger effect on sEMG than a therapy with AP of only one class. PMID:26217236

  16. Estimation of average muscle fiber conduction velocity from simulated surface EMG in pinnate muscles.

    PubMed

    Mesin, Luca; Damiano, Luisa; Farina, Dario

    2007-03-15

    The aim of this simulation study was to assess the bias in estimating muscle fiber conduction velocity (CV) from surface electromyographic (EMG) signals in muscles with one and two pinnation angles. The volume conductor was a layered medium simulating anisotropic muscle tissue and isotropic homogeneous subcutaneous tissue. The muscle tissue was homogeneous for one pinnation angle and inhomogeneous for bipinnate muscles (two fiber directions). Interference EMG signals were obtained by simulating recruitment thresholds and discharge patterns of a set of 100 and 200 motor units for the pinnate and bipinnate muscle, respectively (15 degrees pinnation angel in both cases). Without subcutaneous layer and muscle fibers with CV 4m/s, average CV estimates from the pinnate (bipinnate) muscle were 4.81+/-0.18 m/s (4.80+/-0.18 m/s) for bipolar, 4.71+/-0.19 m/s (4.71+/-0.12 m/s) for double differential, and 4.78+/-0.16 m/s (4.79+/-0.15m/s) for Laplacian recordings. When subcutaneous layer was added (thickness 1mm) in the same conditions, estimated CV values were 4.93+/-0.25 m/s (5.16+/-0.41 m/s), 4.70+/-0.21 m/s (4.83+/-0.33 m/s), and 4.89+/-0.21 m/s (4.99+/-0.39 m/s), for the three recording systems, respectively. The main factor biasing CV estimates was the propagation of action potentials in the two directions which influenced the recording due to the scatter of the projection of end-plate and tendon locations along the fiber direction, as a consequence of pinnation. The same problem arises in muscles with the line of innervation zone locations not perpendicular to fiber direction. These results indicate an important limitation in reliability of CV estimates from the interference EMG when the innervation zone and tendon locations are not distributed perpendicular to fiber direction.

  17. [Study on the surface EMG pattern classification with BP neural networks].

    PubMed

    Wang, R; Huang, C; Li, B; Jin, D; Zhang, J

    1998-03-01

    This paper presents a surface electromyography (EMG) motion pattern classifier which combines Neural Network (NN) with parametric model such as autoregressive (AR) model. This motion pattern classifier can successfully identify four types of movement of human hand, wrist flexion, wrist extension, forearm pronation and forearm supination, by using of the surface EMG detected from the flexor carpi radialis and the extensor carpi ulnaris. The result shows that it has a great potential application to the control of bionic man-machine systems such as prostheses because of its fast calculating speed, high recognition ability, and good robust.

  18. Integrating heterogeneous classifier ensembles for EMG signal decomposition based on classifier agreement.

    PubMed

    Rasheed, Sarbast; Stashuk, Daniel W; Kamel, Mohamed S

    2010-05-01

    In this paper, we present a design methodology for integrating heterogeneous classifier ensembles by employing a diversity-based hybrid classifier fusion approach, whose aggregator module consists of two classifier combiners, to achieve an improved classification performance for motor unit potential classification during electromyographic (EMG) signal decomposition. Following the so-called overproduce and choose strategy to classifier ensemble combination, the developed system allows the construction of a large set of base classifiers, and then automatically chooses subsets of classifiers to form candidate classifier ensembles for each combiner. The system exploits kappa statistic diversity measure to design classifier teams through estimating the level of agreement between base classifier outputs. The pool of base classifiers consists of different kinds of classifiers: the adaptive certainty-based, the adaptive fuzzy k -NN, and the adaptive matched template filter classifiers; and utilizes different types of features. Performance of the developed system was evaluated using real and simulated EMG signals, and was compared with the performance of the constituent base classifiers. Across the EMG signal datasets used, the developed system had better average classification performance overall, especially in terms of reducing classification errors. For simulated signals of varying intensity, the developed system had an average correct classification rate CCr of 93.8% and an error rate Er of 2.2% compared to 93.6% and 3.2%, respectively, for the best base classifier in the ensemble. For simulated signals with varying amounts of shape and/or firing pattern variability, the developed system had a CCr of 89.1% with an Er of 4.7% compared to 86.3% and 5.6%, respectively, for the best classifier. For real signals, the developed system had a CCr of 89.4% with an Er of 3.9% compared to 84.6% and 7.1%, respectively, for the best classifier.

  19. Classification of upper arm EMG signals during object-specific grasp.

    PubMed

    Martelloni, C; Carpaneto, J; Micera, S

    2008-01-01

    Electromyographic (EMG) signals can represent an interesting solution to control artificial hands because they are easy to record and can allow the user to control different robotic systems. However, after limb amputation the 'homologous' muscles are no more available to control the prosthetic device and for this reason complex pattern recognition approaches have to be developed to extract the voluntary commands by the user. This makes the control strategy less natural and acceptable and asks for alternative approaches. At the same time, it has been recently shown that (in monkeys) it is possible to discriminate grasping tasks just analyzing the activation onset/offset of upper limb muscles during the reaching phase. This kind of information can be very interesting because it can allow the development of a natural EMG-based control strategy based on the natural muscular activities selected by the central nervous system. In this paper, preliminary experiments have been carried out in order to verify whether these results can be confirmed also in human beings. In particular, a support vector machine (SVM) based pattern recognition algorithm has been developed and used for the prediction of grip types from the EMG recorded from proximal and distal muscles during reach to grasp movements of three able bodied subjects.

  20. [The blind source separation method based on self-organizing map neural network and convolution kernel compensation for multi-channel sEMG signals].

    PubMed

    Ning, Yong; Zhu, Shan'an; Zhao, Yuming

    2015-02-01

    A new method based on convolution kernel compensation (CKC) for decomposing multi-channel surface electromyogram (sEMG) signals is proposed in this paper. Unsupervised learning and clustering function of self-organizing map (SOM) neural network are employed in this method. An initial innervations pulse train (IPT) is firstly estimated, some time instants corresponding to the highest peaks from the initial IPT are clustered by SOM neural network. Then the final IPT can be obtained from the observations corresponding to these time instants. In this paper, the proposed method was tested on the simulated signal, the influence of signal to noise ratio (SNR), the number of groups clustered by SOM and the number of highest peaks selected from the initial pulse train on the number of reconstructed sources and the pulse accuracy were studied, and the results show that the proposed approach is effective in decomposing multi-channel sEMG signals. PMID:25997257

  1. Fourier and wavelet spectral analysis of EMG signals in supramaximal constant load dynamic exercise.

    PubMed

    Camata, Thiago V; Dantas, Jose L; Abrao, Taufik; Brunetto, Maria A C; Moraes, Antonio C; Altimari, Leandro R

    2010-01-01

    Frequency domain analyses of changes in electromyographic (EMG) signals over time are frequently used to assess muscle fatigue. Fourier based approaches are typically used in these analyses, yet Fourier analysis assumes signal stationarity, which is unlikely during dynamic contractions. Wavelet based methods of signal analysis do not assume stationarity and may be more appropriate for joint time-frequency domain analysis. The purpose of this study was to compare Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) in assessing muscle fatigue in supramaximal constant load dynamic exercise (110% VO(2peak)). The results of this study indicate that CWT and STFT analyses give similar fatigue estimates (slope of median frequency) in supramaximal constant load dynamic exercise (P>0.05). However, the results of the variance was significantly lower for at least one of the muscles studied in CWT compared to STFT (P < 0.05) indicating more variability in the EMG signal analysis using STFT. Thus, the stationarity assumption may not be the sole factor responsible for affecting the Fourier based estimates.

  2. Fourier and wavelet spectral analysis of EMG signals in maximal constant load dynamic exercise.

    PubMed

    Costa, Marcelo V; Pereira, Lucas A; Oliveira, Ricardo S; Pedro, Rafael E; Camata, Thiago V; Abrao, Taufik; Brunetto, Maria A C; Altimari, Leandro R

    2010-01-01

    Frequency domain analyses of changes in electromyographic (EMG) signals over time are frequently used to assess muscle fatigue. Fourier based approaches are typically used in these analyses, yet Fourier analysis assumes signal stationarity, which is unlikely during dynamic contractions. Wavelet based methods of signal analysis do not assume stationarity and may be more appropriate for joint time-frequency domain analysis. The purpose of this study was to compare Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) in assessing muscle fatigue in maximal constant load dynamic exercise (100% W(max)). The results of this study indicate that CWT and STFT analyses give similar fatigue estimates (slope of median frequency) in maximal constant load dynamic exercise (P>0.05). However, the results of the variance was significantly lower for at least one of the muscles studied in CWT compared to STFT (P〈0.05) indicating more variability in the EMG signal analysis using STFT. Thus, the stationarity assumption may not be the sole factor responsible for affecting the Fourier based estimates.

  3. Fourier and wavelet spectral analysis of EMG signals in isometric and dynamic maximal effort exercise.

    PubMed

    Dantas, José L; Camata, Thiago V; Brunetto, Maria A C; Moraes, Antonio C; Abrão, Taufik; Altimari, Leandro R

    2010-01-01

    Frequency domain analyses of changes in electromyographic (EMG) signals over time are frequently used to assess muscle fatigue. Fourier based approaches are typically used in these analyses, yet Fourier analysis assumes signal stationarity, which is unlikely during dynamic contractions. Wavelet based methods of signal analysis do not assume stationarity and may be more appropriate for joint time-frequency domain analysis. The purpose of this study was to compare Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) in assessing muscle fatigue in isometric and dynamic exercise. The results of this study indicate that CWT and STFT analyses give similar fatigue estimates (slope of median frequency) in isometric and dynamic exercise (P>0.05). However, the results of the variance was lower for both types of exercise in CWT compared to STFT (P < 0.05) indicating more variability in the EMG signal analysis using STFT. Thus, the stationarity assumption may not be the sole factor responsible for affecting the Fourier based estimates.

  4. Estimating Isometric Tension of Finger Muscle Using Needle EMG Signals and the Twitch Contraction Model

    NASA Astrophysics Data System (ADS)

    Tachibana, Hideyuki; Suzuki, Takafumi; Mabuchi, Kunihiko

    We address an estimation method of isometric muscle tension of fingers, as fundamental research for a neural signal-based prosthesis of fingers. We utilize needle electromyogram (EMG) signals, which have approximately equivalent information to peripheral neural signals. The estimating algorithm comprised two convolution operations. The first convolution is between normal distribution and a spike array, which is detected by needle EMG signals. The convolution estimates the probability density of spike-invoking time in the muscle. In this convolution, we hypothesize that each motor unit in a muscle activates spikes independently based on a same probability density function. The second convolution is between the result of the previous convolution and isometric twitch, viz., the impulse response of the motor unit. The result of the calculation is the sum of all estimated tensions of whole muscle fibers, i.e., muscle tension. We confirmed that there is good correlation between the estimated tension of the muscle and the actual tension, with >0.9 correlation coefficients at 59%, and >0.8 at 89% of all trials.

  5. High efficiency and simple technique for controlling mechanisms by EMG signals

    NASA Astrophysics Data System (ADS)

    Dugarte, N.; Álvarez, A.; Balacco, J.; Mercado, G.; Gonzalez, A.; Dugarte, E.; Javier, F.; Ceballos, G.; Olivares, A.

    2016-04-01

    This article reports the development of a simple and efficient system that allows control of mechanisms through electromyography (EMG) signals. The novelty about this instrument is focused on individual control of each motion vector mechanism through independent electronic circuits. Each of electronic circuit does positions a motor according to intensity of EMG signal captured. This action defines movement in one mechanical axis considered from an initial point, based on increased muscle tension. The final displacement of mechanism depends on individual’s ability to handle the levels of muscle tension at different body parts. This is the design of a robotic arm where each degree of freedom is handled with a specific microcontroller that responds to signals taken from a defined muscle. The biophysical interaction between the person and the final positioning of the robotic arm is used as feedback. Preliminary tests showed that the control operates with minimal positioning error margins. The constant use of system with the same operator showed that the person adapts and progressively improves at control technique.

  6. Between-day reliability of triceps surae responses to standing perturbations in people post-stroke and healthy controls: A high-density surface EMG investigation.

    PubMed

    Gallina, A; Pollock, C L; Vieira, T M; Ivanova, T D; Garland, S J

    2016-02-01

    The reliability of triceps surae electromyographic responses to standing perturbations in people after stroke and healthy controls is unknown. High-Density surface Electromyography (HDsEMG) is a technique that records electromyographic signals from different locations over a muscle, overcoming limitations of traditional surface EMG such as between-day differences in electrode placement. In this study, HDsEMG was used to measure responses from soleus (SOL, 18 channels) and medial and lateral gastrocnemius (MG and LG, 16 channels each) in 10 people after stroke and 10 controls. Timing and amplitude of the response were estimated for each channel of the grids. Intraclass Correlation Coefficient (ICC) and normalized Standard Error of Measurement (SEM%) were calculated for each channel individually (single-channel configuration) and on the median of each grid (all-channels configuration). Both timing (single-channel: ICC=0.75-0.96, SEM%=5.0-9.1; all-channels: ICC=0.85-0.97; SEM%=3.5-6.2%) and amplitude (single-channel: ICC=0.60-0.91, SEM%=25.1-46.6; ICC=0.73-0.95, SEM%=19.3-42.1) showed good-to-excellent reliability. HDsEMG provides reliable estimates of EMG responses to perturbations both in individuals after stroke and in healthy controls; reliability was marginally better for the all-channels compared to the single-channel configuration.

  7. Between-day reliability of triceps surae responses to standing perturbations in people post-stroke and healthy controls: A high-density surface EMG investigation.

    PubMed

    Gallina, A; Pollock, C L; Vieira, T M; Ivanova, T D; Garland, S J

    2016-02-01

    The reliability of triceps surae electromyographic responses to standing perturbations in people after stroke and healthy controls is unknown. High-Density surface Electromyography (HDsEMG) is a technique that records electromyographic signals from different locations over a muscle, overcoming limitations of traditional surface EMG such as between-day differences in electrode placement. In this study, HDsEMG was used to measure responses from soleus (SOL, 18 channels) and medial and lateral gastrocnemius (MG and LG, 16 channels each) in 10 people after stroke and 10 controls. Timing and amplitude of the response were estimated for each channel of the grids. Intraclass Correlation Coefficient (ICC) and normalized Standard Error of Measurement (SEM%) were calculated for each channel individually (single-channel configuration) and on the median of each grid (all-channels configuration). Both timing (single-channel: ICC=0.75-0.96, SEM%=5.0-9.1; all-channels: ICC=0.85-0.97; SEM%=3.5-6.2%) and amplitude (single-channel: ICC=0.60-0.91, SEM%=25.1-46.6; ICC=0.73-0.95, SEM%=19.3-42.1) showed good-to-excellent reliability. HDsEMG provides reliable estimates of EMG responses to perturbations both in individuals after stroke and in healthy controls; reliability was marginally better for the all-channels compared to the single-channel configuration. PMID:27004641

  8. Reconstructing surface EMG from scalp EEG during myoelectric control of a closed looped prosthetic device.

    PubMed

    Paek, Andrew Y; Brown, Jeremy D; Gillespie, R Brent; O'Malley, Marcia K; Shewokis, Patricia A; Contreras-Vidal, Jose L

    2013-01-01

    In this study, seven able-bodied human subjects controlled a robotic gripper with surface electromyography (sEMG) activity from the biceps. While subjects controlled the gripper, they felt the forces measured by the robotic gripper through an exoskeleton fitted on their non-dominant left arm. Subjects were instructed to identify objects with the force feedback provided by the exoskeleton. While subjects operated the robotic gripper, scalp electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) were recorded. We developed neural decoders that used scalp EEG to reconstruct the sEMG used to control the robotic gripper. The neural decoders used a genetic algorithm embedded in a linear model with memory to reconstruct the sEMG from a plurality of EEG channels. The performance of the decoders, measured with Pearson correlation coefficients (median r-value = 0.59, maximum r-value = 0.91) was found to be comparable to previous studies that reconstructed sEMG linear envelopes from neural activity recorded with invasive techniques. These results show the feasibility of developing EEG-based neural interfaces that in turn could be used to control a robotic device.

  9. The effect of single-pulse transcranial magnetic stimulation and peripheral nerve stimulation on complexity of EMG signal: fractal analysis.

    PubMed

    Cukic, M; Oommen, J; Mutavdzic, D; Jorgovanovic, N; Ljubisavljevic, M

    2013-07-01

    The aim of this study was to examine whether single-pulse transcranial magnetic stimulation (spTMS) affects the pattern of corticospinal activity once voluntary drive has been restored after spTMS-induced EMG silence. We used fractal dimension (FD) to explore the 'complexity' of the electromyography (EMG) signal, and median frequency of the spectra (MDF) to examine changes in EMG spectral characteristics. FD and MDF of the raw EMG epochs immediately before were compared with those obtained from epochs after the EMG silence. Changes in FD and MDF after spTMS were examined with three levels of muscle contraction corresponding to weak (20-40%), moderate (40-60%) and strong (60-80% of maximal voluntary contraction) and three intensities of stimulation set at 10, 20 and 30% above the resting motor threshold. FD was calculated using the Higuchi fractal dimension algorithm. Finally, to discern the origin of FD changes between the CNS and muscle, we compared the effects of spTMS with the effects of peripheral nerve stimulation (PNS) on FD and MDF. The results show that spTMS induced significant decrease in both FD and MDF of EMG signal after stimulation. PNS did not have any significant effects on FD nor MDF. Changes in TMS intensity did not have any significant effect on FD or MDF after stimulation nor had the strength of muscle contraction. However, increase in contraction strength decreased FD before stimulation but only between weak and moderate contraction. The results suggest that the effects of spTMS on corticospinal activity, underlying voluntary motor output, outlast the TMS stimulus. It appears that the complexity of the EMG signal is reduced after spTMS, suggesting that TMS alters the dynamics of the ongoing corticospinal activity most likely temporarily synchronizing the neural network activity. Further studies are needed to confirm whether observed changes after TMS occur at the cortical level. PMID:23652725

  10. Combining data fusion with multiresolution analysis for improving the classification accuracy of uterine EMG signals

    NASA Astrophysics Data System (ADS)

    Moslem, Bassam; Diab, Mohamad; Khalil, Mohamad; Marque, Catherine

    2012-12-01

    Multisensor data fusion is a powerful solution for solving difficult pattern recognition problems such as the classification of bioelectrical signals. It is the process of combining information from different sensors to provide a more stable and more robust classification decisions. We combine here data fusion with multiresolution analysis based on the wavelet packet transform (WPT) in order to classify real uterine electromyogram (EMG) signals recorded by 16 electrodes. Herein, the data fusion is done at the decision level by using a weighted majority voting (WMV) rule. On the other hand, the WPT is used to achieve significant enhancement in the classification performance of each channel by improving the discrimination power of the selected feature. We show that the proposed approach tested on our recorded data can improve the recognition accuracy in labor prediction and has a competitive and promising performance.

  11. EMG-Derived Respiration Signal Using the Fixed Sample Entropy during an Inspiratory Load Protocol.

    PubMed

    Estrada, Luis; Torres, Abel; Sarlabous, Leonardo; Jané, Raimon

    2015-08-01

    Extracting clinical information from one single measurement represents a step forward in the assessment of the respiratory muscle function. This attracting idea entails the reduction of the instrumentation and fosters to develop new medical integrated technologies. We present the use of the fixed sample entropy (fSampEn) as a more direct method to non-invasively derive the breathing activity from the diaphragm electromyographic (EMGdi) signal, and thus to extract the respiratory rate, an important vital sign which is cumbersome and time-consuming to be measured by clinicians. fSampEn is a method to evaluate the EMGdi activity that is less sensitive to the cardiac activity (ECG) and its application has proven to be useful to evaluate the load of the respiratory muscles. The behavior of the proposed method was tested in signals from two subjects that performed an inspiratory load protocol, which consists of increments in the inspiratory mouth pressure (P mouth). Two respiratory signals were derived and compared to the P mouth signal: the ECG-derived respiration (EDR) signal from the lead-I configuration, and the EMG-derived respiration (EMGDR) signal by applying the fSampEn method over the EMGdi signal. The similitude and the lag between signals were calculated through the cross-correlation between each derived respiratory signal and the P mouth. The EMGDR signal showed higher correlation and lower lag values (≥ 0.91 and ≤ 0.70 s, respectively) than the EDR signal (≥ 0.83 and ≤ 0.99 s, respectively). Additionally, the respiratory rate was estimated with the P mouth, EDR and EMGDR signals showing very similar values. The results from this preliminary work suggest that the fSampEn method can be used to derive the respiration waveform from the respiratory muscle electrical activity.

  12. EMG responses to maintain stance during multidirectional surface translations

    NASA Technical Reports Server (NTRS)

    Henry, S. M.; Fung, J.; Horak, F. B.; Peterson, B. W. (Principal Investigator)

    1998-01-01

    To characterize muscle synergy organization underlying multidirectional control of stance posture, electromyographic activity was recorded from 11 lower limb and trunk muscles of 7 healthy subjects while they were subjected to horizontal surface translations in 12 different, randomly presented directions. The latency and amplitude of muscle responses were quantified for each perturbation direction. Tuning curves for each muscle were examined to relate the amplitude of the muscle response to the direction of surface translation. The latencies of responses for the shank and thigh muscles were constant, regardless of perturbation direction. In contrast, the latencies for another thigh [tensor fascia latae (TFL)] and two trunk muscles [rectus abdominis (RAB) and erector spinae (ESP)] were either early or late, depending on the perturbation direction. These three muscles with direction-specific latencies may play different roles in postural control as prime movers or as stabilizers for different translation directions, depending on the timing of recruitment. Most muscle tuning curves were within one quadrant, having one direction of maximal activity, generally in response to diagonal surface translations. Two trunk muscles (RAB and ESP) and two lower limb muscles (semimembranosus and peroneus longus) had bipolar tuning curves, with two different directions of maximal activity, suggesting that these muscle can play different roles as part of different synergies, depending on translation direction. Muscle tuning curves tended to group into one of three regions in response to 12 different directions of perturbations. Two muscles [rectus femoris (RFM) and TFL] were maximally active in response to lateral surface translations. The remaining muscles clustered into one of two diagonal regions. The diagonal regions corresponded to the two primary directions of active horizontal force vector responses. Two muscles (RFM and adductor longus) were maximally active orthogonal to

  13. Noninvasive imaging of internal muscle activities from multi-channel surface EMG recordings.

    PubMed

    Zhang, Yingchun

    2013-01-01

    Surface Electromyogram (sEMG) technology provides a non-invasive way for rapid monitoring muscle activities, but its poor spatial resolution and specificity limit its application in clinic. To overcome these limitations, a noninvasive muscle activity imaging (MAI) approach has been developed and used to reconstruct internal muscle activities from multi-channel sEMG recordings. A realistic geometric hand model is developed from high-resolution MR images and a distributed bioelectric dipole source model is employed to describe the internal muscle activity space of the muscles. The finite element method and weighted minimum norm method are utilized solve the forward and inverse problems respectively involved in the proposed MAI technique. A series of computer simulations was conducted to test the performance of the proposed MAI approach. Results show that reconstruction results achieved by the MAI technique indeed provide us more detailed and dynamic information of internal muscle activities, which enhance our understanding of the mechanisms underlying the surface EMG recordings.

  14. Surface electromyography signal processing and classification techniques.

    PubMed

    Chowdhury, Rubana H; Reaz, Mamun B I; Ali, Mohd Alauddin Bin Mohd; Bakar, Ashrif A A; Chellappan, K; Chang, T G

    2013-09-17

    Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.

  15. Surface Electromyography Signal Processing and Classification Techniques

    PubMed Central

    Chowdhury, Rubana H.; Reaz, Mamun B. I.; Ali, Mohd Alauddin Bin Mohd; Bakar, Ashrif A. A.; Chellappan, Kalaivani; Chang, Tae. G.

    2013-01-01

    Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above. PMID:24048337

  16. Abnormal surface EMG during clinically normal wrist movement in cervical dystonia.

    PubMed

    de Vries, P M; Leenders, K L; van der Hoeven, J H; de Jong, B M; Kuiper, A J; Maurits, N M

    2007-11-01

    We investigated whether patients with cervical dystonia (CD) have abnormal muscle activation in non-dystonic body parts. Eight healthy controls and eight CD patients performed a flexion-extension movement of the right wrist. Movement execution was recorded by surface electromyography (EMG) from forearm muscles. Although patients had no complaints concerning wrist movement and had no apparent difficulty in executing the task, they demonstrated lower mean EMG amplitude (flexor: 0.32 mV and extensor: 0.61 mV) than controls (flexor: 0.67 mV; P = 0.021 and extensor: 1.18 mV; P = 0.068; borderline significant). Mean extensor muscle contraction was prolonged in patients (1860 ms) compared with controls (1334 ms; P = 0.026). Variation in mean EMG amplitude over movements tended to be higher in patients (flexor: 43% and extensor: 35%) than controls (flexor: 34%; P = 0.072 and extensor: 26%; P = 0.073). These results suggest that CD patients also have abnormal muscle activation in non-dystonic body parts at a subclinical level. This would support the concept that in dystonia, non-dystonic limbs are in a 'pre-dystonic state'.

  17. Complexity analysis of EMG signals for patients after stroke during robot-aided rehabilitation training using fuzzy approximate entropy.

    PubMed

    Sun, Rui; Song, Rong; Tong, Kai-yu

    2014-09-01

    The paper presents a novel viewpoint to monitor the motor function improvement during a robot-aided rehabilitation training. Eight chronic poststroke subjects were recruited to attend the 20-session training, and in each session, subjects were asked to perform voluntary movements of elbow flexion and extension together with the robotic system. The robotic system was continuously controlled by the electromyographic (EMG) signal from the affected triceps. Fuzzy approximate entropy (fApEn) was applied to investigate the complexity of the EMG segment, and maximum voluntary contraction (MVC) during elbow flexion and extension was applied to reflect force generating capacity of the affected muscles. The results showed that the group mean fApEn of EMG signals from triceps and biceps increased significantly after the robot-aided rehabilitation training . There was also significant increase in maximum voluntary flexion and extension torques after the robot-aided rehabilitation training . There was significant correlation between fApEn of agonist and MVC , which implied that the increase of motorneuron number is one of factors that may explain the increase in muscle strength. These findings based on fApEn of the EMG signals expand the existing interpretation of training-induced function improvement in patients after stroke, and help us to understand the neurological change induced by the robot-aided rehabilitation training.

  18. DCT domain feature extraction scheme based on motor unit action potential of EMG signal for neuromuscular disease classification.

    PubMed

    Doulah, Abul Barkat Mollah Sayeed Ud; Fattah, Shaikh Anowarul; Zhu, Wei-Ping; Ahmad, M Omair

    2014-01-01

    A feature extraction scheme based on discrete cosine transform (DCT) of electromyography (EMG) signals is proposed for the classification of normal event and a neuromuscular disease, namely the amyotrophic lateral sclerosis. Instead of employing DCT directly on EMG data, it is employed on the motor unit action potentials (MUAPs) extracted from the EMG signal via a template matching-based decomposition technique. Unlike conventional MUAP-based methods, only one MUAP with maximum dynamic range is selected for DCT-based feature extraction. Magnitude and frequency values of a few high-energy DCT coefficients corresponding to the selected MUAP are used as the desired feature which not only reduces computational burden, but also offers better feature quality with high within-class compactness and between-class separation. For the purpose of classification, the K-nearest neighbourhood classifier is employed. Extensive analysis is performed on clinical EMG database and it is found that the proposed method provides a very satisfactory performance in terms of specificity, sensitivity and overall classification accuracy.

  19. DCT domain feature extraction scheme based on motor unit action potential of EMG signal for neuromuscular disease classification

    PubMed Central

    Doulah, Abul Barkat Mollah Sayeed Ud; Zhu, Wei-Ping; Ahmad, M. Omair

    2014-01-01

    A feature extraction scheme based on discrete cosine transform (DCT) of electromyography (EMG) signals is proposed for the classification of normal event and a neuromuscular disease, namely the amyotrophic lateral sclerosis. Instead of employing DCT directly on EMG data, it is employed on the motor unit action potentials (MUAPs) extracted from the EMG signal via a template matching-based decomposition technique. Unlike conventional MUAP-based methods, only one MUAP with maximum dynamic range is selected for DCT-based feature extraction. Magnitude and frequency values of a few high-energy DCT coefficients corresponding to the selected MUAP are used as the desired feature which not only reduces computational burden, but also offers better feature quality with high within-class compactness and between-class separation. For the purpose of classification, the K-nearest neighbourhood classifier is employed. Extensive analysis is performed on clinical EMG database and it is found that the proposed method provides a very satisfactory performance in terms of specificity, sensitivity and overall classification accuracy. PMID:26609372

  20. Surface EMG and intra-socket force measurement to control a prosthetic device

    NASA Astrophysics Data System (ADS)

    Sanford, Joe; Patterson, Rita; Popa, Dan

    2015-06-01

    Surface electromyography (SEMG) has been shown to be a robust and reliable interaction method allowing for basic control of powered prosthetic devices. Research has shown a marked decrease in EMG-classification efficiency throughout activities of daily life due to socket shift and movement and fatigue as well as changes in degree of fit of the socket throughout the subject's lifetime. Users with the most severe levels of amputation require the most complex devices with the greatest number of degrees of freedom. Controlling complex dexterous devices with limited available inputs requires the addition of sensing and interaction modalities. However, the larger the amputation severity, the fewer viable SEMG sites are available as control inputs. Previous work reported the use of intra-socket pressure, as measured during wrist flexion and extension, and has shown that it is possible to control a powered prosthetic device with pressure sensors. In this paper, we present data correlations of SEMG data with intra-socket pressure data. Surface EMG sensors and force sensors were housed within a simulated prosthetic cuff fit to a healthy-limbed subject. EMG and intra-socket force data was collected from inside the cuff as a subject performed pre-defined grip motions with their dominant hand. Data fusion algorithms were explored and allowed a subject to use both intra-socket pressure and SEMG data as control inputs for a powered prosthetic device. This additional input modality allows for an improvement in input classification as well as information regarding socket fit through out activities of daily life.

  1. Alteration of Surface EMG amplitude levels of five major trunk muscles by defined electrode location displacement.

    PubMed

    Huebner, Agnes; Faenger, Bernd; Schenk, Philipp; Scholle, Hans-Christoph; Anders, Christoph

    2015-04-01

    Exact electrode positioning is vital for obtaining reliable results in Surface EMG. This study aimed at systematically assessing the influence of defined electrode shifts on measured Surface EMG amplitudes of trunk muscles in a group of 15 middle aged healthy male subjects. The following leftsided muscles were investigated: rectus abdominis muscle, internal and external oblique abdominal muscles, lumbar multifidus muscle, and longissimus muscle. In addition to the recommended electrode positions, extra electrodes were placed parallel to these and along muscle fiber direction. Measurements were performed under isometric conditions in upright body position. Gradually changing, but defined loads were applied considering subject's upper body weight. For the abdominal muscles amplitude differences varied considerably depending on load level, magnitude, and direction. For both back muscles amplitudes dropped consistently but rather little for parallel electrode displacements. However, for the longissimus muscle a caudal electrode shift resulted in an amplitude increase of similar extent and independent from load level. Influence of electrode position variations can be proven for all trunk muscles but are more evident in abdominal than back muscles. Those muscle-specific effects confirm the necessity for an exact definition of electrode positioning to allow comparisons between individual subjects, groups of subjects, and studies.

  2. iEMG: Imaging electromyography.

    PubMed

    Urbanek, Holger; van der Smagt, Patrick

    2016-04-01

    Advanced data analysis and visualization methodologies have played an important role in making surface electromyography both a valuable diagnostic methodology of neuromuscular disorders and a robust brain-machine interface, usable as a simple interface for prosthesis control, arm movement analysis, stiffness control, gait analysis, etc. But for diagnostic purposes, as well as for interfaces where the activation of single muscles is of interest, surface EMG suffers from severe crosstalk between deep and superficial muscle activation, making the reliable detection of the source of the signal, as well as reliable quantification of deeper muscle activation, prohibitively difficult. To address these issues we present a novel approach for processing surface electromyographic data. Our approach enables the reconstruction of 3D muscular activity location, making the depth of muscular activity directly visible. This is even possible when deep muscles are overlaid with superficial muscles, such as seen in the human forearm. The method, which we call imaging EMG (iEMG), is based on using the crosstalk between a sufficiently large number of surface electromyographic electrodes to reconstruct the 3D generating electrical potential distribution within a given area. Our results are validated by in vivo measurements of iEMG and ultrasound on the human forearm.

  3. Automatic classification of motor unit potentials in surface EMG recorded from thenar muscles paralyzed by spinal cord injury.

    PubMed

    Winslow, Jeffrey; Dididze, Marine; Thomas, Christine K

    2009-12-15

    Involuntary electromyographic (EMG) activity has only been analyzed in the paralyzed thenar muscles of spinal cord injured (SCI) subjects for several minutes. It is unknown if this motor unit activity is ongoing. Longer duration EMG recordings can investigate the biological significance of this activity. Since no software is currently capable of classifying 24h of EMG data at a single motor unit level, the goal of this research was to devise an algorithm that would automatically classify motor unit potentials by tracking the firing behavior of motor units over 24h. Two channels of thenar muscle surface EMG were recorded over 24h from seven SCI subjects with a chronic cervical level injury using a custom data logging device with custom software. The automatic motor unit classification algorithm developed here employed multiple passes through these 24-h EMG recordings to segment, cluster, form global templates and classify motor unit potentials, including superimposed potentials. The classification algorithm was able to track an average of 19 global classes in seven 24-h recordings with a mean (+/-SE) accuracy of 89.9% (+/-0.98%) and classify potentials from these individual motor units with a mean accuracy of 90.3% (+/-0.97%). The algorithm could analyze 24h of data in 2-3 weeks with minimal input from a person, while a human operator was estimated to take more than 2 years. This automatic method could be applied clinically to investigate the fasciculation potentials often found in motoneuron disorders such as amyotrophic lateral sclerosis.

  4. An investigative redesign of the ECG and EMG signal conditioning circuits for two-fault tolerance and circuit improvement

    NASA Astrophysics Data System (ADS)

    Obrien, Edward M.

    1991-12-01

    An investigation was undertaken to make the elctrocardiography (ECG) and the electromyography (EMG) signal conditioning circuits two-fault tolerant and to update the circuitry. The present signal conditioning circuits provide at least one level of subject protection against electrical shock hazard but at a level of 100 micro-A (for voltages of up to 200 V). However, it is necessary to provide catastrophic fault tolerance protection for the astronauts and to provide protection at a current level of less that 100 micro-A. For this study, protection at the 10 micro-A level was sought. This is the generally accepted value below which no possibility of microshock exists. Only the possibility of macroshock exists in the case of the signal conditioners. However, this extra amount of protection is desirable. The initial part deals with current limiter circuits followed by an investigation into the signal conditioner specifications and circuit design.

  5. An Investigative Redesign of the ECG and EMG Signal Conditioning Circuits for Two-fault Tolerance and Circuit Improvement

    NASA Technical Reports Server (NTRS)

    Obrien, Edward M.

    1991-01-01

    An investigation was undertaken to make the elctrocardiography (ECG) and the electromyography (EMG) signal conditioning circuits two-fault tolerant and to update the circuitry. The present signal conditioning circuits provide at least one level of subject protection against electrical shock hazard but at a level of 100 micro-A (for voltages of up to 200 V). However, it is necessary to provide catastrophic fault tolerance protection for the astronauts and to provide protection at a current level of less that 100 micro-A. For this study, protection at the 10 micro-A level was sought. This is the generally accepted value below which no possibility of microshock exists. Only the possibility of macroshock exists in the case of the signal conditioners. However, this extra amount of protection is desirable. The initial part deals with current limiter circuits followed by an investigation into the signal conditioner specifications and circuit design.

  6. Feasibility of using combined EMG and kinematic signals for prosthesis control: A simulation study using a virtual reality environment.

    PubMed

    Blana, Dimitra; Kyriacou, Theocharis; Lambrecht, Joris M; Chadwick, Edward K

    2016-08-01

    Transhumeral amputation has a significant effect on a person's independence and quality of life. Myoelectric prostheses have the potential to restore upper limb function, however their use is currently limited due to lack of intuitive and natural control of multiple degrees of freedom. The goal of this study was to evaluate a novel transhumeral prosthesis controller that uses a combination of kinematic and electromyographic (EMG) signals recorded from the person's proximal humerus. Specifically, we trained a time-delayed artificial neural network to predict elbow flexion/extension and forearm pronation/supination from six proximal EMG signals, and humeral angular velocity and linear acceleration. We evaluated this scheme with ten able-bodied subjects offline, as well as in a target-reaching task presented in an immersive virtual reality environment. The offline training had a target of 4° for flexion/extension and 8° for pronation/supination, which it easily exceeded (2.7° and 5.5° respectively). During online testing, all subjects completed the target-reaching task with path efficiency of 78% and minimal overshoot (1.5%). Thus, combining kinematic and muscle activity signals from the proximal humerus can provide adequate prosthesis control, and testing in a virtual reality environment can provide meaningful data on controller performance. PMID:26190031

  7. The Rancho EMG analyzer: a computerized system for gait analysis.

    PubMed

    Perry, J; Bontrager, E L; Bogey, R A; Gronley, J K; Barnes, L A

    1993-11-01

    This paper describes a computer system which accurately defines the EMG patterns of the lower extremities during gait. Footswitches are used to identify the temporal relationships and determine the phases of the gait cycle. Fine wire electrodes, inserted in the desired muscles of the patient being tested, provide EMG signals for comparison with a normal database. The system is also usable with surface electrodes when an appropriate normal database for surface electrodes is incorporated. Descriptive qualifiers (such as 'premature onset', 'delayed cessation', 'no clinically significant EMG', 'continuous activity' etc.) are used to produce a clinically relevant printed (textual) report. The intensity filtered average (IFA) of the EMG is shown graphically with the representative profile of each stride. The IFAs for all muscles tested can be plotted together (up to six on a page) and the graphic representation of the 'raw' EMG can be produced. The methods of generating the normal database by creating time-adjusted mean profiles (TAMP) are enumerated. The clinical use of the system is discussed. A detailed analysis of 31 of the most recent patient tests for which the system was used provides an indication of its accuracy. For 86% of the 428 muscle tests examined, the EMG analyser was considered to have given the correct result as compared with a visual analysis of the raw EMG record by a trained expert. Recommendations for the use and future improvements of the EMG analyser are made.

  8. A real-time pinch-to-zoom motion detection by means of a surface EMG-based human-computer interface.

    PubMed

    Kim, Jongin; Cho, Dongrae; Lee, Kwang Jin; Lee, Boreom

    2014-12-29

    In this paper, we propose a system for inferring the pinch-to-zoom gesture using surface EMG (Electromyography) signals in real time. Pinch-to-zoom, which is a common gesture in smart devices such as an iPhone or an Android phone, is used to control the size of images or web pages according to the distance between the thumb and index finger. To infer the finger motion, we recorded EMG signals obtained from the first dorsal interosseous muscle, which is highly related to the pinch-to-zoom gesture, and used a support vector machine for classification between four finger motion distances. The powers which are estimated by Welch's method were used as feature vectors. In order to solve the multiclass classification problem, we applied a one-versus-one strategy, since a support vector machine is basically a binary classifier. As a result, our system yields 93.38% classification accuracy averaged over six subjects. The classification accuracy was estimated using 10-fold cross validation. Through our system, we expect to not only develop practical prosthetic devices but to also construct a novel user experience (UX) for smart devices.

  9. A real-time pinch-to-zoom motion detection by means of a surface EMG-based human-computer interface.

    PubMed

    Kim, Jongin; Cho, Dongrae; Lee, Kwang Jin; Lee, Boreom

    2015-01-01

    In this paper, we propose a system for inferring the pinch-to-zoom gesture using surface EMG (Electromyography) signals in real time. Pinch-to-zoom, which is a common gesture in smart devices such as an iPhone or an Android phone, is used to control the size of images or web pages according to the distance between the thumb and index finger. To infer the finger motion, we recorded EMG signals obtained from the first dorsal interosseous muscle, which is highly related to the pinch-to-zoom gesture, and used a support vector machine for classification between four finger motion distances. The powers which are estimated by Welch's method were used as feature vectors. In order to solve the multiclass classification problem, we applied a one-versus-one strategy, since a support vector machine is basically a binary classifier. As a result, our system yields 93.38% classification accuracy averaged over six subjects. The classification accuracy was estimated using 10-fold cross validation. Through our system, we expect to not only develop practical prosthetic devices but to also construct a novel user experience (UX) for smart devices. PMID:25551482

  10. A Real-Time Pinch-to-Zoom Motion Detection by Means of a Surface EMG-Based Human-Computer Interface

    PubMed Central

    Kim, Jongin; Cho, Dongrae; Lee, Kwang Jin; Lee, Boreom

    2015-01-01

    In this paper, we propose a system for inferring the pinch-to-zoom gesture using surface EMG (Electromyography) signals in real time. Pinch-to-zoom, which is a common gesture in smart devices such as an iPhone or an Android phone, is used to control the size of images or web pages according to the distance between the thumb and index finger. To infer the finger motion, we recorded EMG signals obtained from the first dorsal interosseous muscle, which is highly related to the pinch-to-zoom gesture, and used a support vector machine for classification between four finger motion distances. The powers which are estimated by Welch's method were used as feature vectors. In order to solve the multiclass classification problem, we applied a one-versus-one strategy, since a support vector machine is basically a binary classifier. As a result, our system yields 93.38% classification accuracy averaged over six subjects. The classification accuracy was estimated using 10-fold cross validation. Through our system, we expect to not only develop practical prosthetic devices but to also construct a novel user experience (UX) for smart devices. PMID:25551482

  11. Segmentation of ECG from Surface EMG Using DWT and EMD: A Comparison Study

    NASA Astrophysics Data System (ADS)

    Shahbakhti, Mohammad; Heydari, Elnaz; Luu, Gia Thien

    2014-10-01

    The electrocardiographic (ECG) signal is a major artifact during recording the surface electromyography (SEMG). Removal of this artifact is one of the important tasks before SEMG analysis for biomedical goals. In this paper, the application of discrete wavelet transform (DWT) and empirical mode decomposition (EMD) for elimination of ECG artifact from SEMG is investigated. The focus of this research is to reach the optimized number of decomposed levels using mean power frequency (MPF) by both techniques. In order to implement the proposed methods, ten simulated and three real ECG contaminated SEMG signals have been tested. Signal-to-noise ratio (SNR) and mean square error (MSE) between the filtered and the pure signals are applied as the performance indexes of this research. The obtained results suggest both techniques could remove ECG artifact from SEMG signals fair enough, however, DWT performs much better and faster in real data.

  12. Biomechanical Correlates of Surface Electromyography Signals Obtained during Swallowing by Healthy Adults

    ERIC Educational Resources Information Center

    Crary, Michael A.; Carnaby (Mann), Giselle D.; Groher, Michael E.

    2006-01-01

    Purpose: The purpose of this study was to describe biomechanical correlates of the surface electromyographic signal obtained during swallowing by healthy adult volunteers. Method: Seventeen healthy adults were evaluated with simultaneous videofluoroscopy and surface electromyography (sEMG) while swallowing 5 mL of liquid barium sulfate. Three…

  13. [Research on the surface electromyography signal decomposition based on multi-channel signal fusion analysis].

    PubMed

    Li, Qiang; Yang, Jihai

    2012-10-01

    The decomposition method of surface electromyography (sEMG) signals was explored by using the multi-channel information extraction and fusion analysis to acquire the motor unit action potential (MUAP) patterns. The action potential waveforms were detected with the combined method of continuous wavelet transform and hypothesis testing, and the effective detection analysis was judged with the multi-channel firing processes of motor units. The cluster number of MUAPs was confirmed by the hierarchical clustering technique, and then the decomposition was implemented by the fuzzy k-means clustering algorithms. The unclassified waveforms were processed by the template matching and peel-off methods. The experimental results showed that several kinds of MUAPs were precisely extracted from the multi-channel sEMG signals. The space potential distribution information of motor units could be satisfyingly represented by the proposed decomposition method. PMID:23198440

  14. Man-Machine Interface System for Neuromuscular Training and Evaluation Based on EMG and MMG Signals

    PubMed Central

    de la Rosa, Ramon; Alonso, Alonso; Carrera, Albano; Durán, Ramon; Fernández, Patricia

    2010-01-01

    This paper presents the UVa-NTS (University of Valladolid Neuromuscular Training System), a multifunction and portable Neuromuscular Training System. The UVa-NTS is designed to analyze the voluntary control of severe neuromotor handicapped patients, their interactive response, and their adaptation to neuromuscular interface systems, such as neural prostheses or domotic applications. Thus, it is an excellent tool to evaluate the residual muscle capabilities in the handicapped. The UVa-NTS is composed of a custom signal conditioning front-end and a computer. The front-end electronics is described thoroughly as well as the overall features of the custom software implementation. The software system is composed of a set of graphical training tools and a processing core. The UVa-NTS works with two classes of neuromuscular signals: the classic myoelectric signals (MES) and, as a novelty, the myomechanic signals (MMS). In order to evaluate the performance of the processing core, a complete analysis has been done to classify its efficiency and to check that it fulfils with the real-time constraints. Tests were performed both with healthy and selected impaired subjects. The adaptation was achieved rapidly, applying a predefined protocol for the UVa-NTS set of training tools. Fine voluntary control was demonstrated to be reached with the myoelectric signals. And the UVa-NTS demonstrated to provide a satisfactory voluntary control when applying the myomechanic signals. PMID:22163515

  15. Man-machine interface system for neuromuscular training and evaluation based on EMG and MMG signals.

    PubMed

    de la Rosa, Ramon; Alonso, Alonso; Carrera, Albano; Durán, Ramon; Fernández, Patricia

    2010-01-01

    This paper presents the UVa-NTS (University of Valladolid Neuromuscular Training System), a multifunction and portable Neuromuscular Training System. The UVa-NTS is designed to analyze the voluntary control of severe neuromotor handicapped patients, their interactive response, and their adaptation to neuromuscular interface systems, such as neural prostheses or domotic applications. Thus, it is an excellent tool to evaluate the residual muscle capabilities in the handicapped. The UVa-NTS is composed of a custom signal conditioning front-end and a computer. The front-end electronics is described thoroughly as well as the overall features of the custom software implementation. The software system is composed of a set of graphical training tools and a processing core. The UVa-NTS works with two classes of neuromuscular signals: the classic myoelectric signals (MES) and, as a novelty, the myomechanic signals (MMS). In order to evaluate the performance of the processing core, a complete analysis has been done to classify its efficiency and to check that it fulfils with the real-time constraints. Tests were performed both with healthy and selected impaired subjects. The adaptation was achieved rapidly, applying a predefined protocol for the UVa-NTS set of training tools. Fine voluntary control was demonstrated to be reached with the myoelectric signals. And the UVa-NTS demonstrated to provide a satisfactory voluntary control when applying the myomechanic signals.

  16. Recognition of grasp types through principal components of DWT based EMG features.

    PubMed

    Kakoty, Nayan M; Hazarika, Shyamanta M

    2011-01-01

    With the advancement in machine learning and signal processing techniques, electromyogram (EMG) signals have increasingly gained importance in man-machine interaction. Multifingered hand prostheses using surface EMG for control has appeared in the market. However, EMG based control is still rudimentary, being limited to a few hand postures based on higher number of EMG channels. Moreover, control is non-intuitive, in the sense that the user is required to learn to associate muscle remnants actions to unrelated posture of the prosthesis. Herein lies the promise of a low channel EMG based grasp classification architecture for development of an embedded intelligent prosthetic controller. This paper reports classification of six grasp types used during 70% of daily living activities based on two channel forearm EMG. A feature vector through principal component analysis of discrete wavelet transform coefficients based features of the EMG signal is derived. Classification is through radial basis function kernel based support vector machine following preprocessing and maximum voluntary contraction normalization of EMG signals. 10-fold cross validation is done. We have achieved an average recognition rate of 97.5%.

  17. Surface EMG during the Push-up plus Exercise on a Stable Support or Swiss Ball: Scapular Stabilizer Muscle Exercise

    PubMed Central

    Seo, Sung-Hwa; Jeon, In-Ho; Cho, Yong-Ho; Lee, Hyun-Gi; Hwang, Yoon-Tae; Jang, Jee-Hun

    2013-01-01

    [Purpose] Scapular stabilizer strengthening exercise is crucial for shoulder rehabilitation. The purpose of this study was to compare two types of push-up plus exercises, on a stable and unstable bases of support, using surface electromyography (EMG), to suggest an effective shoulder rehabilitation program. [Subjects and Methods] Ten healthy men volunteered for this study. All volunteers performed two sets of push-up plus exercise (standard push up and knee push up) on stable and unstable bases of support. The muscle activities of five important scapular stabilizer muscles (upper trapezius, middle trapezius, lower trapezius, serratus anterior, latissimus dorsi) were recorded during the exercise. [Results] The upper trapezius showed greater mean electric activation amplitude in the scapular retraction posture than in the scapular protraction posture, and the serratus anterior showed greater mean electric activation amplitude in the scapular protraction posture than in the scapular retraction posture. The root-mean-square normalized EMG values of the muscles were greater during the exercise performed on the unstable support than those on the stable support. [Conclusion] The standard push-up plus exercise on an unstable base of support helps to increase muscle activity, especially those of the upper/middle trapezius and serratus anterior. PMID:24259864

  18. Rectification of the EMG is an unnecessary and inappropriate step in the calculation of Corticomuscular coherence.

    PubMed

    McClelland, Verity M; Cvetkovic, Zoran; Mills, Kerry R

    2012-03-30

    Corticomuscular coherence (CMC) estimation is a frequency domain method used to detect a linear coupling between rhythmic activity recorded from sensorimotor cortex (EEG or MEG) and the electromyogram (EMG) of active muscles. In motor neuroscience, rectification of the surface EMG is a common pre-processing step prior to calculating CMC, intended to maximize information about action potential timing, whilst suppressing information relating to motor unit action potential (MUAP) shape. Rectification is believed to produce a general shift in the EMG spectrum towards lower frequencies, including those around the mean motor unit discharge rate. However, there are no published data to support the claim that EMG rectification enhances the detection of CMC. Furthermore, performing coherence analysis after the non-linear procedure of rectification, which results in a significant distortion of the EMG spectrum, is considered fundamentally flawed in engineering and digital signal processing. We calculated CMC between sensorimotor cortex EEG and EMG of two hand muscles during a key grip task in 14 healthy subjects. CMC calculated using unrectified and rectified EMG was compared. The use of rectified EMG did not enhance the detection of CMC, nor was there any evidence that MUAP shape information had an adverse effect on the CMC estimation. EMG rectification had inconsistent effects on the power and coherence spectra and obscured the detection of CMC in some cases. We also provide a comprehensive theoretical analysis, which, along with our empirical data, demonstrates that rectification is neither necessary nor appropriate in the calculation of CMC.

  19. Pathological tremor prediction using surface EMG and acceleration: potential use in “ON-OFF” demand driven deep brain stimulator design

    PubMed Central

    Basu, Ishita; Graupe, Daniel; Tuninetti, Daniela; Shukla, Pitamber; Slavin, Konstantin V.; Metman, Leo Verhagen; Corcos, Daniel M.

    2013-01-01

    Objective We present a proof of concept for a novel method of predicting the onset of pathological tremor using non-invasively measured surface electromyogram (sEMG) and acceleration from tremor-affected extremities of patients with Parkinson’s disease (PD) and Essential tremor (ET). Approach The tremor prediction algorithm uses a set of spectral (fourier and wavelet) and non-linear time series (entropy and recurrence rate) parameters extracted from the non-invasively recorded sEMG and acceleration signals. Main results The resulting algorithm is shown to successfully predict tremor onset for all 91 trials recorded in 4 PD patients and for all 91 trials recorded in 4 ET patients. The predictor achieves a 100% sensitivity for all trials considered, along with an overall accuracy of 85.7% for all ET trials and 80.2% for all PD trials. By using a Pearson’s chi-square test, the prediction results are shown to significantly differ from a random prediction outcome. Significance The tremor prediction algorithm can be potentially used for designing the next generation of non-invasive closed-loop predictive ON-OFF controllers for deep brain stimulation (DBS), used for suppressing pathological tremor in such patients. Such a system is based on alternating ON and OFF DBS periods, an incoming tremor being predicted during the time intervals when DBS is OFF, so as to turn DBS back ON. The prediction should be a few seconds before tremor re-appears so that the patient is tremor-free for the entire DBS ON-OFF cycle as well as the tremor-free DBS OFF interval should be maximized in order to minimize the current injected in the brain and battery usage. PMID:23658233

  20. IDENTIFICATION OF TERM AND PRE-TERM LABOR IN RATS USING ARTIFICIAL NEURAL NETWORKS ON UTERINE EMG SIGNALS

    PubMed Central

    SHI, Shao Q.; MANER, William L.; MACKAY, Lynette B.; GARFIELD, Robert E.

    2008-01-01

    CONDENSATION Term or preterm delivery in rats can be effectively predicted using artificial neural network analysis of uterine EMG data. Objective To use artificial neural networks (ANN) on uterine electromyography (EMG) data to identify term and preterm labor in rats. Study Design Controls (G1:N=4) and preterm labor models (G2:N=4, treated with onapristone) were used. Uterine EMG and intrauterine pressure (IUP) variables were measured by implanted telemetric devices. For each time-point assessed, either a “labor-event” or “non-labor-event” was first assigned using visual and other means. 112 total labor and non-labor events were observed. ANN was then used with EMG and IUP parameters to attempt algorithmic, objective identification for time of labor in each group. Results For G1, 8/8 (100%) of labor events and 44/44 (100%) of non-labor events were correctly identified by the ANN. For G2, 22/24 (92%) of labor events and 31/36 (86%) of non-labor events were correctly determined by the ANN. Conclusion ANN can effectively predict term and preterm labor during pregnancy using uterine EMG and IUP variables. PMID:18226633

  1. Robust Features Of Surface Electromyography Signal

    NASA Astrophysics Data System (ADS)

    Sabri, M. I.; Miskon, M. F.; Yaacob, M. R.

    2013-12-01

    Nowadays, application of robotics in human life has been explored widely. Robotics exoskeleton system are one of drastically areas in recent robotic research that shows mimic impact in human life. These system have been developed significantly to be used for human power augmentation, robotics rehabilitation, human power assist, and haptic interaction in virtual reality. This paper focus on solving challenges in problem using neural signals and extracting human intent. Commonly, surface electromyography signal (sEMG) are used in order to control human intent for application exoskeleton robot. But the problem lies on difficulty of pattern recognition of the sEMG features due to high noises which are electrode and cable motion artifact, electrode noise, dermic noise, alternating current power line interface, and other noise came from electronic instrument. The main objective in this paper is to study the best features of electromyography in term of time domain (statistical analysis) and frequency domain (Fast Fourier Transform).The secondary objectives is to map the relationship between torque and best features of muscle unit activation potential (MaxPS and RMS) of biceps brachii. This project scope use primary data of 2 male sample subject which using same dominant hand (right handed), age between 20-27 years old, muscle diameter 32cm to 35cm and using single channel muscle (biceps brachii muscle). The experiment conduct 2 times repeated task of contraction and relaxation of biceps brachii when lifting different load from no load to 3kg with ascending 1kg The result shows that Fast Fourier Transform maximum power spectrum (MaxPS) has less error than mean value of reading compare to root mean square (RMS) value. Thus, Fast Fourier Transform maximum power spectrum (MaxPS) show the linear relationship against torque experience by elbow joint to lift different load. As the conclusion, the best features is MaxPS because it has the lowest error than other features and show

  2. Effect of interelectrode distance on surface electromyographic signals of vastus intermedius muscle in women and men.

    PubMed

    Tomita, Aya; Ando, Ryosuke; Saito, Akira; Watanabe, Kohei; Akima, Hiroshi

    2015-12-01

    We previously developed a novel technique to record surface electromyography (EMG) of the vastus intermedius (VI) in men. The purpose of the present study was to assess whether this technique can be applied to women in the same way. We measured the subcutaneous fat thickness at the site of electrode placement on VI using ultrasonography. Nine men and ten women performed isometric knee extensions at 25%, 50%, 75%, and 100% of the maximal voluntary contraction. During the tasks, surface EMG signals were recorded from the superficial region of VI with interelectrode distances (IEDs) of 10 mm (IED-10) and 20 mm (IED-20). The subcutaneous fat thickness in women was significantly greater than in men (women: 8.7 ± 2.1 mm; men: 5.6 ± 1.6 mm, p < 0.01). However, the amplitude and frequency of the EMG signal of VI at the different force levels were not affected by IEDs in either sex. These results suggest that surface EMG recording of VI with both IED-10 and IED-20 would be applicable to relatively lean women with a similar sensitivity to that in men.

  3. Unilateral and bilateral subthalamic nucleus stimulation in Parkinson's disease: effects on EMG signals of lower limb muscles during walking.

    PubMed

    Ferrarin, Maurizio; Carpinella, Ilaria; Rabuffetti, Marco; Rizzone, Mario; Lopiano, Leonardo; Crenna, Paolo

    2007-06-01

    The effects of subthalamic nucleus (STN) stimulation on the spatio-temporal organization of locomotor commands directed to lower limb muscles were studied in subjects with idiopathic Parkinson's Disease (PD) by recording the EMG activity produced during steady-state walking in representative thigh (rectus femoris, RF, and semimembranosus, SM) and leg (gatrocnemius medialis, GAM, and tibialis anterior, TA) muscles, under four experimental conditions: basal stimulation OFF, unilateral (right and left) stimulation ON, and bilateral stimulation ON. Locomotor profiles of all of the muscles tested were found to be substantially affected by STN stimulation, either in terms of restoration/enhancement of the main activity bursts or normalization of recruitment timing thereof. Responses showed relatively higher statistical significance in the distal groups (GAM and TA) and, within them, for the EMG components called into action over the ground-contact (ankle dorsiflexors) and midstance (ankle plantarflexors) phases of the stride cycle. In line with data obtained from clinical rating, unilateral stimulation produced less consistent EMG changes compared with bilateral stimulation. However, at variance with clinical effects, which prevailed on the side of the body contralateral to stimulation, EMG responses to unilateral stimulation were usually symmetrical. Results indicate that the impact of STN stimulation on locomotor activation of lower limb muscles in PD is characterized by: 1) substantial effects exhibiting differential topographical (distal versus proximal) and stride-phase (stance versus swing) consistency and 2) absence of the lateralized actions typically observed for the clinical signs of the disease. Interaction with the activity of functionally different executive systems might account for the observed pattern of responsiveness.

  4. Effect of vibrotactile feedback on an EMG-based proportional cursor control system.

    PubMed

    Li, Shunchong; Chen, Xingyu; Zhang, Dingguo; Sheng, Xinjun; Zhu, Xiangyang

    2013-01-01

    Surface electromyography (sEMG) has been introduced into the bio-mechatronics systems, however, most of them are lack of the sensory feedback. In this paper, the effect of vibrotactile feedback for a myoelectric cursor control system is investigated quantitatively. Simultaneous and proportional control signals are extracted from EMG using a muscle synergy model. Different types of feedback including vibrotactile feedback and visual feedback are added, assessed and compared with each other. The results show that vibrotactile feedback is capable of improving the performance of EMG-based human machine interface.

  5. Analysis of surface EMG activation in hand percussion playing depending on the grasping type and the tempo.

    PubMed

    Chong, Hyun Ju; Kim, Soo Ji; Lee, Eun Kyoung; Yoo, Ga Eul

    2015-08-01

    Although instrument playing-based training has been repeatedly reported to improve functional hand movements including grasping, the attempts to present quantitative information on physiological mechanism of grasping have been relatively insufficient to determine the type and the intensity of the exercises involved. This study aimed to examine the muscle activation during hand percussion playing depending on the grasping type and the playing tempo. A total of twelve healthy older adults with a mean age of 71.5 years participated in this study. Surface electrodes were placed on three grasping-related muscles: Flexor digitorum superficialis, extensor digitorum, and flexor pollicis brevis. Participants were instructed to play with the egg shaker, paddle drum mallet and clave involving different types of grasp at three different tempi (i.e., 80, 100, and 120 bpm) and sEMG data were collected during each playing. Significantly greater muscle activation was generated with the small sphere type of egg shaker, compared to the handle type of paddle drum mallet and the small cylinder type of clave. Playing at faster tempo also elicited significantly greater muscle activation than at slower tempo. With regard to the rise time of muscle activation, while tempo significantly affected the rise time, the time to peak muscle did not significantly change depending on the grasping type. This study confirmed that grasping pattern and the tempo of movement significantly influence the muscular activation of grasping involved in instrument playing. Based on these results, clinical implication for instrument selection and structured instrument playing would be suggested.

  6. Evaluation of jaw and neck muscle activities while chewing using EMG-EMG transfer function and EMG-EMG coherence function analyses in healthy subjects.

    PubMed

    Ishii, Tomohiro; Narita, Noriyuki; Endo, Hiroshi

    2016-06-01

    This study aims to quantitatively clarify the physiological features in rhythmically coordinated jaw and neck muscle EMG activities while chewing gum using EMG-EMG transfer function and EMG-EMG coherence function analyses in 20 healthy subjects. The chewing side masseter muscle EMG signal was used as the reference signal, while the other jaw (non-chewing side masseter muscle, bilateral anterior temporal muscles, and bilateral anterior digastric muscles) and neck muscle (bilateral sternocleidomastoid muscles) EMG signals were used as the examined signals in EMG-EMG transfer function and EMG-EMG coherence function analyses. Chewing-related jaw and neck muscle activities were aggregated in the first peak of the power spectrum in rhythmic chewing. The gain in the peak frequency represented the power relationships between jaw and neck muscle activities during rhythmic chewing. The phase in the peak frequency represented the temporal relationships between the jaw and neck muscle activities, while the non-chewing side neck muscle presented a broad range of distributions across jaw closing and opening phases. Coherence in the peak frequency represented the synergistic features in bilateral jaw closing muscles and chewing side neck muscle activities. The coherence and phase in non-chewing side neck muscle activities exhibited a significant negative correlation. From above, the bilateral coordination between the jaw and neck muscle activities is estimated while chewing when the non-chewing side neck muscle is synchronously activated with the jaw closing muscles, while the unilateral coordination is estimated when the non-chewing side neck muscle is irregularly activated in the jaw opening phase. Thus, the occurrence of bilateral or unilateral coordinated features in the jaw and neck muscle activities may correspond to the phase characteristics in the non-chewing side neck muscle activities during rhythmical chewing. Considering these novel findings in healthy subjects, EMG-EMG

  7. Evaluation of jaw and neck muscle activities while chewing using EMG-EMG transfer function and EMG-EMG coherence function analyses in healthy subjects.

    PubMed

    Ishii, Tomohiro; Narita, Noriyuki; Endo, Hiroshi

    2016-06-01

    This study aims to quantitatively clarify the physiological features in rhythmically coordinated jaw and neck muscle EMG activities while chewing gum using EMG-EMG transfer function and EMG-EMG coherence function analyses in 20 healthy subjects. The chewing side masseter muscle EMG signal was used as the reference signal, while the other jaw (non-chewing side masseter muscle, bilateral anterior temporal muscles, and bilateral anterior digastric muscles) and neck muscle (bilateral sternocleidomastoid muscles) EMG signals were used as the examined signals in EMG-EMG transfer function and EMG-EMG coherence function analyses. Chewing-related jaw and neck muscle activities were aggregated in the first peak of the power spectrum in rhythmic chewing. The gain in the peak frequency represented the power relationships between jaw and neck muscle activities during rhythmic chewing. The phase in the peak frequency represented the temporal relationships between the jaw and neck muscle activities, while the non-chewing side neck muscle presented a broad range of distributions across jaw closing and opening phases. Coherence in the peak frequency represented the synergistic features in bilateral jaw closing muscles and chewing side neck muscle activities. The coherence and phase in non-chewing side neck muscle activities exhibited a significant negative correlation. From above, the bilateral coordination between the jaw and neck muscle activities is estimated while chewing when the non-chewing side neck muscle is synchronously activated with the jaw closing muscles, while the unilateral coordination is estimated when the non-chewing side neck muscle is irregularly activated in the jaw opening phase. Thus, the occurrence of bilateral or unilateral coordinated features in the jaw and neck muscle activities may correspond to the phase characteristics in the non-chewing side neck muscle activities during rhythmical chewing. Considering these novel findings in healthy subjects, EMG-EMG

  8. DIFFERENTIATING sEMG SIGNALS UNDER MUSCLE FATIGUE AND NON-FATIGUE CONDITIONS USING LOGISTIC REGRESSION CLASSIFIERS.

    PubMed

    Venugopal, G; Ramakrishnan, S

    2014-01-01

    In this work, an attempt has been made to differentiate surface electromyography signals under fatigue and non-fatigue conditions. Signals are recorded from the biceps brachii muscles of 50 healthy volunteers. A well-established experimental protocol is followed for this purpose. Signals are subjected to further processing and features namely amplitude of first burst, myopulse percentage rate, Willison amplitude, power spectrum ratio and variance of central frequency are extracted. Three types of logistic regression classifiers, linear logistic, polykernel logistic regression and multinomial regression with ridge estimator are used for automated analysis. Classifier parameters are tuned to enhance the accuracy and performance indices of algorithms, and are compared. The results show distinct values for extracted features in fatigue conditions which are statistically significant (0.0027 = P = 0.03). All classifiers are found to be effective in demarcating the signals. The linear logistic regression algorithm provides 79% accuracy with 40 iterations. However, in the case of multinomial regression with ridge estimator, only 7 iterations are required to achieve 80% accuracy. The polykernel logistic regression algorithm (0.06 = ? = 0.1) also provides 80% accuracy but with a marginal increment (1 % to 4 %) for precision, recall and specificity compared to other two classifiers.

  9. Computed myography: three-dimensional reconstruction of motor functions from surface EMG data

    NASA Astrophysics Data System (ADS)

    van den Doel, Kees; Ascher, Uri M.; Pai, Dinesh K.

    2008-12-01

    We describe a methodology called computed myography to qualitatively and quantitatively determine the activation level of individual muscles by voltage measurements from an array of voltage sensors on the skin surface. A finite element model for electrostatics simulation is constructed from morphometric data. For the inverse problem, we utilize a generalized Tikhonov regularization. This imposes smoothness on the reconstructed sources inside the muscles and suppresses sources outside the muscles using a penalty term. Results from experiments with simulated and human data are presented for activation reconstructions of three muscles in the upper arm (biceps brachii, bracialis and triceps). This approach potentially offers a new clinical tool to sensitively assess muscle function in patients suffering from neurological disorders (e.g., spinal cord injury), and could more accurately guide advances in the evaluation of specific rehabilitation training regimens.

  10. Designing a Low-noise, High-resolution, and Portable Four Channel Acquisition System for Recording Surface Electromyographic Signal.

    PubMed

    Pashaei, Akbar; Yazdchi, Mohammad Reza; Marateb, Hamid Reza

    2015-01-01

    In current years, the application of biopotential signals has received a lot of attention in literature. One of these signals is an electromyogram (EMG) generated by active muscles. Surface EMG (sEMG) signal is recorded over the skin, as the representative of the muscle activity. Since its amplitude can be as low as 50 μV, it is sensitive to undesirable noise signals such as power-line interferences. This study aims at designing a battery-powered portable four-channel sEMG signal acquisition system. The performance of the proposed system was assessed in terms of the input voltage and current noise, noise distribution, synchronization and input noise level among different channels. The results indicated that the designed system had several inbuilt operational merits such as low referred to input noise (lower than 0.56 μV between 8 Hz and 1000 Hz), considerable elimination of power-line interference and satisfactory recorded signal quality in terms of signal-to-noise ratio. The muscle conduction velocity was also estimated using the proposed system on the brachial biceps muscle during isometric contraction. The estimated values were in then normal ranges. In addition, the system included a modular configuration to increase the number of recording channels up to 96. PMID:26951952

  11. Designing a Low-noise, High-resolution, and Portable Four Channel Acquisition System for Recording Surface Electromyographic Signal

    PubMed Central

    Pashaei, Akbar; Yazdchi, Mohammad Reza; Marateb, Hamid Reza

    2015-01-01

    In current years, the application of biopotential signals has received a lot of attention in literature. One of these signals is an electromyogram (EMG) generated by active muscles. Surface EMG (sEMG) signal is recorded over the skin, as the representative of the muscle activity. Since its amplitude can be as low as 50 μV, it is sensitive to undesirable noise signals such as power-line interferences. This study aims at designing a battery-powered portable four-channel sEMG signal acquisition system. The performance of the proposed system was assessed in terms of the input voltage and current noise, noise distribution, synchronization and input noise level among different channels. The results indicated that the designed system had several inbuilt operational merits such as low referred to input noise (lower than 0.56 μV between 8 Hz and 1000 Hz), considerable elimination of power-line interference and satisfactory recorded signal quality in terms of signal-to-noise ratio. The muscle conduction velocity was also estimated using the proposed system on the brachial biceps muscle during isometric contraction. The estimated values were in then normal ranges. In addition, the system included a modular configuration to increase the number of recording channels up to 96. PMID:26951952

  12. Modeling nonlinear errors in surface electromyography due to baseline noise: a new methodology.

    PubMed

    Law, Laura Frey; Krishnan, Chandramouli; Avin, Keith

    2011-01-01

    The surface electromyographic (EMG) signal is often contaminated by some degree of baseline noise. It is customary for scientists to subtract baseline noise from the measured EMG signal prior to further analyses based on the assumption that baseline noise adds linearly to the observed EMG signal. The stochastic nature of both the baseline and EMG signal, however, may invalidate this assumption. Alternately, "true" EMG signals may be either minimally or nonlinearly affected by baseline noise. This information is particularly relevant at low contraction intensities when signal-to-noise ratios (SNR) may be lowest. Thus, the purpose of this simulation study was to investigate the influence of varying levels of baseline noise (approximately 2-40% maximum EMG amplitude) on mean EMG burst amplitude and to assess the best means to account for signal noise. The simulations indicated baseline noise had minimal effects on mean EMG activity for maximum contractions, but increased nonlinearly with increasing noise levels and decreasing signal amplitudes. Thus, the simple baseline noise subtraction resulted in substantial error when estimating mean activity during low intensity EMG bursts. Conversely, correcting EMG signal as a nonlinear function of both baseline and measured signal amplitude provided highly accurate estimates of EMG amplitude. This novel nonlinear error modeling approach has potential implications for EMG signal processing, particularly when assessing co-activation of antagonist muscles or small amplitude contractions where the SNR can be low.

  13. Detection of tremor bursts from the sEMG signal: an optimization procedure for different detection methods.

    PubMed

    De Marchis, C; Conforto, S; Severini, G; Schmid, M; D'Alessio, T

    2011-01-01

    Two different detection techniques for EMG burst detection are here used to reveal tremor in both a set of synthetic data and in a small sample of experimental trials. An optimization procedure that employs the minimization of a cost function to provide the parameter set characterizing the two techniques is here presented and its performance assessed. The results obtained with the optimization procedure are satisfactory and suitable for practical use: the values for both bias and standard deviation in the estimation of both onset and offset time instants are lower than 10 ms, and the sensitivity and positive predictive value in the detection of tremor bursts are > 96% for SNR levels higher than 6 dB.

  14. Development of new muscle contraction sensor to replace sEMG for using in muscles analysis fields.

    PubMed

    Zhang, D; Matsuoka, Y; Kong, W; Imtiaz, U; Bartolomeo, L; Cosentino, S; Zecca, M; Sessa, S; Ishii, H; Takanishi, A

    2014-01-01

    Nowadays, the technologies for detecting, processing and interpreting bioelectrical signals have improved tremendously. In particular, surface electromyography (sEMG) has gained momentum in a wide range of applications in various fields. However, sEMG sensing has several shortcomings, the most important being: measurements are heavily sensible to individual differences, sensors are difficult to position and very expensive. In this paper, the authors will present an innovative muscle contraction sensing device (MC sensor), aiming to replace sEMG sensing in the field of muscle movement analysis. Compared with sEMG, this sensor is easier to position, setup and use, less dependent from individual differences, and less expensive. Preliminary experiments, described in this paper, confirm that MC sensing is suitable for muscle contraction analysis, and compare the results of sEMG and MC sensor for the measurement of forearm muscle contraction.

  15. Generating Control Commands From Gestures Sensed by EMG

    NASA Technical Reports Server (NTRS)

    Wheeler, Kevin R.; Jorgensen, Charles

    2006-01-01

    An effort is under way to develop noninvasive neuro-electric interfaces through which human operators could control systems as diverse as simple mechanical devices, computers, aircraft, and even spacecraft. The basic idea is to use electrodes on the surface of the skin to acquire electromyographic (EMG) signals associated with gestures, digitize and process the EMG signals to recognize the gestures, and generate digital commands to perform the actions signified by the gestures. In an experimental prototype of such an interface, the EMG signals associated with hand gestures are acquired by use of several pairs of electrodes mounted in sleeves on a subject s forearm (see figure). The EMG signals are sampled and digitized. The resulting time-series data are fed as input to pattern-recognition software that has been trained to distinguish gestures from a given gesture set. The software implements, among other things, hidden Markov models, which are used to recognize the gestures as they are being performed in real time. Thus far, two experiments have been performed on the prototype interface to demonstrate feasibility: an experiment in synthesizing the output of a joystick and an experiment in synthesizing the output of a computer or typewriter keyboard. In the joystick experiment, the EMG signals were processed into joystick commands for a realistic flight simulator for an airplane. The acting pilot reached out into the air, grabbed an imaginary joystick, and pretended to manipulate the joystick to achieve left and right banks and up and down pitches of the simulated airplane. In the keyboard experiment, the subject pretended to type on a numerical keypad, and the EMG signals were processed into keystrokes. The results of the experiments demonstrate the basic feasibility of this method while indicating the need for further research to reduce the incidence of errors (including confusion among gestures). Topics that must be addressed include the numbers and arrangements

  16. An adaptation strategy of using LDA classifier for EMG pattern recognition.

    PubMed

    Zhang, Haoshi; Zhao, Yaonan; Yao, Fuan; Xu, Lisheng; Shang, Peng; Li, Guanglin

    2013-01-01

    The time-varying character of myoelectric signal usually causes a low classification accuracy in traditional supervised pattern recognition method. In this work, an unsupervised adaptation strategy of linear discriminant analysis (ALDA) based on probability weighting and cycle substitution was suggested in order to improve the performance of electromyography (EMG)-based motion classification in multifunctional myoelectric prostheses control in changing environment. The adaptation procedure was firstly introduced, and then the proposed ALDA classifier was trained and tested with surface EMG recordings related to multiple motion patterns. The accuracies of the ALDA classifier and traditional LDA classifier were compared when the EMG recordings were added with different degrees of noise. The experimental results showed that compared to the LDA method, the suggested ALDA method had a better performance in improving the classification accuracy of sEMG pattern recognition, in both stable situation and noise added situation.

  17. Evaluation of higher order statistics parameters for multi channel sEMG using different force levels.

    PubMed

    Naik, Ganesh R; Kumar, Dinesh K

    2011-01-01

    The electromyograpy (EMG) signal provides information about the performance of muscles and nerves. The shape of the muscle signal and motor unit action potential (MUAP) varies due to the movement of the position of the electrode or due to changes in contraction level. This research deals with evaluating the non-Gaussianity in Surface Electromyogram signal (sEMG) using higher order statistics (HOS) parameters. To achieve this, experiments were conducted for four different finger and wrist actions at different levels of Maximum Voluntary Contractions (MVCs). Our experimental analysis shows that at constant force and for non-fatiguing contractions, probability density functions (PDF) of sEMG signals were non-Gaussian. For lesser MVCs (below 30% of MVC) PDF measures tends to be Gaussian process. The above measures were verified by computing the Kurtosis values for different MVCs.

  18. EOG-sEMG Human Interface for Communication.

    PubMed

    Tamura, Hiroki; Yan, Mingmin; Sakurai, Keiko; Tanno, Koichi

    2016-01-01

    The aim of this study is to present electrooculogram (EOG) and surface electromyogram (sEMG) signals that can be used as a human-computer interface. Establishing an efficient alternative channel for communication without overt speech and hand movements is important for increasing the quality of life for patients suffering from amyotrophic lateral sclerosis, muscular dystrophy, or other illnesses. In this paper, we propose an EOG-sEMG human-computer interface system for communication using both cross-channels and parallel lines channels on the face with the same electrodes. This system could record EOG and sEMG signals as "dual-modality" for pattern recognition simultaneously. Although as much as 4 patterns could be recognized, dealing with the state of the patients, we only choose two classes (left and right motion) of EOG and two classes (left blink and right blink) of sEMG which are easily to be realized for simulation and monitoring task. From the simulation results, our system achieved four-pattern classification with an accuracy of 95.1%. PMID:27418924

  19. EOG-sEMG Human Interface for Communication

    PubMed Central

    Tamura, Hiroki; Yan, Mingmin; Sakurai, Keiko; Tanno, Koichi

    2016-01-01

    The aim of this study is to present electrooculogram (EOG) and surface electromyogram (sEMG) signals that can be used as a human-computer interface. Establishing an efficient alternative channel for communication without overt speech and hand movements is important for increasing the quality of life for patients suffering from amyotrophic lateral sclerosis, muscular dystrophy, or other illnesses. In this paper, we propose an EOG-sEMG human-computer interface system for communication using both cross-channels and parallel lines channels on the face with the same electrodes. This system could record EOG and sEMG signals as “dual-modality” for pattern recognition simultaneously. Although as much as 4 patterns could be recognized, dealing with the state of the patients, we only choose two classes (left and right motion) of EOG and two classes (left blink and right blink) of sEMG which are easily to be realized for simulation and monitoring task. From the simulation results, our system achieved four-pattern classification with an accuracy of 95.1%. PMID:27418924

  20. Comparison of sEMG processing methods during whole-body vibration exercise.

    PubMed

    Lienhard, Karin; Cabasson, Aline; Meste, Olivier; Colson, Serge S

    2015-12-01

    The objective was to investigate the influence of surface electromyography (sEMG) processing methods on the quantification of muscle activity during whole-body vibration (WBV) exercises. sEMG activity was recorded while the participants performed squats on the platform with and without WBV. The spikes observed in the sEMG spectrum at the vibration frequency and its harmonics were deleted using state-of-the-art methods, i.e. (1) a band-stop filter, (2) a band-pass filter, and (3) spectral linear interpolation. The same filtering methods were applied on the sEMG during the no-vibration trial. The linear interpolation method showed the highest intraclass correlation coefficients (no vibration: 0.999, WBV: 0.757-0.979) with the comparison measure (unfiltered sEMG during the no-vibration trial), followed by the band-stop filter (no vibration: 0.929-0.975, WBV: 0.661-0.938). While both methods introduced a systematic bias (P < 0.001), the error increased with increasing mean values to a higher degree for the band-stop filter. After adjusting the sEMG(RMS) during WBV for the bias, the performance of the interpolation method and the band-stop filter was comparable. The band-pass filter was in poor agreement with the other methods (ICC: 0.207-0.697), unless the sEMG(RMS) was corrected for the bias (ICC ⩾ 0.931, %LOA ⩽ 32.3). In conclusion, spectral linear interpolation or a band-stop filter centered at the vibration frequency and its multiple harmonics should be applied to delete the artifacts in the sEMG signals during WBV. With the use of a band-stop filter it is recommended to correct the sEMG(RMS) for the bias as this procedure improved its performance.

  1. Evaluation of sonomyography (SMG) for control compared with electromyography (EMG) in a discrete target tracking task.

    PubMed

    Guo, Jing-Yi; Zheng, Yong-Ping; Kenney, Laurence P; Xie, Hong-Bo

    2009-01-01

    Most of the commercial upper-limb externally powered prosthetic devices are controlled by electromyography (EMG) signals. We previously proposed using the real-time change of muscle thickness detected using ultrasound, namely sonomyography (SMG), for the control of prostheses. In this study, we compared the performance of subjects using 1-D SMG signal and surface EMG signal, using a discrete target tracking protocol involving a series of letter cancellation tasks. Each task involved using grip force, EMG or SMG from a wrist extensor muscle to move a cursor to one of 5 locations on a computer screen, at the first four of which were located a letter and last of which was a word of "NEXT". The target was defined by the location showing the letter "E" and, once the subject reached this target, they were instructed to "cancel" the E from the screen, using a button operated by the contralateral hand. A paired t-test revealed that the percentage of letters correctly cancelled with force/angle and SMG signal in isometric force control, and with SMG in wrist extension were significantly higher than with EMG (P<0.05) for both isometric control and wrist extension. The results suggest that SMG signal has great potential as an alternative to EMG for prosthetic control.

  2. Baseline Adaptive Wavelet Thresholding Technique for sEMG Denoising

    NASA Astrophysics Data System (ADS)

    Bartolomeo, L.; Zecca, M.; Sessa, S.; Lin, Z.; Mukaeda, Y.; Ishii, H.; Takanishi, Atsuo

    2011-06-01

    The surface Electromyography (sEMG) signal is affected by different sources of noises: current technology is considerably robust to the interferences of the power line or the cable motion artifacts, but still there are many limitations with the baseline and the movement artifact noise. In particular, these sources have frequency spectra that include also the low-frequency components of the sEMG frequency spectrum; therefore, a standard all-bandwidth filtering could alter important information. The Wavelet denoising method has been demonstrated to be a powerful solution in processing white Gaussian noise in biological signals. In this paper we introduce a new technique for the denoising of the sEMG signal: by using the baseline of the signal before the task, we estimate the thresholds to apply to the Wavelet thresholding procedure. The experiments have been performed on ten healthy subjects, by placing the electrodes on the Extensor Carpi Ulnaris and Triceps Brachii on right upper and lower arms, and performing a flexion and extension of the right wrist. An Inertial Measurement Unit, developed in our group, has been used to recognize the movements of the hands to segment the exercise and the pre-task baseline. Finally, we show better performances of the proposed method in term of noise cancellation and distortion of the signal, quantified by a new suggested indicator of denoising quality, compared to the standard Donoho technique.

  3. EMG activity of the serratus anterior and trapezius muscles during the different phases of the push-up plus exercise on different support surfaces and different hand positions

    PubMed Central

    Gioftsos, George; Arvanitidis, Michail; Tsimouris, Dimitrios; Kanellopoulos, Assimakis; Paras, George; Trigkas, Panagiotis; Sakellari, Vasiliki

    2016-01-01

    [Purpose] The appropriate exercise prescription is crucial for achieving scapular stability and providing successful rehabilitation, and the Push-up Plus (PuP) exercise has an important role in shoulder rehabilitation. Consequently, this study examined the effect of support surface stability, hand positioning, and phase of exercise, on the trapezius and serratus anterior muscle contractions as well as on the EMG ratio of the upper/lower trapezius. [Subjects and Methods] Thirteen healthy male volunteers participated in this study. The subjects performed the PuP exercise on stable and unstable supporting surfaces with three different hand orientations. During the PuP exercise, the muscle activities of the upper (UT) and lower (LT) trapezius, as well as the serratus anterior (SA) were measured and expressed as percentages of maximum voluntary isometric contraction (%MVIC). [Results] The EMG activities of UT and LT were statistically greater during the push-up phase compared to the plus phase of the exercise. The contrary was recorded for the activity of the SA. SA was affected by the support surface as well as by the hand positioning. [Conclusion] The results suggest that different phases of the PuP exercise require different muscle stability actions with corresponding activations of appropriate muscle fibers. A detailed prescription of the required phase of the exercise can more effectively activate the scapula-thoracic musculature. PMID:27512278

  4. Design, Development and Testing of a Low-Cost sEMG System and Its Use in Recording Muscle Activity in Human Gait

    PubMed Central

    Supuk, Tamara Grujic; Skelin, Ana Kuzmanic; Cic, Maja

    2014-01-01

    Surface electromyography (sEMG) is an important measurement technique used in biomechanical, rehabilitation and sport environments. In this article the design, development and testing of a low-cost wearable sEMG system are described. The hardware architecture consists of a two-cascade small-sized bioamplifier with a total gain of 2,000 and band-pass of 3 to 500 Hz. The sampling frequency of the system is 1,000 Hz. Since real measured EMG signals are usually corrupted by various types of noises (motion artifacts, white noise and electromagnetic noise present at 50 Hz and higher harmonics), we have tested several denoising techniques, both on artificial and measured EMG signals. Results showed that a wavelet—based technique implementing Daubechies5 wavelet and soft sqtwolog thresholding is the most appropriate for EMG signals denoising. To test the system performance, EMG activities of six dominant muscles of ten healthy subjects during gait were measured (gluteus maximus, biceps femoris, sartorius, rectus femoris, tibialis anterior and medial gastrocnemius). The obtained EMG envelopes presented against the duration of gait cycle were compared favourably with the EMG data available in the literature, suggesting that the proposed system is suitable for a wide range of applications in biomechanics. PMID:24811078

  5. The influence of occlusion on jaw and neck muscle activity: a surface EMG study in healthy young adults.

    PubMed

    Ferrario, V F; Tartaglia, G M; Galletta, A; Grassi, G P; Sforza, C

    2006-05-01

    The electromyographic (EMG) characteristics of masseter, temporalis and sternocleidomastoid (SCM) muscles during maximum voluntary teeth clench were assessed in 27 male and 35 female healthy young adults. Subjects were divided into two groups: (i) 'complete' Angle Class I (bilateral, symmetric canine and molar Class I relationships), and (ii) 'partial' Angle Class I (one to three canine/molar Class I relationships, the remaining relationships were Class II or Class III). On average, standardized muscular symmetry ranged 80.7-87.9%. During maximum voluntary teeth clench, average co-contraction of SCM muscle was 13.7-23.5% of its maximum contraction. On average, all torque coefficients (potential lateral displacing component) were >90%, while all antero-posterior coefficients (relative activities of masseter and temporalis muscles) were >85%. The average integrated areas of the masseter and temporalis EMG potentials over time ranged 87.4-106.8 muV/muV s%. Standardized contractile muscular activities did not differ between 'complete' and 'partial' Angle Class I, and between sexes (two-way analysis of variance). A trend toward a larger intragroup variability in EMG indices was observed in the subjects with 'partial' Angle Class I than in those with 'complete' Angle Class I (significant difference for the temporalis muscle symmetry, P = 0.013, analysis of variance). In conclusion, the presence of a complete or partial Angle occlusal Class I did not seem to influence the standardized contractile activities of masseter, temporalis and SCM muscles during a maximum voluntary clench. Subjects with a 'complete' Angle Class I were somewhat a more homogenous group than subjects with 'partial' Angle Class I.

  6. Continuous motion decoding from EMG using independent component analysis and adaptive model training.

    PubMed

    Zhang, Qin; Xiong, Caihua; Chen, Wenbin

    2014-01-01

    Surface Electromyography (EMG) is popularly used to decode human motion intention for robot movement control. Traditional motion decoding method uses pattern recognition to provide binary control command which can only move the robot as predefined limited patterns. In this work, we proposed a motion decoding method which can accurately estimate 3-dimensional (3-D) continuous upper limb motion only from multi-channel EMG signals. In order to prevent the muscle activities from motion artifacts and muscle crosstalk which especially obviously exist in upper limb motion, the independent component analysis (ICA) was applied to extract the independent source EMG signals. The motion data was also transferred from 4-manifold to 2-manifold by the principle component analysis (PCA). A hidden Markov model (HMM) was proposed to decode the motion from the EMG signals after the model trained by an adaptive model identification process. Experimental data were used to train the decoding model and validate the motion decoding performance. By comparing the decoded motion with the measured motion, it is found that the proposed motion decoding strategy was feasible to decode 3-D continuous motion from EMG signals.

  7. Improved discrete Fourier transform based spectral feature for surface electromyogram signal classification.

    PubMed

    He, Jiayuan; Zhang, Dingguo; Sheng, Xinjun; Meng, Jianjun; Zhu, Xiangyang

    2013-01-01

    An improved discrete Fourier transform (iDFT) is presented in this study as a novel feature for surface electromyogram (sEMG) pattern classification. It employs the principle that the spectrum of sEMG signals changes regarding different motions. iDFT feature focuses on global information of local bands to increase the inter-class distance. The experiment results showed that iDFT feature had a better separability than two other spectral features, auto regression (AR) and Power spectral density (PSD), both on experienced and inexperienced subjects. The optimal bandwidth is between 30 and 50 Hz and influence of division methods is not significant. With the low computation cost and property of insensitivity to sampling frequency, our proposed method provides a competitive choice for prosthetic control.

  8. Wideband EMG telemetry system

    NASA Technical Reports Server (NTRS)

    Rosatino, S. A.; Westbrook, R. M.

    1979-01-01

    Miniature, individual crystal-controlled RF transmitters located in EMG pressure sensors simplifies multichannel EMG telemetry for electronic gait monitoring. Transmitters which are assigned operating frequencies within 174 - 216 MHz band have linear frequency response from 20 - 2000 Hz and operate over range of 15 m.

  9. Analysis of Muscle Fatigue Progression using Cyclostationary Property of Surface Electromyography Signals.

    PubMed

    Karthick, P A; Venugopal, G; Ramakrishnan, S

    2016-01-01

    Analysis of neuromuscular fatigue finds various applications ranging from clinical studies to biomechanics. Surface electromyography (sEMG) signals are widely used for these studies due to its non-invasiveness. During cyclic dynamic contractions, these signals are nonstationary and cyclostationary. In recent years, several nonstationary methods have been employed for the muscle fatigue analysis. However, cyclostationary based approach is not well established for the assessment of muscle fatigue. In this work, cyclostationarity associated with the biceps brachii muscle fatigue progression is analyzed using sEMG signals and Spectral Correlation Density (SCD) functions. Signals are recorded from fifty healthy adult volunteers during dynamic contractions under a prescribed protocol. These signals are preprocessed and are divided into three segments, namely, non-fatigue, first muscle discomfort and fatigue zones. Then SCD is estimated using fast Fourier transform accumulation method. Further, Cyclic Frequency Spectral Density (CFSD) is calculated from the SCD spectrum. Two features, namely, cyclic frequency spectral area (CFSA) and cyclic frequency spectral entropy (CFSE) are proposed to study the progression of muscle fatigue. Additionally, degree of cyclostationarity (DCS) is computed to quantify the amount of cyclostationarity present in the signals. Results show that there is a progressive increase in cyclostationary during the progression of muscle fatigue. CFSA shows an increasing trend in muscle fatiguing contraction. However, CFSE shows a decreasing trend. It is observed that when the muscle progresses from non-fatigue to fatigue condition, the mean DCS of fifty subjects increases from 0.016 to 0.99. All the extracted features found to be distinct and statistically significant in the three zones of muscle contraction (p < 0.05). It appears that these SCD features could be useful in the automated analysis of sEMG signals for different neuromuscular conditions.

  10. Evaluation of muscle fatigue of wheelchair basketball players with spinal cord injury using recurrence quantification analysis of surface EMG.

    PubMed

    Uzun, S; Pourmoghaddam, A; Hieronymus, M; Thrasher, T A

    2012-11-01

    Wheelchair basketball is the most popular exercise activity among individuals with spinal cord injury (SCI). The purpose of this study was to investigate muscular endurance and fatigue in wheelchair basketball athletes with SCI using surface electromyography (SEMG) and maximal torque values. SEMG characteristics of 10 wheelchair basketball players (WBP) were compared to 13 able-bodied basketball players and 12 sedentary able-bodied subjects. Participants performed sustained isometric elbow flexion at 50% maximal voluntary contraction until exhaustion. Elbow flexion torque and SEMG signals were recorded from three elbow flexor muscles: biceps brachii longus, biceps brachii brevis and brachioradialis. SEMG signals were clustered into 0.5-s epochs with 50% overlap. Root mean square (RMS) and median frequency (MDF) of SEMG signals were calculated for each muscle and epoch as traditional fatigue monitoring. Recurrence quantification analysis was used to extract the percentage of determinism (%DET) of SEMG signals. The slope of the %DET for basketball players and WBP showed slower increase with time than the sedentary able-bodied control group for three different elbow flexor muscles, while no difference was observed for the slope of the %DET between basketball and WBP. This result indicated that the athletes are less fatigable during the task effort than the nonathletes. Normalized MDF slope decay exhibited similar results between the groups as %DET, while the slope of the normalized RMS failed to show any significant differences among the groups (p > 0.05). MDF and %DET could be useful for the evaluation of muscle fatigue in wheelchair basketball training. No conclusions about special training for WBP could be determined.

  11. Validity of surface electromyography for vastus intermedius muscle assessed by needle electromyography.

    PubMed

    Watanabe, Kohei; Akima, Hiroshi

    2011-06-15

    Recently, a new recording technique for surface electromyography (EMG) of the deeper muscle component of the quadriceps femoris muscle group, i.e., vastus intermedius (VI) muscle, from the distal portion of the VI muscle has been developed; however, the effect of electrode location on EMG signal of the VI muscle remains unclear. The aim of this study is to compare neuromuscular activation detected at the middle and distal portions of the VI muscle, in order to clarify whether the surface EMG of the VI muscle can be used to assess the neuromuscular activation of the entire muscle. Six healthy men participated in this study. During incremental ramp contraction of isometric knee extension (~30% of maximal voluntary contraction), needle EMG was recorded from the middle and distal regions of the VI muscle and surface EMG was performed at the distal region of the VI muscle. Excellent correlation was observed between needle EMG at the middle and distal regions (r=0.897-0.984, p<0.001). No significant difference was observed between correlation coefficient of surface EMG detected at the distal versus needle EMG detected at the middle and that of surface EMG detected at distal versus needle EMG detected at distal (p<0.05). These results suggest that surface EMG at the distal portion of the VI muscle, which is the only region available for surface EMG, can be used to evaluate global neuromuscular activation of the VI muscle during isometric contraction at a low force level.

  12. Nicotine and elevated body temperature reduce the complexity of the genioglossus and diaphragm EMG signals in rats during early maturation

    NASA Astrophysics Data System (ADS)

    Akkurt, David; Akay, Yasemin M.; Akay, Metin

    2009-10-01

    In this paper, we examined the effect of nicotine exposure and increased body temperature on the complexity (dynamics) of the genioglossus muscle (EMGg) and the diaphragm muscle (EMGdia) to explore the effects of nicotine and hyperthermia. Nonlinear dynamical analysis of the EMGdia and EMGg signals was performed using the approximate entropy method on 15 (7 saline- and 8 nicotine-treated) juvenile rats (P25-P35) and 19 (11 saline- and 8 nicotine-treated) young adult rats (P36-P44). The mean complexity values were calculated over the ten consecutive breaths using the approximate entropy method during mild elevated body temperature (38 °C) and severe elevated body temperature (39-40 °C) in two groups. In the first (nicotine) group, rats were treated with single injections of nicotine enough to produce brain levels of nicotine similar to those achieved in human smokers (2.5 (mg kg-1)/day) until the recording day. In the second (control) group, rats were treated with injections of saline, beginning at postnatal 5 days until the recording day. Our results show that warming the rat by 2-3 °C and nicotine exposure significantly decreased the complexity of the EMGdia and EMGg for the juvenile age group. This reduction in the complexity of the EMGdia and EMGg for the nicotine group was much greater than the normal during elevated body temperatures. We speculate that the generalized depressive effects of nicotine exposure and elevated body temperature on the respiratory neural firing rate and the behavior of the central respiratory network could be responsible for the drastic decrease in the complexity of the EMGdia and EMGg signals, the outputs of the respiratory neural network during early maturation.

  13. sEMG during Whole-Body Vibration Contains Motion Artifacts and Reflex Activity

    PubMed Central

    Lienhard, Karin; Cabasson, Aline; Meste, Olivier; Colson, Serge S.

    2015-01-01

    The purpose of this study was to determine whether the excessive spikes observed in the surface electromyography (sEMG) spectrum recorded during whole-body vibration (WBV) exercises contain motion artifacts and/or reflex activity. The occurrence of motion artifacts was tested by electrical recordings of the patella. The involvement of reflex activity was investigated by analyzing the magnitude of the isolated spikes during changes in voluntary background muscle activity. Eighteen physically active volunteers performed static squats while the sEMG was measured of five lower limb muscles during vertical WBV using no load and an additional load of 33 kg. In order to record motion artifacts during WBV, a pair of electrodes was positioned on the patella with several layers of tape between skin and electrodes. Spectral analysis of the patella signal revealed recordings of motion artifacts as high peaks at the vibration frequency (fundamental) and marginal peaks at the multiple harmonics were observed. For the sEMG recordings, the root mean square of the spikes increased with increasing additional loads (p < 0.05), and was significantly correlated to the sEMG signal without the spikes of the respective muscle (r range: 0.54 - 0.92, p < 0.05). This finding indicates that reflex activity might be contained in the isolated spikes, as identical behavior has been found for stretch reflex responses evoked during direct vibration. In conclusion, the spikes visible in the sEMG spectrum during WBV exercises contain motion artifacts and possibly reflex activity. Key points The spikes observed in the sEMG spectrum during WBV exercises contain motion artifacts and possibly reflex activity The motion artifacts are more pronounced in the first spike than the following spikes in the sEMG spectrum Reflex activity during WBV exercises is enhanced with an additional load of approximately 50% of the body mass PMID:25729290

  14. EMG (Electromyography) (For Parents)

    MedlinePlus

    ... conditions that might be causing muscle weakness, including muscular dystrophy and nerve disorders. How Is an EMG Done? ... contraction: diseases of the muscle itself (most commonly, muscular dystrophy in children) diseases of the neuromuscular junction , which ...

  15. Gesture Based Control and EMG Decomposition

    NASA Technical Reports Server (NTRS)

    Wheeler, Kevin R.; Chang, Mindy H.; Knuth, Kevin H.

    2005-01-01

    This paper presents two probabilistic developments for use with Electromyograms (EMG). First described is a new-electric interface for virtual device control based on gesture recognition. The second development is a Bayesian method for decomposing EMG into individual motor unit action potentials. This more complex technique will then allow for higher resolution in separating muscle groups for gesture recognition. All examples presented rely upon sampling EMG data from a subject's forearm. The gesture based recognition uses pattern recognition software that has been trained to identify gestures from among a given set of gestures. The pattern recognition software consists of hidden Markov models which are used to recognize the gestures as they are being performed in real-time from moving averages of EMG. Two experiments were conducted to examine the feasibility of this interface technology. The first replicated a virtual joystick interface, and the second replicated a keyboard. Moving averages of EMG do not provide easy distinction between fine muscle groups. To better distinguish between different fine motor skill muscle groups we present a Bayesian algorithm to separate surface EMG into representative motor unit action potentials. The algorithm is based upon differential Variable Component Analysis (dVCA) [l], [2] which was originally developed for Electroencephalograms. The algorithm uses a simple forward model representing a mixture of motor unit action potentials as seen across multiple channels. The parameters of this model are iteratively optimized for each component. Results are presented on both synthetic and experimental EMG data. The synthetic case has additive white noise and is compared with known components. The experimental EMG data was obtained using a custom linear electrode array designed for this study.

  16. Signal noise ratio of small intestine myoelectrical signal recorded from external surface.

    PubMed

    Martinez-de-Juan, Jose L; Garcia-Casado, Javier; Ye, Yiyao; Guardiola, Jose L; Ponce, Jose L

    2006-01-01

    Electroenterogram (EEnG), which is the myoelectrical activity of the small bowel, can be non-invasively recorded from abdominal external surface. However, this bioelectrical signal is weak and noisy compared to internal recording from bowel serous layers, because of bioelectric transmission through abdominal layers. Furthermore, it is contaminated with several interferences from other biological activities as cardiac muscle (ECG), skeletal muscles (EMG), or respiration movements. The goal of present work is to study abdominal recording of EEnG and its signal-to-noise ratio by means of the coherence estimation technique. External and internal recordings were obtained simultaneously in 12 sessions, which went on more than two hours in six beagle dogs. Coherence function, based on periodograms, is estimated in periods of 15 minutes. Thus, SNR is calculated from coherence estimation for each recording session. Results show that SNR reaches a maximum value of 8.8 dB for 0.31 Hz, which corresponds to fundamental frequency of the EEnG slow wave. However, SNR is weak at frequencies upper 2 Hz, which corresponds to rapid action potentials (spike bursts) of the EEnG. In conclusion, slow wave can be clearly identified in abdominal recording; however spike bursts are contaminated by noise, attenuation and biological interferences.

  17. EMG analysis of the lower extremities during pitching in high-school baseball.

    PubMed

    Yamanouchi, T

    1998-01-01

    I evaluated the contractions of the muscles of the lower extremities during baseball pitching using video imaging and simultaneous surface EMG. The subjects were 10 members of a high school baseball club and, for contrast, 10 students without any baseball club experience. I divided their pitching movements into two phases determined with respect to the landing of the non-pivot leg. The EMG signal intensities over the 2 seconds prior to landing, and over the 2 seconds after landing, were then integrated to give an EMG value to each phase. I then computed this value as the % MMT. The abductor and adductor of the hip muscles of both lower extremities in the players were strongly contracted, especially the adductor. This finding was consistent with the observation that pitching tends to lead to adductor muscle disorders. Strengthening the adductor and its antagonist abductor can therefore directly influence the capability for pitching, and can reduce the risk for the adductor disorders. PMID:9658746

  18. EMG analysis of the lower extremities during pitching in high-school baseball.

    PubMed

    Yamanouchi, T

    1998-01-01

    I evaluated the contractions of the muscles of the lower extremities during baseball pitching using video imaging and simultaneous surface EMG. The subjects were 10 members of a high school baseball club and, for contrast, 10 students without any baseball club experience. I divided their pitching movements into two phases determined with respect to the landing of the non-pivot leg. The EMG signal intensities over the 2 seconds prior to landing, and over the 2 seconds after landing, were then integrated to give an EMG value to each phase. I then computed this value as the % MMT. The abductor and adductor of the hip muscles of both lower extremities in the players were strongly contracted, especially the adductor. This finding was consistent with the observation that pitching tends to lead to adductor muscle disorders. Strengthening the adductor and its antagonist abductor can therefore directly influence the capability for pitching, and can reduce the risk for the adductor disorders.

  19. An EMG frequency-based test for estimating the neuromuscular fatigue threshold during cycle ergometry.

    PubMed

    Camic, Clayton L; Housh, Terry J; Johnson, Glen O; Hendrix, C Russell; Zuniga, Jorge M; Mielke, Michelle; Schmidt, Richard J

    2010-01-01

    The purposes of this investigation were twofold: (1) to determine if the model used for estimating the physical working capacity at the fatigue threshold (PWC(FT)) from electromyographic (EMG) amplitude data could be applied to the frequency domain of the signal to derive a new fatigue threshold for cycle ergometry called the mean power frequency fatigue threshold (MPF(FT)), and (2) to compare the power outputs associated with the PWC(FT), MPF(FT), ventilatory threshold (VT), and respiratory compensation point (RCP). Sixteen men [mean (SD) age = 23.4 (3.2) years] performed incremental cycle ergometer rides to exhaustion with bipolar surface EMG signals recorded from the vastus lateralis. There were significant (p < 0.05) mean differences for PWC(FT) [mean (SD) = 168 (36) W] versus MPF(FT) [208 (37) W] and VT [152 (33) W] versus RCP [205 (84) W], but no mean differences for PWC(FT) versus VT or MPF(FT) versus RCP. The mean difference between PWC(FT) and MPF(FT) may be due to the effects of specific metabolites that independently influence the time and frequency domains of the EMG signal. These findings indicated that the PWC(FT) model could be applied to the frequency domain of the EMG signal to estimate MPF(FT). Furthermore, the current findings suggested that the PWC(FT) may demarcate the moderate from heavy exercise domains, while the MPF(FT) demarcates heavy from severe exercise intensities.

  20. Young, Healthy Subjects Can Reduce the Activity of Calf Muscles When Provided with EMG Biofeedback in Upright Stance.

    PubMed

    Vieira, Taian M; Baudry, Stéphane; Botter, Alberto

    2016-01-01

    Recent evidence suggests the minimization of muscular effort rather than of the size of bodily sway may be the primary, nervous system goal when regulating the human, standing posture. Different programs have been proposed for balance training; none however has been focused on the activation of postural muscles during standing. In this study we investigated the possibility of minimizing the activation of the calf muscles during standing through biofeedback. By providing subjects with an audio signal that varied in amplitude and frequency with the amplitude of surface electromyograms (EMG) recorded from different regions of the gastrocnemius and soleus muscles, we expected them to be able to minimize the level of muscle activation during standing without increasing the excursion of the center of pressure (CoP). CoP data and surface EMG from gastrocnemii, soleus and tibialis anterior muscles were obtained from 10 healthy participants while standing at ease and while standing with EMG biofeedback. Four sensitivities were used to test subjects' responsiveness to the EMG biofeedback. Compared with standing at ease, the two most sensitive feedback conditions induced a decrease in plantar flexor activity (~15%; P < 0.05) and an increase in tibialis anterior EMG (~10%; P < 0.05). Furthermore, CoP mean position significantly shifted backward (~30 mm). In contrast, the use of less sensitive EMG biofeedback resulted in a significant decrease in EMG activity of ankle plantar flexors with a marginal increase in TA activity compared with standing at ease. These changes were not accompanied by greater CoP displacements or significant changes in mean CoP position. Key results revealed subjects were able to keep standing stability while reducing the activity of gastrocnemius and soleus without loading their tibialis anterior muscle when standing with EMG biofeedback. These results may therefore posit the basis for the development of training protocols aimed at assisting subjects in

  1. Young, Healthy Subjects Can Reduce the Activity of Calf Muscles When Provided with EMG Biofeedback in Upright Stance

    PubMed Central

    Vieira, Taian M.; Baudry, Stéphane; Botter, Alberto

    2016-01-01

    Recent evidence suggests the minimization of muscular effort rather than of the size of bodily sway may be the primary, nervous system goal when regulating the human, standing posture. Different programs have been proposed for balance training; none however has been focused on the activation of postural muscles during standing. In this study we investigated the possibility of minimizing the activation of the calf muscles during standing through biofeedback. By providing subjects with an audio signal that varied in amplitude and frequency with the amplitude of surface electromyograms (EMG) recorded from different regions of the gastrocnemius and soleus muscles, we expected them to be able to minimize the level of muscle activation during standing without increasing the excursion of the center of pressure (CoP). CoP data and surface EMG from gastrocnemii, soleus and tibialis anterior muscles were obtained from 10 healthy participants while standing at ease and while standing with EMG biofeedback. Four sensitivities were used to test subjects' responsiveness to the EMG biofeedback. Compared with standing at ease, the two most sensitive feedback conditions induced a decrease in plantar flexor activity (~15%; P < 0.05) and an increase in tibialis anterior EMG (~10%; P < 0.05). Furthermore, CoP mean position significantly shifted backward (~30 mm). In contrast, the use of less sensitive EMG biofeedback resulted in a significant decrease in EMG activity of ankle plantar flexors with a marginal increase in TA activity compared with standing at ease. These changes were not accompanied by greater CoP displacements or significant changes in mean CoP position. Key results revealed subjects were able to keep standing stability while reducing the activity of gastrocnemius and soleus without loading their tibialis anterior muscle when standing with EMG biofeedback. These results may therefore posit the basis for the development of training protocols aimed at assisting subjects in

  2. Finite State Machine with Adaptive Electromyogram (EMG) Feature Extraction to Drive Meal Assistance Robot

    NASA Astrophysics Data System (ADS)

    Zhang, Xiu; Wang, Xingyu; Wang, Bei; Sugi, Takenao; Nakamura, Masatoshi

    Surface electromyogram (EMG) from elbow, wrist and hand has been widely used as an input of multifunction prostheses for many years. However, for patients with high-level limb deficiencies, muscle activities in upper-limbs are not strong enough to be used as control signals. In this paper, EMG from lower-limbs is acquired and applied to drive a meal assistance robot. An onset detection method with adaptive threshold based on EMG power is proposed to recognize different muscle contractions. Predefined control commands are output by finite state machine (FSM), and applied to operate the robot. The performance of EMG control is compared with joystick control by both objective and subjective indices. The results show that FSM provides the user with an easy-performing control strategy, which successfully operates robots with complicated control commands by limited muscle motions. The high accuracy and comfortableness of the EMG-control meal assistance robot make it feasible for users with upper limbs motor disabilities.

  3. Surface Laplacian of central scalp electrical signals is insensitive to muscle contamination.

    PubMed

    Fitzgibbon, Sean P; Lewis, Trent W; Powers, David M W; Whitham, Emma W; Willoughby, John O; Pope, Kenneth J

    2013-01-01

    The objective of this paper was to investigate the effects of surface Laplacian processing on gross and persistent electromyographic (EMG) contamination of electroencephalographic (EEG) signals in electrical scalp recordings. We made scalp recordings during passive and active tasks, on awake subjects in the absence and in the presence of complete neuromuscular blockade. Three scalp surface Laplacian estimators were compared to left ear and common average reference (CAR). Contamination was quantified by comparing power after paralysis (brain signal, B) with power before paralysis (brain plus muscle signal, B+M). Brain:Muscle (B:M) ratios for the methods were calculated using B and differences in power after paralysis to represent muscle (M). There were very small power differences after paralysis up to 600 Hz using surface Laplacian transforms (B:M > 6 above 30 Hz in central scalp leads). Scalp surface Laplacian transforms reduce muscle power in central and pericentral leads to less than one sixth of the brain signal, two to three times better signal detection than CAR. Scalp surface Laplacian transformations provide robust estimates for detecting high-frequency (gamma) activity, for assessing electrophysiological correlates of disease, and also for providing a measure of brain electrical activity for use as a standard in the development of brain/muscle signal separation methods.

  4. Characterizing EMG data using machine-learning tools.

    PubMed

    Yousefi, Jamileh; Hamilton-Wright, Andrew

    2014-08-01

    Effective electromyographic (EMG) signal characterization is critical in the diagnosis of neuromuscular disorders. Machine-learning based pattern classification algorithms are commonly used to produce such characterizations. Several classifiers have been investigated to develop accurate and computationally efficient strategies for EMG signal characterization. This paper provides a critical review of some of the classification methodologies used in EMG characterization, and presents the state-of-the-art accomplishments in this field, emphasizing neuromuscular pathology. The techniques studied are grouped by their methodology, and a summary of the salient findings associated with each method is presented.

  5. Dynamic tension EMG to characterize the effects of DBS treatment of advanced Parkinson's disease.

    PubMed

    Ruonala, V; Pekkonen, E; Rissanen, S; Airaksinen, O; Miroshnichenko, G; Kankaanpää, M; Karjalainen, P

    2014-01-01

    Deep brain stimulation (DBS) is an effective treatment method for motor symptoms of advanced Parkinson's disease. DBS-electrode is implanted to subthalamic nucleus to give precisely allocated electrical stimuli to brain. The optimal stimulus type has to be adjusted individually. Disease severity, main symptoms and biological factors play a role in correctly setting up the device. Currently there are no objective methods to assess the efficacy of DBS, hence the adjustment is based solely on clinical assessment. In optimal case an objectively measurable feature would point the right settings of DBS. Surface electromyographic and kinematic measurements have been used in Parkinson's disease research. As Parkinson's disease symptoms are known to change the EMG signal properties, these methods could be helpful aid in the clinical adjustment of DBS. In this study, 13 patients with advanced Parkinson's disease who received DBS treatment were measured. The patients were measured with seven different settings of the DBS in clinical range including changes in stimulation amplitude, frequency and pulse width. The EMG analysis was based on parameters that characterize EMG signal morphology. Correlation dimension and recurrence rate made the most significant difference in relation to optimal settings. In conclusion, EMG analysis is able to detect differences between the DBS setups, and can help in finding the correct parameters. PMID:25570683

  6. Variation in EMG activity: a hierarchical approach

    PubMed Central

    German, Rebecca Z.; Crompton, A. W.; Thexton, A. J.

    2008-01-01

    Recordings of naturally occurring Electromyographic (EMG) signals are variable. One of the first formal and successful attempts to quantify variation in EMG signals was Shaffer and Lauder's (1985) study examining several levels of variation but not within muscle. The goal of the current study was to quantify the variation that exists at different levels, using more detailed measures of EMG activity than did Shaffer and Lauder (1985). The importance of accounting for different levels of variation in an EMG study is both biological and statistical. Signal variation within the same muscle for a stereotyped action suggests that each recording represents a sample drawn from a pool of a large number of motor units that, while biologically functioning in an integrated fashion, showed statistical variation. Different levels of variation for different muscles could be related to different functions or different tasks of those muscles. The statistical impact of unaccounted or inappropriately analyzed variation can lead to false rejection (type I error) or false acceptance (type II error) of the null hypothesis. Type II errors occur because such variation will accrue to the error, reducing power, and producing an artificially low F-value. Type I errors are associated with pseudoreplication, in which the replicated units are not truly independent, thereby leading to inflated degrees of freedom, and an underestimate of the error mean square. To address these problems, we used a repeated measures, nested multifactor model to measure the relative contribution of different hierarchical levels of variation to the total variation in EMG signals during swallowing. We found that variation at all levels, among electrodes in the same muscle, in sequences of the same animal, and among individuals and between differently named muscles, was significant. These findings suggest that a single intramuscular electrode, recording from a limited sample of the motor units, cannot be relied upon to

  7. EMG-Torque correction on Human Upper extremity using Evolutionary Computation

    NASA Astrophysics Data System (ADS)

    JL, Veronica; Parasuraman, S.; Khan, M. K. A. Ahamed; Jeba DSingh, Kingsly

    2016-09-01

    There have been many studies indicating that control system of rehabilitative robot plays an important role in determining the outcome of the therapy process. Existing works have done the prediction of feedback signal in the controller based on the kinematics parameters and EMG readings of upper limb's skeletal system. Kinematics and kinetics based control signal system is developed by reading the output of the sensors such as position sensor, orientation sensor and F/T (Force/Torque) sensor and there readings are to be compared with the preceding measurement to decide on the amount of assistive force. There are also other works that incorporated the kinematics parameters to calculate the kinetics parameters via formulation and pre-defined assumptions. Nevertheless, these types of control signals analyze the movement of the upper limb only based on the movement of the upper joints. They do not anticipate the possibility of muscle plasticity. The focus of the paper is to make use of the kinematics parameters and EMG readings of skeletal system to predict the individual torque of upper extremity's joints. The surface EMG signals are fed into different mathematical models so that these data can be trained through Genetic Algorithm (GA) to find the best correlation between EMG signals and torques acting on the upper limb's joints. The estimated torque attained from the mathematical models is called simulated output. The simulated output will then be compared with the actual individual joint which is calculated based on the real time kinematics parameters of the upper movement of the skeleton when the muscle cells are activated. The findings from this contribution are extended into the development of the active control signal based controller for rehabilitation robot.

  8. Knee extensor torque and quadriceps femoris EMG during perceptually-guided isometric contractions.

    PubMed

    Pincivero, D M; Coelho, A J; Campy, R M; Salfetnikov, Y; Suter, E

    2003-04-01

    The aim of this study was to examine superficial quadriceps femoris (QF) EMG and torque at perceived voluntary contraction efforts. Thirty subjects (15 males, 15 females) performed 9, 5 s, sub-maximal contractions at prescribed levels of perceived voluntary effort at points 1-9 on an 11-point scale (0-10), in a random order. Surface electromyograms (EMG) of the vastus medialis (VM), vastus lateralis (VL), and rectus femoris (RF) muscles, as well as QF peak torque (PT), average torque (AT), and torque coefficient of variation (C.V.), were sampled. The raw EMG signals were full-wave rectified and integrated over the middle three s of each contraction. The sampled EMG signals, and PT and AT at each perceived exertion level were normalized to the average of three maximal voluntary contractions. The normalized EMG and torque values at each perceived exertion level were then compared to equivalent percent values (i.e., 10% at a perceived level of 1). The results demonstrated that at all perceived exertion levels, with the exception of the RF at a level of 2 which was equivalent to 20%, and the VL and RF muscles at a level 1 in which activation was greater than 10%, activation was significantly less than the equivalent percent value at each point on the scale. VM EMG was found to be less than the VL and RF from contraction levels 3-9. PT was shown to be less than the equivalent percent values at contraction levels 6-9. The AT was found to be lower than the expected percent value at perceived effort levels 2-9. Torque C.V. was not found to be different across the range of perceived effort. The major findings of this study suggested that humans over-estimate voluntary QF muscle torque when guided by perceptual sensations. It is also suggested that the produced EMG signals revealed a reliance on the VL muscle for knee extensor torque generation at sub-maximal levels.

  9. Local Wavelet-Based Filtering of Electromyographic Signals to Eliminate the Electrocardiographic-Induced Artifacts in Patients with Spinal Cord Injury

    PubMed Central

    Nitzken, Matthew; Bajaj, Nihit; Aslan, Sevda; Gimel’farb, Georgy; Ovechkin, Alexander

    2013-01-01

    Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorders associated with motor control deficits. However, EMG potentials recorded from these muscles are often contaminated with heart-induced electrocardiographic (ECG) signals. Elimination of these artifacts plays a critical role in the precise measure of the respiratory muscle electrical activity. This study was undertaken to find an optimal approach to eliminate the ECG artifacts from EMG recordings. Conventional global filtering can be used to decrease the ECG-induced artifact. However, this method can alter the EMG signal and changes physiologically relevant information. We hypothesize that, unlike global filtering, localized removal of ECG artifacts will not change the original EMG signals. We develop an approach to remove the ECG artifacts without altering the amplitude and frequency components of the EMG signal by using an externally recorded ECG signal as a mask to locate areas of the ECG spikes within EMG data. These segments containing ECG spikes were decomposed into 128 sub-wavelets by a custom-scaled Morlet Wavelet Transform. The ECG-related sub-wavelets at the ECG spike location were removed and a de-noised EMG signal was reconstructed. Validity of the proposed method was proven using mathematical simulated synthetic signals and EMG obtained from SCI patients. We compare the Root-mean Square Error and the Relative Change in Variance between this method, global, notch and adaptive filters. The results show that the localized wavelet-based filtering has the benefit of not introducing error in the native EMG signal and accurately removing ECG artifacts from EMG signals

  10. A frequency and pulse-width co-modulation strategy for transcutaneous neuromuscular electrical stimulation based on sEMG time-domain features

    NASA Astrophysics Data System (ADS)

    Zhou, Yu-Xuan; Wang, Hai-Peng; Bao, Xue-Liang; Lü, Xiao-Ying; Wang, Zhi-Gong

    2016-02-01

    Objective. Surface electromyography (sEMG) is often used as a control signal in neuromuscular electrical stimulation (NMES) systems to enhance the voluntary control and proprioceptive sensory feedback of paralyzed patients. Most sEMG-controlled NMES systems use the envelope of the sEMG signal to modulate the stimulation intensity (current amplitude or pulse width) with a constant frequency. The aims of this study were to develop a strategy that co-modulates frequency and pulse width based on features of the sEMG signal and to investigate the torque-reproduction performance and the level of fatigue resistance achieved with our strategy. Approach. We examined the relationships between wrist torque and two stimulation parameters (frequency and pulse width) and between wrist torque and two sEMG time-domain features (mean absolute value (MAV) and number of slope sign changes (NSS)) in eight healthy volunteers. By using wrist torque as an intermediate variable, customized and generalized transfer functions were constructed to convert the two features of the sEMG signal into the two stimulation parameters, thereby establishing a MAV/NSS dual-coding (MNDC) algorithm. Wrist torque reproduction performance was assessed by comparing the torque generated by the algorithms with that originally recorded during voluntary contractions. Muscle fatigue was assessed by measuring the decline percentage of the peak torque and by comparing the torque time integral of the response to test stimulation trains before and after fatigue sessions. Main Results. The MNDC approach could produce a wrist torque that closely matched the voluntary wrist torque. In addition, a smaller decay in the wrist torque was observed after the MNDC-coded fatigue stimulation was applied than after stimulation using pulse-width modulation alone. Significance. Compared with pulse-width modulation stimulation strategies that are based on sEMG detection, the MNDC strategy is more effective for both voluntary muscle

  11. Adaptive neuron-to-EMG decoder training for FES neuroprostheses

    NASA Astrophysics Data System (ADS)

    Ethier, Christian; Acuna, Daniel; Solla, Sara A.; Miller, Lee E.

    2016-08-01

    Objective. We have previously demonstrated a brain-machine interface neuroprosthetic system that provided continuous control of functional electrical stimulation (FES) and restoration of grasp in a primate model of spinal cord injury (SCI). Predicting intended EMG directly from cortical recordings provides a flexible high-dimensional control signal for FES. However, no peripheral signal such as force or EMG is available for training EMG decoders in paralyzed individuals. Approach. Here we present a method for training an EMG decoder in the absence of muscle activity recordings; the decoder relies on mapping behaviorally relevant cortical activity to the inferred EMG activity underlying an intended action. Monkeys were trained at a 2D isometric wrist force task to control a computer cursor by applying force in the flexion, extension, ulnar, and radial directions and execute a center-out task. We used a generic muscle force-to-endpoint force model based on muscle pulling directions to relate each target force to an optimal EMG pattern that attained the target force while minimizing overall muscle activity. We trained EMG decoders during the target hold periods using a gradient descent algorithm that compared EMG predictions to optimal EMG patterns. Main results. We tested this method both offline and online. We quantified both the accuracy of offline force predictions and the ability of a monkey to use these real-time force predictions for closed-loop cursor control. We compared both offline and online results to those obtained with several other direct force decoders, including an optimal decoder computed from concurrently measured neural and force signals. Significance. This novel approach to training an adaptive EMG decoder could make a brain-control FES neuroprosthesis an effective tool to restore the hand function of paralyzed individuals. Clinical implementation would make use of individualized EMG-to-force models. Broad generalization could be achieved by

  12. Knowledge of electromyography (EMG) in patients undergoing EMG examinations.

    PubMed

    Mondelli, Mauro; Aretini, Alessandro; Greco, Giuseppe

    2014-01-01

    The aim of this study was to evaluate knowledge of electromyography (EMG) in patients undergoing the procedure. In one year, 1,586 consecutive patients (mean age 56 years; 58.8% women) were admitted to two EMG labs to undergo EMG for the first time. The patients found to be "informed" about the how an EMG examination is performed and about the purpose of EMG numbered 448 (28.2%), while those found to be "informed" only about the manner of its execution or only about its purpose numbered 161 (10.2%) and 151 (9.5%), respectively. The remaining 826 (52.1%) patients had either no information, or the information they had was very poor or incorrect (this was particularly true if they had been consulting websites). Being "informed" was associated with level of education (high), type of referring physician (specialist) and with an appropriate referral diagnosis specified in the EMG request. The quality of patient information on EMG was found to be very poor and could be improved. Physicians referring patients for EMG examinations, especially general practitioners, should assume primary responsibility for patient education and counseling in this field.

  13. Computational Intelligence Based Data Fusion Algorithm for Dynamic sEMG and Skeletal Muscle Force Modelling

    SciTech Connect

    Chandrasekhar Potluri,; Madhavi Anugolu; Marco P. Schoen; D. Subbaram Naidu

    2013-08-01

    In this work, an array of three surface Electrography (sEMG) sensors are used to acquired muscle extension and contraction signals for 18 healthy test subjects. The skeletal muscle force is estimated using the acquired sEMG signals and a Non-linear Wiener Hammerstein model, relating the two signals in a dynamic fashion. The model is obtained from using System Identification (SI) algorithm. The obtained force models for each sensor are fused using a proposed fuzzy logic concept with the intent to improve the force estimation accuracy and resilience to sensor failure or misalignment. For the fuzzy logic inference system, the sEMG entropy, the relative error, and the correlation of the force signals are considered for defining the membership functions. The proposed fusion algorithm yields an average of 92.49% correlation between the actual force and the overall estimated force output. In addition, the proposed fusionbased approach is implemented on a test platform. Experiments indicate an improvement in finger/hand force estimation.

  14. Re-examination of the surface EMG activity of the masseter muscle in young adults during chewing of two test foods.

    PubMed

    Karkazis, H C; Kossioni, A E

    1997-03-01

    The purpose of this study was to investigate the effect of the texture of food on the masseter EMG activity during chewing. Fresh raw carrots and non-adhesive chewing gums of similar size and weight were used as representing a hard and a soft food respectively. The mean values for the IEMG activity, the duration of the chewing cycle, the chewing rate and the relative contraction time during chewing were significantly higher for the carrots while no significant difference was found in the chewing burst duration between the two test foods. Finally a strong inverse correlation was found between chewing rate and cycle duration. It was concluded that the texture of food has an obvious effect on EMG activity during chewing and that adjustments to changes in food consistency are made mainly by altering the chewing rate, the duration of the chewing cycle and the IEMG activity.

  15. EMG-based facial gesture recognition through versatile elliptic basis function neural network

    PubMed Central

    2013-01-01

    Background Recently, the recognition of different facial gestures using facial neuromuscular activities has been proposed for human machine interfacing applications. Facial electromyograms (EMGs) analysis is a complicated field in biomedical signal processing where accuracy and low computational cost are significant concerns. In this paper, a very fast versatile elliptic basis function neural network (VEBFNN) was proposed to classify different facial gestures. The effectiveness of different facial EMG time-domain features was also explored to introduce the most discriminating. Methods In this study, EMGs of ten facial gestures were recorded from ten subjects using three pairs of surface electrodes in a bi-polar configuration. The signals were filtered and segmented into distinct portions prior to feature extraction. Ten different time-domain features, namely, Integrated EMG, Mean Absolute Value, Mean Absolute Value Slope, Maximum Peak Value, Root Mean Square, Simple Square Integral, Variance, Mean Value, Wave Length, and Sign Slope Changes were extracted from the EMGs. The statistical relationships between these features were investigated by Mutual Information measure. Then, the feature combinations including two to ten single features were formed based on the feature rankings appointed by Minimum-Redundancy-Maximum-Relevance (MRMR) and Recognition Accuracy (RA) criteria. In the last step, VEBFNN was employed to classify the facial gestures. The effectiveness of single features as well as the feature sets on the system performance was examined by considering the two major metrics, recognition accuracy and training time. Finally, the proposed classifier was assessed and compared with conventional methods support vector machines and multilayer perceptron neural network. Results The average classification results showed that the best performance for recognizing facial gestures among all single/multi-features was achieved by Maximum Peak Value with 87.1% accuracy

  16. Effects of EMG processing on biomechanical models of muscle joint systems: sensitivity of trunk muscle moments, spinal forces, and stability.

    PubMed

    Staudenmann, Didier; Potvin, Jim R; Kingma, Idsart; Stegeman, Dick F; van Dieën, Jaap H

    2007-01-01

    Biomechanical models are in use to estimate parameters such as contact forces and stability at various joints. In one class of these models, surface electromyography (EMG) is used to address the problem of mechanical indeterminacy such that individual muscle activation patterns are accounted for. Unfortunately, because of the stochastical properties of EMG signals, EMG based estimates of muscle force suffer from substantial estimation errors. Recent studies have shown that improvements in muscle force estimation can be achieved through adequate EMG processing, specifically whitening and high-pass (HP) filtering of the signals. The aim of this paper is to determine the effect of such processing on outcomes of a biomechanical model of the lumbosacral joint and surrounding musculature. Goodness of fit of estimated muscle moments to net moments and also estimated joint stability significantly increased with increasing cut-off frequencies in HP filtering, whereas no effect on joint contact forces was found. Whitening resulted in moment estimations comparable to those obtained from optimal HP filtering with cut-off frequencies over 250 Hz. Moreover, compared to HP filtering, whitening led to a further increase in estimated joint-stability. Based on theoretical models and on our experimental results, we hypothesize that the processing leads to an increase in pick-up area. This then would explain the improvements from a better balance between deep and superficial motor unit contributions to the signal. PMID:16765965

  17. Body surface ECG signal shape dispersion.

    PubMed

    Khaddoumi, Balkine; Rix, Hervé; Meste, Olivier; Fereniec, Małgorzata; Maniewski, Roman

    2006-12-01

    The spatial distribution of the shape of the electrocardiography (ECG) waves obtained by body surface potential mapping (BSPM) is studied, using a 64-channel high-resolution ECG system. The index associated to each lead is the shape difference between its ECG wave and a reference computed taking into account all the leads on the same column. The reference is either a selected real wave or a synthetic signal computed by integral shape averaging (ISA). Better results are obtained with the ISA signal using the distribution function method (DFM) for computing the shape difference. The spatial dispersion of ECG waves is showed to allow the separation of patients after myocardial infarction (MI) from healthy subjects. In addition, the reference signal position for each column is computed. The path linking these positions appears as an invariant, i.e., it is independent of the subject and the ECG wave.

  18. Establishment of a recording method for surface electromyography in the iliopsoas muscle.

    PubMed

    Jiroumaru, Takumi; Kurihara, Toshiyuki; Isaka, Tadao

    2014-08-01

    We examined the availability and reliability of surface electromyography (EMG) signals from the iliopsoas muscle (IL). Using serial magnetic resonance images from fifty healthy young males, we evaluated whether the superficial region of IL was adequate for attaching surface EMG electrodes. Subsequently, we assessed EMG cross-talk from the sartorius muscle (SA)-the nearest to IL-using a selective cooling method in fourteen subjects. The skin above SA was cooled, and the median frequencies of EMG signals from IL and SA were determined. The maximum voluntary contraction during isometric hip flexion was measured before and after selective cooling, and surface EMG signals from SA and IL were measured. The superficial area of IL was adequately large (13.2±2.7cm(2)) for recording surface EMG in all fifty subjects. The maximum perimeter for the medial-lateral skin facing IL was noted at a level 3-5cm distal to the anterior superior iliac spine. Following cooling, the median frequency for SA decreased significantly (from 70.1 to 51.9Hz, p<0.001); however, that for IL did not alter significantly. These results demonstrated that EMG cross-talk from SA was negligible for surface EMG signals from IL during hip flexion.

  19. Decoding the neural drive to muscles from the surface electromyogram.

    PubMed

    Farina, Dario; Holobar, Ales; Merletti, Roberto; Enoka, Roger M

    2010-10-01

    This brief review discusses the methods used to estimate the neural drive to muscles from the surface electromyogram (EMG). Surface EMG has been classically used to infer the neural activation of muscle by associating its amplitude with the number of action potentials discharged by a population of motor neurons. Although this approach is valuable in some applications, the amplitude of the surface EMG is only a crude indicator of the neural drive to muscle. More advanced methods are now available to estimate the neural drive to muscle from the surface EMG. These approaches identify the discharge times of a few motor units by decomposing the EMG signal to determine the relative changes in neural activation. This approach is reliable in several conditions and muscles for isometric contractions of moderate force, but is limited to the few superficial units that can be identified in the recordings. PMID:20444646

  20. fMRI analysis for motor paradigms using EMG-based designs: a validation study.

    PubMed

    van Rootselaar, Anne-Fleur; Renken, Remco; de Jong, Bauke M; Hoogduin, Johannes M; Tijssen, Marina A J; Maurits, Natasha M

    2007-11-01

    The goal of the present validation study is to show that continuous surface EMG recorded simultaneously with 3T fMRI can be used to identify local brain activity related to (1) motor tasks, and to (2) muscle activity independently of a specific motor task, i.e. spontaneous (abnormal) movements. Five healthy participants performed a motor task, consisting of posture (low EMG power), and slow (medium EMG power) and fast (high EMG power) wrist flexion-extension movements. Brain activation maps derived from a conventional block design analysis (block-only design) were compared with brain activation maps derived using EMG-based regressors: (1) using the continuous EMG power as a single regressor of interest (EMG-only design) to relate motor performance and brain activity, and (2) using EMG power variability as an additional regressor in the fMRI block design analysis to relate movement variability and brain activity (mathematically) independent of the motor task. The agreement between the identified brain areas for the block-only design and the EMG-only design was excellent for all participants. Additionally, we showed that EMG power variability correlated well with activity in brain areas known to be involved in movement modulation. These innovative EMG-fMRI analysis techniques will allow the application of novel motor paradigms. This is an important step forward in the study of both the normally functioning motor system and the pathophysiological mechanisms in movement disorders.

  1. Estimation and application of EMG amplitude during dynamic contractions.

    PubMed

    Clancy, E A; Bouchard, S; Rancourt, D

    2001-01-01

    The sections above have described an EMG amplitude estimator and an initial application of this estimator to the EMG-torque problem. The amplitude estimator consists of six stages. In the first stage, motion artifact and power-line interference are attenuated. Motion artifact is typically removed with a highpass filter. Elimination of power-line noise is more difficult. Commercial systems tend to use notch filters, accepting the concomitant loss of "true" signal power in exchange for simplicity and robustness. Adaptive methods may be preferable, however, to preserve more "true" signal power. In stage two, the signal is whitened. One fixed whitening technique and two adaptive whitening methods were described. For low-amplitude levels, the adaptive whitening technique that includes adaptive noise cancellation may be necessary. In stage three, multiple EMG channels (all overlying the same muscle) are combined. For most applications, simple gain normalization is all that is required. Stage four rectifies the signal and then applies the power law required to demodulate the signal. In stage six, the inverse of the power law is applied to relinearize the signal. Direct comparison of MAV (first power) to RMS (second power) processing demonstrates little difference between the two. Therefore, unless there is reason to believe that the EMG density departs strongly from that found in the existing studies, RMS and MAV processing are essentially identical. In stage five, the demodulated samples are averaged across all channels and then smoothed (time averaged) to reduce the variance of the amplitude estimate, but at the expense of increasing the bias. For best performance, the window length that best trades off variance and bias error is selected. The advanced EMG processing was next applied to dynamic EMG-torque estimation about the elbow joint. Results showed that improved EMG amplitude estimates led to improved EMG-torque estimates. An initial comparison of different system

  2. Prosthetic EMG control enhancement through the application of man-machine principles

    NASA Technical Reports Server (NTRS)

    Simcox, W. A.

    1977-01-01

    An area in medicine that appears suitable to man-machine principles is rehabilitation research, particularly when the motor aspects of the body are involved. If one considers the limb, whether functional or not, as the machine, the brain as the controller and the neuromuscular system as the man-machine interface, the human body is reduced to a man-machine system that can benefit from the principles behind such systems. The area of rehabilitation that this paper deals with is that of an arm amputee and his prosthetic device. Reducing this area to its man-machine basics, the problem becomes one of attaining natural multiaxis prosthetic control using Electromyographic activity (EMG) as the means of communication between man and prothesis. In order to use EMG as the communication channel it must be amplified and processed to yield a high information signal suitable for control. The most common processing scheme employed is termed Mean Value Processing. This technique for extracting the useful EMG signal consists of a differential to single ended conversion to the surface activity followed by a rectification and smoothing.

  3. Effects of innovative virtual reality game and EMG biofeedback on neuromotor control in cerebral palsy.

    PubMed

    Yoo, Ji Won; Lee, Dong Ryul; Sim, Yon Ju; You, Joshua H; Kim, Cheol J

    2014-01-01

    Sensorimotor control dysfunction or dyskinesia is a hallmark of neuromuscular impairment in children with cerebral palsy (CP), and is often implicated in reaching and grasping deficiencies due to a neuromuscular imbalance between the triceps and biceps. To mitigate such muscle imbalances, an innovative electromyography (EMG)-virtual reality (VR) biofeedback system were designed to provide accurate information about muscle activation and motivation. However, the clinical efficacy of this approach has not yet been determined in children with CP. The purpose of this study was to investigate the effectiveness of a combined EMG biofeedback and VR (EMG-VR biofeedback) intervention system to improve muscle imbalance between triceps and biceps during reaching movements in children with spastic CP. Raw EMG signals were recorded at a sampling rate of 1,000 Hz, band-pass filtered between 20-450 Hz, and notch-filtered at 60 Hz during elbow flexion and extension movements. EMG data were then processed using MyoResearch Master Edition 1.08 XP software. All participants underwent both interventions consisting of the EMG-VR biofeedback combination and EMG biofeedback alone. EMG analysis resulted in improved muscle activation in the underactive triceps while decreasing overactive or hypertonic biceps in the EMG-VR biofeedback compared with EMG biofeedback. The muscle imbalance ratio between the triceps and biceps was consistently improved. The present study is the first clinical trial to provide evidence for the additive benefits of VR intervention for enhancing the upper limb function of children with spastic CP.

  4. Effects of innovative virtual reality game and EMG biofeedback on neuromotor control in cerebral palsy.

    PubMed

    Yoo, Ji Won; Lee, Dong Ryul; Sim, Yon Ju; You, Joshua H; Kim, Cheol J

    2014-01-01

    Sensorimotor control dysfunction or dyskinesia is a hallmark of neuromuscular impairment in children with cerebral palsy (CP), and is often implicated in reaching and grasping deficiencies due to a neuromuscular imbalance between the triceps and biceps. To mitigate such muscle imbalances, an innovative electromyography (EMG)-virtual reality (VR) biofeedback system were designed to provide accurate information about muscle activation and motivation. However, the clinical efficacy of this approach has not yet been determined in children with CP. The purpose of this study was to investigate the effectiveness of a combined EMG biofeedback and VR (EMG-VR biofeedback) intervention system to improve muscle imbalance between triceps and biceps during reaching movements in children with spastic CP. Raw EMG signals were recorded at a sampling rate of 1,000 Hz, band-pass filtered between 20-450 Hz, and notch-filtered at 60 Hz during elbow flexion and extension movements. EMG data were then processed using MyoResearch Master Edition 1.08 XP software. All participants underwent both interventions consisting of the EMG-VR biofeedback combination and EMG biofeedback alone. EMG analysis resulted in improved muscle activation in the underactive triceps while decreasing overactive or hypertonic biceps in the EMG-VR biofeedback compared with EMG biofeedback. The muscle imbalance ratio between the triceps and biceps was consistently improved. The present study is the first clinical trial to provide evidence for the additive benefits of VR intervention for enhancing the upper limb function of children with spastic CP. PMID:25227075

  5. Blind separation of convolutive sEMG mixtures based on independent vector analysis

    NASA Astrophysics Data System (ADS)

    Wang, Xiaomei; Guo, Yina; Tian, Wenyan

    2015-12-01

    An independent vector analysis (IVA) method base on variable-step gradient algorithm is proposed in this paper. According to the sEMG physiological properties, the IVA model is applied to the frequency-domain separation of convolutive sEMG mixtures to extract motor unit action potentials information of sEMG signals. The decomposition capability of proposed method is compared to the one of independent component analysis (ICA), and experimental results show the variable-step gradient IVA method outperforms ICA in blind separation of convolutive sEMG mixtures.

  6. Accuracy assessment of a surface electromyogram decomposition system in human first dorsal interosseus muscle

    NASA Astrophysics Data System (ADS)

    Hu, Xiaogang; Rymer, William Z.; Suresh, Nina L.

    2014-04-01

    Objective. The aim of this study is to assess the accuracy of a surface electromyogram (sEMG) motor unit (MU) decomposition algorithm during low levels of muscle contraction. Approach. A two-source method was used to verify the accuracy of the sEMG decomposition system, by utilizing simultaneous intramuscular and surface EMG recordings from the human first dorsal interosseous muscle recorded during isometric trapezoidal force contractions. Spike trains from each recording type were decomposed independently utilizing two different algorithms, EMGlab and dEMG decomposition algorithms. The degree of agreement of the decomposed spike timings was assessed for three different segments of the EMG signals, corresponding to specified regions in the force task. A regression analysis was performed to examine whether certain properties of the sEMG and force signal can predict the decomposition accuracy. Main results. The average accuracy of successful decomposition among the 119 MUs that were common to both intramuscular and surface records was approximately 95%, and the accuracy was comparable between the different segments of the sEMG signals (i.e., force ramp-up versus steady state force versus combined). The regression function between the accuracy and properties of sEMG and force signals revealed that the signal-to-noise ratio of the action potential and stability in the action potential records were significant predictors of the surface decomposition accuracy. Significance. The outcomes of our study confirm the accuracy of the sEMG decomposition algorithm during low muscle contraction levels and provide confidence in the overall validity of the surface dEMG decomposition algorithm.

  7. sEMG wavelet-based indices predicts muscle power loss during dynamic contractions.

    PubMed

    González-Izal, M; Rodríguez-Carreño, I; Malanda, A; Mallor-Giménez, F; Navarro-Amézqueta, I; Gorostiaga, E M; Izquierdo, M

    2010-12-01

    The purpose of this study was to investigate the sensitivity of new surface electromyography (sEMG) indices based on the discrete wavelet transform to estimate acute exercise-induced changes on muscle power output during a dynamic fatiguing protocol. Fifteen trained subjects performed five sets consisting of 10 leg press, with 2 min rest between sets. sEMG was recorded from vastus medialis (VM) muscle. Several surface electromyographic parameters were computed. These were: mean rectified voltage (MRV), median spectral frequency (F(med)), Dimitrov spectral index of muscle fatigue (FI(nsm5)), as well as five other parameters obtained from the stationary wavelet transform (SWT) as ratios between different scales. The new wavelet indices showed better accuracy to map changes in muscle power output during the fatiguing protocol. Moreover, the new wavelet indices as a single parameter predictor accounted for 46.6% of the performance variance of changes in muscle power and the log-FI(nsm5) and MRV as a two-factor combination predictor accounted for 49.8%. On the other hand, the new wavelet indices proposed, showed the highest robustness in presence of additive white Gaussian noise for different signal to noise ratios (SNRs). The sEMG wavelet indices proposed may be a useful tool to map changes in muscle power output during dynamic high-loading fatiguing task.

  8. Rectification of EMG in low force contractions improves detection of motor unit coherence in the beta-frequency band.

    PubMed

    Ward, Nicholas J; Farmer, Simon F; Berthouze, Luc; Halliday, David M

    2013-10-01

    Rectification of surface EMG before spectral analysis is a well-established preprocessing method used in the detection of motor unit firing patterns. A number of recent studies have called into question the need for rectification before spectral analysis, pointing out that there is no supporting experimental evidence to justify rectification. We present an analysis of 190 records from 13 subjects consisting of simultaneous recordings of paired single motor units and surface EMG from the extensor digitorum longus muscle during middle finger extension against gravity (unloaded condition) and against gravity plus inertial loading (loaded condition). We directly examine the hypothesis that rectified surface EMG is a better predictor of the frequency components of motor unit synchronization than the unrectified (or raw) EMG in the beta-frequency band (15-32 Hz). We use multivariate analysis and estimate the partial coherence between the paired single units using both rectified and unrectified surface EMG as a predictor. We use a residual partial correlation measure to quantify the difference between raw and rectified EMG as predictor and analyze unloaded and loaded conditions separately. The residual correlation for the unloaded condition is 22% with raw EMG and 3.5% with rectified EMG and for the loaded condition it is 5.2% with raw EMG and 1.4% with rectified EMG. We interpret these results as strong supporting experimental evidence in favor of using the preprocessing step of surface EMG rectification before spectral analysis.

  9. Zebrafish needle EMG: a new tool for high-throughput drug screens.

    PubMed

    Cho, Sung-Joon; Nam, Tai-Seung; Byun, Donghak; Choi, Seok-Yong; Kim, Myeong-Kyu; Kim, Sohee

    2015-09-01

    Zebrafish models have recently been highlighted as a valuable tool in studying the molecular basis of neuromuscular diseases and developing new pharmacological treatments. Needle electromyography (EMG) is needed not only for validating transgenic zebrafish models with muscular dystrophies (MD), but also for assessing the efficacy of therapeutics. However, performing needle EMG on larval zebrafish has not been feasible due to the lack of proper EMG sensors and systems for such small animals. We introduce a new type of EMG needle electrode to measure intramuscular activities of larval zebrafish, together with a method to hold the animal in position during EMG, without anesthetization. The silicon-based needle electrode was found to be sufficiently strong and sharp to penetrate the skin and muscles of zebrafish larvae, and its shape and performance did not change after multiple insertions. With the use of the proposed needle electrode and measurement system, EMG was successfully performed on zebrafish at 30 days postfertilization (dpf) and at 5 dpf. Burst patterns and spike morphology of the recorded EMG signals were analyzed. The measured single spikes were triphasic with an initial positive deflection, which is typical for motor unit action potentials, with durations of ∼10 ms, whereas the muscle activity was silent during the anesthetized condition. These findings confirmed the capability of this system of detecting EMG signals from very small animals such as 5 dpf zebrafish. The developed EMG sensor and system are expected to become a helpful tool in validating zebrafish MD models and further developing therapeutics.

  10. Zebrafish needle EMG: a new tool for high-throughput drug screens

    PubMed Central

    Cho, Sung-Joon; Nam, Tai-Seung; Byun, Donghak; Choi, Seok-Yong; Kim, Myeong-Kyu

    2015-01-01

    Zebrafish models have recently been highlighted as a valuable tool in studying the molecular basis of neuromuscular diseases and developing new pharmacological treatments. Needle electromyography (EMG) is needed not only for validating transgenic zebrafish models with muscular dystrophies (MD), but also for assessing the efficacy of therapeutics. However, performing needle EMG on larval zebrafish has not been feasible due to the lack of proper EMG sensors and systems for such small animals. We introduce a new type of EMG needle electrode to measure intramuscular activities of larval zebrafish, together with a method to hold the animal in position during EMG, without anesthetization. The silicon-based needle electrode was found to be sufficiently strong and sharp to penetrate the skin and muscles of zebrafish larvae, and its shape and performance did not change after multiple insertions. With the use of the proposed needle electrode and measurement system, EMG was successfully performed on zebrafish at 30 days postfertilization (dpf) and at 5 dpf. Burst patterns and spike morphology of the recorded EMG signals were analyzed. The measured single spikes were triphasic with an initial positive deflection, which is typical for motor unit action potentials, with durations of ∼10 ms, whereas the muscle activity was silent during the anesthetized condition. These findings confirmed the capability of this system of detecting EMG signals from very small animals such as 5 dpf zebrafish. The developed EMG sensor and system are expected to become a helpful tool in validating zebrafish MD models and further developing therapeutics. PMID:26180124

  11. Re-evaluation of EMG-torque relation in chronic stroke using linear electrode array EMG recordings

    PubMed Central

    Bhadane, Minal; Liu, Jie; Rymer, W. Zev; Zhou, Ping; Li, Sheng

    2016-01-01

    The objective was to re-evaluate the controversial reports of EMG-torque relation between impaired and non-impaired sides using linear electrode array EMG recordings. Ten subjects with chronic stroke performed a series of submaximal isometric elbow flexion tasks. A 20-channel linear array was used to record surface EMG of the biceps brachii muscles from both impaired and non-impaired sides. M-wave recordings for bilateral biceps brachii muscles were also made. Distribution of the slope of the EMG-torque relations for the individual channels showed a quasi-symmetrical “M” shaped pattern. The lowest value corresponded to the innervation zone (IZ) location. The highest value from the slope curve for each side was selected for comparison to minimize the effect of electrode placement and IZ asymmetry. The slope was greater on the impaired side in 4 of 10 subjects. There were a weak correlation between slope ratio and strength ratio and a moderate to high correlation between slope ratio and M-wave ratio between two sides. These findings suggest that the EMG-torque relations are likely mediated and influenced by multiple factors. Our findings emphasize the importance of electrode placement and suggest the primary role of peripheral adaptive changes in the EMG-torque relations in chronic stroke. PMID:27349938

  12. Signaling reactions on membrane surfaces: breaking the law of averages

    NASA Astrophysics Data System (ADS)

    Groves, Jay T.

    Most intracellular signal transduction reactions take place on the membrane surface. The membrane provides much more than just a surface environment on which signaling molecules are concentrated. There is a growing realization that multiple physical and chemical mechanisms allow the membrane to actively participate in the signaling reactions. Using a combination of single molecule imaging and spectroscopic techniques, my research seeks to directly resolve the actual mechanics of signaling reactions on membrane surfaces both in reconstituted systems and in living cells. These observations are revealing new insights into cellular signaling processes as well as some unexpected functional behaviors of proteins on the membrane surface.

  13. Are External Knee Load and EMG Measures Accurate Indicators of Internal Knee Contact Forces during Gait?

    PubMed Central

    Meyer, Andrew J.; D'Lima, Darryl D.; Besier, Thor F.; Lloyd, David G.; Colwell, Clifford W.; Fregly, Benjamin J.

    2013-01-01

    Mechanical loading is believed to be a critical factor in the development and treatment of knee osteoarthritis. However, the contact forces to which the knee articular surfaces are subjected during daily activities cannot be measured clinically. Thus, the ability to predict internal knee contact forces accurately using external measures (i.e., external knee loads and muscle EMG signals) would be clinically valuable. This study quantifies how well external knee load and EMG measures predict internal knee contact forces during gait. A single subject with a force-measuring tibial prosthesis and post-operative valgus alignment performed four gait patterns (normal, medial thrust, walking pole, and trunk sway) to induce a wide range of external and internal knee joint loads. Linear regression analyses were performed to assess how much of the variability in internal contact forces was accounted for by variability in the external measures. Though the different gait patterns successfully induced significant changes in the external and internal quantities, changes in external measures were generally weak indicators of changes in total, medial, and lateral contact force. Our results suggest that when total contact force may be changing, caution should be exercised when inferring changes in knee contact forces based on observed changes in external knee load and EMG measures. Advances in musculoskeletal modeling methods may be needed for accurate estimation of in vivo knee contact forces. PMID:23280647

  14. Design of a robust EMG sensing interface for pattern classification

    PubMed Central

    Huang, He; Zhang, Fan; Sun, Yan L.; He, Haibo

    2010-01-01

    Electromyographic (EMG) pattern classification has been widely investigated for neural control of external devices in order to assist with movements of patients with motor deficits. Classification performance deteriorates due to inevitable disturbances to the sensor interface, which significantly challenges the clinical value of this technique. This study aimed to design a sensor fault detection (SFD) module in the sensor interface to provide reliable EMG pattern classification. This module monitored the recorded signals from individual EMG electrodes and performed a self-recovery strategy to recover the classification performance when one or more sensors were disturbed. To evaluate this design, we applied synthetic disturbances to EMG signals collected from leg muscles of able-bodied subjects and a subject with a transfemoral amputation and compared the accuracies for classifying transitions between different locomotion modes with and without the SFD module. The results showed that the SFD module maintained classification performance when one signal was distorted and recovered about 20% of classification accuracy when four signals were distorted simultaneously. The method was simple to implement. Additionally, these outcomes were observed for all subjects, including the leg amputee, which implies the promise of the designed sensor interface for providing a reliable neural-machine interface for artificial legs. PMID:20811091

  15. Design of a robust EMG sensing interface for pattern classification

    NASA Astrophysics Data System (ADS)

    Huang, He; Zhang, Fan; Sun, Yan L.; He, Haibo

    2010-10-01

    Electromyographic (EMG) pattern classification has been widely investigated for neural control of external devices in order to assist with movements of patients with motor deficits. Classification performance deteriorates due to inevitable disturbances to the sensor interface, which significantly challenges the clinical value of this technique. This study aimed to design a sensor fault detection (SFD) module in the sensor interface to provide reliable EMG pattern classification. This module monitored the recorded signals from individual EMG electrodes and performed a self-recovery strategy to recover the classification performance when one or more sensors were disturbed. To evaluate this design, we applied synthetic disturbances to EMG signals collected from leg muscles of able-bodied subjects and a subject with a transfemoral amputation and compared the accuracies for classifying transitions between different locomotion modes with and without the SFD module. The results showed that the SFD module maintained classification performance when one signal was distorted and recovered about 20% of classification accuracy when four signals were distorted simultaneously. The method was simple to implement. Additionally, these outcomes were observed for all subjects, including the leg amputee, which implies the promise of the designed sensor interface for providing a reliable neural-machine interface for artificial legs.

  16. Proportional EMG control for upper-limb powered exoskeletons.

    PubMed

    Lenzi, T; De Rossi, S M M; Vitiello, N; Carrozza, M C

    2011-01-01

    Electromyography (EMG) has been frequently proposed as the driving signal for controlling powered exoskeletons. Lot of effort has been spent to design accurate algorithms for muscular torque estimation, while very few studies attempted to understand to what extent an accurate torque estimate is indeed necessary to provide effective movement assistance through powered exoskeletons. In this study, we focus on the latter aspect by using a simple and "low-accuracy" torque estimate, an EMG-proportional control, to provide assistance through an elbow exoskeleton. Preliminary results show that subjects adapt almost instantaneously to the assistance provided by the exoskeleton and can reduce their effort while keeping full control of the movement. PMID:22254387

  17. The relation between the surface electromyogram and muscular force.

    PubMed Central

    Milner-Brown, H S; Stein, R B

    1975-01-01

    1. Motor units in the first dorsal interosseus muscle of normal human subjects were recorded by needle electrodes, together with the surface electromyogram (e.m.g.). The wave form contributed by each motor unit to the surface e.m.g. was determined by signal averaging. 2. The peak-to-peak amplitude of the wave form contributed to the surface e.m.g. by a motor unit increased approximately as the square root of the threshold force at which the unit was recruited. The peak-to-peak duration of the wave form was independent of the threshold force. 3. Large and small motor units are uniformly distributed throughout this muscle, and the muscle fibres making up a motor unit may be widely dispersed. 4. The rectified surface e.m.g. was computed as a function of force, based on the sample of motor units recorded. The largest contribution of motor unit recruitment occurs at low force levels, while the contribution of increased firing rate becomes more important at higher force levels. 5. Possible bases for the common experimental observation that the mean rectified surface e.m.g. varies linearly with the force generated by a muscle are discussed. E.m.g. potentials and contractile responses may both sum non-linearly at moderate to high force levels, but in such a way that the rectified surface e.m.g. is still approximately linearly related to the force produced by the muscle. PMID:1133787

  18. Digitally controlled feedback for DC offset cancellation in a wearable multichannel EMG platform.

    PubMed

    Tomasini, M; Benatti, S; Casamassima, F; Milosevic, B; Fateh, S; Farella, E; Benini, L

    2015-01-01

    Wearable systems capable to capture vital signs allow the development of advanced medical applications. One notable example is the use of surface electromyography (EMG) to gather muscle activation potentials, in principle an easy input for prosthesis control. However, the acquisition of such signals is affected by high variability and ground loop problems. Moreover, the input impedance influenced in time by motion and perspiration determines an offset, which can be orders of magnitude higher than the signal of interest. We propose a wearable device equipped with a digitally controlled Analog Front End (AFE) for biopotentials acquisition with zero-offset. The proposed AFE solution has an internal Digital to Analog Converter (DAC) used to adjust independently the reference of each channel removing any DC offset. The analog integrated circuit is coupled with a microcontroller, which periodically estimates the offset and implements a closed loop feedback on the analog part. The proposed approach was tested on EMG signals acquired from 4 subjects while performing different activities and shows that the system correctly acquires signals with no DC offset. PMID:26736970

  19. Electrotactile EMG feedback improves the control of prosthesis grasping force

    NASA Astrophysics Data System (ADS)

    Schweisfurth, Meike A.; Markovic, Marko; Dosen, Strahinja; Teich, Florian; Graimann, Bernhard; Farina, Dario

    2016-10-01

    Objective. A drawback of active prostheses is that they detach the subject from the produced forces, thereby preventing direct mechanical feedback. This can be compensated by providing somatosensory feedback to the user through mechanical or electrical stimulation, which in turn may improve the utility, sense of embodiment, and thereby increase the acceptance rate. Approach. In this study, we compared a novel approach to closing the loop, namely EMG feedback (emgFB), to classic force feedback (forceFB), using electrotactile interface in a realistic task setup. Eleven intact-bodied subjects and one transradial amputee performed a routine grasping task while receiving emgFB or forceFB. The two feedback types were delivered through the same electrotactile interface, using a mixed spatial/frequency coding to transmit 8 discrete levels of the feedback variable. In emgFB, the stimulation transmitted the amplitude of the processed myoelectric signal generated by the subject (prosthesis input), and in forceFB the generated grasping force (prosthesis output). The task comprised 150 trials of routine grasping at six forces, randomly presented in blocks of five trials (same force). Interquartile range and changes in the absolute error (AE) distribution (magnitude and dispersion) with respect to the target level were used to assess precision and overall performance, respectively. Main results. Relative to forceFB, emgFB significantly improved the precision of myoelectric commands (min/max of the significant levels) for 23%/36% as well as the precision of force control for 12%/32%, in intact-bodied subjects. Also, the magnitude and dispersion of the AE distribution were reduced. The results were similar in the amputee, showing considerable improvements. Significance. Using emgFB, the subjects therefore decreased the uncertainty of the forward pathway. Since there is a correspondence between the EMG and force, where the former anticipates the latter, the emgFB allowed for

  20. Monopolar electromyographic signals recorded by a current amplifier in air and under water without insulation.

    PubMed

    Whitting, John W; von Tscharner, Vinzenz

    2014-12-01

    It was recently proposed that one could use signal current instead of voltage to collect surface electromyography (EMG). With EMG-current, the electrodes remain at the ground potential, thereby eliminating lateral currents. The purpose of this study was to determine whether EMG-currents can be recorded in Tap and Salt water, as well as in air, without electrically shielding the electrodes. It was hypothesized that signals would display consistent information between experimental conditions regarding muscle responses to changes in contraction effort. EMG-currents were recorded from the flexor digitorum muscles as participant's squeezed a pre-inflated blood pressure cuff bladder in each experimental condition at standardized efforts. EMG-current measurements performed underwater showed no loss of signal amplitude when compared to measurements made in air, although some differences in amplitude and spectral components were observed between conditions. However, signal amplitudes and frequencies displayed consistent behavior across contraction effort levels, irrespective of the experimental condition. This new method demonstrates that information regarding muscle activity is comparable between wet and dry conditions when using EMG-current. Considering the difficulties imposed by the need to waterproof traditional bipolar EMG electrodes when underwater, this new methodology is tremendously promising for assessments of muscular function in aquatic environments.

  1. Monopolar electromyographic signals recorded by a current amplifier in air and under water without insulation.

    PubMed

    Whitting, John W; von Tscharner, Vinzenz

    2014-12-01

    It was recently proposed that one could use signal current instead of voltage to collect surface electromyography (EMG). With EMG-current, the electrodes remain at the ground potential, thereby eliminating lateral currents. The purpose of this study was to determine whether EMG-currents can be recorded in Tap and Salt water, as well as in air, without electrically shielding the electrodes. It was hypothesized that signals would display consistent information between experimental conditions regarding muscle responses to changes in contraction effort. EMG-currents were recorded from the flexor digitorum muscles as participant's squeezed a pre-inflated blood pressure cuff bladder in each experimental condition at standardized efforts. EMG-current measurements performed underwater showed no loss of signal amplitude when compared to measurements made in air, although some differences in amplitude and spectral components were observed between conditions. However, signal amplitudes and frequencies displayed consistent behavior across contraction effort levels, irrespective of the experimental condition. This new method demonstrates that information regarding muscle activity is comparable between wet and dry conditions when using EMG-current. Considering the difficulties imposed by the need to waterproof traditional bipolar EMG electrodes when underwater, this new methodology is tremendously promising for assessments of muscular function in aquatic environments. PMID:25241214

  2. Objectivity and validity of EMG method in estimating anaerobic threshold.

    PubMed

    Kang, S-K; Kim, J; Kwon, M; Eom, H

    2014-08-01

    The purposes of this study were to verify and compare the performances of anaerobic threshold (AT) point estimates among different filtering intervals (9, 15, 20, 25, 30 s) and to investigate the interrelationships of AT point estimates obtained by ventilatory threshold (VT) and muscle fatigue thresholds using electromyographic (EMG) activity during incremental exercise on a cycle ergometer. 69 untrained male university students, yet pursuing regular exercise voluntarily participated in this study. The incremental exercise protocol was applied with a consistent stepwise increase in power output of 20 watts per minute until exhaustion. AT point was also estimated in the same manner using V-slope program with gas exchange parameters. In general, the estimated values of AT point-time computed by EMG method were more consistent across 5 filtering intervals and demonstrated higher correlations among themselves when compared with those values obtained by VT method. The results found in the present study suggest that the EMG signals could be used as an alternative or a new option in estimating AT point. Also the proposed computing procedure implemented in Matlab for the analysis of EMG signals appeared to be valid and reliable as it produced nearly identical values and high correlations with VT estimates. PMID:24988194

  3. Comparison of sEMG-Based Feature Extraction and Motion Classification Methods for Upper-Limb Movement

    PubMed Central

    Guo, Shuxiang; Pang, Muye; Gao, Baofeng; Hirata, Hideyuki; Ishihara, Hidenori

    2015-01-01

    The surface electromyography (sEMG) technique is proposed for muscle activation detection and intuitive control of prostheses or robot arms. Motion recognition is widely used to map sEMG signals to the target motions. One of the main factors preventing the implementation of this kind of method for real-time applications is the unsatisfactory motion recognition rate and time consumption. The purpose of this paper is to compare eight combinations of four feature extraction methods (Root Mean Square (RMS), Detrended Fluctuation Analysis (DFA), Weight Peaks (WP), and Muscular Model (MM)) and two classifiers (Neural Networks (NN) and Support Vector Machine (SVM)), for the task of mapping sEMG signals to eight upper-limb motions, to find out the relation between these methods and propose a proper combination to solve this issue. Seven subjects participated in the experiment and six muscles of the upper-limb were selected to record sEMG signals. The experimental results showed that NN classifier obtained the highest recognition accuracy rate (88.7%) during the training process while SVM performed better in real-time experiments (85.9%). For time consumption, SVM took less time than NN during the training process but needed more time for real-time computation. Among the four feature extraction methods, WP had the highest recognition rate for the training process (97.7%) while MM performed the best during real-time tests (94.3%). The combination of MM and NN is recommended for strict real-time applications while a combination of MM and SVM will be more suitable when time consumption is not a key requirement. PMID:25894941

  4. An open and configurable embedded system for EMG pattern recognition implementation for artificial arms.

    PubMed

    Jun Liu; Fan Zhang; Huang, He Helen

    2014-01-01

    Pattern recognition (PR) based on electromyographic (EMG) signals has been developed for multifunctional artificial arms for decades. However, assessment of EMG PR control for daily prosthesis use is still limited. One of the major barriers is the lack of a portable and configurable embedded system to implement the EMG PR control. This paper aimed to design an open and configurable embedded system for EMG PR implementation so that researchers can easily modify and optimize the control algorithms upon our designed platform and test the EMG PR control outside of the lab environments. The open platform was built on an open source embedded Linux Operating System running a high-performance Gumstix board. Both the hardware and software system framework were openly designed. The system was highly flexible in terms of number of inputs/outputs and calibration interfaces used. Such flexibility enabled easy integration of our embedded system with different types of commercialized or prototypic artificial arms. Thus far, our system was portable for take-home use. Additionally, compared with previously reported embedded systems for EMG PR implementation, our system demonstrated improved processing efficiency and high system precision. Our long-term goals are (1) to develop a wearable and practical EMG PR-based control for multifunctional artificial arms, and (2) to quantify the benefits of EMG PR-based control over conventional myoelectric prosthesis control in a home setting.

  5. Facial EMG responses to noise.

    PubMed

    Kjellberg, A; Sköldström, B; Tesarz, M; Dallner, M

    1994-12-01

    Tension of the forehead increases as a response to unpleasant stimuli. In three experiments EMG activity in corrugator muscle was measured to test this response as an indicator of noise annoyance. In Exp. 1 (n = 24) monotonic sound level-response functions were obtained for four levels of 100- and 1000-Hz tones. In Exp. 2 (n = 20) recordings were made during work with a simple and a difficult task in a group of women and a group of men. Larger responses were obtained during the difficult task, especially during noise exposure. The response was much larger for the women. Exp. 3 (n = 24) showed that the sex difference was unaffected by a correction for differences in maximum level of corrugator response. Rated annoyance was a linear function of log EMG.

  6. Influence of Amplitude Cancellation on the Accuracy of Determining the Onset of Muscle Activity from the Surface Electromyogram

    PubMed Central

    Jesunathadas, Mark; Aidoor, Sameer S.; Keenan, Kevin G.; Farina, Dario; Enoka, Roger M.

    2012-01-01

    The purpose of the study was to quantify the influence of amplitude cancellation on the accuracy of detecting the onset of muscle activity based on an analysis of simulated surface electromyographic (EMG) signals. EMG activity of a generic lower limb muscle was simulated during the stance phase of human gait. Surface EMG signals were generated with and without amplitude cancellation by summing simulated motor unit potentials either before (cancellation EMG) or after (no-cancellation EMG) the potentials had been rectified. The two sets of EMG signals were compared at forces of 30 and 80% of maximum voluntary contraction (MVC) and with various low-pass filter cut-off frequencies. Onset time was determined both visually and by an algorithm that identified when the mean amplitude of the signal within a sliding window exceeded a specified standard deviation (SD) above the baseline mean. Onset error was greater for the no-cancellation conditions when determined automatically and by visual inspection. However, the differences in onset error between the two cancellation conditions appear to be clinically insignificant. Therefore, amplitude cancellation does not appear to limit the ability to detect the onset of muscle activity from the surface EMG. PMID:22330887

  7. EMGs Analysis of Lumbar, Pelvic and Leg Muscles in Leg Length Discrepancy Adolescents

    NASA Astrophysics Data System (ADS)

    Sotelo-Barroso, Fernando; Márquez-Gamiño, Sergio; Caudillo-Cisneros, Cipriana

    2004-09-01

    To evaluate differences in surface electromyography (EMGs) activity of lumbar, pelvic and leg muscles in adolescents with and without LLD. EMGs activity records were taken during rest and maximal isometric voluntary contractions (MIVC). Peak to peak amplitude (PPA), mean rectified voltage (MRV) and root mean square (RMS), were analyzed. Statistical differences between short and large sides of LLD adolescents, were found (p<0.05). Higher values occurred in shorter limb muscles. No significative differences were found between left and right legs of the control subjects. When EMGs values were compared between short and large sides of LLD subjects with ipsilateral sides of controls, selective, statistically different EMGs values were exhibited. It is suggested that adaptative behavior to secondary biomechanical and/or neural changes occurred, even when none clinical symptoms were reported. The observations were remarked by the absence of EMGs differences between right and left sides of control subjects.

  8. Estradiol signaling via sequestrable surface receptors.

    PubMed

    Benten, W P; Stephan, C; Lieberherr, M; Wunderlich, F

    2001-04-01

    Estradiol (E(2))-signaling is widely considered to be exclusively mediated through the transcription-regulating intracellular estrogen receptor (ER) alpha and ERbeta. The aim of this study was to investigate transcription-independent E(2)-signaling in mouse IC-21 macrophages. E(2) and E(2)-BSA induce a rapid rise in the intracellular free Ca(2+) concentration ([Ca(2+)](i)) of Fura-2 loaded IC-21 cells as examined by spectrofluorometry. These changes in [Ca(2+)](i) can be inhibited by pertussis toxin, but not by the ER-blockers tamoxifen and raloxifene. The E(2)-signaling initiated at the plasma membrane is mediated through neither ERalpha nor ERbeta, but rather through a novel G protein-coupled membrane E(2)-receptor as revealed by RT-PCR, flow cytometry, and confocal laser scanning microscopy. A special feature of this E(2)-receptor is its sequestration upon agonist stimulation. Sequestration depends on energy and temperature, and it proceeds through a clathrin- and caveolin-independent pathway. PMID:11250949

  9. An adaptive detector of genioglossus EMG reflex using Berkner transform for time latency measurement in OSA pathophysiological studies.

    PubMed

    Guméry, Pierre Yves; Roux-Buisson, Hervé; Meignen, Sylvain; Comyn, François Louis; Dematteis, Maurice; Wuyam, Bernard; Pépin, Jean Louis; Lévy, Patrick

    2005-08-01

    To investigate obstructive sleep apnea syndrome mechanisms, we developed a device to measure the surface electromyogram (EMG) time latency reflex of the genioglossus muscle stimulated by time and amplitude calibrated negative pharyngeal pressure drops. The reflex signals were found to be disturbed by transient signals that generate false alarms. Thus, to reduce false alarm occurrences we designed an adaptive multiscale method. Continuous wavelet transform (CWT) is widely used in biomedical signal event detection processes. The Berkner transform is an approximation of a CWT that is based on a hierarchical scheme similar to discrete wavelet transform. We used the Berkner transform to build a multiscale detector because it offers the possibility of maxima coefficients linkage that leads to good accuracy in reflex onset localization. As a contribution to this novel approach we used a reconstruction formula to develop an adaptive method for scale range determination in our surface EMG reflex detector. Finally, we characterized our detector in terms of accuracy and robustness, first on synthesized signals and second, on signals acquired on apneic patients and healthy subjects. Preliminary results showed a significant difference (p < 0.01) between the two populations regarding the genioglossus muscle mean latency time. These physiological findings may partly explain why the upper airway protective reflex occurring when a negative pressure is applied to the upper airway is ineffective in OSA patients, leading to pharyngeal collapse.

  10. A Versatile Embedded Platform for EMG Acquisition and Gesture Recognition.

    PubMed

    Benatti, Simone; Casamassima, Filippo; Milosevic, Bojan; Farella, Elisabetta; Schönle, Philipp; Fateh, Schekeb; Burger, Thomas; Huang, Qiuting; Benini, Luca

    2015-10-01

    Wearable devices offer interesting features, such as low cost and user friendliness, but their use for medical applications is an open research topic, given the limited hardware resources they provide. In this paper, we present an embedded solution for real-time EMG-based hand gesture recognition. The work focuses on the multi-level design of the system, integrating the hardware and software components to develop a wearable device capable of acquiring and processing EMG signals for real-time gesture recognition. The system combines the accuracy of a custom analog front end with the flexibility of a low power and high performance microcontroller for on-board processing. Our system achieves the same accuracy of high-end and more expensive active EMG sensors used in applications with strict requirements on signal quality. At the same time, due to its flexible configuration, it can be compared to the few wearable platforms designed for EMG gesture recognition available on market. We demonstrate that we reach similar or better performance while embedding the gesture recognition on board, with the benefit of cost reduction. To validate this approach, we collected a dataset of 7 gestures from 4 users, which were used to evaluate the impact of the number of EMG channels, the number of recognized gestures and the data rate on the recognition accuracy and on the computational demand of the classifier. As a result, we implemented a SVM recognition algorithm capable of real-time performance on the proposed wearable platform, achieving a classification rate of 90%, which is aligned with the state-of-the-art off-line results and a 29.7 mW power consumption, guaranteeing 44 hours of continuous operation with a 400 mAh battery.

  11. A Versatile Embedded Platform for EMG Acquisition and Gesture Recognition.

    PubMed

    Benatti, Simone; Casamassima, Filippo; Milosevic, Bojan; Farella, Elisabetta; Schönle, Philipp; Fateh, Schekeb; Burger, Thomas; Huang, Qiuting; Benini, Luca

    2015-10-01

    Wearable devices offer interesting features, such as low cost and user friendliness, but their use for medical applications is an open research topic, given the limited hardware resources they provide. In this paper, we present an embedded solution for real-time EMG-based hand gesture recognition. The work focuses on the multi-level design of the system, integrating the hardware and software components to develop a wearable device capable of acquiring and processing EMG signals for real-time gesture recognition. The system combines the accuracy of a custom analog front end with the flexibility of a low power and high performance microcontroller for on-board processing. Our system achieves the same accuracy of high-end and more expensive active EMG sensors used in applications with strict requirements on signal quality. At the same time, due to its flexible configuration, it can be compared to the few wearable platforms designed for EMG gesture recognition available on market. We demonstrate that we reach similar or better performance while embedding the gesture recognition on board, with the benefit of cost reduction. To validate this approach, we collected a dataset of 7 gestures from 4 users, which were used to evaluate the impact of the number of EMG channels, the number of recognized gestures and the data rate on the recognition accuracy and on the computational demand of the classifier. As a result, we implemented a SVM recognition algorithm capable of real-time performance on the proposed wearable platform, achieving a classification rate of 90%, which is aligned with the state-of-the-art off-line results and a 29.7 mW power consumption, guaranteeing 44 hours of continuous operation with a 400 mAh battery. PMID:26513799

  12. Terrain-Moisture Classification Using GPS Surface-Reflected Signals

    NASA Technical Reports Server (NTRS)

    Grant, Michael S.; Acton, Scott T.; Katzberg, Stephen J.

    2006-01-01

    In this study we present a novel method of land surface classification using surface-reflected GPS signals in combination with digital imagery. Two GPS-derived classification features are merged with visible image data to create terrain-moisture (TM) classes, defined here as visibly identifiable terrain or landcover classes containing a surface/soil moisture component. As compared to using surface imagery alone, classification accuracy is significantly improved for a number of visible classes when adding the GPS-based signal features. Since the strength of the reflected GPS signal is proportional to the amount of moisture in the surface, use of these GPS features provides information about the surface that is not obtainable using visible wavelengths alone. Application areas include hydrology, precision agriculture, and wetlands mapping.

  13. Modulation of photoacoustic signal generation from metallic surfaces.

    PubMed

    Mitcham, Trevor; Homan, Kimberly; Frey, Wolfgang; Chen, Yun-Sheng; Emelianov, Stanislav; Hazle, John; Bouchard, Richard

    2013-05-01

    The ability to image metallic implants is important for medical applications ranging from diagnosis to therapy. Photoacoustic (PA) imaging has been recently pursued as a means to localize metallic implants in soft tissue. The work presented herein investigates different mechanisms to modulate the PA signal generated by macroscopic metallic surfaces. Wires of five different metals are tested to simulate medical implants/tools, while surface roughness is altered or physical vapor deposition (PVD) coatings are added to change the wires' overall optical absorption. PA imaging data of the wires are acquired at 970 nm. Results indicate that PA signal generation predominately occurs in a wire's metallic surface and not its aqueous surroundings. PA signal generation is similar for all metals tested, while addition of PVD coatings offers significant modulations (i.e., 4-dB enhancement and 26-dB reduction achieved) in PA signal generation. Results also suggest that PA signal increases with increasing surface roughness. Different coating and roughness schemes are then successfully utilized to generate spatial PA signal patterns. This work demonstrates the potential of surface modifications to enhance or reduce PA signal generation to permit improved PA imaging of implants/tools (i.e., providing location/orientation information) or to allow PA imaging of surrounding tissue.

  14. Low-Amplitude Craniofacial EMG Power Spectral Density and 3D Muscle Reconstruction from MRI.

    PubMed

    Wiedemann, Lukas; Chaberova, Jana; Edmunds, Kyle; Einarsdóttir, Guðrún; Ramon, Ceon; Gargiulo, Paolo

    2015-03-11

    Improving EEG signal interpretation, specificity, and sensitivity is a primary focus of many current investigations, and the successful application of EEG signal processing methods requires a detailed knowledge of both the topography and frequency spectra of low-amplitude, high-frequency craniofacial EMG. This information remains limited in clinical research, and as such, there is no known reliable technique for the removal of these artifacts from EEG data. The results presented herein outline a preliminary investigation of craniofacial EMG high-frequency spectra and 3D MRI segmentation that offers insight into the development of an anatomically-realistic model for characterizing these effects. The data presented highlights the potential for confounding signal contribution from around 60 to 200 Hz, when observed in frequency space, from both low and high-amplitude EMG signals. This range directly overlaps that of both low γ (30-50 Hz) and high γ (50-80 Hz) waves, as defined traditionally in standatrd EEG measurements, and mainly with waves presented in dense-array EEG recordings. Likewise, average EMG amplitude comparisons from each condition highlights the similarities in signal contribution of low-activity muscular movements and resting, control conditions. In addition to the FFT analysis performed, 3D segmentation and reconstruction of the craniofacial muscles whose EMG signals were measured was successful. This recapitulation of the relevant EMG morphology is a crucial first step in developing an anatomical model for the isolation and removal of confounding low-amplitude craniofacial EMG signals from EEG data. Such a model may be eventually applied in a clinical setting to ultimately help to extend the use of EEG in various clinical roles. PMID:26913150

  15. Low-Amplitude Craniofacial EMG Power Spectral Density and 3D Muscle Reconstruction from MRI

    PubMed Central

    Wiedemann, Lukas; Chaberova, Jana; Edmunds, Kyle; Einarsdóttir, Guðrún; Ramon, Ceon

    2015-01-01

    Improving EEG signal interpretation, specificity, and sensitivity is a primary focus of many current investigations, and the successful application of EEG signal processing methods requires a detailed knowledge of both the topography and frequency spectra of low-amplitude, high-frequency craniofacial EMG. This information remains limited in clinical research, and as such, there is no known reliable technique for the removal of these artifacts from EEG data. The results presented herein outline a preliminary investigation of craniofacial EMG high-frequency spectra and 3D MRI segmentation that offers insight into the development of an anatomically-realistic model for characterizing these effects. The data presented highlights the potential for confounding signal contribution from around 60 to 200 Hz, when observed in frequency space, from both low and high-amplitude EMG signals. This range directly overlaps that of both low γ (30-50 Hz) and high γ (50-80 Hz) waves, as defined traditionally in standatrd EEG measurements, and mainly with waves presented in dense-array EEG recordings. Likewise, average EMG amplitude comparisons from each condition highlights the similarities in signal contribution of low-activity muscular movements and resting, control conditions. In addition to the FFT analysis performed, 3D segmentation and reconstruction of the craniofacial muscles whose EMG signals were measured was successful. This recapitulation of the relevant EMG morphology is a crucial first step in developing an anatomical model for the isolation and removal of confounding low-amplitude craniofacial EMG signals from EEG data. Such a model may be eventually applied in a clinical setting to ultimately help to extend the use of EEG in various clinical roles. PMID:26913150

  16. Low-Amplitude Craniofacial EMG Power Spectral Density and 3D Muscle Reconstruction from MRI.

    PubMed

    Wiedemann, Lukas; Chaberova, Jana; Edmunds, Kyle; Einarsdóttir, Guðrún; Ramon, Ceon; Gargiulo, Paolo

    2015-03-11

    Improving EEG signal interpretation, specificity, and sensitivity is a primary focus of many current investigations, and the successful application of EEG signal processing methods requires a detailed knowledge of both the topography and frequency spectra of low-amplitude, high-frequency craniofacial EMG. This information remains limited in clinical research, and as such, there is no known reliable technique for the removal of these artifacts from EEG data. The results presented herein outline a preliminary investigation of craniofacial EMG high-frequency spectra and 3D MRI segmentation that offers insight into the development of an anatomically-realistic model for characterizing these effects. The data presented highlights the potential for confounding signal contribution from around 60 to 200 Hz, when observed in frequency space, from both low and high-amplitude EMG signals. This range directly overlaps that of both low γ (30-50 Hz) and high γ (50-80 Hz) waves, as defined traditionally in standatrd EEG measurements, and mainly with waves presented in dense-array EEG recordings. Likewise, average EMG amplitude comparisons from each condition highlights the similarities in signal contribution of low-activity muscular movements and resting, control conditions. In addition to the FFT analysis performed, 3D segmentation and reconstruction of the craniofacial muscles whose EMG signals were measured was successful. This recapitulation of the relevant EMG morphology is a crucial first step in developing an anatomical model for the isolation and removal of confounding low-amplitude craniofacial EMG signals from EEG data. Such a model may be eventually applied in a clinical setting to ultimately help to extend the use of EEG in various clinical roles.

  17. Shoulder muscles recruitment during a power backward giant swing on high bar: a wavelet-EMG-analysis.

    PubMed

    Frère, Julien; Göpfert, Beat; Slawinski, Jean; Tourny-Chollet, Claire

    2012-04-01

    This study aimed at determining the upper limb muscles coordination during a power backward giant swing (PBGS) and the recruitment pattern of motor units (MU) of co-activated muscles. The wavelet transformation (WT) was applied to the surface electromyographic (EMG) signal of eight shoulder muscles. Total gymnast's body energy and wavelet synergies extracted from the WT-EMG by using a non-negative matrix factorization were analyzed as a function of the body position angle of the gymnast. A cross-correlation analysis of the EMG patterns allowed determining two main groups of co-activated muscles. Two wavelet synergies representing the main spectral features (82% of the variance accounted for) discriminated the recruitment of MU. Although no task-group of MU was found among the muscles, it appeared that a higher proportion of fast MU was recruited within the muscles of the first group during the upper part of the PBGS. The last increase of total body energy before bar release was induced by the recruitment of the muscles of the second group but did not necessitate the recruitment of a higher proportion of fast MU. Such muscle coordination agreed with previous simulations of elements on high bar as well as the findings related to the recruitment of MU. PMID:22534213

  18. Novel algorithm for real-time onset detection of surface electromyography in step-tracking wrist movements.

    PubMed

    Kuroda, Yoshihiro; Nisky, Ilana; Uranishi, Yuki; Imura, Masataka; Okamura, Allison M; Oshiro, Osamu

    2013-01-01

    We present a novel algorithm for real-time detection of the onset of surface electromyography signal in step-tracking wrist movements. The method identifies abrupt increase of the quasi-tension signal calculated from sEMG resulting from the step-by-step recruitment of activated motor units. We assessed the performance of our proposed algorithm using both simulated and real sEMG signals, and compared with two existing detection methods. Evaluation with simulated sEMG showed that the detection accuracy of our method is robust to different signal-to-noise ratios, and that it outperforms the existing methods in terms of bias when the noise is large (low SNR). Evaluation with real sEMG analysis also indicated better detection performance compared to existing methods. PMID:24110123

  19. Interpreting sign components from accelerometer and sEMG data for automatic sign language recognition.

    PubMed

    Li, Yun; Chen, Xiang; Zhang, Xu; Wang, Kongqiao; Yang, Jihai

    2011-01-01

    The identification of constituent components of each sign gesture is a practical way of establishing large-vocabulary sign language recognition (SLR) system. Aiming at developing such a system using portable accelerometer (ACC) and surface electromyographic (sEMG) sensors, this work proposes a method for automatic SLR at the component level. The preliminary experimental results demonstrate the effectiveness of the proposed method and the feasibility of interpreting sign components from ACC and sEMG data. Our study improves the performance of SLR based on ACC and sEMG sensors and will promote the realization of a large-vocabulary portable SLR system. PMID:22255059

  20. Evaluation of methods for extraction of the volitional EMG in dynamic hybrid muscle activation

    PubMed Central

    Langzam, Eran; Isakov, Eli; Mizrahi, Joseph

    2006-01-01

    Background Hybrid muscle activation is a modality used for muscle force enhancement, in which muscle contraction is generated from two different excitation sources: volitional and external, by means of electrical stimulation (ES). Under hybrid activation, the overall EMG signal is the combination of the volitional and ES-induced components. In this study, we developed a computational scheme to extract the volitional EMG envelope from the overall dynamic EMG signal, to serve as an input signal for control purposes, and for evaluation of muscle forces. Methods A "synthetic" database was created from in-vivo experiments on the Tibialis Anterior of the right foot to emulate hybrid EMG signals, including the volitional and induced components. The database was used to evaluate the results obtained from six signal processing schemes, including seven different modules for filtration, rectification and ES component removal. The schemes differed from each other by their module combinations, as follows: blocking window only, comb filter only, blocking window and comb filter, blocking window and peak envelope, comb filter and peak envelope and, finally, blocking window, comb filter and peak envelope. Results and conclusion The results showed that the scheme including all the modules led to an excellent approximation of the volitional EMG envelope, as extracted from the hybrid signal, and underlined the importance of the artifact blocking window module in the process. The results of this work have direct implications on the development of hybrid muscle activation rehabilitation systems for the enhancement of weakened muscles. PMID:17123447

  1. Compression of surface myoelectric signals using MP3 encoding.

    PubMed

    Chan, Adrian D C

    2011-01-01

    The potential of MP3 compression of surface myoelectric signals is explored in this paper. MP3 compression is a perceptual-based encoder scheme, used traditionally to compress audio signals. The ubiquity of MP3 compression (e.g., portable consumer electronics and internet applications) makes it an attractive option for remote monitoring and telemedicine applications. The effects of muscle site and contraction type are examined at different MP3 encoding bitrates. Results demonstrate that MP3 compression is sensitive to the myoelectric signal bandwidth, with larger signal distortion associated with myoelectric signals that have higher bandwidths. Compared to other myoelectric signal compression techniques reported previously (embedded zero-tree wavelet compression and adaptive differential pulse code modulation), MP3 compression demonstrates superior performance (i.e., lower percent residual differences for the same compression ratios). PMID:22255464

  2. High-density surface electromyography improves the identification of oscillatory synaptic inputs to motoneurons.

    PubMed

    Steeg, Chiel van de; Daffertshofer, Andreas; Stegeman, Dick F; Boonstra, Tjeerd W

    2014-05-15

    Many studies have addressed corticomuscular coherence (CMC), but broad applications are limited by low coherence values and the variability across subjects and recordings. Here, we investigated how the use of high-density surface electromyography (HDsEMG) can improve the detection of CMC. Sixteen healthy subjects performed isometric contractions at six low-force levels using a pinch-grip, while HDsEMG of the adductor pollicis transversus and flexor and abductor pollicis brevis and whole-head magnetoencephalography were recorded. Different configurations were constructed from the HDsEMG grid, such as a bipolar and Laplacian montage, as well as a montage based on principal component analysis (PCA). CMC was estimated for each configuration, and the strength of coherence was compared across configurations. As expected, performance of the precision-grip task resulted in significant CMC in the β-frequency band (16-26 Hz). Compared with a bipolar EMG montage, all multichannel configurations obtained from the HDsEMG grid revealed a significant increase in CMC. The configuration, based on PCA, showed the largest (37%) increase. HDsEMG did not reduce the between-subject variability; rather, many configurations showed an increased coefficient of variation. Increased CMC presumably reflects the ability of HDsEMG to counteract inherent EMG signal factors-such as amplitude cancellation-which impact the detection of oscillatory inputs. In contrast, the between-subject variability of CMC most likely has a cortical origin.

  3. Improvements on EMG-based handwriting recognition with DTW algorithm.

    PubMed

    Li, Chengzhang; Ma, Zheren; Yao, Lin; Zhang, Dingguo

    2013-01-01

    Previous works have shown that Dynamic Time Warping (DTW) algorithm is a proper method of feature extraction for electromyography (EMG)-based handwriting recognition. In this paper, several modifications are proposed to improve the classification process and enhance recognition accuracy. A two-phase template making approach has been introduced to generate templates with more salient features, and modified Mahalanobis Distance (mMD) approach is used to replace Euclidean Distance (ED) in order to minimize the interclass variance. To validate the effectiveness of such modifications, experiments were conducted, in which four subjects wrote lowercase letters at a normal speed and four-channel EMG signals from forearms were recorded. Results of offline analysis show that the improvements increased the average recognition accuracy by 9.20%.

  4. Human joint motion estimation for electromyography (EMG)-based dynamic motion control.

    PubMed

    Zhang, Qin; Hosoda, Ryo; Venture, Gentiane

    2013-01-01

    This study aims to investigate a joint motion estimation method from Electromyography (EMG) signals during dynamic movement. In most EMG-based humanoid or prosthetics control systems, EMG features were directly or indirectly used to trigger intended motions. However, both physiological and nonphysiological factors can influence EMG characteristics during dynamic movements, resulting in subject-specific, non-stationary and crosstalk problems. Particularly, when motion velocity and/or joint torque are not constrained, joint motion estimation from EMG signals are more challenging. In this paper, we propose a joint motion estimation method based on muscle activation recorded from a pair of agonist and antagonist muscles of the joint. A linear state-space model with multi input single output is proposed to map the muscle activity to joint motion. An adaptive estimation method is proposed to train the model. The estimation performance is evaluated in performing a single elbow flexion-extension movement in two subjects. All the results in two subjects at two load levels indicate the feasibility and suitability of the proposed method in joint motion estimation. The estimation root-mean-square error is within 8.3% ∼ 10.6%, which is lower than that being reported in several previous studies. Moreover, this method is able to overcome subject-specific problem and compensate non-stationary EMG properties.

  5. Microprocessor-based simulator of surface ECG signals

    NASA Astrophysics Data System (ADS)

    Martínez, A. E.; Rossi, E.; Siri, L. Nicola

    2007-11-01

    In this work, a simulator of surface electrocardiogram recorded signals (ECG) is presented. The device, based on a microcontroller and commanded by a personal computer, produces an analog signal resembling actual ECGs, not only in time course and voltage levels, but also in source impedance. The simulator is a useful tool for electrocardiograph calibration and monitoring, to incorporate as well in educational tasks and in clinical environments for early detection of faulty behaviour.

  6. Steering a Tractor by Means of an EMG-Based Human-Machine Interface

    PubMed Central

    Gomez-Gil, Jaime; San-Jose-Gonzalez, Israel; Nicolas-Alonso, Luis Fernando; Alonso-Garcia, Sergio

    2011-01-01

    An electromiographic (EMG)-based human-machine interface (HMI) is a communication pathway between a human and a machine that operates by means of the acquisition and processing of EMG signals. This article explores the use of EMG-based HMIs in the steering of farm tractors. An EPOC, a low-cost human-computer interface (HCI) from the Emotiv Company, was employed. This device, by means of 14 saline sensors, measures and processes EMG and electroencephalographic (EEG) signals from the scalp of the driver. In our tests, the HMI took into account only the detection of four trained muscular events on the driver’s scalp: eyes looking to the right and jaw opened, eyes looking to the right and jaw closed, eyes looking to the left and jaw opened, and eyes looking to the left and jaw closed. The EMG-based HMI guidance was compared with manual guidance and with autonomous GPS guidance. A driver tested these three guidance systems along three different trajectories: a straight line, a step, and a circumference. The accuracy of the EMG-based HMI guidance was lower than the accuracy obtained by manual guidance, which was lower in turn than the accuracy obtained by the autonomous GPS guidance; the computed standard deviations of error to the desired trajectory in the straight line were 16 cm, 9 cm, and 4 cm, respectively. Since the standard deviation between the manual guidance and the EMG-based HMI guidance differed only 7 cm, and this difference is not relevant in agricultural steering, it can be concluded that it is possible to steer a tractor by an EMG-based HMI with almost the same accuracy as with manual steering. PMID:22164006

  7. Steering a tractor by means of an EMG-based human-machine interface.

    PubMed

    Gomez-Gil, Jaime; San-Jose-Gonzalez, Israel; Nicolas-Alonso, Luis Fernando; Alonso-Garcia, Sergio

    2011-01-01

    An electromiographic (EMG)-based human-machine interface (HMI) is a communication pathway between a human and a machine that operates by means of the acquisition and processing of EMG signals. This article explores the use of EMG-based HMIs in the steering of farm tractors. An EPOC, a low-cost human-computer interface (HCI) from the Emotiv Company, was employed. This device, by means of 14 saline sensors, measures and processes EMG and electroencephalographic (EEG) signals from the scalp of the driver. In our tests, the HMI took into account only the detection of four trained muscular events on the driver's scalp: eyes looking to the right and jaw opened, eyes looking to the right and jaw closed, eyes looking to the left and jaw opened, and eyes looking to the left and jaw closed. The EMG-based HMI guidance was compared with manual guidance and with autonomous GPS guidance. A driver tested these three guidance systems along three different trajectories: a straight line, a step, and a circumference. The accuracy of the EMG-based HMI guidance was lower than the accuracy obtained by manual guidance, which was lower in turn than the accuracy obtained by the autonomous GPS guidance; the computed standard deviations of error to the desired trajectory in the straight line were 16 cm, 9 cm, and 4 cm, respectively. Since the standard deviation between the manual guidance and the EMG-based HMI guidance differed only 7 cm, and this difference is not relevant in agricultural steering, it can be concluded that it is possible to steer a tractor by an EMG-based HMI with almost the same accuracy as with manual steering.

  8. Surface Wave Multipath Signals in Near-Field Microwave Imaging

    PubMed Central

    Meaney, Paul M.; Shubitidze, Fridon; Fanning, Margaret W.; Kmiec, Maciej; Epstein, Neil R.; Paulsen, Keith D.

    2012-01-01

    Microwave imaging techniques are prone to signal corruption from unwanted multipath signals. Near-field systems are especially vulnerable because signals can scatter and reflect from structural objects within or on the boundary of the imaging zone. These issues are further exacerbated when surface waves are generated with the potential of propagating along the transmitting and receiving antenna feed lines and other low-loss paths. In this paper, we analyze the contributions of multi-path signals arising from surface wave effects. Specifically, experiments were conducted with a near-field microwave imaging array positioned at variable heights from the floor of a coupling fluid tank. Antenna arrays with different feed line lengths in the fluid were also evaluated. The results show that surface waves corrupt the received signals over the longest transmission distances across the measurement array. However, the surface wave effects can be eliminated provided the feed line lengths are sufficiently long independently of the distance of the transmitting/receiving antenna tips from the imaging tank floor. Theoretical predictions confirm the experimental observations. PMID:22566992

  9. Surface wave multipath signals in near-field microwave imaging.

    PubMed

    Meaney, Paul M; Shubitidze, Fridon; Fanning, Margaret W; Kmiec, Maciej; Epstein, Neil R; Paulsen, Keith D

    2012-01-01

    Microwave imaging techniques are prone to signal corruption from unwanted multipath signals. Near-field systems are especially vulnerable because signals can scatter and reflect from structural objects within or on the boundary of the imaging zone. These issues are further exacerbated when surface waves are generated with the potential of propagating along the transmitting and receiving antenna feed lines and other low-loss paths. In this paper, we analyze the contributions of multi-path signals arising from surface wave effects. Specifically, experiments were conducted with a near-field microwave imaging array positioned at variable heights from the floor of a coupling fluid tank. Antenna arrays with different feed line lengths in the fluid were also evaluated. The results show that surface waves corrupt the received signals over the longest transmission distances across the measurement array. However, the surface wave effects can be eliminated provided the feed line lengths are sufficiently long independently of the distance of the transmitting/receiving antenna tips from the imaging tank floor. Theoretical predictions confirm the experimental observations.

  10. Performances evaluation of textile electrodes for EMG remote measurements.

    PubMed

    Sumner, B; Mancuso, C; Paradiso, R

    2013-01-01

    This work focus on the evaluation of textile electrodes for EMG signals acquisition. Signals have been acquired simultaneously from textile electrode and from gold standard electrodes, by using the same acquisition system; tests were done across subjects and with multiple trials to enable a more complete analysis. This research activity was done in the frame of the European Project Interaction, aiming at the development of a system for a continuous daily-life monitoring of the functional performance of stroke survivors in their physical interaction with the environment.

  11. An online hybrid BCI system based on SSVEP and EMG

    NASA Astrophysics Data System (ADS)

    Lin, Ke; Cinetto, Andrea; Wang, Yijun; Chen, Xiaogang; Gao, Shangkai; Gao, Xiaorong

    2016-04-01

    Objective. A hybrid brain-computer interface (BCI) is a device combined with at least one other communication system that takes advantage of both parts to build a link between humans and machines. To increase the number of targets and the information transfer rate (ITR), electromyogram (EMG) and steady-state visual evoked potential (SSVEP) were combined to implement a hybrid BCI. A multi-choice selection method based on EMG was developed to enhance the system performance. Approach. A 60-target hybrid BCI speller was built in this study. A single trial was divided into two stages: a stimulation stage and an output selection stage. In the stimulation stage, SSVEP and EMG were used together. Every stimulus flickered at its given frequency to elicit SSVEP. All of the stimuli were divided equally into four sections with the same frequency set. The frequency of each stimulus in a section was different. SSVEPs were used to discriminate targets in the same section. Different sections were classified using EMG signals from the forearm. Subjects were asked to make different number of fists according to the target section. Canonical Correlation Analysis (CCA) and mean filtering was used to classify SSVEP and EMG separately. In the output selection stage, the top two optimal choices were given. The first choice with the highest probability of an accurate classification was the default output of the system. Subjects were required to make a fist to select the second choice only if the second choice was correct. Main results. The online results obtained from ten subjects showed that the mean accurate classification rate and ITR were 81.0% and 83.6 bits min-1 respectively only using the first choice selection. The ITR of the hybrid system was significantly higher than the ITR of any of the two single modalities (EMG: 30.7 bits min-1, SSVEP: 60.2 bits min-1). After the addition of the second choice selection and the correction task, the accurate classification rate and ITR was

  12. Reprogramming cellular signaling machinery using surface-modified carbon nanotubes.

    PubMed

    Zhang, Yi; Wu, Ling; Jiang, Cuijuan; Yan, Bing

    2015-03-16

    Nanoparticles, such as carbon nanotubes (CNTs), interact with cells and are easily internalized, causing various perturbations to cell functions. The mechanisms involved in such perturbations are investigated by a systematic approach that utilizes modified CNTs and various chemical-biological assays. Three modes of actions are (1) CNTs bind to different cell surface receptors and perturb different cell signaling pathways; (2) CNTs bind to a receptor with different affinity and, therefore, strengthen or weaken signals; (3) CNTs enter cells and bind to soluble signaling proteins involved in a signaling pathway. Understanding of such mechanisms not only clarifies how CNTs cause cytotoxicity but also demonstrates a useful method to modulate biological/toxicological activities of CNTs for their various industrial, biomedical, and consumer applications.

  13. Only scratching the cell surface: extracellular signals in cerebrum development.

    PubMed

    Hébert, Jean M

    2013-08-01

    Numerous roles have been identified for extracellular signals such as Fibroblast Growth Factors (FGFs), Transforming Growth Factor-βs (TGFβs), Wingless-Int proteins (WNTs), and Sonic Hedgehog (SHH) in assigning fates to cells during development of the cerebrum. However, several fundamental questions remain largely unexplored. First, how does the same extracellular signal instruct precursor cells in different locations or at different stages to adopt distinct fates? And second, how does a precursor cell integrate multiple signals to adopt a specific fate? Answers to these questions require knowing the mechanisms that underlie each cell type's competence to respond to certain extracellular signals. This brief review provides illustrative examples of potential mechanisms that begin to bridge the gap between cell surface and cell fate during cerebrum development.

  14. Reprogramming cellular signaling machinery using surface-modified carbon nanotubes.

    PubMed

    Zhang, Yi; Wu, Ling; Jiang, Cuijuan; Yan, Bing

    2015-03-16

    Nanoparticles, such as carbon nanotubes (CNTs), interact with cells and are easily internalized, causing various perturbations to cell functions. The mechanisms involved in such perturbations are investigated by a systematic approach that utilizes modified CNTs and various chemical-biological assays. Three modes of actions are (1) CNTs bind to different cell surface receptors and perturb different cell signaling pathways; (2) CNTs bind to a receptor with different affinity and, therefore, strengthen or weaken signals; (3) CNTs enter cells and bind to soluble signaling proteins involved in a signaling pathway. Understanding of such mechanisms not only clarifies how CNTs cause cytotoxicity but also demonstrates a useful method to modulate biological/toxicological activities of CNTs for their various industrial, biomedical, and consumer applications. PMID:25536342

  15. An EMG-Controlled Robotic Hand Exoskeleton for Bilateral Rehabilitation.

    PubMed

    Leonardis, Daniele; Barsotti, Michele; Loconsole, Claudio; Solazzi, Massimiliano; Troncossi, Marco; Mazzotti, Claudio; Castelli, Vincenzo Parenti; Procopio, Caterina; Lamola, Giuseppe; Chisari, Carmelo; Bergamasco, Massimo; Frisoli, Antonio

    2015-01-01

    This paper presents a novel electromyography (EMG)-driven hand exoskeleton for bilateral rehabilitation of grasping in stroke. The developed hand exoskeleton was designed with two distinctive features: (a) kinematics with intrinsic adaptability to patient's hand size, and (b) free-palm and free-fingertip design, preserving the residual sensory perceptual capability of touch during assistance in grasping of real objects. In the envisaged bilateral training strategy, the patient's non paretic hand acted as guidance for the paretic hand in grasping tasks. Grasping force exerted by the non paretic hand was estimated in real-time from EMG signals, and then replicated as robotic assistance for the paretic hand by means of the hand-exoskeleton. Estimation of the grasping force through EMG allowed to perform rehabilitation exercises with any, non sensorized, graspable objects. This paper presents the system design, development, and experimental evaluation. Experiments were performed within a group of six healthy subjects and two chronic stroke patients, executing robotic-assisted grasping tasks. Results related to performance in estimation and modulation of the robotic assistance, and to the outcomes of the pilot rehabilitation sessions with stroke patients, positively support validity of the proposed approach for application in stroke rehabilitation.

  16. EMG spike time difference based feedback control.

    PubMed

    Butala, Jaydrath; Arkles, Anthony; Gray, John R

    2007-01-01

    Flight control in insects has been studied extensively; however the underlying neural mechanisms are not fully understood. Output from the central nervous system (CNS) must drive wing phase shifts and flight muscle depressor asymmetries associated with adaptive flight maneuvers. These maneuvers will, in turn, influence the insect's sensory environment, thus closing the feedback loop. We present a novel method that utilizes asymmetrical timing of bilateral depressor muscles, the forewing first basalars (m97), of the locust to close a visual feedback loop in a computer-generated flight simulator. The method converts the time difference between left and right m97s to analog voltage values. These voltage values can be obtained using open-loop experiments (visual motion controlled by the experimenter), or can be used to control closed-loop experiments (muscle activity controls the visual stimuli) experiments. Electromyographic (EMG) signals were obtained from right and left m97 muscles; spike time difference between them was calculated and converted to voltage values. Testing this circuit with real animals, we were able to detect the spike time difference and convert that to voltage that controlled the presentation of a stimulus in a closed-loop environment. This method may be used in conjunction with the flight simulator to understand the manner in which sensory information is integrated with the activity of the flight circuitry to study the neural control of this complex behaviour. PMID:18003414

  17. A Study of an EMG-Based Exoskeletal Robot for Human Shoulder Motion Support

    NASA Astrophysics Data System (ADS)

    Kiguchi, Kazuo; Iwami, Koya; Watanabe, Keigo; Fukuda, Toshio

    We have been developing exoskeletal robots in order to realize the human motion support (especially for physically weak people). In this paper, we propose a 2-DOF exoskeletal robot and its method of control to support the human shoulder motion. In this exoskeletal robot, the flexion-extension and abduction-adduction motions of the shoulder are supported by activating the arm holder of the robot, which is atached to the upper arm of the human subject, using wires driven by DC motors. A fuzzy-neuro controller is designed to control the robot according to the skin surface electromyogram(EMG) signals in which the intention of the human subject is reflected. The proposed controller controls the flexion-extension and abduction-adduction motion of the human subject. The effectiveness of the proposed exoskeletal robot has been evaluated experimentally.

  18. Learning an EMG Controlled Game: Task-Specific Adaptations and Transfer.

    PubMed

    van Dijk, Ludger; van der Sluis, Corry K; van Dijk, Hylke W; Bongers, Raoul M

    2016-01-01

    Video games that aim to improve myoelectric control (myogames) are gaining popularity and are often part of the rehabilitation process following an upper limb amputation. However, direct evidence for their effect on prosthetic skill is limited. This study aimed to determine whether and how myogaming improves EMG control and whether performance improvements transfer to a prosthesis-simulator task. Able-bodied right-handed participants (N = 28) were randomly assigned to 1 of 2 groups. The intervention group was trained to control a video game (Breakout-EMG) using the myosignals of wrist flexors and extensors. Controls played a regular Mario computer game. Both groups trained 20 minutes a day for 4 consecutive days. Before and after training, two tests were conducted: one level of the Breakout-EMG game, and grasping objects with a prosthesis-simulator. Results showed a larger increase of in-game accuracy for the Breakout-EMG group than for controls. The Breakout-EMG group moreover showed increased adaptation of the EMG signal to the game. No differences were found in using a prosthesis-simulator. This study demonstrated that myogames lead to task-specific myocontrol skills. Transfer to a prosthesis task is therefore far from easy. We discuss several implications for future myogame designs. PMID:27556154

  19. Learning an EMG Controlled Game: Task-Specific Adaptations and Transfer

    PubMed Central

    van Dijk, Ludger; van der Sluis, Corry K.; van Dijk, Hylke W.; Bongers, Raoul M.

    2016-01-01

    Video games that aim to improve myoelectric control (myogames) are gaining popularity and are often part of the rehabilitation process following an upper limb amputation. However, direct evidence for their effect on prosthetic skill is limited. This study aimed to determine whether and how myogaming improves EMG control and whether performance improvements transfer to a prosthesis-simulator task. Able-bodied right-handed participants (N = 28) were randomly assigned to 1 of 2 groups. The intervention group was trained to control a video game (Breakout-EMG) using the myosignals of wrist flexors and extensors. Controls played a regular Mario computer game. Both groups trained 20 minutes a day for 4 consecutive days. Before and after training, two tests were conducted: one level of the Breakout-EMG game, and grasping objects with a prosthesis-simulator. Results showed a larger increase of in-game accuracy for the Breakout-EMG group than for controls. The Breakout-EMG group moreover showed increased adaptation of the EMG signal to the game. No differences were found in using a prosthesis-simulator. This study demonstrated that myogames lead to task-specific myocontrol skills. Transfer to a prosthesis task is therefore far from easy. We discuss several implications for future myogame designs. PMID:27556154

  20. Iridescent flowers? Contribution of surface structures to optical signaling.

    PubMed

    van der Kooi, Casper J; Wilts, Bodo D; Leertouwer, Hein L; Staal, Marten; Elzenga, J Theo M; Stavenga, Doekele G

    2014-07-01

    The color of natural objects depends on how they are structured and pigmented. In flowers, both the surface structure of the petals and the pigments they contain determine coloration. The aim of the present study was to assess the contribution of structural coloration, including iridescence, to overall floral coloration. We studied the reflection characteristics of flower petals of various plant species with an imaging scatterometer, which allows direct visualization of the angle dependence of the reflected light in the hemisphere above the petal. To separate the light reflected by the flower surface from the light backscattered by the components inside (e.g. the vacuoles), we also investigated surface casts. A survey among angiosperms revealed three different types of floral surface structure, each with distinct reflections. Petals with a smooth and very flat surface had mirror-like reflections and petal surfaces with cones yielded diffuse reflections. Petals with striations yielded diffraction patterns when single cells were illuminated. The iridescent signal, however, vanished when illumination similar to that found in natural conditions was applied. Pigmentary rather than structural coloration determines the optical appearance of flowers. Therefore, the hypothesized signaling by flowers with striated surfaces to attract potential pollinators presently seems untenable.

  1. Iridescent flowers? Contribution of surface structures to optical signaling.

    PubMed

    van der Kooi, Casper J; Wilts, Bodo D; Leertouwer, Hein L; Staal, Marten; Elzenga, J Theo M; Stavenga, Doekele G

    2014-07-01

    The color of natural objects depends on how they are structured and pigmented. In flowers, both the surface structure of the petals and the pigments they contain determine coloration. The aim of the present study was to assess the contribution of structural coloration, including iridescence, to overall floral coloration. We studied the reflection characteristics of flower petals of various plant species with an imaging scatterometer, which allows direct visualization of the angle dependence of the reflected light in the hemisphere above the petal. To separate the light reflected by the flower surface from the light backscattered by the components inside (e.g. the vacuoles), we also investigated surface casts. A survey among angiosperms revealed three different types of floral surface structure, each with distinct reflections. Petals with a smooth and very flat surface had mirror-like reflections and petal surfaces with cones yielded diffuse reflections. Petals with striations yielded diffraction patterns when single cells were illuminated. The iridescent signal, however, vanished when illumination similar to that found in natural conditions was applied. Pigmentary rather than structural coloration determines the optical appearance of flowers. Therefore, the hypothesized signaling by flowers with striated surfaces to attract potential pollinators presently seems untenable. PMID:24713039

  2. Analysis of using EMG and mechanical sensors to enhance intent recognition in powered lower limb prostheses

    NASA Astrophysics Data System (ADS)

    Young, A. J.; Kuiken, T. A.; Hargrove, L. J.

    2014-10-01

    Objective. The purpose of this study was to determine the contribution of electromyography (EMG) data, in combination with a diverse array of mechanical sensors, to locomotion mode intent recognition in transfemoral amputees using powered prostheses. Additionally, we determined the effect of adding time history information using a dynamic Bayesian network (DBN) for both the mechanical and EMG sensors. Approach. EMG signals from the residual limbs of amputees have been proposed to enhance pattern recognition-based intent recognition systems for powered lower limb prostheses, but mechanical sensors on the prosthesis—such as inertial measurement units, position and velocity sensors, and load cells—may be just as useful. EMG and mechanical sensor data were collected from 8 transfemoral amputees using a powered knee/ankle prosthesis over basic locomotion modes such as walking, slopes and stairs. An offline study was conducted to determine the benefit of different sensor sets for predicting intent. Main results. EMG information was not as accurate alone as mechanical sensor information (p < 0.05) for any classification strategy. However, EMG in combination with the mechanical sensor data did significantly reduce intent recognition errors (p < 0.05) both for transitions between locomotion modes and steady-state locomotion. The sensor time history (DBN) classifier significantly reduced error rates compared to a linear discriminant classifier for steady-state steps, without increasing the transitional error, for both EMG and mechanical sensors. Combining EMG and mechanical sensor data with sensor time history reduced the average transitional error from 18.4% to 12.2% and the average steady-state error from 3.8% to 1.0% when classifying level-ground walking, ramps, and stairs in eight transfemoral amputee subjects. Significance. These results suggest that a neural interface in combination with time history methods for locomotion mode classification can enhance intent

  3. A high-density multichannel surface electromyography system for the characterization of single motor units

    NASA Astrophysics Data System (ADS)

    Blok, J. H.; van Dijk, J. P.; Drost, G.; Zwarts, M. J.; Stegeman, D. F.

    2002-04-01

    An electromyography (EMG) system is presented that noninvasively records the electrical activity of a muscle with 126 densely spaced skin-surface electrodes. The electrodes are arranged in a two-dimensional array and integrated in a single container for ease of application. Signals are recorded "monopolarly", with a reference electrode placed at a distance from the array. With this recording configuration, the surface EMG (sEMG) potential distribution can be described not only as a function of time, but also topographically. The availability of topographical information opens up a range of applications. Some of these have been described previously. However, the system presented is unique in that it allows exploration of all clinical and scientific possibilities of topographical sEMG. In its design, special attention was paid to user-friendliness and flexibility. With high-density multichannel sEMG, both the properties of a whole muscle and those of single motor units, the functional units of a muscle, can be studied. The latter belong to a realm that was long considered accessible only with needle-EMG, a conventional, invasive diagnostic technique. It is demonstrated that the additional topographical information can be used to characterize motor units in a way that is partially superior to needle EMG.

  4. A new and fast approach towards sEMG decomposition.

    PubMed

    Gligorijević, Ivan; van Dijk, Johannes P; Mijović, Bogdan; Van Huffel, Sabine; Blok, Joleen H; De Vos, Maarten

    2013-05-01

    The decomposition of high-density surface EMG (HD-sEMG) interference patterns into the contribution of motor units is still a challenging task. We introduce a new, fast solution to this problem. The method uses a data-driven approach for selecting a set of electrodes to enable discrimination of present motor unit action potentials (MUAPs). Then, using shapes detected on these channels, the hierarchical clustering algorithm as reported by Quian Quiroga et al. (Neural Comput 16:1661-1687, 2004) is extended for multichannel data in order to obtain the motor unit action potential (MUAP) signatures. After this first step, more motor unit firings are obtained using the extracted signatures by a novel demixing technique. In this demixing stage, we propose a time-efficient solution for the general convolutive system that models the motor unit firings on the HD-sEMG grid. We constrain this system by using the extracted signatures as prior knowledge and reconstruct the firing patterns in a computationally efficient way. The algorithm performance is successfully verified on simulated data containing up to 20 different MUAP signatures. Moreover, we tested the method on real low contraction recordings from the lateral vastus leg muscle by comparing the algorithm's output to the results obtained by manual analysis of the data from two independent trained operators. The proposed method showed to perform about equally successful as the operators.

  5. Quantitative analysis of surface electromyography: Biomarkers for convulsive seizures.

    PubMed

    Beniczky, Sándor; Conradsen, Isa; Pressler, Ronit; Wolf, Peter

    2016-08-01

    Muscle activity during seizures is in electroencephalographical (EEG) praxis often considered an irritating artefact. This article discusses ways by surface electromyography (EMG) to turn it into a valuable tool of epileptology. Muscles are in direct synaptic contact with motor neurons. Therefore, EMG signals provide direct information about the electric activity in the motor cortex. Qualitative analysis of EMG has traditionally been a part of the long-term video-EEG recordings. Recent development in quantitative analysis of EMG signals yielded valuable information on the pathomechanisms of convulsive seizures, demonstrating that it was different from maximal voluntary contraction, and different from convulsive psychogenic non-epileptic seizures. Furthermore, the tonic phase of the generalised tonic-clonic seizures (GTCS) proved to have different quantitative features than tonic seizures. The high temporal resolution of EMG allowed detailed characterisation of temporal dynamics of the GTCS, suggesting that the same inhibitory mechanisms that try to prevent the build-up of the seizure activity, contribute to ending the seizure. These findings have clinical implications: the quantitative EMG features provided the pathophysiologic substrate for developing neurophysiologic biomarkers that accurately identify GTCS. This proved to be efficient both for seizure detection and for objective, automated distinction between convulsive and non-convulsive epileptic seizures.

  6. Hand gesture recognition based on surface electromyography.

    PubMed

    Samadani, Ali-Akbar; Kulic, Dana

    2014-01-01

    Human hands are the most dexterous of human limbs and hand gestures play an important role in non-verbal communication. Underlying electromyograms associated with hand gestures provide a wealth of information based on which varying hand gestures can be recognized. This paper develops an inter-individual hand gesture recognition model based on Hidden Markov models that receives surface electromyography (sEMG) signals as inputs and predicts a corresponding hand gesture. The developed recognition model is tested with a dataset of 10 various hand gestures performed by 25 subjects in a leave-one-subject-out cross validation and an inter-individual recognition rate of 79% was achieved. The promising recognition rate demonstrates the efficacy of the proposed approach for discriminating between gesture-specific sEMG signals and could inform the design of sEMG-controlled prostheses and assistive devices. PMID:25570917

  7. Surface code—biophysical signals for apoptotic cell clearance

    NASA Astrophysics Data System (ADS)

    Biermann, Mona; Maueröder, Christian; Brauner, Jan M.; Chaurio, Ricardo; Janko, Christina; Herrmann, Martin; Muñoz, Luis E.

    2013-12-01

    Apoptotic cell death and the clearance of dying cells play an important and physiological role in embryonic development and normal tissue turnover. In contrast to necrosis, apoptosis proceeds in an anti-inflammatory manner. It is orchestrated by the timed release and/or exposure of so-called ‘find-me’, ‘eat me’ and ‘tolerate me’ signals. Mononuclear phagocytes are attracted by various ‘find-me’ signals, including proteins, nucleotides, and phospholipids released by the dying cell, whereas the involvement of granulocytes is prevented via ‘stay away’ signals. The exposure of anionic phospholipids like phosphatidylserine (PS) by apoptotic cells on the outer leaflet of the plasma membrane is one of the main ‘eat me’ signals. PS is recognized by a number of innate receptors as well as by soluble bridging molecules on the surface of phagocytes. Importantly, phagocytes are able to discriminate between viable and apoptotic cells both exposing PS. Due to cytoskeleton remodeling PS has a higher lateral mobility on the surfaces of apoptotic cells thereby promoting receptor clustering on the phagocyte. PS not only plays an important role in the engulfment process, but also acts as ‘tolerate me’ signal inducing the release of anti-inflammatory cytokines by phagocytes. An efficient and fast clearance of apoptotic cells is required to prevent secondary necrosis and leakage of intracellular danger signals into the surrounding tissue. Failure or prolongation of the clearance process leads to the release of intracellular antigens into the periphery provoking inflammation and development of systemic inflammatory autoimmune disease like systemic lupus erythematosus. Here we review the current findings concerning apoptosis-inducing pathways, important players of apoptotic cell recognition and clearance as well as the role of membrane remodeling in the engulfment of apoptotic cells by phagocytes.

  8. Trust sensor interface for improving reliability of EMG-based user intent recognition.

    PubMed

    Liu, Yuhong; Zhang, Fan; Sun, Yan Lindsay; Huang, He

    2011-01-01

    To achieve natural and smooth control of prostheses, Electromyographic (EMG) signals have been investigated for decoding user intent. However, EMG signals can be easily contaminated by diverse disturbances, leading to errors in user intent recognition and threatening the safety of prostheses users. To address this problem, we propose a trust sensor interface (TSI) that contains 2 modules: (1) abnormality detector that detects diverse disturbances with high accuracy and low latency and (2) trust evaluation that dynamically evaluates the reliability of EMG sensors. Based on the output of the TSI, the user intention recognition (UIR) algorithm is able to dynamically adjust their operations or decisions. Our experiments on an able-bodied subject have demonstrated that the proposed TSI can effectively detect two types of disturbances (i.e. motion artifacts and baseline shifts) and improve the reliability of the UIR.

  9. Single-Channel EMG Classification With Ensemble-Empirical-Mode-Decomposition-Based ICA for Diagnosing Neuromuscular Disorders.

    PubMed

    Naik, Ganesh R; Selvan, S Easter; Nguyen, Hung T

    2016-07-01

    An accurate and computationally efficient quantitative analysis of electromyography (EMG) signals plays an inevitable role in the diagnosis of neuromuscular disorders, prosthesis, and several related applications. Since it is often the case that the measured signals are the mixtures of electric potentials that emanate from surrounding muscles (sources), many EMG signal processing approaches rely on linear source separation techniques such as the independent component analysis (ICA). Nevertheless, naive implementations of ICA algorithms do not comply with the task of extracting the underlying sources from a single-channel EMG measurement. In this respect, the present work focuses on a classification method for neuromuscular disorders that deals with the data recorded using a single-channel EMG sensor. The ensemble empirical mode decomposition algorithm decomposes the single-channel EMG signal into a set of noise-canceled intrinsic mode functions, which in turn are separated by the FastICA algorithm. A reduced set of five time domain features extracted from the separated components are classified using the linear discriminant analysis, and the classification results are fine-tuned with a majority voting scheme. The performance of the proposed method has been validated with a clinical EMG database, which reports a higher classification accuracy (98%). The outcome of this study encourages possible extension of this approach to real settings to assist the clinicians in making correct diagnosis of neuromuscular disorders. PMID:26173218

  10. Paralyzed subject controls telepresence mobile robot using novel sEMG brain-computer interface: case study.

    PubMed

    Lyons, Kenneth R; Joshi, Sanjay S

    2013-06-01

    Here we demonstrate the use of a new singlesignal surface electromyography (sEMG) brain-computer interface (BCI) to control a mobile robot in a remote location. Previous work on this BCI has shown that users are able to perform cursor-to-target tasks in two-dimensional space using only a single sEMG signal by continuously modulating the signal power in two frequency bands. Using the cursor-to-target paradigm, targets are shown on the screen of a tablet computer so that the user can select them, commanding the robot to move in different directions for a fixed distance/angle. A Wifi-enabled camera transmits video from the robot's perspective, giving the user feedback about robot motion. Current results show a case study with a C3-C4 spinal cord injury (SCI) subject using a single auricularis posterior muscle site to navigate a simple obstacle course. Performance metrics for operation of the BCI as well as completion of the telerobotic command task are developed. It is anticipated that this noninvasive and mobile system will open communication opportunities for the severely paralyzed, possibly using only a single sensor. PMID:24187246

  11. Paralyzed subject controls telepresence mobile robot using novel sEMG brain-computer interface: case study.

    PubMed

    Lyons, Kenneth R; Joshi, Sanjay S

    2013-06-01

    Here we demonstrate the use of a new singlesignal surface electromyography (sEMG) brain-computer interface (BCI) to control a mobile robot in a remote location. Previous work on this BCI has shown that users are able to perform cursor-to-target tasks in two-dimensional space using only a single sEMG signal by continuously modulating the signal power in two frequency bands. Using the cursor-to-target paradigm, targets are shown on the screen of a tablet computer so that the user can select them, commanding the robot to move in different directions for a fixed distance/angle. A Wifi-enabled camera transmits video from the robot's perspective, giving the user feedback about robot motion. Current results show a case study with a C3-C4 spinal cord injury (SCI) subject using a single auricularis posterior muscle site to navigate a simple obstacle course. Performance metrics for operation of the BCI as well as completion of the telerobotic command task are developed. It is anticipated that this noninvasive and mobile system will open communication opportunities for the severely paralyzed, possibly using only a single sensor.

  12. Muscle fiber conduction velocity and fractal dimension of EMG during fatiguing contraction of young and elderly active men.

    PubMed

    Boccia, Gennaro; Dardanello, Davide; Beretta-Piccoli, Matteo; Cescon, Corrado; Coratella, Giuseppe; Rinaldo, Nicoletta; Barbero, Marco; Lanza, Massimo; Schena, Federico; Rainoldi, Alberto

    2016-01-01

    Over the past decade, linear and nonlinear surface electromyography (EMG) variables highlighting different components of fatigue have been developed. In this study, we tested fractal dimension (FD) and conduction velocity (CV) rate of changes as descriptors, respectively, of motor unit synchronization and peripheral manifestations of fatigue. Sixteen elderly (69  ±  4 years) and seventeen young (23  ±  2 years) physically active men (almost 3-5 h of physical activity per week) executed one knee extensor contraction at 70% of a maximal voluntary contraction for 30 s. Muscle fiber CV and FD were calculated from the multichannel surface EMG signal recorded from the vastus lateralis and medialis muscles. The main findings were that the two groups showed a similar rate of change of CV, whereas FD rate of change was higher in the young than in the elderly group. The trends were the same for both muscles. CV findings highlighted a non-different extent of peripheral manifestations of fatigue between groups. Nevertheless, FD rate of change was found to be steeper in the elderly than in the young, suggesting a greater increase in motor unit synchronization with ageing. These findings suggest that FD analysis could be used as a complementary variable providing further information on central mechanisms with respect to CV in fatiguing contractions.

  13. Acoustic (loudspeaker) facial EMG monitoring: II. Use of evoked EMG activity during acoustic neuroma resection.

    PubMed

    Prass, R L; Kinney, S E; Hardy, R W; Hahn, J F; Lüders, H

    1987-12-01

    Facial electromyographic (EMG) activity was continuously monitored via loudspeaker during eleven translabyrinthine and nine suboccipital consecutive unselected acoustic neuroma resections. Ipsilateral facial EMG activity was synchronously recorded on the audio channels of operative videotapes, which were retrospectively reviewed in order to allow detailed evaluation of the potential benefit of various acoustic EMG patterns in the performance of specific aspects of acoustic neuroma resection. The use of evoked facial EMG activity was classified and described. Direct local mechanical (surgical) stimulation and direct electrical stimulation were of benefit in the localization and/or delineation of the facial nerve contour. Burst and train acoustic patterns of EMG activity appeared to indicate surgical trauma to the facial nerve that would not have been appreciated otherwise. Early results of postoperative facial function of monitored patients are presented, and the possible value of burst and train acoustic EMG activity patterns in the intraoperative assessment of facial nerve function is discussed. Acoustic facial EMG monitoring appears to provide a potentially powerful surgical tool for delineation of the facial nerve contour, the ongoing use of which may lead to continued improvement in facial nerve function preservation through modification of dissection strategy.

  14. An EMG study on TMJ disorders.

    PubMed

    Valentino, B; Aldi, B; Melito, F; Valentino, T

    2002-01-01

    The Authors have described a clinical case involving a patient with a classical TMJ syndrome and a full range of typical symptoms, both dental and non-dental. The patient underwent a set of EMG tests before his occlusal plane was restored using a special material, immediately following reconstruction and, lastly, three months following the application of a prosthesis. The findings of these EMG tests have shown that the complex symptoms reported by the patient could be traced back to his occlusal plane. Once it was reconstructed, all the typical dental and non-dental symptoms of TMJ disorders subsided.

  15. Unsupervised learning technique for surface electromyogram denoising from power line interference and baseline wander.

    PubMed

    Niegowski, Maciej; Zivanovic, Miroslav; Gomez, Marisol; Lecumberri, Pablo

    2015-08-01

    We present a novel approach to single-channel power line interference (PLI) and baseline wander (BW) removal from surface electromyograms (EMG). It is based on non-negative matrix factorization (NMF) using a priori knowledge about the interferences. It performs a linear decomposition of the input signal spectrogram into non-negative components, which represent the PLI, BW and EMG spectrogram estimates. They all exhibit very different time-frequency patterns: PLI and BW are both sparse whereas EMG is noise-like. Initialization of the classical NMF algorithm with accurately designed PLI, BW and EMG structures and a carefully adjusted matrix decomposition rank increases the separation performance. The comparative study suggests that the proposed method outperforms two state-of-the-art reference methods. PMID:26737971

  16. Auditory Evaluation of Sound Signals Radiated by a Vibrating Surface

    NASA Astrophysics Data System (ADS)

    MEUNIER, S.; HABAULT, D.; CANÉVET, G.

    2001-11-01

    This paper presents a combination of vibroacoustic and psychoacoustic studies of sounds radiated by a vibrating structure. The calculated sound field is the sound pressure radiated by a baffled thin-plate structure immersed in a fluid, on the surface of which the acceleration is given. Various configurations are selected for the time and space functions of the acceleration variable, each configuration leading to a particular acoustic signal (a low-frequency tone complex in our case). These signals are then transformed into sound files, which are used as test signals in psychoacoustic experiments for assessing their perceptual attributes and quality. Two experiments were run. In the first one, the unpleasantness of a series of signals at different levels was measured by direct estimation and compared with their calculated loudness and sharpness using Zwicker's model. The same measurements were repeated with the signals set to the same maximum amplitude. In the second experiment, the pleasantness of another series of sounds at equal loudness was measured, as well as dissimilarity and preference on pairs of these sounds. An MDS analysis was run to extract auditory attributes that could account for the perceived differences between sounds and correlate with the estimated pleasantness. The results from the first experiment show that pleasantness is always highly (and negatively) correlated with loudness. The same holds for sharpness, when sounds are played at the same maximum amplitude. The second experiment shows that the perceptual attributes revealed by the MDS analysis are related to pitch and timbre, the latter being highly correlated with pleasantness. Overall, this study confirms the interest of extending vibroacoustic studies to a more complete “psychomechanical” investigation of the whole process of sound generation. It is suggested that such investigations may apply to product sound quality and to active or passive noise control, by providing

  17. Measuring leg movements during sleep using accelerometry: comparison with EMG and piezo-electric scored events.

    PubMed

    Terrill, Philip I; Leong, Matthew; Barton, Katrina; Freakley, Craig; Downey, Carl; Vanniekerk, Mark; Jorgensen, Greg; Douglas, James

    2013-01-01

    Periodic Limb Movements during Sleep (PLMS) can cause significant disturbance to sleep, resulting in daytime sleepiness and reduced quality of life. In conventional clinical practice, PLMS are measured using overnight electromyogram (EMG) of the tibialis anterior muscle, although historically they have also been measured using piezo-electric gauges placed over the muscle. However, PLMS counts (PLM index) do not correlate well with clinical symptomology. In this study, we propose that because EMG and piezo derived signals measure muscle activation rather than actual movement, they may count events with no appreciable movement of the limb and therefore no contribution to sleep disturbance. The aim of this study is thus to determine the percentage of clinically scored limb movements which are not associated with movement of the great toe measured using accelerometry. 9 participants were studied simultaneously with an overnight diagnostic polysomnogram (including EMG and piezo instrumentation of the right leg) and high temporal resolution accelerometry of the right great toe. Limb movements were scored, and peak acceleration during each scored movement was quantified. Across the participant population, 54.9% (range: 26.7-76.3) and 39.0% (range: 4.8-69.6) of limb movements scored using piezo and EMG instrumentation respectively, were not associated with toe movement measured with accelerometry. If sleep disturbance is the consequence of the limb movements, these results may explain why conventional piezo or EMG derived PLMI is poorly correlated with clinical symptomology.

  18. Surface electromyogram analysis of the direction of isometric torque generation by the first dorsal interosseous muscle

    NASA Astrophysics Data System (ADS)

    Zhou, Ping; Suresh, Nina L.; Zev Rymer, William

    2011-06-01

    The objective of this study was to determine whether a novel technique using high density surface electromyogram (EMG) recordings can be used to detect the directional dependence of muscle activity in a multifunctional muscle, the first dorsal interosseous (FDI). We used surface EMG recordings with a two-dimensional electrode array to search for inhomogeneous FDI activation patterns with changing torque direction at the metacarpophalangeal joint, the locus of action of the FDI muscle. The interference EMG distribution across the whole FDI muscle was recorded during isometric contraction at the same force magnitude in five different directions in the index finger abduction-flexion plane. The electrode array EMG activity was characterized by contour plots, interpolating the EMG amplitude between electrode sites. Across all subjects the amplitude of the flexion EMG was consistently lower than that of the abduction EMG at the given force. Pattern recognition methods were used to discriminate the isometric muscle contraction tasks with a linear discriminant analysis classifier, based on the extraction of two different feature sets of the surface EMG signal: the time domain (TD) feature set and a combination of autoregressive coefficients and the root mean square amplitude (AR+RMS) as a feature set. We found that high accuracies were obtained in the classification of different directions of the FDI muscle isometric contraction. With a monopolar electrode configuration, the average overall classification accuracy from nine subjects was 94.1 ± 2.3% for the TD feature set and 95.8 ± 1.5% for the AR+RMS feature set. Spatial filtering of the signal with bipolar electrode configuration improved the average overall classification accuracy to 96.7 ± 2.7% for the TD feature set and 98.1 ± 1.6% for the AR+RMS feature set. The distinct EMG contour plots and the high classification accuracies obtained from this study confirm distinct interference EMG pattern distributions as a

  19. Surface electromyogram analysis of the direction of isometric torque generation by the first dorsal interosseous muscle.

    PubMed

    Zhou, Ping; Suresh, Nina L; Rymer, William Zev

    2011-06-01

    The objective of this study was to determine whether a novel technique using high density surface electromyogram (EMG) recordings can be used to detect the directional dependence of muscle activity in a multifunctional muscle, the first dorsal interosseous (FDI). We used surface EMG recordings with a two-dimensional electrode array to search for inhomogeneous FDI activation patterns with changing torque direction at the metacarpophalangeal joint, the locus of action of the FDI muscle. The interference EMG distribution across the whole FDI muscle was recorded during isometric contraction at the same force magnitude in five different directions in the index finger abduction-flexion plane. The electrode array EMG activity was characterized by contour plots, interpolating the EMG amplitude between electrode sites. Across all subjects the amplitude of the flexion EMG was consistently lower than that of the abduction EMG at the given force. Pattern recognition methods were used to discriminate the isometric muscle contraction tasks with a linear discriminant analysis classifier, based on the extraction of two different feature sets of the surface EMG signal: the time domain (TD) feature set and a combination of autoregressive coefficients and the root mean square amplitude (AR+RMS) as a feature set. We found that high accuracies were obtained in the classification of different directions of the FDI muscle isometric contraction. With a monopolar electrode configuration, the average overall classification accuracy from nine subjects was 94.1 ± 2.3% for the TD feature set and 95.8 ± 1.5% for the AR+RMS feature set. Spatial filtering of the signal with bipolar electrode configuration improved the average overall classification accuracy to 96.7 ± 2.7% for the TD feature set and 98.1 ± 1.6% for the AR+RMS feature set. The distinct EMG contour plots and the high classification accuracies obtained from this study confirm distinct interference EMG pattern distributions as a

  20. Use of electromyographic and electrocardiographic signals to detect sleep bruxism episodes in a natural environment.

    PubMed

    Castroflorio, Tommaso; Mesin, Luca; Tartaglia, Gianluca Martino; Sforza, Chiarella; Farina, Dario

    2013-11-01

    Diagnosis of bruxism is difficult since not all contractions of masticatory muscles during sleeping are bruxism episodes. In this paper, we propose the use of both EMG and ECG signals for the detection of sleep bruxism. Data have been acquired from 21 healthy volunteers and 21 sleep bruxers. The masseter surface EMGs were detected with bipolar concentric electrodes and the ECG with monopolar electrodes located on the clavicular regions. Recordings were made at the subjects' homes during sleeping. Bruxism episodes were automatically detected as characterized by masseter EMG amplitude greater than 10% of the maximum and heart rate increasing by more than 25% with respect to baseline within 1 s before the increase in EMG amplitude above the 10% threshold. Furthermore, the subjects were classified as bruxers and nonbruxers by a neural network. The number of bruxism episodes per night was 24.6 ± 8.4 for bruxers and 4.3 ± 4.5 for controls ( P < 0.0001). The classification error between bruxers and nonbruxers was 1% which was substantially lower than when using EMG only for the classification. These results show that the proposed system, based on the joint analysis of EMG and ECG, can provide support for the clinical diagnosis of bruxism.

  1. Development of a learning module using a virtual environment to demonstrate EMG and telerobotic control principles.

    PubMed

    Patterson, P E

    2002-01-01

    A prototype system was developed for use as a teaching tool, allowing students to link EMG monitoring, data smoothing, robotic control, and neural network training within a rapid prototyping virtual environment (VE). The VE software allowed for the rapid development of scenarios and, when linked with EMG data input to a neural network, allowed the user to control an artificial world containing a virtual arm. Student teams then attempted to control the arm in the VE while performing the tasks by use of a neural network system they had specifically developed and trained using their own EMG signals. The results from their system were then translated into a form that enabled the control of a real robot. Students enjoyed the challenge and uniqueness of the module, and were enthusiastic about extending the concept to other areas of interest.

  2. Amplitude and bilateral coherency of facial and jaw-elevator EMG activity as an index of effort during a two-choice serial reaction task.

    PubMed

    Van Boxtel, A; Jessurun, M

    1993-11-01

    In earlier studies, positive but inconsistent relationships have been reported between mental effort and electromyogram (EMG) amplitude in task-irrelevant limb muscles. In this study, we explored whether facial EMG activity would provide more consistent results. Tonic EMG activity of six different facial and jaw-elevator muscles was bilaterally recorded during a two-choice serial reaction task with paced presentation of auditory or visual signals. In Experiment 1, task load (signal presentation rate) was kept constant for 20 min at the level of the subject's maximal capacity. In Experiment 2, task load was increased in a stepwise fashion over six successive 2-min periods from sub- to supramaximal capacity levels. EMG amplitude and coherency between momentary bilateral amplitude fluctuations were measured. In Experiment 1, EMG amplitude of frontalis, corrugator supercilii, and orbicularis oris inferior showed a strong gradual increase throughout the task period, whereas taks performance remained fairly stable. Orbicularis oculi, zygomaticus major, and temporalis EMG showed a much smaller increase or no increase. In Experiment 2, the first three muscles showed a fairly consistent increase in EMG amplitude with increasing task load. Orbicularis oculi and zygomaticus major were not active until task load became supramaximal. Effects of stimulus modality or laterality were not found in any experiment. These results are consistent with the notion that EMG amplitude of frontalis, corrugator, and orbicularis oris provides a sensitive index of the degree of exerted mental effort. PMID:8248451

  3. The Response of Hyperkinesis to EMG Biofeedback.

    ERIC Educational Resources Information Center

    Haight, Maryellen J.; And Others

    A study was conducted involving eight hyperkinetic males (11-15 years old) to determine if Ss receiving electromyography (EMG) biofeedback training would show a reduction in frontalis muscle tension, hyperactivity, and lability, and increases in self-esteem and visual and auditory attention span. Individual 45- and 30-minute relaxation exercises…

  4. Effect of hypnosis on masseter EMG recorded during the 'resting' and a slightly open jaw posture.

    PubMed

    Al-Enaizan, N; Davey, K J; Lyons, M F; Cadden, S W

    2015-11-01

    The aim of this experimental study was to determine whether minimal levels of electromyographic activity in the masseter muscle are altered when individuals are in a verified hypnotic state. Experiments were performed on 17 volunteer subjects (8 male, 9 female) all of whom gave informed consent. The subjects were dentate and had no symptoms of pain or masticatory dysfunction. Surface electromyograms (EMGs) were made from the masseter muscles and quantified by integration following full-wave rectification and averaging. The EMGs were obtained (i) with the mandible in 'resting' posture; (ii) with the mandible voluntarily lowered (but with the lips closed); (iii) during maximum voluntary clenching (MVC). The first two recordings were made before, during and after the subjects were in a hypnotic state. Susceptibility to hypnosis was assessed with Spiegel's eye-roll test, and the existence of the hypnotic state was verified by changes in ventilatory pattern. On average, EMG levels expressed as percentages of MVC were less: (i) when the jaw was deliberately lowered as opposed to being in the postural position: (ii) during hypnosis compared with during the pre- and post-hypnotic periods. However, analysis of variance followed by post hoc tests with multiple comparison corrections (Bonferroni) revealed that only the differences between the level during hypnosis and those before and after hypnosis were statistically significant (P < 0·05). As the level of masseter EMG when the mandible was in 'resting' posture was reduced by hypnosis, it appears that part of that EMG is of biological origin.

  5. EMG reactivity and oral habits among facial pain patients in a scheduled-waiting competitive task.

    PubMed

    Nicholson, R A; Lakatos, C A; Gramling, S E

    1999-12-01

    For individuals with temporomandibular disorder (TMD) it has been theorized that stressful events trigger oral habits (e.g., teeth grinding), thereby increasing masticatory muscle tension and subsequent pain. Recent research involving adjunctive behaviors found an increase in masseter surface EMG (sEMG) and oral habits when students with TMD symptomatology were placed on a fixed-time reinforcement schedule. The current study used a treatment-seeking community sample with TMD symptomatology in a competitive task designed to be a more naturalistic Fixed Time task. The experiment consisted of Adaptation, Free-Play, Scheduled-Play, and Recovery phases. During the Scheduled-Play phase participants played, and waited to play, an electronic poker game. Results indicated that masseter muscle tension in the Scheduled-Play phase was significantly higher (p < .001) than in any other phase. Moreover, during the Scheduled-Play phase masseter sEMG was higher (p < .001) when participants waited to play. Self-reported oral habits and overall affect were significantly higher (p's < .05) in the Free-Play and Scheduled-Play phases relative to Adaptation and Recovery. The observation that masseter sEMG was elevated during the Scheduled-Play phase relative to all other phases, and within the Scheduled-Play phase sEMG was highest while waiting, suggests that adjunctive oral habits may lead to TMD symptomatology.

  6. A Combined sEMG and Accelerometer System for Monitoring Functional Activity in Stroke

    PubMed Central

    Roy, Serge H.; Cheng, M. Samuel; Chang, Shey-Sheen; Moore, John; De Luca, Gianluca; Nawab, S. Hamid; De Luca, Carlo J.

    2010-01-01

    Remote monitoring of physical activity using body-worn sensors provides an alternative to assessment of functional independence by subjective, paper-based questionnaires. This study investigated the classification accuracy of a combined surface electromyographic (sEMG) and accelerometer (ACC) sensor system for monitoring activities of daily living in patients with stroke. sEMG and ACC data (eight channels each) were recorded from 10 hemiparetic patients while they carried out a sequence of 11 activities of daily living (identification tasks), and 10 activities used to evaluate misclassification errors (nonidentification tasks). The sEMG and ACC sensor data were analyzed using a multilayered neural network and an adaptive neuro-fuzzy inference system to identify the minimal sensor configuration needed to accurately classify the identification tasks, with a minimal number of misclassifications from the nonidentification tasks. The results demonstrated that the highest sensitivity and specificity for the identification tasks was achieved using a subset of four ACC sensors and adjacent sEMG sensors located on both upper arms, one forearm, and one thigh, respectively. This configuration resulted in a mean sensitivity of 95.0%, and a mean specificity of 99.7% for the identification tasks, and a mean misclassification error of <10% for the nonidentification tasks. The findings support the feasibility of a hybrid sEMG and ACC wearable sensor system for automatic recognition of motor tasks used to assess functional independence in patients with stroke. PMID:20051332

  7. Effect of hypnosis on masseter EMG recorded during the 'resting' and a slightly open jaw posture.

    PubMed

    Al-Enaizan, N; Davey, K J; Lyons, M F; Cadden, S W

    2015-11-01

    The aim of this experimental study was to determine whether minimal levels of electromyographic activity in the masseter muscle are altered when individuals are in a verified hypnotic state. Experiments were performed on 17 volunteer subjects (8 male, 9 female) all of whom gave informed consent. The subjects were dentate and had no symptoms of pain or masticatory dysfunction. Surface electromyograms (EMGs) were made from the masseter muscles and quantified by integration following full-wave rectification and averaging. The EMGs were obtained (i) with the mandible in 'resting' posture; (ii) with the mandible voluntarily lowered (but with the lips closed); (iii) during maximum voluntary clenching (MVC). The first two recordings were made before, during and after the subjects were in a hypnotic state. Susceptibility to hypnosis was assessed with Spiegel's eye-roll test, and the existence of the hypnotic state was verified by changes in ventilatory pattern. On average, EMG levels expressed as percentages of MVC were less: (i) when the jaw was deliberately lowered as opposed to being in the postural position: (ii) during hypnosis compared with during the pre- and post-hypnotic periods. However, analysis of variance followed by post hoc tests with multiple comparison corrections (Bonferroni) revealed that only the differences between the level during hypnosis and those before and after hypnosis were statistically significant (P < 0·05). As the level of masseter EMG when the mandible was in 'resting' posture was reduced by hypnosis, it appears that part of that EMG is of biological origin. PMID:26059538

  8. Evaluation of Novel EMG Biofeedback for Postural Correction During Computer Use.

    PubMed

    Gaffney, Brecca M; Maluf, Katrina S; Davidson, Bradley S

    2016-06-01

    Postural correction is an effective rehabilitation technique used to treat chronic neck and shoulder pain, and is aimed toward reducing the load on the surrounding muscles by adopting a neutral posture. The objective of this investigation was to evaluate the effectiveness of real-time high-density surface EMG (HDsEMG) biofeedback for postural correction during typing. Twenty healthy participants performed a typing task with two forms of postural feedback: (1) verbal postural coaching and (2) verbal postural coaching plus HDsEMG biofeedback. The interface used activity from two HDsEMG arrays placed over the trapezius designed to shift trapezius muscle activity inferiorly. The center of gravity across both arrays was used to quantify the spatial distribution of trapezius activity. Planar angles taken from upper extremity reflective markers quantified cervicoscapular posture. During the biofeedback condition, trapezius muscle activity was located 12.74 ± 3.73 mm more inferior, the scapula was 2.58 ± 1.18° more adducted and 0.23 ± 0.24° more depressed in comparison to verbal postural coaching alone. The results demonstrate the short-term effectiveness of a real-time HDsEMG biofeedback intervention to achieve postural correction, and may be more effective at creating an inferior shift in trapezius muscle activity in comparison to verbal postural coaching alone. PMID:26718205

  9. Variability in surface ECG morphology: signal or noise?

    NASA Technical Reports Server (NTRS)

    Smith, J. M.; Rosenbaum, D. S.; Cohen, R. J.

    1988-01-01

    Using data collected from canine models of acute myocardial ischemia, we investigated two issues of major relevance to electrocardiographic signal averaging: ECG epoch alignment, and the spectral characteristics of the beat-to-beat variability in ECG morphology. With initial digitization rates of 1 kHz, an iterative a posteriori matched filtering alignment scheme, and linear interpolation, we demonstrated that there is sufficient information in the body surface ECG to merit alignment to a precision of 0.1 msecs. Applying this technique to align QRS complexes and atrial pacing artifacts independently, we demonstrated that the conduction delay from atrial stimulus to ventricular activation may be so variable as to preclude using atrial pacing as an alignment mechanism, and that this variability in conduction time be modulated at the frequency of respiration and at a much lower frequency (0.02-0.03Hz). Using a multidimensional spectral technique, we investigated the beat-to-beat variability in ECG morphology, demonstrating that the frequency spectrum of ECG morphological variation reveals a readily discernable modulation at the frequency of respiration. In addition, this technique detects a subtle beat-to-beat alternation in surface ECG morphology which accompanies transient coronary artery occlusion. We conclude that physiologically important information may be stored in the variability in the surface electrocardiogram, and that this information is lost by conventional averaging techniques.

  10. Effects of viewing affective pictures on sEMG activity of masticatory and postural muscles.

    PubMed

    D'Attilio, Michele; Rodolfino, Daria; Saccucci, Matteo; Abate, Michele; Romani, Gian Luca; Festa, Felice; Merla, Arcangelo

    2013-06-01

    Recently there has been an upsurge of interest in the question to what extent the human motor control system is influenced by the emotional state of the actor. The aim of this study was to evaluate whether emotional inputs modify the activity of masticatory and postural muscles. Twenty healthy young adults viewed affective pictures, while surface electromyography (sEMG) of masticatory and postural muscles was recorded to investigate the coupling between emotional reactions and body muscular activity. One hundred and twenty pictures, chosen from the International Affective Picture System (IAPS), divided in two blocks of six sets, were presented to the subjects. sEMG data were statistically analyzed (RM ANOVA on Ranks). Root Mean Square (RMS) amplitudes, comparing the subsequent sets (Neutral, Unpleasant, Neutral, Pleasant) with the first and the last Baseline set, changed significantly only randomly. The results show that emotional inputs seems not influence the activity of masticatory and postural muscles, recorded by sEMG.

  11. Intention-based EMG control for powered exoskeletons.

    PubMed

    Lenzi, T; De Rossi, S M M; Vitiello, N; Carrozza, M C

    2012-08-01

    Electromyographical (EMG) signals have been frequently used to estimate human muscular torques. In the field of human-assistive robotics, these methods provide valuable information to provide effectively support to the user. However, their usability is strongly limited by the necessity of complex user-dependent and session-dependent calibration procedures, which confine their use to the laboratory environment. Nonetheless, an accurate estimate of muscle torque could be unnecessary to provide effective movement assistance to users. The natural ability of human central nervous system of adapting to external disturbances could compensate for a lower accuracy of the torque provided by the robot and maintain the movement accuracy unaltered, while the effort is reduced. In order to explore this possibility, in this paper we study the reaction of ten healthy subjects to the assistance provided through a proportional EMG control applied by an elbow powered exoskeleton. This system gives only a rough estimate of the user muscular torque but does not require any specific calibration. Experimental results clearly show that subjects adapt almost instantaneously to the assistance provided by the robot and can reduce their effort while keeping full control of the movement under different dynamic conditions (i.e., no alterations of movement accuracy are observed). PMID:22588573

  12. The Effectiveness of FES-Evoked EMG Potentials to Assess Muscle Force and Fatigue in Individuals with Spinal Cord Injury

    PubMed Central

    Ibitoye, Morufu Olusola; Estigoni, Eduardo H.; Hamzaid, Nur Azah; Wahab, Ahmad Khairi Abdul; Davis, Glen M.

    2014-01-01

    The evoked electromyographic signal (eEMG) potential is the standard index used to monitor both electrical changes within the motor unit during muscular activity and the electrical patterns during evoked contraction. However, technical and physiological limitations often preclude the acquisition and analysis of the signal especially during functional electrical stimulation (FES)-evoked contractions. Hence, an accurate quantification of the relationship between the eEMG potential and FES-evoked muscle response remains elusive and continues to attract the attention of researchers due to its potential application in the fields of biomechanics, muscle physiology, and rehabilitation science. We conducted a systematic review to examine the effectiveness of eEMG potentials to assess muscle force and fatigue, particularly as a biofeedback descriptor of FES-evoked contractions in individuals with spinal cord injury. At the outset, 2867 citations were identified and, finally, fifty-nine trials met the inclusion criteria. Four hypotheses were proposed and evaluated to inform this review. The results showed that eEMG is effective at quantifying muscle force and fatigue during isometric contraction, but may not be effective during dynamic contractions including cycling and stepping. Positive correlation of up to r = 0.90 (p < 0.05) between the decline in the peak-to-peak amplitude of the eEMG and the decline in the force output during fatiguing isometric contractions has been reported. In the available prediction models, the performance index of the eEMG signal to estimate the generated muscle force ranged from 3.8% to 34% for 18 s to 70 s ahead of the actual muscle force generation. The strength and inherent limitations of the eEMG signal to assess muscle force and fatigue were evident from our findings with implications in clinical management of spinal cord injury (SCI) population. PMID:25025551

  13. The effectiveness of FES-evoked EMG potentials to assess muscle force and fatigue in individuals with spinal cord injury.

    PubMed

    Ibitoye, Morufu Olusola; Estigoni, Eduardo H; Hamzaid, Nur Azah; Wahab, Ahmad Khairi Abdul; Davis, Glen M

    2014-07-14

    The evoked electromyographic signal (eEMG) potential is the standard index used to monitor both electrical changes within the motor unit during muscular activity and the electrical patterns during evoked contraction. However, technical and physiological limitations often preclude the acquisition and analysis of the signal especially during functional electrical stimulation (FES)-evoked contractions. Hence, an accurate quantification of the relationship between the eEMG potential and FES-evoked muscle response remains elusive and continues to attract the attention of researchers due to its potential application in the fields of biomechanics, muscle physiology, and rehabilitation science. We conducted a systematic review to examine the effectiveness of eEMG potentials to assess muscle force and fatigue, particularly as a biofeedback descriptor of FES-evoked contractions in individuals with spinal cord injury. At the outset, 2867 citations were identified and, finally, fifty-nine trials met the inclusion criteria. Four hypotheses were proposed and evaluated to inform this review. The results showed that eEMG is effective at quantifying muscle force and fatigue during isometric contraction, but may not be effective during dynamic contractions including cycling and stepping. Positive correlation of up to r = 0.90 (p < 0.05) between the decline in the peak-to-peak amplitude of the eEMG and the decline in the force output during fatiguing isometric contractions has been reported. In the available prediction models, the performance index of the eEMG signal to estimate the generated muscle force ranged from 3.8% to 34% for 18 s to 70 s ahead of the actual muscle force generation. The strength and inherent limitations of the eEMG signal to assess muscle force and fatigue were evident from our findings with implications in clinical management of spinal cord injury (SCI) population.

  14. Advances in targeting cell surface signalling molecules for immune modulation

    PubMed Central

    Yao, Sheng; Zhu, Yuwen; Chen, Lieping

    2013-01-01

    The past decade has witnessed a surge in the development of immunomodulatory approaches to combat a broad range of human diseases, including cancer, viral infections, autoimmunity and inflammation as well as in the prevention of transplant rejection. Immunomodulatory approaches mostly involve the use of monoclonal antibodies or recombinant fusion proteins that target cell surface signalling molecules on immune cells to drive immune responses towards the desired direction. Advances in our understanding of the human immune system, along with valuable lessons learned from the first generation of therapeutic biologics, are aiding the design of the next generation of immunomodulatory biologics with better therapeutic efficacy, minimized adverse effects and long-lasting clinical benefit. The recent encouraging results from antibodies targeting programmed cell death protein 1 (PD1) and B7 homolog 1 (B7H1; also known as PDL1) for the treatment of various advanced human cancers show that immunomodulatory therapy has come of age. PMID:23370250

  15. Agreement between clinical and portable EMG/ECG diagnosis of sleep bruxism.

    PubMed

    Castroflorio, T; Bargellini, A; Rossini, G; Cugliari, G; Deregibus, A; Manfredini, D

    2015-10-01

    The aim of this study was to compare clinical sleep bruxism (SB) diagnosis with an instrumental diagnosis obtained with a device providing electromyography/electrocardiography (EMG/ECG) recordings. Forty-five (N = 45) subjects (19 males and 26 females, mean age 28 ± 11 years) were selected among patients referring to the Gnathology Unit of the Dental School of the University of Torino. An expert clinician assessed the presence of SB based on the presence of one or more signs/symptoms (i.e., transient jaw muscle pain in the morning, muscle fatigue at awakening, presence of tooth wear, masseter hypertrophy). Furthermore, all participants underwent an instrumental recording at home with a portable device (Bruxoff; OT Bioelettronica, Torino, Italy) allowing a simultaneous recording of EMG signals from both the masseter muscles as well as heart frequency. Statistical procedures were performed with the software Statistical Package for the Social Science v. 20.0 (SPSS 20.0; IBM, Milan, Italy). Based on the EMG/ECG analysis, 26 subjects (11 males, 15 females, mean age 28 ± 10 years) were diagnosed as sleep bruxers, whilst 19 subjects (7 males, 12 females, mean age 30 ± 10 years) were diagnosed as non-bruxers. The correlation between the clinical and EMG/ECG SB diagnoses was low (ϕ value = 0.250), with a 62.2% agreement (28/45 subjects) between the two approaches (kappa = 0.248). Assuming instrumental EMG/ECG diagnosis as the standard of reference for definite SB diagnosis in this investigation, the false-positive and false-negative rates were unacceptable for all clinical signs/symptoms. In conclusion, findings from clinical assessment are not related with SB diagnosis performed with a portable EMG/ECG recorder.

  16. Use of surface electromyography to estimate neck muscle activity.

    PubMed

    Sommerich, C M; Joines, S M; Hermans, V; Moon, S D

    2000-12-01

    This paper reviews the literature concerning the use of surface electromyography (sEMG) for the study of the neck musculature in response to work and workplace design during light work and semi-static tasks. The paper also draws upon basic research and biomechanical modeling in order to provide methodological recommendations for the use of surface electromyography in this region of the body and to identify areas which require further investigation. The paper includes review and discussion of electrode site location, methods of normalization, data reliability, and factors that can affect sEMG signals from this region, including noise, physiologic artifact, stress, visual deficiencies, and pain. General guidance for maximum exertions with the neck musculature, for sEMG normalization or other purposes, is also included.

  17. Analysis and Simple Circuit Design of Double Differential EMG Active Electrode.

    PubMed

    Guerrero, Federico Nicolás; Spinelli, Enrique Mario; Haberman, Marcelo Alejandro

    2016-06-01

    In this paper we present an analysis of the voltage amplifier needed for double differential (DD) sEMG measurements and a novel, very simple circuit for implementing DD active electrodes. The three-input amplifier that standalone DD active electrodes require is inherently different from a differential amplifier, and general knowledge about its design is scarce in the literature. First, the figures of merit of the amplifier are defined through a decomposition of its input signal into three orthogonal modes. This analysis reveals a mode containing EMG crosstalk components that the DD electrode should reject. Then, the effect of finite input impedance is analyzed. Because there are three terminals, minimum bounds for interference rejection ratios due to electrode and input impedance unbalances with two degrees of freedom are obtained. Finally, a novel circuit design is presented, including only a quadruple operational amplifier and a few passive components. This design is nearly as simple as the branched electrode and much simpler than the three instrumentation amplifier design, while providing robust EMG crosstalk rejection and better input impedance using unity gain buffers for each electrode input. The interference rejection limits of this input stage are analyzed. An easily replicable implementation of the proposed circuit is described, together with a parameter design guideline to adjust it to specific needs. The electrode is compared with the established alternatives, and sample sEMG signals are obtained, acquired on different body locations with dry contacts, successfully rejecting interference sources. PMID:26841414

  18. Analysis and Simple Circuit Design of Double Differential EMG Active Electrode.

    PubMed

    Guerrero, Federico Nicolás; Spinelli, Enrique Mario; Haberman, Marcelo Alejandro

    2016-06-01

    In this paper we present an analysis of the voltage amplifier needed for double differential (DD) sEMG measurements and a novel, very simple circuit for implementing DD active electrodes. The three-input amplifier that standalone DD active electrodes require is inherently different from a differential amplifier, and general knowledge about its design is scarce in the literature. First, the figures of merit of the amplifier are defined through a decomposition of its input signal into three orthogonal modes. This analysis reveals a mode containing EMG crosstalk components that the DD electrode should reject. Then, the effect of finite input impedance is analyzed. Because there are three terminals, minimum bounds for interference rejection ratios due to electrode and input impedance unbalances with two degrees of freedom are obtained. Finally, a novel circuit design is presented, including only a quadruple operational amplifier and a few passive components. This design is nearly as simple as the branched electrode and much simpler than the three instrumentation amplifier design, while providing robust EMG crosstalk rejection and better input impedance using unity gain buffers for each electrode input. The interference rejection limits of this input stage are analyzed. An easily replicable implementation of the proposed circuit is described, together with a parameter design guideline to adjust it to specific needs. The electrode is compared with the established alternatives, and sample sEMG signals are obtained, acquired on different body locations with dry contacts, successfully rejecting interference sources.

  19. Comparison of electromyographic signals from monopolar current and potential amplifiers derived from a penniform muscle, the gastrocnemius medialis.

    PubMed

    von Tscharner, Vinzenz; Maurer, Christian; Ruf, Florian; Nigg, Benno M

    2013-10-01

    Electromyograms (EMGs) are measured by bipolar surface electrodes that quantify potential differences. Bipolar potentials over penniform muscles may be associated with errors. Our assumption was that muscle activity can be quantified more reliably and with a higher spatial resolution using current measurements. The purpose of this work is: (a) to introduce the concept of current measurements to detect muscle activity, (b) to show the coherences observed over a segment of a typical penniform muscle, the gastrocnemius medialis where one would expect a synchronicity of the activation, and (c) to show the amount of mixing that is caused by the finite inter electrode resistance. A current amplifier was developed. EMGs were recorded at 40% of maximum voluntary contraction during isometric contractions of the gastrocnemius medialis. EMGs of twelve persons were recorded with an array of four peripheral and one central electrode. Monopolar EMGs were recorded for "all-potential", "center at current" and "all-current" conditions. Coherence revealed the similarity of signals recorded from neighboring electrodes. Coherence was high for the "all-potential", significant for the "current at center" condition and disappeared in the "all-current" condition. It was concluded that EMG array recordings strongly depends on the measurement configuration. The proposed current amplifier significantly improves spatial resolution of EMG array recordings because the inter-electrode cross talk is reduced.

  20. Curved Microneedle Array-Based sEMG Electrode for Robust Long-Term Measurements and High Selectivity.

    PubMed

    Kim, Minjae; Kim, Taewan; Kim, Dong Sung; Chung, Wan Kyun

    2015-01-01

    Surface electromyography is widely used in many fields to infer human intention. However, conventional electrodes are not appropriate for long-term measurements and are easily influenced by the environment, so the range of applications of sEMG is limited. In this paper, we propose a flexible band-integrated, curved microneedle array electrode for robust long-term measurements, high selectivity, and easy applicability. Signal quality, in terms of long-term usability and sensitivity to perspiration, was investigated. Its motion-discriminating performance was also evaluated. The results show that the proposed electrode is robust to perspiration and can maintain a high-quality measuring ability for over 8 h. The proposed electrode also has high selectivity for motion compared with a commercial wet electrode and dry electrode. PMID:26153773

  1. Curved Microneedle Array-Based sEMG Electrode for Robust Long-Term Measurements and High Selectivity

    PubMed Central

    Kim, Minjae; Kim, Taewan; Kim, Dong Sung; Chung, Wan Kyun

    2015-01-01

    Surface electromyography is widely used in many fields to infer human intention. However, conventional electrodes are not appropriate for long-term measurements and are easily influenced by the environment, so the range of applications of sEMG is limited. In this paper, we propose a flexible band-integrated, curved microneedle array electrode for robust long-term measurements, high selectivity, and easy applicability. Signal quality, in terms of long-term usability and sensitivity to perspiration, was investigated. Its motion-discriminating performance was also evaluated. The results show that the proposed electrode is robust to perspiration and can maintain a high-quality measuring ability for over 8 h. The proposed electrode also has high selectivity for motion compared with a commercial wet electrode and dry electrode. PMID:26153773

  2. Curved Microneedle Array-Based sEMG Electrode for Robust Long-Term Measurements and High Selectivity.

    PubMed

    Kim, Minjae; Kim, Taewan; Kim, Dong Sung; Chung, Wan Kyun

    2015-07-06

    Surface electromyography is widely used in many fields to infer human intention. However, conventional electrodes are not appropriate for long-term measurements and are easily influenced by the environment, so the range of applications of sEMG is limited. In this paper, we propose a flexible band-integrated, curved microneedle array electrode for robust long-term measurements, high selectivity, and easy applicability. Signal quality, in terms of long-term usability and sensitivity to perspiration, was investigated. Its motion-discriminating performance was also evaluated. The results show that the proposed electrode is robust to perspiration and can maintain a high-quality measuring ability for over 8 h. The proposed electrode also has high selectivity for motion compared with a commercial wet electrode and dry electrode.

  3. Alternative methods of normalising EMG during running.

    PubMed

    Albertus-Kajee, Yumna; Tucker, Ross; Derman, Wayne; Lamberts, Robert P; Lambert, Michael I

    2011-08-01

    We evaluated possible methods of normalising EMG measured during running. MVC, Sprint and 70% Peak Running Speed methods were evaluated and their repeatability, reliability and sensitivity to incremental running speed were compared. Twelve runners performed the same experimental protocol on three separate occasions. Each day, subjects firstly performed MVCs, followed by a 20 m maximal sprint (with a 20-30 m run-up). Following this, they performed the peak running speed (PRS) test until exhaustion. After which they ran at 70% of PRS for 5 laps. Results indicated that normalising EMG data to MVC and Sprint methods are more repeatable for VM, BF, MG and RF, VL, LG, respectively, with the average ICC>0.80. The 70% PRS demonstrated poor to fair levels of repeatability ranging between ICC 0.27 and 0.70. Whereas the 70% PRS method had the least intra-subject variability and the greatest sensitivity to increasing running speeds. More specifically, demonstrating significant changes in muscle activity in VM with increasing running speed while MVC and Sprint methods were unable to detect these changes. The dynamic methods were the most appropriate for EMG normalisation showing repeatability, better intra-subject reliability and better sensitivity during running over different days and for once-off measurements. PMID:21531148

  4. High-density EMG E-textile systems for the control of active prostheses.

    PubMed

    Farina, Dario; Lorrain, Thomas; Negro, Francesco; Jiang, Ning

    2010-01-01

    Myoelectric control of active prostheses requires electrode systems that are easy to apply for daily repositioning of the electrodes by the user. In this study we propose the use of Smart Fabric and Interactive Textile (SFIT) systems as an alternative solution for recording high-density EMG signals for myoelectric control. A sleeve covering the upper and lower arm, which contains 100 electrodes arranged in four grids of 5 × 5 electrodes, was used to record EMG signals in 3 subjects during the execution of 9 tasks of the wrist and hand. The signals were analyzed by extracting wavelet coefficients which were classified with linear discriminant analysis. The average classification accuracy for the nine tasks was 89.1 ± 1.9 %. These results show that SFIT systems can be used as an effective way for muscle-machine interfacing. PMID:21096838

  5. Using evoked EMG as a synthetic force sensor of isometric electrically stimulated muscle.

    PubMed

    Erfanian, A; Chizeck, H J; Hashemi, R M

    1998-02-01

    A method for the estimation of the force generated by electrically stimulated muscle during isometric contraction is developed here. It is based upon measurements of the evoked electromyogram (EMG) [EEMG] signal. Muscle stimulation is provided to the quadriceps muscle of a paralyzed human subject using percutaneous intramuscular electrodes, and EEMG signals are collected using surface electrodes. Through the use of novel signal acquisition and processing techniques, as well as a mathematical model that reflects both the excitation and activation phenomena involved in isometric muscle force generation, accurate prediction of stimulated muscle forces is obtained for large time horizons. This approach yields synthetic muscle force estimates for both unfatigued and fatigued states of the stimulated muscle. In addition, a method is developed that accomplishes automatic recalibration of the model to account for day-to-day changes in pickup electrode mounting as well as other factors contributing to EEMG gain variations. It is demonstrated that the use of the measured EEMG as the input to a predictive model of muscle torque generation is superior to the use of the electrical stimulation signal as the model input. This is because the measured EEMG signal captures all of the neural excitation, whereas stimulation-to-torque models only reflect that portion of the neural excitation that results directly from stimulation. The time-varying properties of the excitation process cannot be captured by existing stimulation-to-torque models, but they are tracked by the EEMG-to-torque models that are developed here. This work represents a promising approach to the real-time estimation of stimulated muscle force in functional neuromuscular stimulation applications.

  6. Intramuscular pressure: A better tool than EMG to optimize exercise for long-duration space flight

    NASA Technical Reports Server (NTRS)

    Hargens, A. R.; Ballard, R. E.; Aratow, M.; Crenshaw, A.; Styf, J.; Kahan, N.; Watenpaugh, D. E.

    1992-01-01

    A serious problem experienced by astronauts during long-duration space flight is muscle atrophy. In order to develop countermeasures for this problem, a simple method for monitoring in vivo function of specific muscles is needed. Previous studies document that both intramuscular pressure (IMP) and electromyography (EMG) provide quantitative indices of muscle contraction force during isometric exercise. However, at present there are no data available concerning the usefulness of IMP versus EMG during dynamic exercise. Methods: IMP (Myopress catheter) and surface EMG activity were measured continuously and simultaneously in the tibalis anterior (TA) and soleus (SOL) muscles of 9 normal male volunteers (28-54 years). These parameters were recorded during both concentric and eccentric exercises which consisted of plantarflexon and dorsiflexon of the ankle joint. A Lido Active Isokinetic Dynamometer concurrently recorded ankle joint torque and position. Results: Intramuscular pressure correlated linearly with contraction force for both SOL (r exp 2 = 0.037) and TA (R exp 2 = 0.716 and r exp 2 = 0.802, respectively). During eccentric exercises, SOL and TA IMP also correlated linearly with contraction force (r(exp 2) = 0.883 and r(exp 2) = 0.904 respectively), but SOL and TA EMG correlated poorly with force (r(exp 2) = 0.489 and r(exp 2) = 0.702 respectively). Conclusion: IMP measurement provides a better index of muscle contraction force than EMG during concentric and eccentric exercise. IMP reflects intrinsic mechanical properties of individual muscles, such as length tension relationships. Although invasive, IMP provides a more powerful tool and EMG for developing exercise hardware and protocols for astronauts exposed to long-duration space flight.

  7. EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model

    PubMed Central

    2014-01-01

    Background This paper describes the “EMG Driven Force Estimator (EMGD-FE)”, a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results. Results An example of the application’s functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown. Conclusions The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues. PMID:24708668

  8. Analysis of intramuscular electromyogram signals.

    PubMed

    Merletti, Roberto; Farina, Dario

    2009-01-28

    Intramuscular electromyographic (EMG) signals are detected with needles or wires inserted into muscles. With respect to non-invasive techniques, intramuscular electromyography has high selectivity for individual motor unit action potentials and is thus used to measure motor unit activity. Decomposition of intramuscular signals into individual motor unit action potentials consists in detection and classification, usually followed by separation of superimposed action potentials. Although intramuscular EMG signal decomposition is the primary tool for physiological investigations of motor unit properties, it is rarely applied in clinical routine, because of the need for human interaction and the difficulty in interpreting the quantitative data provided by EMG signal decomposition to support clinical decisions. The current clinical use of intramuscular EMG signals relates to the diagnosis of myopathies, of diseases of the alpha-motor neuron and of the neuromuscular junction through the analysis of the interference signal or of the shape of some motor unit action potentials, usually without a full decomposition of the signal.

  9. Autogenic EMG-controlled functional electrical stimulation for ankle dorsiflexion control.

    PubMed

    Yeom, Hojun; Chang, Young-Hui

    2010-10-30

    Our objectives were to develop and test a new system for the potential for stable, real-time cancellation of residual stimulation artefacts (RSA) using surface electrode autogenic electromyography-controlled functional electrical stimulator (aEMGcFES). This type of closed-loop FES could be used to provide more natural, continuous control of lower extremity paretic muscles. We built upon work that has been done in the field of FES with one major technological innovation, an adaptive Gram-Schmidt filtering algorithm, which allowed us to digitally cancel RSA in real-time. This filtering algorithm resulted in a stable real-time estimation of the volitional intent of the stimulated muscle, which then acted as the direct signal for continuously controlling homonymous muscle stimulation. As a first step toward clinical application, we tested the viability of our aEMGcFES system to continuously control ankle dorsiflexion in a healthy subject. Our results indicate positively that an aEMGcFES device with adaptive filtering can respond proportionally to voluntary EMG and activate forceful movements to assist dorsiflexion during controlled isometric activation at the ankle. We also verified that normal ankle joint range of movement could be maintained while using the aEMGcFES system. We suggest that real-time cancellation of both primary and RSA is possible with surface electrode aEMGcFES in healthy subjects and shows promising potential for future clinical application to gait pathologies such as drop foot related to hemiparetic stroke.

  10. Autogenic EMG-Controlled Functional Electrical Stimulation for Ankle Dorsiflexion Control

    PubMed Central

    Yeom, Hojun; Chang, Young-Hui

    2010-01-01

    Our objectives were to develop and test a new system for the potential for stable, real-time cancellation of residual stimulation artefacts (RSA) using surface electrode autogenic electromyography-controlled functional electrical stimulator (aEMGcFES). This type of closed-loop FES could be used to provide more natural, continuous control of lower extremity paretic muscles. We built upon work that has been done in the field of FES with one major technological innovation, an adaptive Gram-Schmidt filtering algorithm, which allowed us to digitally cancel RSA in real-time. This filtering algorithm resulted in a stable real-time estimation of the volitional intent of the stimulated muscle, which then acted as the direct signal for continuously controlling homonymous muscle stimulation. As a first step toward clinical application, we tested the viability of our aEMGcFES system to continuously control ankle dorsiflexion in a healthy subject. Our results indicate positively that an aEMGcFES device with adaptive filtering can respond proportionally to voluntary EMG and activate forceful movements to assist dorsiflexion during controlled isometric activation at the ankle. We also verified that normal ankle joint range of movement could be maintained while using the aEMGcFES system. We suggest that real-time cancellation of both primary and RSA is possible with surface electrode aEMGcFES in healthy subjects and shows promising potential for future clinical application to gait pathologies such as drop foot related to hemiparetic stroke. PMID:20713086

  11. Time-frequency and principal-component methods for the analysis of EMGs recorded during a mildly fatiguing exercise on a cycle ergometer.

    PubMed

    von Tscharner, Vinzenz

    2002-12-01

    Electromyographic signals contain the information on muscle activity and have to be frequently averaged, compared, classified or details need to be extracted. A time-frequency analysis, based on wavelets, was previously presented. The analysis transformed an EMG signal into an EMG-intensity-pattern showing the intensities at any point in time for the frequencies filtered out by the wavelets. The purpose of the present study was:to define and apply a new EMG-pattern-space for the analysis of EMG-intensity-patterns; and to determine the variation of EMG-intensity-patterns while getting mildly fatigued by cycling on a cycle-ergometer. The coordinates spanning the pattern space were principal components of the measured EMG-intensity-patterns. A point in pattern-space thus represented an EMG-intensity-pattern. Fatigue resulted in points moving along a line in pattern space. The line was characterized by an intercept at time 0 and a slope. Thus mild fatigue caused a shift from an initial intensity-pattern representing the intercept to a final intensity-pattern adding gradually larger amounts of the pattern representing the slope. The intensity-pattern of the slope revealed the physiologically important individual strategies for coping with mild fatigue. Changes were observed at different times and at different frequencies during the cycling movement.

  12. Real-time simultaneous and proportional myoelectric control using intramuscular EMG

    NASA Astrophysics Data System (ADS)

    Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

    2014-12-01

    Objective. Myoelectric prostheses use electromyographic (EMG) signals to control movement of prosthetic joints. Clinically available myoelectric control strategies do not allow simultaneous movement of multiple degrees of freedom (DOFs); however, the use of implantable devices that record intramuscular EMG signals could overcome this constraint. The objective of this study was to evaluate the real-time simultaneous control of three DOFs (wrist rotation, wrist flexion/extension, and hand open/close) using intramuscular EMG. Approach. We evaluated task performance of five able-bodied subjects in a virtual environment using two control strategies with fine-wire EMG: (i) parallel dual-site differential control, which enabled simultaneous control of three DOFs and (ii) pattern recognition control, which required sequential control of DOFs. Main results. Over the course of the experiment, subjects using parallel dual-site control demonstrated increased use of simultaneous control and improved performance in a Fitts’ Law test. By the end of the experiment, performance using parallel dual-site control was significantly better (up to a 25% increase in throughput) than when using sequential pattern recognition control for tasks requiring multiple DOFs. The learning trends with parallel dual-site control suggested that further improvements in performance metrics were possible. Subjects occasionally experienced difficulty in performing isolated single-DOF movements with parallel dual-site control but were able to accomplish related Fitts’ Law tasks with high levels of path efficiency. Significance. These results suggest that intramuscular EMG, used in a parallel dual-site configuration, can provide simultaneous control of a multi-DOF prosthetic wrist and hand and may outperform current methods that enforce sequential control.

  13. Real-time simultaneous and proportional myoelectric control using intramuscular EMG

    PubMed Central

    Kuiken, Todd A; Hargrove, Levi J

    2014-01-01

    Objective Myoelectric prostheses use electromyographic (EMG) signals to control movement of prosthetic joints. Clinically available myoelectric control strategies do not allow simultaneous movement of multiple degrees of freedom (DOFs); however, the use of implantable devices that record intramuscular EMG signals could overcome this constraint. The objective of this study was to evaluate the real-time simultaneous control of three DOFs (wrist rotation, wrist flexion/extension, and hand open/close) using intramuscular EMG. Approach We evaluated task performance of five able-bodied subjects in a virtual environment using two control strategies with fine-wire EMG: (i) parallel dual-site differential control, which enabled simultaneous control of three DOFs and (ii) pattern recognition control, which required sequential control of DOFs. Main Results Over the course of the experiment, subjects using parallel dual-site control demonstrated increased use of simultaneous control and improved performance in a Fitts' Law test. By the end of the experiment, performance using parallel dual-site control was significantly better (up to a 25% increase in throughput) than when using sequential pattern recognition control for tasks requiring multiple DOFs. The learning trends with parallel dual-site control suggested that further improvements in performance metrics were possible. Subjects occasionally experienced difficulty in performing isolated single-DOF movements with parallel dual-site control but were able to accomplish related Fitts' Law tasks with high levels of path efficiency. Significance These results suggest that intramuscular EMG, used in a parallel dual-site configuration, can provide simultaneous control of a multi-DOF prosthetic wrist and hand and may outperform current methods that enforce sequential control. PMID:25394366

  14. Classification of finger movements for the dexterous hand prosthesis control with surface electromyography.

    PubMed

    Al-Timemy, Ali H; Bugmann, Guido; Escudero, Javier; Outram, Nicholas

    2013-05-01

    A method for the classification of finger movements for dexterous control of prosthetic hands is proposed. Previous research was mainly devoted to identify hand movements as these actions generate strong electromyography (EMG) signals recorded from the forearm. In contrast, in this paper, we assess the use of multichannel surface electromyography (sEMG) to classify individual and combined finger movements for dexterous prosthetic control. sEMG channels were recorded from ten intact-limbed and six below-elbow amputee persons. Offline processing was used to evaluate the classification performance. The results show that high classification accuracies can be achieved with a processing chain consisting of time domain-autoregression feature extraction, orthogonal fuzzy neighborhood discriminant analysis for feature reduction, and linear discriminant analysis for classification. We show that finger and thumb movements can be decoded accurately with high accuracy with latencies as short as 200 ms. Thumb abduction was decoded successfully with high accuracy for six amputee persons for the first time. We also found that subsets of six EMG channels provide accuracy values similar to those computed with the full set of EMG channels (98% accuracy over ten intact-limbed subjects for the classification of 15 classes of different finger movements and 90% accuracy over six amputee persons for the classification of 12 classes of individual finger movements). These accuracy values are higher than previous studies, whereas we typically employed half the number of EMG channels per identified movement.

  15. Frenulectomy of the tongue and the influence of rehabilitation exercises on the sEMG activity of masticatory muscles.

    PubMed

    Tecco, Simona; Baldini, Aberto; Mummolo, Stefano; Marchetti, Enrico; Giuca, Maria Rita; Marzo, Giuseppe; Gherlone, Enrico Felice

    2015-08-01

    This study aimed to assess by surface electromyography (sEMG) the changes in sub-mental, orbicularis oris, and masticatory muscle activity after a lingual frenulectomy. Rehabilitation exercises in subjects with ankyloglossia, characterized by Class I malocclusion, were assessed as well. A total of 24 subjects were selected. Thirteen subjects (mean age 7±2.5years) with Class I malocclusion and ankyloglossia were treated with lingual frenulectomy and rehabilitation exercises, while 11 subjects (mean age 7±0.8years) with normal occlusion and normal lingual frenulum were used as controls. The inclusion criteria for both groups were the presence of mixed dentition and no previous orthodontic treatment. The sEMG recordings were taken at the time of the first visit (T0), and after 1 (T1) and 6months (T2) for the treated group. Recordings were taken at the same time for the control group. Due to the noise inherent with the sEMG recording, special attention was paid to obtain reproducible and standardized recordings. The tested muscles were the masseter, anterior temporalis, upper and lower orbicularis oris, and sub-mental muscles. The sEMG recordings were performed at rest, while kissing, swallowing, opening the mouth, clenching the teeth and during protrusion of the mandible. These recordings were made by placing electrodes in the area of muscle contraction. At T0, the treated group showed different sEMG activity of the muscles with respect to the control group, with significant differences at rest and during some test tasks (p<0.05). In the treated group, an increase in sEMG potentials was observed for the masseter muscle, from T0 to T2, during maximal voluntary clenching. During swallowing and kissing, the masseter and sub-mental muscles showed a significant increase in their sEMG potentials from T0 to T2. During the protrusion of the mandible, the masseter and anterior temporalis significantly decreased their sEMG activity, while the sub-mental area increased

  16. Discrimination of EMG and acceleration measurements between patients with Parkinson's disease and healthy persons.

    PubMed

    Rissanen, Saara M; Kankaanpaa, Markku; Tarvainen, Mika P; Meigal, Alexander; Nuutinen, Juho; Jakala, Pekka; Airaksinen, Olavi; Karjalainen, Pasi A

    2010-01-01

    In this paper, we examine the potential of electromyographic (EMG) and acceleration measurements in discriminating patients with Parkinson's disease (PD) from healthy persons. Two types of muscle contractions are examined: static contractions of biceps brachii muscles and elbow extension movements. Twelve features are extracted from static and ten features from extension measurements. These features describe signal morphology and nonlinear characteristics, power spreading in EMG wavelet scalograms and spectral coherence. Principal component approach is applied separately for static and extension trial to reduce the number of features before discrimination. The discrimination between subjects is done in a two-dimensional space by applying cluster analysis to the best discriminating principal components. The discrimination power of the used method was estimated with EMG and acceleration data measured from 56 patients with PD and 59 healthy controls. In the cluster analysis, three clusters were formed: one cluster with most (85%) of the healthy persons and two clusters with 80% of patients. Patients were divided into two clusters based on their type of motor disability (problems during movement and/or static contraction). Discrimination results show that EMG and acceleration measurements are potential for discriminating patients with PD from healthy persons. Furthermore, they have potential in the objective clinical assessment of PD. PMID:21096652

  17. Predicting Blood Lactate Concentration and Oxygen Uptake from sEMG Data during Fatiguing Cycling Exercise.

    PubMed

    Ražanskas, Petras; Verikas, Antanas; Olsson, Charlotte; Viberg, Per-Arne

    2015-01-01

    This article presents a study of the relationship between electromyographic (EMG) signals from vastus lateralis, rectus femoris, biceps femoris and semitendinosus muscles, collected during fatiguing cycling exercises, and other physiological measurements, such as blood lactate concentration and oxygen consumption. In contrast to the usual practice of picking one particular characteristic of the signal, e.g., the median or mean frequency, multiple variables were used to obtain a thorough characterization of EMG signals in the spectral domain. Based on these variables, linear and non-linear (random forest) models were built to predict blood lactate concentration and oxygen consumption. The results showed that mean and median frequencies are sub-optimal choices for predicting these physiological quantities in dynamic exercises, as they did not exhibit significant changes over the course of our protocol and only weakly correlated with blood lactate concentration or oxygen uptake. Instead, the root mean square of the original signal and backward difference, as well as parameters describing the tails of the EMG power distribution were the most important variables for these models. Coefficients of determination ranging from R(2) = 0:77 to R(2) = 0:98 (for blood lactate) and from R(2) = 0:81 to R(2) = 0:97 (for oxygen uptake) were obtained when using random forest regressors. PMID:26295396

  18. Predicting Blood Lactate Concentration and Oxygen Uptake from sEMG Data during Fatiguing Cycling Exercise

    PubMed Central

    Ražanskas, Petras; Verikas, Antanas; Olsson, Charlotte; Viberg, Per-Arne

    2015-01-01

    This article presents a study of the relationship between electromyographic (EMG) signals from vastus lateralis, rectus femoris, biceps femoris and semitendinosus muscles, collected during fatiguing cycling exercises, and other physiological measurements, such as blood lactate concentration and oxygen consumption. In contrast to the usual practice of picking one particular characteristic of the signal, e.g., the median or mean frequency, multiple variables were used to obtain a thorough characterization of EMG signals in the spectral domain. Based on these variables, linear and non-linear (random forest) models were built to predict blood lactate concentration and oxygen consumption. The results showed that mean and median frequencies are sub-optimal choices for predicting these physiological quantities in dynamic exercises, as they did not exhibit significant changes over the course of our protocol and only weakly correlated with blood lactate concentration or oxygen uptake. Instead, the root mean square of the original signal and backward difference, as well as parameters describing the tails of the EMG power distribution were the most important variables for these models. Coefficients of determination ranging from R2=0.77 to R2=0.98 (for blood lactate) and from R2=0.81 to R2=0.97 (for oxygen uptake) were obtained when using random forest regressors. PMID:26295396

  19. User adaptation in long-term, open-loop myoelectric training: implications for EMG pattern recognition in prosthesis control

    NASA Astrophysics Data System (ADS)

    He, Jiayuan; Zhang, Dingguo; Jiang, Ning; Sheng, Xinjun; Farina, Dario; Zhu, Xiangyang

    2015-08-01

    Objective. Recent studies have reported that the classification performance of electromyographic (EMG) signals degrades over time without proper classification retraining. This problem is relevant for the applications of EMG pattern recognition in the control of active prostheses. Approach. In this study we investigated the changes in EMG classification performance over 11 consecutive days in eight able-bodied subjects and two amputees. Main results. It was observed that, when the classifier was trained on data from one day and tested on data from the following day, the classification error decreased exponentially but plateaued after four days for able-bodied subjects and six to nine days for amputees. The between-day performance became gradually closer to the corresponding within-day performance. Significance. These results indicate that the relative changes in EMG signal features over time become progressively smaller when the number of days during which the subjects perform the pre-defined motions are increased. The performance of the motor tasks is thus more consistent over time, resulting in more repeatable EMG patterns, even if the subjects do not have any external feedback on their performance. The learning curves for both able-bodied subjects and subjects with limb deficiencies could be modeled as an exponential function. These results provide important insights into the user adaptation characteristics during practical long-term myoelectric control applications, with implications for the design of an adaptive pattern recognition system.

  20. Intra-Individual Variability of Surface Electromyography in Front Crawl Swimming.

    PubMed

    Martens, Jonas; Daly, Daniel; Deschamps, Kevin; Fernandes, Ricardo Jorge Pinto; Staes, Filip

    2015-01-01

    The variability of electromyographic (EMG) recordings between and within participants is a complex problem, rarely studied in swimming. The importance of signal normalization has long been recognized, but the method used might influence variability. The aims of this study were to: (i) assess the intra-individual variability of the EMG signal in highly skilled front crawl swimmers, (ii) determine the influence of two methods of both amplitude and time normalization of the EMG signal on intra-individual variability and of time normalization on muscle activity level and (iii) describe the muscle activity, normalized using MVIC, in relation to upper limb crawl stroke movements. Muscle activity of rectus abdominis and deltoideus medialis was recorded using wireless surface EMG in 15 adult male competitive swimmers during three trials of 12.5 m front crawl at maximal speed without breathing. Two full upper limb cycles were analyzed from each of the swimming trials, resulting in six full cycles used for the intra-individual variability assessment, quantified with the coefficient of variation (CV), coefficient of quartile variation (CQV) and the variance ratio (VR). The results of this study support previous findings on EMG patterns of deltoideus medialis and rectus abdominis as prime mover during the recovery (45% activity relative to MVIC), and stabilizer of the trunk during the pull (14.5% activity) respectively. The intra-individual variability was lower (VR of 0.34-0.47) when compared to other cyclic movements. No meaningful differences were found between variability measures CV or VR when applying either of the amplitude or the time normalization methods. In addition to reporting the mean amplitude and standard deviation, future EMG studies in swimming should also report the intra-individual variability, preferably using VR as it is independent of peak amplitude, provides a good measure of repeatability and is insensitive to mean EMG amplitude and the degree of

  1. Intra-Individual Variability of Surface Electromyography in Front Crawl Swimming.

    PubMed

    Martens, Jonas; Daly, Daniel; Deschamps, Kevin; Fernandes, Ricardo Jorge Pinto; Staes, Filip

    2015-01-01

    The variability of electromyographic (EMG) recordings between and within participants is a complex problem, rarely studied in swimming. The importance of signal normalization has long been recognized, but the method used might influence variability. The aims of this study were to: (i) assess the intra-individual variability of the EMG signal in highly skilled front crawl swimmers, (ii) determine the influence of two methods of both amplitude and time normalization of the EMG signal on intra-individual variability and of time normalization on muscle activity level and (iii) describe the muscle activity, normalized using MVIC, in relation to upper limb crawl stroke movements. Muscle activity of rectus abdominis and deltoideus medialis was recorded using wireless surface EMG in 15 adult male competitive swimmers during three trials of 12.5 m front crawl at maximal speed without breathing. Two full upper limb cycles were analyzed from each of the swimming trials, resulting in six full cycles used for the intra-individual variability assessment, quantified with the coefficient of variation (CV), coefficient of quartile variation (CQV) and the variance ratio (VR). The results of this study support previous findings on EMG patterns of deltoideus medialis and rectus abdominis as prime mover during the recovery (45% activity relative to MVIC), and stabilizer of the trunk during the pull (14.5% activity) respectively. The intra-individual variability was lower (VR of 0.34-0.47) when compared to other cyclic movements. No meaningful differences were found between variability measures CV or VR when applying either of the amplitude or the time normalization methods. In addition to reporting the mean amplitude and standard deviation, future EMG studies in swimming should also report the intra-individual variability, preferably using VR as it is independent of peak amplitude, provides a good measure of repeatability and is insensitive to mean EMG amplitude and the degree of

  2. Intra-Individual Variability of Surface Electromyography in Front Crawl Swimming

    PubMed Central

    Martens, Jonas; Daly, Daniel; Deschamps, Kevin; Fernandes, Ricardo Jorge Pinto; Staes, Filip

    2015-01-01

    The variability of electromyographic (EMG) recordings between and within participants is a complex problem, rarely studied in swimming. The importance of signal normalization has long been recognized, but the method used might influence variability. The aims of this study were to: (i) assess the intra-individual variability of the EMG signal in highly skilled front crawl swimmers, (ii) determine the influence of two methods of both amplitude and time normalization of the EMG signal on intra-individual variability and of time normalization on muscle activity level and (iii) describe the muscle activity, normalized using MVIC, in relation to upper limb crawl stroke movements. Muscle activity of rectus abdominis and deltoideus medialis was recorded using wireless surface EMG in 15 adult male competitive swimmers during three trials of 12.5 m front crawl at maximal speed without breathing. Two full upper limb cycles were analyzed from each of the swimming trials, resulting in six full cycles used for the intra-individual variability assessment, quantified with the coefficient of variation (CV), coefficient of quartile variation (CQV) and the variance ratio (VR). The results of this study support previous findings on EMG patterns of deltoideus medialis and rectus abdominis as prime mover during the recovery (45% activity relative to MVIC), and stabilizer of the trunk during the pull (14.5% activity) respectively. The intra-individual variability was lower (VR of 0.34–0.47) when compared to other cyclic movements. No meaningful differences were found between variability measures CV or VR when applying either of the amplitude or the time normalization methods. In addition to reporting the mean amplitude and standard deviation, future EMG studies in swimming should also report the intra-individual variability, preferably using VR as it is independent of peak amplitude, provides a good measure of repeatability and is insensitive to mean EMG amplitude and the degree of

  3. EMG feedback as a muscle reeducation technique: a controlled study.

    PubMed

    Middaugh, S J

    1978-01-01

    In an effort to evaluate the efficacy and function of EMG feedback in muscle reeducation, improvement of the abductor function of the abductor hallucis muscle was studied under three training conditions involving 1) EMG feedback, 2) sensory stimulation or 3) equal time for unassisted practice; and a fourth, control condition involving testing without training. Active range of motion was measured before and after training to assess ability to use the muscle as an abductor. EMG activity was quantified for a 1-minute test contraction to evaluate ability to maintain and maximize a voluntary contraction of the target muscle. The results indicated that EMG feedback was highly effective when subjects had little initial use of the target muscle. EMG feedback improved the ability of these subjects to maintain and maximize voluntary muscle contractions, as demonstrated on the EMG measure. EMG feedback did not add to the learning situation when only a relatively brief, phasic contraction was required, as on the range-of-motion measure; similar gains were made with equivalent practive without EMG feedback. When subjects already had considerable use of the target muscle prior to training, EMG feedback may have actually interfered with training; in this case unassisted practice was more effective.

  4. Robotic leg control with EMG decoding in an amputee with nerve transfers.

    PubMed

    Hargrove, Levi J; Simon, Ann M; Young, Aaron J; Lipschutz, Robert D; Finucane, Suzanne B; Smith, Douglas G; Kuiken, Todd A

    2013-09-26

    The clinical application of robotic technology to powered prosthetic knees and ankles is limited by the lack of a robust control strategy. We found that the use of electromyographic (EMG) signals from natively innervated and surgically reinnervated residual thigh muscles in a patient who had undergone knee amputation improved control of a robotic leg prosthesis. EMG signals were decoded with a pattern-recognition algorithm and combined with data from sensors on the prosthesis to interpret the patient's intended movements. This provided robust and intuitive control of ambulation--with seamless transitions between walking on level ground, stairs, and ramps--and of the ability to reposition the leg while the patient was seated.

  5. A mixed FES/EMG system for real time analysis of muscular fatigue.

    PubMed

    Yochum, M; Binczak, S; Bakir, T; Jacquir, S; Lepers, R

    2010-01-01

    In this article, we present a functional electrical stimulator allowing the extraction in real time of M-wave characteristics from resulting EMG recodings in order to quantify muscle fatigue. This system is composed of three parts. A Labview software managing the stimulation output and electromyogram (EMG) input signal, a hardware part amplifying the output and input signal and a link between the two previous parts which is made up from input/output module (NIdaq USB 6251). In order to characterize the fatigue level, the Continuous Wavelet Transform is applied yielding a local maxima detection. The fatigue is represented on a scale from 0 for a fine shaped muscle to 100 for a very tired muscle. Premilary results are given. PMID:21096653

  6. Muscle networks: Connectivity analysis of EMG activity during postural control

    NASA Astrophysics Data System (ADS)

    Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

    2015-12-01

    Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures.

  7. Muscle networks: Connectivity analysis of EMG activity during postural control

    PubMed Central

    Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

    2015-01-01

    Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures. PMID:26634293

  8. An algorithm for the estimation of the signal-to-noise ratio in surface myoelectric signals generated during cyclic movements.

    PubMed

    Agostini, Valentina; Knaflitz, Marco

    2012-01-01

    In many applications requiring the study of the surface myoelectric signal (SMES) acquired in dynamic conditions, it is essential to have a quantitative evaluation of the quality of the collected signals. When the activation pattern of a muscle has to be obtained by means of single- or double-threshold statistical detectors, the background noise level e (noise) of the signal is a necessary input parameter. Moreover, the detection strategy of double-threshold detectors may be properly tuned when the SNR and the duty cycle (DC) of the signal are known. The aim of this paper is to present an algorithm for the estimation of e (noise), SNR, and DC of an SMES collected during cyclic movements. The algorithm is validated on synthetic signals with statistical properties similar to those of SMES, as well as on more than 100 real signals.

  9. Robust functional statistics applied to Probability Density Function shape screening of sEMG data.

    PubMed

    Boudaoud, S; Rix, H; Al Harrach, M; Marin, F

    2014-01-01

    Recent studies pointed out possible shape modifications of the Probability Density Function (PDF) of surface electromyographical (sEMG) data according to several contexts like fatigue and muscle force increase. Following this idea, criteria have been proposed to monitor these shape modifications mainly using High Order Statistics (HOS) parameters like skewness and kurtosis. In experimental conditions, these parameters are confronted with small sample size in the estimation process. This small sample size induces errors in the estimated HOS parameters restraining real-time and precise sEMG PDF shape monitoring. Recently, a functional formalism, the Core Shape Model (CSM), has been used to analyse shape modifications of PDF curves. In this work, taking inspiration from CSM method, robust functional statistics are proposed to emulate both skewness and kurtosis behaviors. These functional statistics combine both kernel density estimation and PDF shape distances to evaluate shape modifications even in presence of small sample size. Then, the proposed statistics are tested, using Monte Carlo simulations, on both normal and Log-normal PDFs that mimic observed sEMG PDF shape behavior during muscle contraction. According to the obtained results, the functional statistics seem to be more robust than HOS parameters to small sample size effect and more accurate in sEMG PDF shape screening applications.

  10. The Averaged EMGs Recorded from the Arm Muscles During Bimanual "Rowing" Movements.

    PubMed

    Tomiak, Tomasz; Gorkovenko, Andriy V; Tal'nov, Arkadii N; Abramovych, Tetyana I; Mishchenko, Viktor S; Vereshchaka, Inna V; Kostyukov, Alexander I

    2015-01-01

    The main purpose was to analyze quantitatively the the average surface EMGs of the muscles that function around the elbow and shoulder joints of both arms in bimanual "rowing" movements, which were produced under identical elastic loads applied to the levers ("oars"). The muscles of PM group ("pulling" muscles: elbow flexors, shoulder extensors) generated noticeable velocity-dependent dynamic EMG components during the pulling and returning phases of movement and supported a steady-state activity during the hold phase. The muscles of RM group ("returning" muscles: elbow extensors, shoulder flexors) co-contracted with PM group during the movement phases and decreased activity during the hold phase. The dynamic components of the EMGs strongly depended on the velocity factor in both muscle groups, whereas the side and load factors and combinations of various factors acted only in PM group. Various subjects demonstrated diverse patterns of activity redistribution among muscles. We assume that central commands to the same muscles in two arms may be essentially different during execution of similar movement programs. Extent of the diversity in the EMG patterns of such muscles may reflect the subject's skilling in motor performance; on the other hand, the diversity can be connected with redistribution of activity between synergic muscles, thus providing a mechanism directed against development of the muscle fatigue. PMID:26640440

  11. Muscle fatigue evaluation of astronaut upper limb based on sEMG and subjective assessment

    NASA Astrophysics Data System (ADS)

    Zu, Xiaoqi; Zhou, Qianxiang; Li, Yun

    2012-07-01

    All movements are driven by muscle contraction, and it is easy to cause muscle fatigue. Evaluation of muscle fatigue is a hot topic in the area of astronaut life support training and rehabilitation. If muscle gets into fatigue condition, it may reduce work efficiency and has an impact on psychological performance. Therefore it is necessary to develop an accurate and usable method on muscle fatigue evaluation of astronaut upper limb. In this study, we developed a method based on surface electromyography (sEMG) and subjective assessment (Borg scale) to evaluate local muscle fatigue. Fifteen healthy young male subjects participated in the experiment. They performed isometric muscle contractions of the upper limb. sEMG of the biceps brachii were recorded during the entire process of isotonic muscle contraction and Borg scales of muscle fatigue were collected in certain times. sEMG were divided into several parts, and then mean energy of each parts were calculated by the one-twelfth band octave method. Equations were derived based on the relationship between the mean energy of sEMG and Borg scale. The results showed that cubic curve could describe the degree of local muscle fatigue, and could be used to evaluate and monitor local muscle fatigue during the entire process.

  12. Robust functional statistics applied to Probability Density Function shape screening of sEMG data.

    PubMed

    Boudaoud, S; Rix, H; Al Harrach, M; Marin, F

    2014-01-01

    Recent studies pointed out possible shape modifications of the Probability Density Function (PDF) of surface electromyographical (sEMG) data according to several contexts like fatigue and muscle force increase. Following this idea, criteria have been proposed to monitor these shape modifications mainly using High Order Statistics (HOS) parameters like skewness and kurtosis. In experimental conditions, these parameters are confronted with small sample size in the estimation process. This small sample size induces errors in the estimated HOS parameters restraining real-time and precise sEMG PDF shape monitoring. Recently, a functional formalism, the Core Shape Model (CSM), has been used to analyse shape modifications of PDF curves. In this work, taking inspiration from CSM method, robust functional statistics are proposed to emulate both skewness and kurtosis behaviors. These functional statistics combine both kernel density estimation and PDF shape distances to evaluate shape modifications even in presence of small sample size. Then, the proposed statistics are tested, using Monte Carlo simulations, on both normal and Log-normal PDFs that mimic observed sEMG PDF shape behavior during muscle contraction. According to the obtained results, the functional statistics seem to be more robust than HOS parameters to small sample size effect and more accurate in sEMG PDF shape screening applications. PMID:25570426

  13. A strategy for identifying locomotion modes using surface electromyography.

    PubMed

    Huang, He; Kuiken, Todd A; Lipschutz, Robert D

    2009-01-01

    This study investigated the use of surface electromyography (EMG) combined with pattern recognition (PR) to identify user locomotion modes. Due to the nonstationary characteristics of leg EMG signals during locomotion, a new phase-dependent EMG PR strategy was proposed for classifying the user's locomotion modes. The variables of the system were studied for accurate classification and timely system response. The developed PR system was tested on EMG data collected from eight able-bodied subjects and two subjects with long transfemoral (TF) amputations while they were walking on different terrains or paths. The results showed reliable classification for the seven tested modes. For eight able-bodied subjects, the average classification errors in the four defined phases using ten electrodes located over the muscles above the knee (simulating EMG from the residual limb of a TF amputee) were 12.4% +/- 5.0%, 6.0% +/- 4.7%, 7.5% +/- 5.1%, and 5.2% +/- 3.7%, respectively. Comparable results were also observed in our pilot study on the subjects with TF amputations. The outcome of this investigation could promote the future design of neural-controlled artificial legs.

  14. Treatment of Handwriting Problems Utilizing EMG Biofeedback Training.

    ERIC Educational Resources Information Center

    Hughes, Howard; And Others

    1979-01-01

    The effects of electromyogram (EMG) biofeedback training on cursive handwriting were investigated with nine fourth graders. A significant reduction in EMG between the first baseline session and last training session was obtained. Four of five characteristics of handwriting improved significantly. (Author/SBH)

  15. Statistically significant contrasts between EMG waveforms revealed using wavelet-based functional ANOVA.

    PubMed

    McKay, J Lucas; Welch, Torrence D J; Vidakovic, Brani; Ting, Lena H

    2013-01-01

    We developed wavelet-based functional ANOVA (wfANOVA) as a novel approach for comparing neurophysiological signals that are functions of time. Temporal resolution is often sacrificed by analyzing such data in large time bins, increasing statistical power by reducing the number of comparisons. We performed ANOVA in the wavelet domain because differences between curves tend to be represented by a few temporally localized wavelets, which we transformed back to the time domain for visualization. We compared wfANOVA and ANOVA performed in the time domain (tANOVA) on both experimental electromyographic (EMG) signals from responses to perturbation during standing balance across changes in peak perturbation acceleration (3 levels) and velocity (4 levels) and on simulated data with known contrasts. In experimental EMG data, wfANOVA revealed the continuous shape and magnitude of significant differences over time without a priori selection of time bins. However, tANOVA revealed only the largest differences at discontinuous time points, resulting in features with later onsets and shorter durations than those identified using wfANOVA (P < 0.02). Furthermore, wfANOVA required significantly fewer (~1/4;×; P < 0.015) significant F tests than tANOVA, resulting in post hoc tests with increased power. In simulated EMG data, wfANOVA identified known contrast curves with a high level of precision (r(2) = 0.94 ± 0.08) and performed better than tANOVA across noise levels (P < <0.01). Therefore, wfANOVA may be useful for revealing differences in the shape and magnitude of neurophysiological signals (e.g., EMG, firing rates) across multiple conditions with both high temporal resolution and high statistical power. PMID:23100136

  16. Bcl-2 proteins and calcium signaling: complexity beneath the surface.

    PubMed

    Vervliet, T; Parys, J B; Bultynck, G

    2016-09-29

    Antiapoptotic Bcl-2-family members are well known for their 'mitochondrial' functions as critical neutralizers of proapoptotic Bcl-2-family members, including the executioner multidomain proteins Bax and Bak and the BH3-only proteins. It has been clear for more than 20 years that Bcl-2 proteins can impact intracellular Ca(2+) homeostasis and dynamics. Moreover, altered Ca(2+) signaling is increasingly linked to oncogenic behavior. Specifically targeting the Ca(2+)-signaling machinery may thus prove to be a valuable strategy for cancer treatment. Over 10 years ago a major controversy was recognized concerning whether or not Bcl-2 proteins exerted their antiapoptotic functions via Ca(2+) signaling through lowering the filling state of the endoplasmic reticulum (ER) Ca(2+) stores or by suppressing Ca(2+) release from the ER without affecting the filling state of this Ca(2+) store. Further research from different laboratories indicated a wide variety of mechanisms by which Bcl-2-family members can impact Ca(2+) signaling. In this review, we propose that antiapoptotic Bcl-2-family members are multimodal regulators of intracellular Ca(2+)-signaling events in cell survival and cell death. We will discuss how different Bcl-2-family members impact cell survival and cell death by regulating Ca(2+) transport systems at the ER, mitochondria and plasma membrane and by impacting the organization of organelles and how these insights can be exploited for causing cell death in cancer cells. Finally, we propose that the existing controversy reflects the diversity of links between Bcl-2 proteins and Ca(2+) signaling, as certainly not all targets or mechanisms will be operative in every cell type and every condition.

  17. Dissecting Arabidopsis G beta signal transduction on the protein surface

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The heterotrimeric G protein complex provides signal amplification and target specificity. The Arabidopsis Gbeta subunit of this complex (AGB1) interacts with and modulates the activity of target cytoplasmic proteins. This specificity resides in the structure of the interface between AGB1 and its ta...

  18. EMG characteristics and fibre composition: study on rectus femoris of sprinters and long distance runners.

    PubMed

    Goswami, A; Sadhukhan, A K; Gupta, S

    2001-10-01

    The study was conducted on 9 sprinters and 5 long distance runners to investigate the difference in power spectral characteristics of rectus femoris muscle and the feasibility of using electromyographic techniques in categorization of muscle groups in slow dominant and fast dominant types. EMG signal was recorded, after digitization at 4 KHz, from rectus femoris muscle during isometric knee extension (at maximum voluntary contraction level) until fatigue. Digitized signal was processed for Fast Fourier Transform and Root Mean Square (RMS) voltage. Significant difference (P < 0.05) was found in RMS voltage between sprinters and long distance runners. Both groups showed decline in Mean Power Frequency (MPE) and rate of decline in sprinters was rapid. Normalized MPF showed better discrimination between the two groups. It is concluded that the EMG response observed in this study was possibly a result of differences in the muscle fibre composition of the athletes. EMG study using spectral characteristics would be useful in categorizing the sports persons in terms of suitability of the events.

  19. Pattern classification of Myo-Electrical signal during different Maximum Voluntary Contractions: A study using BSS techniques

    NASA Astrophysics Data System (ADS)

    Naik, Ganesh R.; Kumar, Dinesh K.; Arjunan, Sridhar P.

    2010-01-01

    The presence of noise and cross-talk from closely located and simultaneously active muscles is exaggerated when the level of muscle contraction is very low. Due to this the current applications of surface electromyogram (sEMG) are infeasible and unreliable in pattern classification. This research reports a new technique of sEMG using Independent Component Analysis (ICA). The technique uses blind source separation (BSS) methods to classify the patterns of Myo-electrical signals during different Maximum Voluntary Contraction (MVCs) at different low level finger movements. The results of the experiments indicate that patterns using ICA of sEMG is a reliable (p<0.001) measure of strength of muscle contraction even when muscle activity is only 20% MVC. The authors propose that ICA is a useful indicator of muscle properties and is a useful indicator of the level of muscle activity.

  20. Coordinated upper limb training assisted with an electromyography (EMG)-driven hand robot after stroke.

    PubMed

    Hu, X L; Tong, K Y; Wei, X J; Rong, W; Susanto, E A; Ho, S K

    2013-01-01

    An electromyography (EMG)-driven hand robot had been developed for post-stroke rehabilitation training. The effectiveness of the hand robot assisted whole upper limb training on muscular coordination was investigated on persons with chronic stroke (n=10) in this work. All subjects attended a 20-session training (3-5 times/week) by using the hand robot to practice object grasp/release and arm transportation tasks. Improvements were found in the muscle co-ordination between the antagonist muscle pair (flexor digitorum and extensor digitorum) as measured by muscle co-contractions in EMG signals; and also in the reduction of excessive muscle activities in the biceps brachii. Reduced spasticity in the fingers was also observed as measured by the Modified Ashworth Score.

  1. Supplementing biomechanical modeling with EMG analysis

    NASA Technical Reports Server (NTRS)

    Lewandowski, Beth; Jagodnik, Kathleen; Crentsil, Lawton; Humphreys, Bradley; Funk, Justin; Gallo, Christopher; Thompson, William; DeWitt, John; Perusek, Gail

    2016-01-01

    It is well established that astronauts experience musculoskeletal deconditioning when exposed to microgravity environments for long periods of time. Spaceflight exercise is used to counteract these effects, and the Advanced Resistive Exercise Device (ARED) on the International Space Station (ISS) has been effective in minimizing musculoskeletal losses. However, the exercise devices of the new exploration vehicles will have requirements of limited mass, power and volume. Because of these limitations, there is a concern that the exercise devices will not be as effective as ARED in maintaining astronaut performance. Therefore, biomechanical modeling is being performed to provide insight on whether the small Multi-Purpose Crew Vehicle (MPCV) device, which utilizes a single-strap design, will provide sufficient physiological loading to maintain musculoskeletal performance. Electromyography (EMG) data are used to supplement the biomechanical model results and to explore differences in muscle activation patterns during exercises using different loading configurations.

  2. Chronic Assessment of Diaphragm Muscle EMG Activity across Motor Behaviors

    PubMed Central

    Mantilla, Carlos B.; Seven, Yasin B.; Hurtado-Palomino, Juan N.; Zhan, Wen-Zhi; Sieck, Gary C.

    2011-01-01

    The diaphragm muscle is main inspiratory muscle in mammals. Quantitative analyses documenting the reliability of chronic diaphragm EMG recordings are lacking. Assessment of ventilatory and non-ventilatory motor behaviors may facilitate evaluating diaphragm EMG activity over time. We hypothesized that normalization of diaphragm EMG amplitude across behaviors provides stable and reliable parameters for longitudinal assessments of diaphragm activity. We found that diaphragm EMG activity shows substantial intra-animal variability over 6 weeks, with coefficient of variation (CV) for different behaviors ~29–42%. Normalization of diaphragm EMG activity to near maximal behaviors (e.g., deep breathing) reduced intra-animal variability over time (CV ~22–29%). Plethysmographic measurements of eupneic ventilation were also stable over 6 weeks (CV ~13% for minute ventilation). Thus, stable and reliable measurements of diaphragm EMG activity can be obtained longitudinally using chronically implanted electrodes by examining multiple motor behaviors. By quantitatively determining the reliability of longitudinal diaphragm EMG analyses, we provide an important tool for evaluating the progression of diseases or injuries that impair ventilation. PMID:21414423

  3. Small-signal theory of subterahertz overmoded surface wave oscillator with distributed wall loss

    NASA Astrophysics Data System (ADS)

    Wang, Guangqiang; Wang, Jianguo; Li, Shuang; Wang, Xuefeng

    2015-09-01

    A small-signal theory of the overmoded surface wave oscillator (SWO) with distributed wall loss is presented in this letter. The wall loss considered here includes the surface resistance and surface roughness. The cold and hot characteristics of 0.14 THz SWO are studied by the small-signal theory. Numerical results show that as the increase of wall loss, the working frequency decreases slightly, the rise time and startup time of oscillation increase significantly, and the output power decreases dramatically. Particle-in-cell (PIC) simulation confirms the prediction by the small-signal theory.

  4. A Spiking Neural Network in sEMG Feature Extraction.

    PubMed

    Lobov, Sergey; Mironov, Vasiliy; Kastalskiy, Innokentiy; Kazantsev, Victor

    2015-01-01

    We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy of the proposed model could reach high values comparable with existing sEMG interface systems. Moreover, the algorithm sensibility for different sEMG collecting systems characteristics was estimated. Results showed rather equal accuracy, despite a significant sampling rate difference. The proposed algorithm was successfully tested for mobile robot control. PMID:26540060

  5. A Spiking Neural Network in sEMG Feature Extraction

    PubMed Central

    Lobov, Sergey; Mironov, Vasiliy; Kastalskiy, Innokentiy; Kazantsev, Victor

    2015-01-01

    We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy of the proposed model could reach high values comparable with existing sEMG interface systems. Moreover, the algorithm sensibility for different sEMG collecting systems characteristics was estimated. Results showed rather equal accuracy, despite a significant sampling rate difference. The proposed algorithm was successfully tested for mobile robot control. PMID:26540060

  6. Power of the echo signal at grazing angles of location of a randomly irregular surface

    SciTech Connect

    Belov, M.L.

    1995-03-01

    The power of an optical signal detected upon nonstationary irradiation of a randomly irregular surface in the case when mutual shading of surface elements is an essential factor is investigated. An expression for an average (over an ensemble of irregular surfaces) power detected in location of a surface with a Gaussian distribution of heights and inclinations by a {delta}-pulse under conditions of strong shadings is derived. Shading is shown to produce a substantial distortion of the shape of the echo signal. 6 refs., 1 fig.

  7. Oral EMG Activation Patterns for Speech Are Similar in Preschoolers Who Do and Do Not Stutter

    PubMed Central

    Walsh, Bridget; Smith, Anne

    2014-01-01

    Purpose We determined whether basic patterns of muscle activation for speech were similar in preschool children who stutter and their fluent peers. Method We recorded right and left lower lip muscle activity during conversational speech and sentence repetition in 64 preschool children (CWS) diagnosed as stuttering and in 40 children who do not stutter (CWNS). Measures of EMG amplitude, right/left asymmetry, and bilateral coordination were computed for fluent speech. The potential presence of tremor-like oscillations during disfluencies of CWS was assessed, and EMG amplitudes of fluent and disfluent speech were compared in CWS. Results Across both speaking tasks lip muscle activation was similar in CWS and CWNS in overall amplitude, bilateral synchrony, and degree of right/left asymmetry. EMG amplitude was reduced during disfluent compared to fluent conversational speech of CWS, and there was no evidence of tremor in the disfluencies of CWS. Conclusion These results support the assertion that stuttering in young children arises not from basic features of muscle contraction, but rather from the command signals that control the timing and amplitude of muscle activity. Our results indicate that no frank abnormality is present in muscle activation patterns in preschoolers who stutter. PMID:23838991

  8. Statistical and signal-processing concepts in surface metrology

    SciTech Connect

    Church, E.L.; Takacs, P.Z.

    1986-03-01

    This paper proposes the use of a simple two-scale model of surface roughness for testing and specifying the topographic figure and finish of synchrotron-radiation mirrors. In this approach the effects of figure and finish are described in terms of their slope distribution and power spectrum, respectively, which are then combined with the system point spread function to produce a composite image. The result can be used to predict mirror performance or to translate design requirements into manufacturing specifications. Pacing problems in this approach are the development of a practical long-trace slope-profiling instrument and realistic statistical models for figure and finish errors.

  9. High Cell Surface Death Receptor Expression Determines Type I Versus Type II Signaling*

    PubMed Central

    Meng, Xue Wei; Peterson, Kevin L.; Dai, Haiming; Schneider, Paula; Lee, Sun-Hee; Zhang, Jin-San; Koenig, Alexander; Bronk, Steve; Billadeau, Daniel D.; Gores, Gregory J.; Kaufmann, Scott H.

    2011-01-01

    Previous studies have suggested that there are two signaling pathways leading from ligation of the Fas receptor to induction of apoptosis. Type I signaling involves Fas ligand-induced recruitment of large amounts of FADD (FAS-associated death domain protein) and procaspase 8, leading to direct activation of caspase 3, whereas type II signaling involves Bid-mediated mitochondrial perturbation to amplify a more modest death receptor-initiated signal. The biochemical basis for this dichotomy has previously been unclear. Here we show that type I cells have a longer half-life for Fas message and express higher amounts of cell surface Fas, explaining the increased recruitment of FADD and subsequent signaling. Moreover, we demonstrate that cells with type II Fas signaling (Jurkat or HCT-15) can signal through a type I pathway upon forced receptor overexpression and that shRNA-mediated Fas down-regulation converts cells with type I signaling (A498) to type II signaling. Importantly, the same cells can exhibit type I signaling for Fas and type II signaling for TRAIL (TNF-α-related apoptosis-inducing ligand), indicating that the choice of signaling pathway is related to the specific receptor, not some other cellular feature. Additional experiments revealed that up-regulation of cell surface death receptor 5 levels by treatment with 7-ethyl-10-hydroxy-camptothecin converted TRAIL signaling in HCT116 cells from type II to type I. Collectively, these results suggest that the type I/type II dichotomy reflects differences in cell surface death receptor expression. PMID:21865165

  10. Signals from the surface modulate differentiation of human pluripotent stem cells through glycosaminoglycans and integrins.

    PubMed

    Wrighton, Paul J; Klim, Joseph R; Hernandez, Brandon A; Koonce, Chad H; Kamp, Timothy J; Kiessling, Laura L

    2014-12-23

    The fate decisions of human pluripotent stem (hPS) cells are governed by soluble and insoluble signals from the microenvironment. Many hPS cell differentiation protocols use Matrigel, a complex and undefined substrate that engages multiple adhesion and signaling receptors. Using defined surfaces programmed to engage specific cell-surface ligands (i.e., glycosaminoglycans and integrins), the contribution of specific matrix signals can be dissected. For ectoderm and motor neuron differentiation, peptide-modified surfaces that can engage both glycosaminoglycans and integrins are effective. In contrast, surfaces that interact selectively with glycosaminoglycans are superior to Matrigel in promoting hPS cell differentiation to definitive endoderm and mesoderm. The modular surfaces were used to elucidate the signaling pathways underlying these differences. Matrigel promotes integrin signaling, which in turn inhibits mesendoderm differentiation. The data indicate that integrin-activating surfaces stimulate Akt signaling via integrin-linked kinase (ILK), which is antagonistic to endoderm differentiation. The ability to attribute cellular responses to specific interactions between the cell and the substrate offers new opportunities for revealing and controlling the pathways governing cell fate.

  11. Predicting electromyographic signals under realistic conditions using a multiscale chemo–electro–mechanical finite element model

    PubMed Central

    Mordhorst, Mylena; Heidlauf, Thomas; Röhrle, Oliver

    2015-01-01

    This paper presents a novel multiscale finite element-based framework for modelling electromyographic (EMG) signals. The framework combines (i) a biophysical description of the excitation–contraction coupling at the half-sarcomere level, (ii) a model of the action potential (AP) propagation along muscle fibres, (iii) a continuum-mechanical formulation of force generation and deformation of the muscle, and (iv) a model for predicting the intramuscular and surface EMG. Owing to the biophysical description of the half-sarcomere, the model inherently accounts for physiological properties of skeletal muscle. To demonstrate this, the influence of membrane fatigue on the EMG signal during sustained contractions is investigated. During a stimulation period of 500 ms at 100 Hz, the predicted EMG amplitude decreases by 40% and the AP propagation velocity decreases by 15%. Further, the model can take into account contraction-induced deformations of the muscle. This is demonstrated by simulating fixed-length contractions of an idealized geometry and a model of the human tibialis anterior muscle (TA). The model of the TA furthermore demonstrates that the proposed finite element model is capable of simulating realistic geometries, complex fibre architectures, and can include different types of heterogeneities. In addition, the TA model accounts for a distributed innervation zone, different fibre types and appeals to motor unit discharge times that are based on a biophysical description of the α motor neurons. PMID:25844148

  12. Effect of electrode location on surface electromyography changes due to eccentric elbow flexor exercise.

    PubMed

    Piitulainen, Harri; Bottas, Reijo; Linnamo, Vesa; Komi, Paavo; Avela, Janne

    2009-10-01

    Experiments were carried out to determine whether the location of electrodes has an effect on eccentric exercise-induced changes in surface electromyography (sEMG) variables in the biceps brachii muscle. sEMG signals were recorded with a grid of 64 electrodes before and up to 4 days post-exercise. Root mean square (RMS) and mean power frequency (MNF) were calculated for: (1) each channel; (2) as an average of all channels; and (3) as an average of individual channel rows and columns. Mean muscle-fiber conduction velocity (CV) was estimated similarly but was based on double-differential channels. Maximal isometric voluntary torque decreased 21.3 +/- 5.6% post-exercise. The average sEMG variables decreased after the exercise and recovered 2 days (RMS and CV) or 4 days (MNF) post-exercise. Site-dependent changes were observed in sEMG variables. We conclude that site-dependent changes in sEMG variables after eccentric exercise can be detected and are influenced in part by anatomical factors.

  13. Signal peptides direct surface proteins to two distinct envelope locations of Staphylococcus aureus

    PubMed Central

    DeDent, Andrea; Bae, Taeok; Missiakas, Dominique M; Schneewind, Olaf

    2008-01-01

    Surface proteins of Gram-positive bacteria are covalently linked to the cell wall envelope by a mechanism requiring an N-terminal signal peptide and a C-terminal LPXTG motif sorting signal. We show here that surface proteins of Staphylococcus aureus arrive at two distinct destinations in the bacterial envelope, either distributed as a ring surrounding each cell or as discrete assembly sites. Proteins with ring-like distribution (clumping factor A (ClfA), Spa, fibronectin-binding protein B (FnbpB), serine-aspartate repeat protein C (SdrC) and SdrD) harbour signal peptides with a YSIRK/GS motif, whereas proteins directed to discrete assembly sites (S. aureus surface protein A (SasA), SasD, SasF and SasK) do not. Reciprocal exchange of signal peptides between surface proteins with (ClfA) or without the YSIRK/GS motif (SasF) directed recombinant products to the alternate destination, whereas mutations that altered only the YSIRK sequence had no effect. Our observations suggest that S. aureus distinguishes between signal peptides to address proteins to either the cell pole (signal peptides without YSIRK/GS) or the cross wall, the peptidoglycan layer that forms during cell division to separate new daughter cells (signal peptides with YISRK/GS motif). PMID:18800056

  14. Identifying dispersive GPR signals and inverting for surface waveguide properties

    NASA Astrophysics Data System (ADS)

    van der Kruk, Jan; Jacob, Rob; Steelman, Colby; Endres, Tony; Vereecken, Harry

    2010-05-01

    At locations where a thin surface layer overlies a substrate medium that has a lower permittivity, or a much larger permittivity/conductivity than the surface layer, pronounced dispersion of GPR waves can be observed and the surface layer acts as a waveguide. A low velocity waveguide is present when the substrate has a lower permittivity and total reflection occurs beyond the critical angle on the upper and lower interfaces. A leaky waveguide is present when the substrate medium has a much larger permittivity and/or conductivity. Although the lower interface is a strong reflector, some energy is still transmitted across the interface and total reflection only occurs at the upper waveguide-air interface. In both cases, electromagnetic waves are trapped within the waveguide and the radar energy is internally reflected, resulting in a series of interfering multiples that manifest themselves as shingling reflections that exhibit different phase and group velocities. Normalizing the data on the maximum amplitude for each trace shows that most of the energy is contained within the dispersive waves which propagate over large distances. Phase-velocity spectra calculated from these dispersed GPR data clearly indicate the presence of a frequency-dependent phase velocity that decreases with increasing frequency. The dispersion characteristics depend on the type of waveguide and the source-receiver antenna orientations. For low-velocity waveguides, the transverse electric (TE) modes propagate at lower frequencies compared to transverse magnetic (TM) modes, whereas only uneven TE and even TM modes can propagate through leaky waveguides. The waveguide properties can be obtained by picking dispersion curves from the maxima in the phase-velocity spectra and inverting for a single-layer waveguide model by adjusting the model parameters using a combined global and local minimization algorithm until the difference between the picked dispersion curve and the model-predicted dispersion

  15. Mechanisms by which the inhibition of specific intracellular signaling pathways increase osteoblast proliferation on apatite surfaces.

    PubMed

    Yang, Seungwon; Tian, Yu-Shun; Lee, Yun-Jung; Yu, Frank H; Kim, Hyun-Man

    2011-04-01

    Osteoblasts proliferate slowly on the surface of calcium phosphate apatite which is widely used as a substrate biomaterial in bone regeneration. Owing to poor adhesion signaling in the cells grown on the calcium phosphate surface, inadequate growth factor signaling is generated to trigger cell cycle progression. The present study investigated an intracellular signal transduction pathway involved in the slow cell proliferation in osteoblasts grown on the calcium phosphate surface. Small GTPase RhoA and phosphatase and tensin homolog (PTEN) were more activated in cells grown on the surface of calcium phosphate apatite than on tissue culture plate. Specific inhibition of RhoA and PTEN induced the cells on calcium phosphate apatite surface to proliferate at a similar rate as cells on tissue culture plate surface. Specific inhibition of ROCK, which is a downstream effector of RhoA and an upstream activator of PTEN also increased proliferation of these osteoblasts. Present results indicate that physical property of calcium phosphate crystals that impede cell proliferation may be surmounted by the inhibition of the RhoA/ROCK/PTEN pathway to rescue delayed proliferation of osteoblasts on the calcium phosphate apatite surface. In addition, specific inhibition of ROCK promoted cell migration and osteoblast differentiation. Inhibition of the RhoA/ROCK/PTEN intracellular signaling pathway is expected to enhance cell activity to promote and accelerate bone regeneration on the calcium phosphate apatite surface.

  16. Wireless Neural/EMG Telemetry Systems for Small Freely Moving Animals.

    PubMed

    Harrison, R R; Fotowat, H; Chan, R; Kier, R J; Olberg, R; Leonardo, A; Gabbiani, F

    2011-04-01

    We have developed miniature telemetry systems that capture neural, EMG, and acceleration signals from a freely moving insect or other small animal and transmit the data wirelessly to a remote digital receiver. The systems are based on custom low-power integrated circuits (ICs) that amplify, filter, and digitize four biopotential signals using low-noise circuits. One of the chips also digitizes three acceleration signals from an off-chip microelectromechanical-system accelerometer. All information is transmitted over a wireless ~ 900-MHz telemetry link. The first unit, using a custom chip fabricated in a 0.6- μm BiCMOS process, weighs 0.79 g and runs for two hours on two small batteries. We have used this system to monitor neural and EMG signals in jumping and flying locusts as well as transdermal potentials in weakly swimming electric fish. The second unit, using a custom chip fabricated in a 0.35-μ m complementary metal-oxide semiconductor CMOS process, weighs 0.17 g and runs for five hours on a single 1.5-V battery. This system has been used to monitor neural potentials in untethered perching dragonflies.

  17. Wireless Neural/EMG Telemetry Systems for Small Freely Moving Animals.

    PubMed

    Harrison, R R; Fotowat, H; Chan, R; Kier, R J; Olberg, R; Leonardo, A; Gabbiani, F

    2011-04-01

    We have developed miniature telemetry systems that capture neural, EMG, and acceleration signals from a freely moving insect or other small animal and transmit the data wirelessly to a remote digital receiver. The systems are based on custom low-power integrated circuits (ICs) that amplify, filter, and digitize four biopotential signals using low-noise circuits. One of the chips also digitizes three acceleration signals from an off-chip microelectromechanical-system accelerometer. All information is transmitted over a wireless ~ 900-MHz telemetry link. The first unit, using a custom chip fabricated in a 0.6- μm BiCMOS process, weighs 0.79 g and runs for two hours on two small batteries. We have used this system to monitor neural and EMG signals in jumping and flying locusts as well as transdermal potentials in weakly swimming electric fish. The second unit, using a custom chip fabricated in a 0.35-μ m complementary metal-oxide semiconductor CMOS process, weighs 0.17 g and runs for five hours on a single 1.5-V battery. This system has been used to monitor neural potentials in untethered perching dragonflies. PMID:23851198

  18. Hybrid soft computing systems for electromyographic signals analysis: a review

    PubMed Central

    2014-01-01

    Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis. PMID:24490979

  19. Change in EMG with skin friction at different frequencies during elbow flexion.

    PubMed

    Sugawara, Hitoshi; Shimose, Ryota; Tadano, Chigaya; Ushigome, Nobuyuki; Muro, Masuo

    2013-06-01

    Modulation of muscle activation in superficial and deeper regions may be induced by tactile stimulation. The purpose of this study was to examine changes in muscle activation with skin friction. Subjects performed an isometric elbow flexion at 30% maximal voluntary cotraction (MVC) with skin friction at different frequencies (0.5-2.7 Hz). Surface electromyography (S-EMG) and intramuscular EMG were obtained from the elbow flexor muscles (BBS: short head of biceps brachii, BBL: long head of biceps brachii, BRA: brachialis). S-EMG activity decreased at a higher frequency of 2.7 Hz and increased linearly with an increase in skin friction frequency (0.5-2.7 Hz) in BBS. A decrease in high-threshold motor unit (HT-MU) firing rate in superficial regions and an increase in low-threshold motor unit (LT-MU) firing rate in deeper regions were observed with skin friction (2.7 Hz) in BBS. The actions of inhibitory interneurons may be influenced by cutaneous afferent input with skin friction. Muscle activation of BBS depended on the intensity of the stimulus. Skin friction over BBS results in an inhibitory response in superficial regions of BBS, most likely due to the increase in firing rate of low-threshold cutaneous mechanoreceptors.

  20. EMG Activity of Masseter Muscles in the Elderly According to Rheological Properties of Solid Food

    PubMed Central

    Kang, Au Jin; Kang, Si Hyun; Seo, Kyung Mook; Park, Hyoung Su; Park, Ki-Hwan

    2016-01-01

    Objective To assess the impact of aging on masticatory muscle function according to changes in hardness of solid food. Methods Each of fifteen healthy elderly and young people were selected. Subjects were asked to consume cooked rice, which was processed using the guidelines of the Universal Design Foods concept for elderly people (Japan Care Food Conference 2012). The properties of each cooked rice were categorized as grade 1, 2, 3 and 4 (5×103, 2×104, 5×104, and 5×105 N/m2) respectively. Surface electromyography (sEMG) was used to measure masseter activity from food ingestion to swallowing of test foods. The raw data was normalized by the ratio of sEMG activity to maximal voluntary contraction and compared among subjects. The data was divided according to each sequence of mastication and then calculated within the parameters of EMG activities. Results Intraoral tongue pressure was significantly higher in the young than in the elderly (p<0.05). Maximal value of average amplitude of the sequence in whole mastication showed significant positive correlation with hardness of food in both young and elderly groups (p<0.05). In a comparisons between groups, the maximal value of average amplitude of the sequence in whole mastication and peak amplitude in whole mastication showed that mastication in the elderly requires a higher percentage of maximal muscle activity than in the young, even with soft foods (p<0.05). Conclusion sEMG data of the masseter can provide valuable information to aid in the selection of foods according to hardness for the elderly. The results also support the necessity of specialized food preparation or products for the elderly. PMID:27446781

  1. Electromyography (EMG) accuracy compared to muscle biopsy in childhood.

    PubMed

    Rabie, Malcolm; Jossiphov, Joseph; Nevo, Yoram

    2007-07-01

    Reports show wide variability of electromyography (EMG) in detecting pediatric neuromuscular disorders. The study's aim was to determine EMG/nerve conduction study accuracy compared to muscle biopsy and final clinical diagnosis, and sensitivity for myopathic motor unit potential detection in childhood. Of 550 EMG/nerve conduction studies performed by the same examiner from a pediatric neuromuscular service, 27 children (ages 6 days to 16 years [10 boys; M:F, 1:1.7]) with muscle biopsies and final clinical diagnoses were compared retrospectively. Final clinical diagnoses were congenital myopathies (5 of 27,18%), nonspecific myopathies (biopsy myopathic, final diagnosis uncertain; 6 of 27, 22%), congenital myasthenic syndrome (3 of 27, 11%), juvenile myasthenia gravis (1 of 27, 4%), arthrogryposis multiplex congenita (2 of 27, 7%), hereditary motor and sensory neuropathy (1 of 27, 4%), bilateral peroneal neuropathies (1 of 27, 4%), and normal (8 of 27, 30%). There were no muscular dystrophy or spinal muscular atrophy patients. EMG/nerve conduction studies had a 74% agreement with final clinical diagnoses and 100% agreement in neurogenic, neuromuscular junction, and normal categories. Muscle biopsies concurred with final diagnoses in 87%, and 100% in myopathic and normal categories. In congenital myasthenic syndrome, muscle biopsies showed mild variation in fiber size in 2 of 3 children and were normal in 1 of 3. EMG sensitivity for detecting myopathic motor unit potentials in myopathies was 4 of 11 (36%), greater over 2 years of age (3 of 4, 75%), compared to infants less than 2 years (1 of 7, 14%), not statistically significant (P = .0879). EMGs false-negative for myopathy in infants < 2 years of age were frequently neurogenic (3 of 6, 50%). In congenital myopathies EMG detected myopathic motor unit potentials in 40%, with false-negative results neurogenic (20%) or normal (40%). Because our study has no additional tests for active myopathies, for example Duchenne

  2. Single fiber EMG Fiber density and its relationship to Macro EMG amplitude in reinnervation.

    PubMed

    Sandberg, Arne

    2014-12-01

    The objective was to elucidate the relation between the Macro EMG parameters fiber density (FD) and Macro amplitude in reinnervation in the purpose to use the FD parameter as a surrogate marker for reinnervation instead of the Macro amplitude. Macro EMG with FD was performed in 278 prior polio patients. The Biceps Brachii and the Tibialis anterior muscles were investigated. FD was more sensitive for detection of signs of reinnervation but showed lesser degree of abnormality than the Macro amplitude. FD and Macro MUP amplitude showed a non-linear relation with a great variation in FD for given Macro amplitude level. The relatively smaller increase in FD compared to Macro amplitude in addition to the non-linear relationship between the FD and the Macro amplitude regarding reinnervation in prior polio can be due to technical reasons and muscle fiber hypertrophy. The FD parameter has a relation to Macro MUP amplitude but cannot alone be used as a quantitative marker of the degree of reinnervation.

  3. Effects of charge screening and surface properties on signal transduction in field effect nanowire biosensors

    NASA Astrophysics Data System (ADS)

    Liu, Yang; Dutton, Robert W.

    2009-07-01

    A self-consistent numerical model for silicon-based field effect nanowire biosensors is developed to study the impact of various surface-related physical and chemical processes, including transport of semiconductor carriers and electrolyte mobile ions, protonation and deprotonation of surface charge groups, and charges, and orientations and surface binding dynamics of immobilized biomolecules. It is shown that the sensing signal levels are affected by the gate biasing points, nonlinear screening from both electrolytes and surface charge groups, as well as the biomolecule charges and orientations. The critical role of the nanowire surface heterogeneity in determining the sensing input dynamic range is indicated based on correlations with experimental data.

  4. Utilization of GPS Surface Reflected Signals to Provide Aircraft Altitude Verification for SVS

    NASA Technical Reports Server (NTRS)

    Gance, George G.; Young, Steven D.

    2005-01-01

    The Global Positioning System (GPS) consists of a constellation of Earth orbiting satellites that transmit continuous electromagnetic signals to users on or near the Earth surface. At any moment of time, at least four GPS satellites, and sometimes nine or more, are visible from any point. The electromagnetic signal transmitted from the satellites is reflected to at least some degree from virtually every place on the Earth. When this signal is received by a specially constructed receiver, its characteristics can be used to determine information about the reflected surface. One piece of information collected is the time delay encountered by the reflected signal versus the direct signal. This time delay can be used to determine the altitude (or height) above the local terrain when the terrain in the reflection area is level. However, given the potential of simultaneously using multiple reflections, it should be possible to also determine the elevation above even terrains where the reflecting area is not level. Currently an effort is underway to develop the technology to characterize the reflected signal that is received by the GPS Surface Reflection Experiment (GSRE) instrument. Recent aircraft sorties have been flown to collect data that can be used to refine the technology. This paper provides an update on the status of the instrument development to enable determination of terrain proximity using the GPS Reflected signal. Results found in the data collected to date are also discussed.

  5. A patient-specific EMG-driven neuromuscular model for the potential use of human-inspired gait rehabilitation robots.

    PubMed

    Ma, Ye; Xie, Shengquan; Zhang, Yanxin

    2016-03-01

    A patient-specific electromyography (EMG)-driven neuromuscular model (PENm) is developed for the potential use of human-inspired gait rehabilitation robots. The PENm is modified based on the current EMG-driven models by decreasing the calculation time and ensuring good prediction accuracy. To ensure the calculation efficiency, the PENm is simplified into two EMG channels around one joint with minimal physiological parameters. In addition, a dynamic computation model is developed to achieve real-time calculation. To ensure the calculation accuracy, patient-specific muscle kinematics information, such as the musculotendon lengths and the muscle moment arms during the entire gait cycle, are employed based on the patient-specific musculoskeletal model. Moreover, an improved force-length-velocity relationship is implemented to generate accurate muscle forces. Gait analysis data including kinematics, ground reaction forces, and raw EMG signals from six adolescents at three different speeds were used to evaluate the PENm. The simulation results show that the PENm has the potential to predict accurate joint moment in real-time. The design of advanced human-robot interaction control strategies and human-inspired gait rehabilitation robots can benefit from the application of the human internal state provided by the PENm.

  6. Entropy measures of back muscles EMG for subjects with and without pain

    NASA Astrophysics Data System (ADS)

    Zurcher, Ulrich; Kaufman, Miron; Vyhnalek, Bryan; Sung, Paul

    2007-10-01

    We have previously reported that the time-dependent entropy S(t) calculated from electromyography time series of low back muscles exhibit plateau-like behavior for intermediate times [50 ,ms < t < 0.5 ,s]. We proposed that the plateau value can be used to characterize the sEMG signal of subjects with low back pain [J. Rehab. Res. Dev. 44, 599 (2007)]. We report results of a larger study, and compare the entropies for the left -and right thoracic and left- and right lumbar muscles. We also compare entropies from muscles before and after physical therapy intervention.

  7. Voluntary EMG-to-force estimation with a multi-scale physiological muscle model

    PubMed Central

    2013-01-01

    Background EMG-to-force estimation based on muscle models, for voluntary contraction has many applications in human motion analysis. The so-called Hill model is recognized as a standard model for this practical use. However, it is a phenomenological model whereby muscle activation, force-length and force-velocity properties are considered independently. Perreault reported Hill modeling errors were large for different firing frequencies, level of activation and speed of contraction. It may be due to the lack of coupling between activation and force-velocity properties. In this paper, we discuss EMG-force estimation with a multi-scale physiology based model, which has a link to underlying crossbridge dynamics. Differently from the Hill model, the proposed method provides dual dynamics of recruitment and calcium activation. Methods The ankle torque was measured for the plantar flexion along with EMG measurements of the medial gastrocnemius (GAS) and soleus (SOL). In addition to Hill representation of the passive elements, three models of the contractile parts have been compared. Using common EMG signals during isometric contraction in four able-bodied subjects, torque was estimated by the linear Hill model, the nonlinear Hill model and the multi-scale physiological model that refers to Huxley theory. The comparison was made in normalized scale versus the case in maximum voluntary contraction. Results The estimation results obtained with the multi-scale model showed the best performances both in fast-short and slow-long term contraction in randomized tests for all the four subjects. The RMS errors were improved with the nonlinear Hill model compared to linear Hill, however it showed limitations to account for the different speed of contractions. Average error was 16.9% with the linear Hill model, 9.3% with the modified Hill model. In contrast, the error in the multi-scale model was 6.1% while maintaining a uniform estimation performance in both fast and slow

  8. Analysis of EMG temporal parameters from the tibialis anterior during hemiparetic gait

    NASA Astrophysics Data System (ADS)

    Bonell, Claudia E.; Cherniz, Analía S.; Tabernig, Carolina B.

    2007-11-01

    Functional electrical stimulation is a rehabilitation technique used to restore the motor muscular function by means of electrical stimulus commanded by a trigger signal under volitional control. In order to enhance the motor rehabilitation, a more convenient control signal may be provided by the same muscle that is being stimulated. For example, the tibialis anterior (TA) in the applications of foot drop correction could be used. This work presents the statistical analysis of the root mean square (RMS) and the absolute mean value (VMA) of the TA electromyogram (EMG) signal computed from different phases of the gait cycle related with increases/decreases stages of muscle activity. The EMG records of 40 strides of 2 subjects with hemiparesia were processed. The RMS and VMA parameters allow distinguishing the oscillation phase from the other analyzed intervals, but they present significant spreading of mean values. This led to conclude that it is possible to use these parameters to identify the start of TA muscle activity, but altogether with other parameter or sensor that would reduce the number of false positives.

  9. Comparison Between Sea Surface Wind Speed Estimates From Reflected GPS Signals and Buoy Measurements

    NASA Technical Reports Server (NTRS)

    Garrison, James L.; Katzberg, Steven J.; Zavorotny, Valery U.

    2000-01-01

    Reflected signals from the Global Positioning System (GPS) have been collected from an aircraft at approximately 3.7 km altitude on 5 different days. Estimation of surface wind speed by matching the shape of the reflected signal correlation function against analytical models was demonstrated. Wind speed obtained from this method agreed with that recorded from buoys to with a bias of less than 0.1 m/s, and with a standard derivation of 1.3 meters per second.

  10. Surface Roughness Evaluation Based on Acoustic Emission Signals in Robot Assisted Polishing

    PubMed Central

    de Agustina, Beatriz; Marín, Marta María; Teti, Roberto; Rubio, Eva María

    2014-01-01

    The polishing process is the most common technology used in applications where a high level of surface quality is demanded. The automation of polishing processes is especially difficult due to the high level of skill and dexterity that is required. Much of this difficulty arises because of the lack of reliable data on the effect of the polishing parameters on the resulting surface roughness. An experimental study was developed to evaluate the surface roughness obtained during Robot Assisted Polishing processes by the analysis of acoustic emission signals in the frequency domain. The aim is to find out a trend of a feature or features calculated from the acoustic emission signals detected along the process. Such an evaluation was made with the objective of collecting valuable information for the establishment of the end point detection of polishing process. As a main conclusion, it can be affirmed that acoustic emission (AE) signals can be considered useful to monitor the polishing process state. PMID:25405509

  11. Surface roughness evaluation based on acoustic emission signals in robot assisted polishing.

    PubMed

    de Agustina, Beatriz; Marín, Marta María; Teti, Roberto; Rubio, Eva María

    2014-11-14

    The polishing process is the most common technology used in applications where a high level of surface quality is demanded. The automation of polishing processes is especially difficult due to the high level of skill and dexterity that is required. Much of this difficulty arises because of the lack of reliable data on the effect of the polishing parameters on the resulting surface roughness. An experimental study was developed to evaluate the surface roughness obtained during Robot Assisted Polishing processes by the analysis of acoustic emission signals in the frequency domain. The aim is to find out a trend of a feature or features calculated from the acoustic emission signals detected along the process. Such an evaluation was made with the objective of collecting valuable information for the establishment of the end point detection of polishing process. As a main conclusion, it can be affirmed that acoustic emission (AE) signals can be considered useful to monitor the polishing process state.

  12. Automated Detection of Tonic-Clonic Seizures Using 3-D Accelerometry and Surface Electromyography in Pediatric Patients.

    PubMed

    Milosevic, Milica; Van de Vel, Anouk; Bonroy, Bert; Ceulemans, Berten; Lagae, Lieven; Vanrumste, Bart; Huffel, Sabine Van

    2016-09-01

    Epileptic seizure detection is traditionally done using video/electroencephalography monitoring, which is not applicable for long-term home monitoring. In recent years, attempts have been made to detect the seizures using other modalities. In this study, we investigated the application of four accelerometers (ACM) attached to the limbs and surface electromyography (sEMG) electrodes attached to upper arms for the detection of tonic-clonic seizures. sEMG can identify the tension during the tonic phase of tonic-clonic seizure, while ACM is able to detect rhythmic patterns of the clonic phase of tonic-clonic seizures. Machine learning techniques, including feature selection and least-squares support vector machine classification, were employed for detection of tonic-clonic seizures from ACM and sEMG signals. In addition, the outputs of ACM and sEMG-based classifiers were combined using a late integration approach. The algorithms were evaluated on 1998.3 h of data recorded nocturnally in 56 patients of which seven had 22 tonic-clonic seizures. A multimodal approach resulted in a more robust detection of short and nonstereotypical seizures (91%), while the number of false alarms increased significantly compared with the use of single sEMG modality (0.28-0.5/12h). This study also showed that the choice of the recording system should be made depending on the prevailing pediatric patient-specific seizure characteristics and nonepileptic behavior.

  13. Adaptive filtering of ECG interference on surface EEnGs based on signal averaging.

    PubMed

    Garcia-Casado, Javier; Martinez-de-Juan, Jose L; Ponce, Jose L

    2006-06-01

    An external electroenterogram (EEnG) is the recording of the small bowel myoelectrical signal using contact electrodes placed on the abdominal surface. It is a weak signal affected by possible movements and by the interferences of respiration and, principally, of the cardiac signal. In this paper an adaptive filtering technique was proposed to identify and subsequently cancel ECG interference on canine surface EEnGs by means of a signal averaging process time-locked with the R-wave. Twelve recording sessions were carried out on six conscious dogs in the fasting state. The adaptive filtering technique used increases the signal-to-interference ratio of the raw surface EEnG from 16.7 +/- 6.5 dB up to 31.9 +/- 4.0 dB. In addition to removing ECG interference, this technique has been proven to respect intestinal SB activity, i.e. the EEnG component associated with bowel contractions, despite the fact that they overlap in the frequency domain. In this way, more robust non-invasive intestinal motility indicators can be obtained with correlation coefficients of 0.68 +/- 0.09 with internal intestinal activity. The method proposed here may also be applied to other biological recordings affected by cardiac interference and could be a very helpful tool for future applications of non-invasive recordings of gastrointestinal signals.

  14. Dependence Independence Measure for Posterior and Anterior EMG Sensors Used in Simple and Complex Finger Flexion Movements: Evaluation Using SDICA.

    PubMed

    Naik, Ganesh R; Baker, Kerry G; Nguyen, Hung T

    2015-09-01

    Identification of simple and complex finger flexion movements using surface electromyography (sEMG) and a muscle activation strategy is necessary to control human-computer interfaces such as prosthesis and orthoses. In order to identify these movements, sEMG sensors are placed on both anterior and posterior muscle compartments of the forearm. In general, the accuracy of myoelectric classification depends on several factors, which include number of sensors, features extraction methods, and classification algorithms. Myoelectric classification using a minimum number of sensors and optimal electrode configuration is always a challenging task. Sometimes, using several sensors including high density electrodes will not guarantee high classification accuracy. In this research, we investigated the dependence and independence nature of anterior and posterior muscles during simple and complex finger flexion movements. The outcome of this research shows that posterior parts of the hand muscles are dependent and hence responsible for most of simple finger flexion. On the other hand, this study shows that anterior muscles are responsible for most complex finger flexion. This also indicates that simple finger flexion can be identified using sEMG sensors connected only on anterior muscles (making posterior placement either independent or redundant), and vice versa is true for complex actions which can be easily identified using sEMG sensors on posterior muscles. The result of this study is beneficial for optimal electrode configuration and design of prosthetics and other related devices using a minimum number of sensors.

  15. Mandibular kinematics and masticatory muscles EMG in patients with short lasting TMD of mild-moderate severity.

    PubMed

    De Felício, Cláudia Maria; Mapelli, Andrea; Sidequersky, Fernanda Vincia; Tartaglia, Gianluca M; Sforza, Chiarella

    2013-06-01

    Mandibular kinematic and standardized surface electromyography (sEMG) characteristics of masticatory muscles of subjects with short lasting TMD of mild-moderate severity were examined. Volunteers were submitted to clinical examination and questionnaire of severity. Ten subjects with TMD (age 27.3years, SD 7.8) and 10 control subjects without TMD, matched by age, were selected. Mandibular movements were recorded during free maximum mouth opening and closing (O-C) and unilateral, left and right, gum chewing. sEMG of the masseter and temporal muscles was performed during maximum teeth clenching either on cotton rolls or in intercuspal position, and during gum chewing. sEMG indices were obtained. Subjects with TMD, relative to control subjects, had lower relative mandibular rotation at the end of mouth opening, larger mean number of intersection between interincisal O-C paths during mastication and smaller asymmetry between working and balancing side, with participation beyond the expected of the contralateral muscles (P<0.05, t-test). Overall, TMD subjects showed similarities with the control subjects in several kinematic parameters and the EMG indices of the static test, although some changes in the mastication were observed. PMID:23477915

  16. A real-time EMG-driven virtual arm.

    PubMed

    Manal, Kurt; Gonzalez, Roger V; Lloyd, David G; Buchanan, Thomas S

    2002-01-01

    An EMG-driven virtual arm is being developed in our laboratories for the purposes of studying neuromuscular control of arm movements. The virtual arm incorporates the major muscles spanning the elbow joint and is used to estimate tension developed by individual muscles based on recorded electromyograms (EMGs). It is able to estimate joint moments and the corresponding virtual movements, which are displayed in real-time on a computer screen. In addition, the virtual arm offers artificial control over a variety of physiological and environmental conditions. The virtual arm can be used to examine how the neuromuscular system compensates for the partial or total loss of a muscle's ability to generate force as might result from trauma or pathology. The purpose of this paper is to describe the design objectives, fundamental components and implementation of our real-time, EMG-driven virtual arm. PMID:11738638

  17. A Finite Element Model Approach to Determine the Influence of Electrode Design and Muscle Architecture on Myoelectric Signal Properties

    PubMed Central

    Teklemariam, A.; Hodson-Tole, E. F.; Reeves, N. D.; Costen, N. P.; Cooper, G.

    2016-01-01

    Introduction Surface electromyography (sEMG) is the measurement of the electrical activity of the skeletal muscle tissue detected at the skin’s surface. Typically, a bipolar electrode configuration is used. Most muscles have pennate and/or curved fibres, meaning it is not always feasible to align the bipolar electrodes along the fibres direction. Hence, there is a need to explore how different electrode designs can affect sEMG measurements. Method A three layer finite element (skin, fat, muscle) muscle model was used to explore different electrode designs. The implemented model used as source signal an experimentally recorded intramuscular EMG taken from the biceps brachii muscle of one healthy male. A wavelet based intensity analysis of the simulated sEMG signal was performed to analyze the power of the signal in the time and frequency domain. Results The model showed muscle tissue causing a bandwidth reduction (to 20-92- Hz). The inter-electrode distance (IED) and the electrode orientation relative to the fibres affected the total power but not the frequency filtering response. The effect of significant misalignment between the electrodes and the fibres (60°- 90°) could be reduced by increasing the IED (25–30 mm), which attenuates signal cancellation. When modelling pennated fibres, the muscle tissue started to act as a low pass filter. The effect of different IED seems to be enhanced in the pennated model, while the filtering response is changed considerably only when the electrodes are close to the signal termination within the model. For pennation angle greater than 20°, more than 50% of the source signal was attenuated, which can be compensated by increasing the IED to 25 mm. Conclusion Differences in tissue filtering properties, shown in our model, indicates that different electrode designs should be considered for muscle with different geometric properties (i.e. pennated muscles). PMID:26886908

  18. Radar signal pre-processing to suppress surface bounce and multipath

    DOEpatents

    Paglieroni, David W; Mast, Jeffrey E; Beer, N. Reginald

    2013-12-31

    A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes that return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

  19. Two-dimensional jaw tracking and EMG recording system implanted in the freely moving rabbit.

    PubMed

    Yamada, Y; Haraguchi, N; Oi, K; Sasaki, M

    1988-04-01

    A system for simultaneously recording mandibular position in the sagittal plane together with masticatory muscle activity was designed and tested in rabbits. Two small magnetic sensors were implanted in the maxillary bone and a powerful magnet made of a rare earth metal attached to the mandibular central incisors. The magnetic sensors detected the mandibular movements in the sagittal plane by movement of the magnet. Masseter EMG was recorded by fine wire electrodes and amplified by a specially designed amplifier. The necessary preamplifiers were assembled as an integrated circuit (IC) chip in a small housing. The signals from the preamplifier were then passed through a signal processing unit and taped on an instrumentation tape. The system was applied to the freely moving rabbit supplied with food and water during the night. It worked without any trouble for more than 24 h. Since the implanted magnetic sensors were stable for more than 4 months, long-term recording could be done by merely reimplanting the magnet, the cables and the EMG electrodes, which was simple.

  20. Surface Electromyography for Speech and Swallowing Systems: Measurement, Analysis, and Interpretation

    ERIC Educational Resources Information Center

    Stepp, Cara E.

    2012-01-01

    Purpose: Applying surface electromyography (sEMG) to the study of voice, speech, and swallowing is becoming increasingly popular. An improved understanding of sEMG and building a consensus as to appropriate methodology will improve future research and clinical applications. Method: An updated review of the theory behind recording sEMG for the…

  1. Anomalous Effect of Surface Diffusion on NMR Signal: Tracing the Fiber Geometry

    NASA Astrophysics Data System (ADS)

    Apalkov, Vadym; Edirisinghe, Neranjan; Cymbalyuk, Gennady

    2008-03-01

    We show the strong qualitative effect of the surface diffusion channel on the echo attenuation of the NMR signal from restricted geometry, e.g. fiber system. In some range of parameters of the system the residual echo signal, which is obtained by subtracting the background value, can have anomalous behavior, which means that the echo signal has a maximum value at some finite value of the magnitude of the gradient pulses. This fact can be used to enhance the accuracy of the measurements by studying the echo signal around the maximum value. Effect described here could be also used for tuning the MRI measurements to trace fibers with particular characteristic diameters or for timely detection of changes in the diffusion coefficients and fiber diameters.

  2. Detecting Nasal Vowels in Speech Interfaces Based on Surface Electromyography

    PubMed Central

    Freitas, João; Teixeira, António; Silva, Samuel; Oliveira, Catarina; Dias, Miguel Sales

    2015-01-01

    Nasality is a very important characteristic of several languages, European Portuguese being one of them. This paper addresses the challenge of nasality detection in surface electromyography (EMG) based speech interfaces. We explore the existence of useful information about the velum movement and also assess if muscles deeper down in the face and neck region can be measured using surface electrodes, and the best electrode location to do so. The procedure we adopted uses Real-Time Magnetic Resonance Imaging (RT-MRI), collected from a set of speakers, providing a method to interpret EMG data. By ensuring compatible data recording conditions, and proper time alignment between the EMG and the RT-MRI data, we are able to accurately estimate the time when the velum moves and the type of movement when a nasal vowel occurs. The combination of these two sources revealed interesting and distinct characteristics in the EMG signal when a nasal vowel is uttered, which motivated a classification experiment. Overall results of this experiment provide evidence that it is possible to detect velum movement using sensors positioned below the ear, between mastoid process and the mandible, in the upper neck region. In a frame-based classification scenario, error rates as low as 32.5% for all speakers and 23.4% for the best speaker have been achieved, for nasal vowel detection. This outcome stands as an encouraging result, fostering the grounds for deeper exploration of the proposed approach as a promising route to the development of an EMG-based speech interface for languages with strong nasal characteristics. PMID:26069968

  3. Detecting Nasal Vowels in Speech Interfaces Based on Surface Electromyography.

    PubMed

    Freitas, João; Teixeira, António; Silva, Samuel; Oliveira, Catarina; Dias, Miguel Sales

    2015-01-01

    Nasality is a very important characteristic of several languages, European Portuguese being one of them. This paper addresses the challenge of nasality detection in surface electromyography (EMG) based speech interfaces. We explore the existence of useful information about the velum movement and also assess if muscles deeper down in the face and neck region can be measured using surface electrodes, and the best electrode location to do so. The procedure we adopted uses Real-Time Magnetic Resonance Imaging (RT-MRI), collected from a set of speakers, providing a method to interpret EMG data. By ensuring compatible data recording conditions, and proper time alignment between the EMG and the RT-MRI data, we are able to accurately estimate the time when the velum moves and the type of movement when a nasal vowel occurs. The combination of these two sources revealed interesting and distinct characteristics in the EMG signal when a nasal vowel is uttered, which motivated a classification experiment. Overall results of this experiment provide evidence that it is possible to detect velum movement using sensors positioned below the ear, between mastoid process and the mandible, in the upper neck region. In a frame-based classification scenario, error rates as low as 32.5% for all speakers and 23.4% for the best speaker have been achieved, for nasal vowel detection. This outcome stands as an encouraging result, fostering the grounds for deeper exploration of the proposed approach as a promising route to the development of an EMG-based speech interface for languages with strong nasal characteristics.

  4. Simultaneous measurement of human joint force, surface electromyograms, and functional MRI-measured brain activation.

    PubMed

    Liu, J Z; Dai, T H; Elster, T H; Sahgal, V; Brown, R W; Yue, G H

    2000-08-15

    Functional magnetic resonance imaging (fMRI) has been increasingly used in studying human brain function given its non-invasive feature and good spatial resolution. However, difficulties in acquiring data from peripheral (e.g. information from muscle) during fMRI studies of motor function hinder interpretation of fMRI data and designing more sophisticated investigations. Here we describe a system that was designed to concurrently measure handgrip force, surface electromyograms (EMG) of finger flexor and extensor muscles, and fMRI of human brain. The system included a pressure transducer built in a hydraulic environment, a heavily shielded EMG recording element, and a visual feedback structure for online monitoring of force and/or EMG signal, by the subject positioned in the scanner during an fMRI experiment. System evaluation and subsequent fMRI motor function studies have indicated that by using this system, high quality force and EMG signals can be recorded without sacrificing the quality of the fMRI data. PMID:10967361

  5. Experimental Study and Characterization of SEMG Signals for Upper Limbs

    NASA Astrophysics Data System (ADS)

    Veer, Karan

    2015-04-01

    Surface electromyogram (SEMG) is used to measure the activity of superficial muscles and is an essential tool to carry out biomechanical assessments required for prosthetic design. Many previous attempts suggest that, electromyogram (EMG) signals have random nature. Here, dual channel evaluation of EMG signals acquired from the amputed subjects using computational techniques for classification of arm motion are presented. After recording data from four predefined upper arm motions, interpretation of signal was done for six statistical features. The signals are classified by the neural network (NN) and then interpretation was done using statistical technique to extract the effectiveness of recorded signals. The network performances are analyzed by considering the number of input features, hidden layer, learning algorithm and mean square error. From the results, it is observed that there exists calculative difference in amplitude gain across different motions and have great potential to classify arm motions. The outcome indicates that NN algorithm performs significantly better than other algorithms with classification accuracy (CA) of 96.40%. Analysis of variance technique presents the results to validate the effectiveness of recorded data to discriminate SEMG signals. Results are of significant thrust in identifying the operations that can be implemented for classifying upper limb movements suitable for prostheses design.

  6. Processing Electromyographic Signals to Recognize Words

    NASA Technical Reports Server (NTRS)

    Jorgensen, C. C.; Lee, D. D.

    2009-01-01

    A recently invented speech-recognition method applies to words that are articulated by means of the tongue and throat muscles but are otherwise not voiced or, at most, are spoken sotto voce. This method could satisfy a need for speech recognition under circumstances in which normal audible speech is difficult, poses a hazard, is disturbing to listeners, or compromises privacy. The method could also be used to augment traditional speech recognition by providing an additional source of information about articulator activity. The method can be characterized as intermediate between (1) conventional speech recognition through processing of voice sounds and (2) a method, not yet developed, of processing electroencephalographic signals to extract unspoken words directly from thoughts. This method involves computational processing of digitized electromyographic (EMG) signals from muscle innervation acquired by surface electrodes under a subject's chin near the tongue and on the side of the subject s throat near the larynx. After preprocessing, digitization, and feature extraction, EMG signals are processed by a neural-network pattern classifier, implemented in software, that performs the bulk of the recognition task as described.

  7. Change Mechanisms in EMG Biofeedback Training: Cognitive Changes Underlying Improvements in Tension Headache.

    ERIC Educational Resources Information Center

    Holroyd, Kenneth A.; And Others

    1984-01-01

    Subjects (N=43) suffering from tension headache were assigned to one of four electromyograph (EMG) biofeedback conditions and were led to believe they were achieving high or moderate success in decreasing EMG activity. Regardless of actual EMG changes, subjects receiving high-success feedback showed greater improvement for headaches than…

  8. EMG patterns during assisted walking in the exoskeleton

    PubMed Central

    Sylos-Labini, Francesca; La Scaleia, Valentina; d'Avella, Andrea; Pisotta, Iolanda; Tamburella, Federica; Scivoletto, Giorgio; Molinari, Marco; Wang, Shiqian; Wang, Letian; van Asseldonk, Edwin; van der Kooij, Herman; Hoellinger, Thomas; Cheron, Guy; Thorsteinsson, Freygardur; Ilzkovitz, Michel; Gancet, Jeremi; Hauffe, Ralf; Zanov, Frank; Lacquaniti, Francesco; Ivanenko, Yuri P.

    2014-01-01

    Neuroprosthetic technology and robotic exoskeletons are being developed to facilitate stepping, reduce muscle efforts, and promote motor recovery. Nevertheless, the guidance forces of an exoskeleton may influence the sensory inputs, sensorimotor interactions and resulting muscle activity patterns during stepping. The aim of this study was to report the muscle activation patterns in a sample of intact and injured subjects while walking with a robotic exoskeleton and, in particular, to quantify the level of muscle activity during assisted gait. We recorded electromyographic (EMG) activity of different leg and arm muscles during overground walking in an exoskeleton in six healthy individuals and four spinal cord injury (SCI) participants. In SCI patients, EMG activity of the upper limb muscles was augmented while activation of leg muscles was typically small. Contrary to our expectations, however, in neurologically intact subjects, EMG activity of leg muscles was similar or even larger during exoskeleton-assisted walking compared to normal overground walking. In addition, significant variations in the EMG waveforms were found across different walking conditions. The most variable pattern was observed in the hamstring muscles. Overall, the results are consistent with a non-linear reorganization of the locomotor output when using the robotic stepping devices. The findings may contribute to our understanding of human-machine interactions and adaptation of locomotor activity patterns. PMID:24982628

  9. Effects of load on good morning kinematics and EMG activity.

    PubMed

    Vigotsky, Andrew David; Harper, Erin Nicole; Ryan, David Russell; Contreras, Bret

    2015-01-01

    Many strength and conditioning coaches utilize the good morning (GM) to strengthen the hamstrings and spinal erectors. However, little research exists on its electromyography (EMG) activity and kinematics, and how these variables change as a function of load. The purpose of this investigation was to examine how estimated hamstring length, integrated EMG (IEMG) activity of the hamstrings and spinal erectors, and kinematics of the lumbar spine, hip, knee, and ankle are affected by changes in load. Fifteen trained male participants (age = 24.6 ± 5.3 years; body mass = 84.7 ± 11.3 kg; height = 180.9 ± 6.8 cm) were recruited for this study. Participants performed five sets of the GM, utilizing 50, 60, 70, 80, and 90% of one-repetition maximum (1RM) in a randomized fashion. IEMG activity of hamstrings and spinal erectors tended to increase with load. Knee flexion increased with load on all trials. Estimated hamstring length decreased with load. However, lumbar flexion, hip flexion, and plantar flexion experienced no remarkable changes between trials. These data provide insight as to how changing the load of the GM affects EMG activity, kinematic variables, and estimated hamstring length. Implications for hamstring injury prevention are discussed. More research is needed for further insight as to how load affects EMG activity and kinematics of other exercises. PMID:25653899

  10. EMG Biofeedback Training Versus Systematic Desensitization for Test Anxiety Reduction

    ERIC Educational Resources Information Center

    Romano, John L.; Cabianca, William A.

    1978-01-01

    Biofeedback training to reduce test anxiety among university students was investigated. Biofeedback training with systematic desensitization was compared to an automated systematic desensitization program not using EMG feedback. Biofeedback training is a useful technique for reducing test anxiety, but not necessarily more effective than systematic…

  11. Effects of load on good morning kinematics and EMG activity.

    PubMed

    Vigotsky, Andrew David; Harper, Erin Nicole; Ryan, David Russell; Contreras, Bret

    2015-01-01

    Many strength and conditioning coaches utilize the good morning (GM) to strengthen the hamstrings and spinal erectors. However, little research exists on its electromyography (EMG) activity and kinematics, and how these variables change as a function of load. The purpose of this investigation was to examine how estimated hamstring length, integrated EMG (IEMG) activity of the hamstrings and spinal erectors, and kinematics of the lumbar spine, hip, knee, and ankle are affected by changes in load. Fifteen trained male participants (age = 24.6 ± 5.3 years; body mass = 84.7 ± 11.3 kg; height = 180.9 ± 6.8 cm) were recruited for this study. Participants performed five sets of the GM, utilizing 50, 60, 70, 80, and 90% of one-repetition maximum (1RM) in a randomized fashion. IEMG activity of hamstrings and spinal erectors tended to increase with load. Knee flexion increased with load on all trials. Estimated hamstring length decreased with load. However, lumbar flexion, hip flexion, and plantar flexion experienced no remarkable changes between trials. These data provide insight as to how changing the load of the GM affects EMG activity, kinematic variables, and estimated hamstring length. Implications for hamstring injury prevention are discussed. More research is needed for further insight as to how load affects EMG activity and kinematics of other exercises.

  12. EMG patterns during assisted walking in the exoskeleton.

    PubMed

    Sylos-Labini, Francesca; La Scaleia, Valentina; d'Avella, Andrea; Pisotta, Iolanda; Tamburella, Federica; Scivoletto, Giorgio; Molinari, Marco; Wang, Shiqian; Wang, Letian; van Asseldonk, Edwin; van der Kooij, Herman; Hoellinger, Thomas; Cheron, Guy; Thorsteinsson, Freygardur; Ilzkovitz, Michel; Gancet, Jeremi; Hauffe, Ralf; Zanov, Frank; Lacquaniti, Francesco; Ivanenko, Yuri P

    2014-01-01

    Neuroprosthetic technology and robotic exoskeletons are being developed to facilitate stepping, reduce muscle efforts, and promote motor recovery. Nevertheless, the guidance forces of an exoskeleton may influence the sensory inputs, sensorimotor interactions and resulting muscle activity patterns during stepping. The aim of this study was to report the muscle activation patterns in a sample of intact and injured subjects while walking with a robotic exoskeleton and, in particular, to quantify the level of muscle activity during assisted gait. We recorded electromyographic (EMG) activity of different leg and arm muscles during overground walking in an exoskeleton in six healthy individuals and four spinal cord injury (SCI) participants. In SCI patients, EMG activity of the upper limb muscles was augmented while activation of leg muscles was typically small. Contrary to our expectations, however, in neurologically intact subjects, EMG activity of leg muscles was similar or even larger during exoskeleton-assisted walking compared to normal overground walking. In addition, significant variations in the EMG waveforms were found across different walking conditions. The most variable pattern was observed in the hamstring muscles. Overall, the results are consistent with a non-linear reorganization of the locomotor output when using the robotic stepping devices. The findings may contribute to our understanding of human-machine interactions and adaptation of locomotor activity patterns.

  13. Vibration-induced changes in EMG during human locomotion.

    PubMed

    Verschueren, Sabine M P; Swinnen, Stephan P; Desloovere, Kaat; Duysens, Jacques

    2003-03-01

    The present study was set up to examine the contribution of Ia afferent input in the generation of electromyographic (EMG) activity. Subjects walked blindfolded along a walkway while tendon vibration was applied continuously to a leg muscle. The effects of vibration were measured on mean EMG activity in stance and swing phase. The results show that vibration of the quadriceps femoris (Q) at the knee and of biceps femoris (BF) at the knee enhanced the EMG activity of these muscles and this occurred mainly in the stance phase of walking. These results suggest involvement of Ia afferent input of Q and BF in EMG activation during stance. In contrast, vibration of muscles at the ankle and hip had no significant effect on burst amplitude. Additionally, the onset time of tibialis anterior was measured to look at timing of phase transitions. Only vibration of quadriceps femoris resulted in an earlier onset of tibialis anterior within the gait cycle, suggesting involvement of these Ia afferents in the triggering of phase transitions. In conclusion, the results of the present study suggest involvement of Ia afferent input in the control of muscle activity during locomotion in humans. A limited role in timing of phase transitions is proposed as well. PMID:12626612

  14. Effects of load on good morning kinematics and EMG activity

    PubMed Central

    Harper, Erin Nicole; Ryan, David Russell; Contreras, Bret

    2015-01-01

    Many strength and conditioning coaches utilize the good morning (GM) to strengthen the hamstrings and spinal erectors. However, little research exists on its electromyography (EMG) activity and kinematics, and how these variables change as a function of load. The purpose of this investigation was to examine how estimated hamstring length, integrated EMG (IEMG) activity of the hamstrings and spinal erectors, and kinematics of the lumbar spine, hip, knee, and ankle are affected by changes in load. Fifteen trained male participants (age = 24.6 ± 5.3 years; body mass = 84.7 ± 11.3 kg; height = 180.9 ± 6.8 cm) were recruited for this study. Participants performed five sets of the GM, utilizing 50, 60, 70, 80, and 90% of one-repetition maximum (1RM) in a randomized fashion. IEMG activity of hamstrings and spinal erectors tended to increase with load. Knee flexion increased with load on all trials. Estimated hamstring length decreased with load. However, lumbar flexion, hip flexion, and plantar flexion experienced no remarkable changes between trials. These data provide insight as to how changing the load of the GM affects EMG activity, kinematic variables, and estimated hamstring length. Implications for hamstring injury prevention are discussed. More research is needed for further insight as to how load affects EMG activity and kinematics of other exercises. PMID:25653899

  15. Liposomes with High Refractive Index Encapsulants as Tunable Signal Amplification Tools in Surface Plasmon Resonance Spectroscopy.

    PubMed

    Fenzl, Christoph; Hirsch, Thomas; Baeumner, Antje J

    2015-11-01

    One major goal in the surface plasmon resonance (SPR) technique is the reliable detection of small molecules as well as low analyte concentrations. This can be achieved by a viable signal amplification strategy. We therefore investigated optimal liposome characteristics for use as a signal enhancement system for SPR sensors, as liposomes excel not only at versatility but also at colloidal stability and ease of functionalization. These characteristics include the encapsulation of high refractive index markers, lipid composition, liposome size, and surface modifications to best match the requirements of the SPR system. Our studies of the binding of biotinylated liposomes to surface-immobilized streptavidin show that the refractive index of the encapsulant has a major influence on the SPR signal and outweighs the influence of the thin lipid bilayer. Thus, the signal amplification properties of liposomes can be adjusted to the respective needs of any analytical task by simply exchanging the encapsulant solution. In this work, a maximum enhancement factor of 23 was achieved by encapsulating a 500 mM sucrose solution. Dose-response studies with and without liposome enhancement revealed an improvement of the limit of detection from 10 nmol L(-1) to 320 pmol L(-1) streptavidin concentration with a much higher sensitivity of 3 mRIU per logarithmic unit of the concentration between 500 pmol L(-1) and 10 nmol L(-1). PMID:26455696

  16. Near-surface epigenetic magnetic indicators of buried hydrocarbons and separation of spurious signals

    SciTech Connect

    Donovan, T.J.; O'Brien, D.P.; Bryan, J.G.; Shepherd, M.A.

    1986-05-01

    Significant geochemical alteration zones occurring over buried hydrocarbon deposits can be recognized and mapped by geophysical methods. The authors believe near-surface secondary magnetic minerals formed as a result of seeping hydrocarbons and associated compounds interacting with constituents of the overlying rocks. A new method is described to identify anomalous magnetic signatures associated with this mineralization, and to differentiate that signal from cultural interference and other surface shallow, and intermediate-depth geologic sources. Using low-altitude, high-sensitivity aeromagnetic data, the separation involves detailed spectral analysis, subsequent band-pass filtering, and analytic signal transformation of the filtered data. Depicted in contour form, the analytic signal minimizes spatial aliasing and allows us to map the areal distribution of subtle, near-surface anomalies related to probable epigenetic magnetic mineralization. This method is illustrated using data from the Arctic National Wildlife Refuge and Cook Inlet, Alaska, and from offshore Texas, where high-resolution seismic data support the aeromagnetic interpretation and suggest important structural controls. Correlations of published detailed gravimeter and low-altitude aeromagnetic data at the Cement oil field, Oklahoma, were coupled with interactive modeling studies. Except for the obvious extreme high wave-number spikes, cultural contamination cannot be responsible for the high wave-number signal there, and the epigenetic magnetic mineralization may be more extensive vertically than originally suggested.

  17. Analysis of motor units with high-density surface electromyography.

    PubMed

    Merletti, Roberto; Holobar, Ales; Farina, Dario

    2008-12-01

    Although the behaviour of individual motor units is classically studied with intramuscular EMG, recently developed techniques allow its analysis also from EMG recorded in multiple locations over the skin surface (high-density surface EMG). The analysis of motor units from the surface EMG is useful when the insertion of needles is not desirable or not possible. Moreover, surface EMG allows the measure of motor unit properties which are difficult to assess with invasive technology (e.g., muscle fiber conduction velocity or location of innervation zones) and may increase the number of detectable motor units with respect to selective intramuscular recordings. Although some limitations remain, both the discharge pattern and muscle fiber properties of individual motor units can currently be analyzed non-invasively. This review presents the conditions and methodologies which allow the investigation of motor units with surface EMG.

  18. An improved response surface methodology algorithm with an application to traffic signal optimization for urban networks

    SciTech Connect

    Joshi, S.S.; Rathi, A.K.; Tew, J.D.

    1995-12-31

    This paper illustrates the use of the simulation-optimization technique of response surface methodology (RSM) in traffic signal optimization of urban networks. It also quantifies the gains of using the common random number (CRN) variance reduction strategy in such an optimization procedure. An enhanced RSM algorithm which employs conjugate gradient search techniques and successive second-order models is presented instead of the conventional approach. An illustrative example using an urban traffic network exhibits the superiority of using the CRN strategy ovr direct simulation in performing traffic signal optimization. Relative performance of the two strategies is quantified with computational results using the total network-wide delay as the measure of effectivness.

  19. Sex Discrimination in Gerris remigis: Role of a Surface Wave Signal.

    PubMed

    Wilcox, R S

    1979-12-14

    Even when blinded with masks, adult male water striders (Gerris remigis) accurately ascertain the sex of other adult water striders in the laboratory. Freely moving females that were artificially made to play back computer-generated male surface wave and body-contact signals of about 90 waves per second were treated as males by the masked males and as females when no such playbacks were made. Thus, the males can use presence or absence of the male signal as the sole means for sex discrimination.

  20. EMG/ECG Acquisition System with Online Adjustable Parameters Using ZigBee Wireless Technology

    NASA Astrophysics Data System (ADS)

    Kobayashi, Hiroyuki

    This paper deals with a novel wireless bio-signal acquisition system employing ZigBee wireless technology, which consists of mainly two components, that is, intelligent electrode and data acquisition host. The former is the main topic of this paper. It is put on a subject's body to amplify bio-signal such as EMG or ECG and stream its data at upto 2 ksps. One of the most remarkable feature of the intelligent electrode is that it can change its own parameters including both digital and analog ones on-line. The author describes its design first, then introduces a small, light and low cost implementation of the intelligent electrode named as “VAMPIRE-BAT.” And he show some experimental results to confirm its usability and to estimate its practical performances.

  1. Effect of manipulation of plasma lactate on integrated EMG during cycling.

    PubMed

    Seburn, K L; Sanderson, D J; Belcastro, A N; McKenzie, D C

    1992-08-01

    This investigation was undertaken to record electromyographic activity of the vastus lateralis muscle during incremental cycling exercise and to determine whether it would be sensitive to altered dynamics of plasma lactate increases seen with intense exercise. Trained cyclists (N = 6) performed two progressive, stepwise exercise tests (23.5 W.min-1) to fatigue on a cycle ergometer at 90 rpm. One of the exercise tests was preceded by arm ergometer exercise in an attempt to elevate the circulating plasma lactate levels prior to starting the criterion exercise test. The starting mean plasma lactate values were 4.59 and 26.69 mmol lactate.-1 for the two exercise sessions. Cardiorespiratory values did not differ significantly between exercise sessions completed in the absence and presence of increased circulating plasma lactate. The no-arm trial (i.e., nonelevated plasma lactate condition) was associated with a plasma lactate inflection point (Tlac) at 72.6% VO2max. Previous arm exercise elevated the lactate such that during the criterion exercise plasma lactate values were decreasing with increasing power output at lower exercise intensities. As exercise intensity increased lactate values also increased beginning at a power output of about 76% VO2 max. Mean per cycle integrated EMG (CIEMG) increased linearly with increased power output in both exercise sessions. The slopes of the EMG-power output curve were not significantly different (P less than 0.05). There were no inflection points in these curves. The absence of an inflection point show that surface EMG does not provide an indication of Tlac. PMID:1406177

  2. Convective Signals from Surface Measurements at ARM Tropical Western Pacific Site: Manus

    SciTech Connect

    Wang, Yi; Long, Charles N.; Mather, James H.; Liu, Xiaodong

    2011-02-23

    The Madden-Julian Oscillation (MJO) signal has been detected using observations from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Tropical Western Pacific (TWP). With downwelling shortwave radiative fluxes and fractional sky cover from the ACRF TWP Manus site, and the statistical tools of wavelet and spectrum power, we report finding major convective signals from surface observations spanning the period from 1996 to 2006. Our findings are confirmed with the satellite-retrieved values of precipitation from the Global Precipitation Climatology Project (GPCP), and interpolated outgoing longwave radiation (OLR) satellite measurements from the National Oceanic and Atmospheric Administration (NOAA) for the same location. Our results indicate that the MJO convective signal has a strong seasonal-to-interannual evolution that is likely correlated with the interannual variability of El Ni ˜no Southern Oscillation (ENSO).

  3. Amplification of optical signals in Bi{sub 12}TiO{sub 20} crystal by photorefractive surface waves

    SciTech Connect

    Khomenko, A.V.; Garcia-Weidner, A.; Kamshilin, A.A.

    1996-07-01

    We have demonstrated experimentally beam amplification by coupling between the signal beam and the photorefractive surfaces wave in Bi{sub 12}TiO{sub 20} crystal. A gain of 16,000 has been measured, with an output signal-to-noise ratio of {approx_gt}20 for weak input signals. {copyright} {ital 1996 Optical Society of America.}

  4. Identification of multiple-input systems with highly coupled inputs: application to EMG prediction from multiple intracortical electrodes.

    PubMed

    Westwick, David T; Pohlmeyer, Eric A; Solla, Sara A; Miller, Lee E; Perreault, Eric J

    2006-02-01

    A robust identification algorithm has been developed for linear, time-invariant, multiple-input single-output systems, with an emphasis on how this algorithm can be used to estimate the dynamic relationship between a set of neural recordings and related physiological signals. The identification algorithm provides a decomposition of the system output such that each component is uniquely attributable to a specific input signal, and then reduces the complexity of the estimation problem by discarding those input signals that are deemed to be insignificant. Numerical difficulties due to limited input bandwidth and correlations among the inputs are addressed using a robust estimation technique based on singular value decomposition. The algorithm has been evaluated on both simulated and experimental data. The latter involved estimating the relationship between up to 40 simultaneously recorded motor cortical signals and peripheral electromyograms (EMGs) from four upper limb muscles in a freely moving primate. The algorithm performed well in both cases: it provided reliable estimates of the system output and significantly reduced the number of inputs needed for output prediction. For example, although physiological recordings from up to 40 different neuronal signals were available, the input selection algorithm reduced this to 10 neuronal signals that made significant contributions to the recorded EMGs.

  5. Identification of Multiple-Input Systems with Highly Coupled Inputs: Application to EMG Prediction from Multiple Intracortical Electrodes

    PubMed Central

    Westwick, David T.; Pohlmeyer, Eric A.; Solla, Sara A.; Miller, Lee E.; Perreault, Eric J.

    2008-01-01

    A robust identification algorithm has been developed for linear, time-invariant, multiple-input single-output systems, with an emphasis on how this algorithm can be used to estimate the dynamic relationship between a set of neural recordings and related physiological signals. The identification algorithm provides a decomposition of the system output such that each component is uniquely attributable to a specific input signal, and then reduces the complexity of the estimation problem by discarding those input signals that are deemed to be insignificant. Numerical difficulties due to limited input bandwidth and correlations among the inputs are addressed using a robust estimation technique based on singular value decomposition. The algorithm has been evaluated on both simulated and experimental data. The latter involved estimating the relationship between up to 40 simultaneously recorded motor cortical signals and peripheral electromyograms (EMGs) from four upper limb muscles in a freely moving primate. The algorithm performed well in both cases: it provided reliable estimates of the system output and significantly reduced the number of inputs needed for output prediction. For example, although physiological recordings from up to 40 different neuronal signals were available, the input selection algorithm reduced this to 10 neuronal signals that made significant contributions to the recorded EMGs. PMID:16378517

  6. The pattern of anthropogenic signal emergence in Greenland Ice Sheet surface mass balance

    NASA Astrophysics Data System (ADS)

    Fyke, Jeremy G.; Vizcaíno, Miren; Lipscomb, William H.

    2014-08-01

    Surface mass balance (SMB) trends influence observed Greenland Ice Sheet (GrIS) mass loss, but the component of these trends related to anthropogenic forcing is unclear. Here we study the simulated spatial pattern of emergence of an anthropogenically derived GrIS SMB signal between 1850 and 2100 using the Community Earth System Model. We find emergence timing heterogeneity, with a bimodal structure reflecting interior snowfall increases against a background of low SMB variability, and peripheral surface melting increases against a backdrop of high SMB variability. We also find a nonemerging intermediate region. We conclude that (1) a bimodal pattern of GrIS SMB change will unambiguously reflect the impact of anthropogenic forcing; (2) present-day peripheral and interior SMB trends likely have an underlying anthropogenically forced component; (3) local emergence occurs well before emergence of a spatially integrated signal; and (4) the GrIS summit region may be an ideal location for monitoring regional/global climate change.

  7. Detecting secondary structure and surface orientation of helical peptide monolayers from resonant hybridization signals

    NASA Astrophysics Data System (ADS)

    Alici, Kamil Boratay; Gallardo, Ignacio F.

    2013-10-01

    Hybridization of dominant vibrational modes with meta-surface resonance allows detection of both structural changes and surface orientations of bound helical peptides. Depending on the resonance frequency of meta-molecules, a red- or blue- shift in peptide Amide-I frequency is observed. The underlying coupling mechanism is described by using a temporal coupled mode theory that is in very good agreement with the experimental results. This hybridization phenomenon constitutes the basis of many nanophotonic systems such as tunable coupled mode bio-sensors and dynamic peptide systems driven by infrared signals.

  8. Detecting secondary structure and surface orientation of helical peptide monolayers from resonant hybridization signals

    PubMed Central

    Alici, Kamil Boratay; Gallardo, Ignacio F.

    2013-01-01

    Hybridization of dominant vibrational modes with meta-surface resonance allows detection of both structural changes and surface orientations of bound helical peptides. Depending on the resonance frequency of meta-molecules, a red- or blue- shift in peptide Amide-I frequency is observed. The underlying coupling mechanism is described by using a temporal coupled mode theory that is in very good agreement with the experimental results. This hybridization phenomenon constitutes the basis of many nanophotonic systems such as tunable coupled mode bio-sensors and dynamic peptide systems driven by infrared signals. PMID:24129763

  9. Signaling activities of the Drosophila wingless gene are separately mutable and appear to be transduced at the cell surface

    SciTech Connect

    Bejsovec, A.; Wieschaus, E.

    1995-01-01

    The Drosophila segment polarity gene wingless encodes an intercellular signaling molecule that transmits positional information during development of the embryonic epidermis. We have explored the mechanism of wg signal transduction by perturbing cellular processes genetically and by performing structure/function analysis of the Wg protein. We present evidence that Wingless protein may transduce signal at the cell surface and that Wg may bind to its cell surface receptor without necessarily activating it. We demonstrate that two specific signaling activities of the Wg molecule can be disrupted independently by mutation. Sequence analysis indicates that these different signaling activities are not promoted by discrete functional domains, but rather that the overall conformation of the molecule may control distinct signaling functions. We conclude that wg signaling may involve complex interactions between the Wg ligand and its cell surface receptor molecule(s) and that some of this complexity resides within the Wg ligand itself. 48 refs., 6 figs.

  10. Signaling Activities of the Drosophila Wingless Gene Are Separately Mutable and Appear to Be Transduced at the Cell Surface

    PubMed Central

    Bejsovec, A.; Wieschaus, E.

    1995-01-01

    The Drosophila segment polarity gene wingless encodes an intercellular signaling molecule that transmits positional information during development of the embryonic epidermis. We have explored the mechanism of wg signal transduction by perturbing cellular processes genetically and by performing structure/function analysis of the Wg protein. We present evidence that Wingless protein may transduce signal at the cell surface and that Wg may bind to its cell surface receptor without necessarily activating it. We demonstrate that two specific signaling activities of the Wg molecule can be disrupted independently by mutation. Sequence analysis indicates that these different signaling activities are not promoted by discrete functional domains, but rather that the overall conformation of the molecule may control distinct signaling functions. We conclude that wg signaling may involve complex interactions between the Wg ligand and its cell surface receptor molecule(s) and that some of this complexity resides within the Wg ligand itself. PMID:7705631

  11. A quantitative analysis of signal reproduction from cylinder recordings measured via noncontact full surface mapping.

    PubMed

    Nascè, Antony; Hill, Martyn; McBride, John W; Boltryk, Peter J

    2008-10-01

    Sound reproduction via a noncontact surface mapping technique has great potential for sound archives, aiming to digitize content from early sound recordings such as wax cylinders, which may otherwise be "unplayable" with a stylus. If the noncontact techniques are to be considered a viable solution for sound archivists, a method for quantifying the quality of the reproduced signal needs to be developed. In this study, a specially produced test cylinder recording, encoded with sinusoids, provides the basis for the first quantitative analysis of signal reproduction from the noncontact full surface mapping method. The sampling and resolution of the measurement system are considered with respect to the requirements for digital archiving of cylinder recordings. Two different methods of audio signal estimation from a discrete groove cross section are described and rated in terms of signal-to-noise ratio and total harmonic distortion. Noncontact and stylus methods of sound reproduction are then compared using the same test cylinder. It is shown that noncontact methods appear to have distinct advantages over stylus reproduction, in terms of reduced harmonic distortion and lower frequency modulation. PMID:19062844

  12. Dual-modal silica nanoprobes with surface enhanced Raman spectroscopic and fluorescent signals

    NASA Astrophysics Data System (ADS)

    Lee, Sang-Myung

    2015-07-01

    We present that dual-modal silica nanoprobes based on surface enhanced Raman spectroscopy (SERS) and fluorescence, demonstrating the several combinations of two spectroscopic signals for the noble combinatorial nanoprobes (F-SERS dot). Their synthetic procedure was introduced and dual-modal spectroscopic analyses were performed as preliminary studies. Hopefully, F-SERS dots will be one of promising and multifunctional nanoprobes for the various in vitro and in vivo biological diagnoses and screenings.

  13. Nanometer Scale Titanium Surface Texturing Are Detected by Signaling Pathways Involving Transient FAK and Src Activations

    PubMed Central

    Zambuzzi, Willian F.; Bonfante, Estevam A.; Jimbo, Ryo; Hayashi, Mariko; Andersson, Martin; Alves, Gutemberg; Takamori, Esther R.; Beltrão, Paulo J.; Coelho, Paulo G.; Granjeiro, José M.

    2014-01-01

    Background It is known that physico/chemical alterations on biomaterial surfaces have the capability to modulate cellular behavior, affecting early tissue repair. Such surface modifications are aimed to improve early healing response and, clinically, offer the possibility to shorten the time from implant placement to functional loading. Since FAK and Src are intracellular proteins able to predict the quality of osteoblast adhesion, this study evaluated the osteoblast behavior in response to nanometer scale titanium surface texturing by monitoring FAK and Src phosphorylations. Methodology Four engineered titanium surfaces were used for the study: machined (M), dual acid-etched (DAA), resorbable media microblasted and acid-etched (MBAA), and acid-etch microblasted (AAMB). Surfaces were characterized by scanning electron microscopy, interferometry, atomic force microscopy, x-ray photoelectron spectroscopy and energy dispersive X-ray spectroscopy. Thereafter, those 4 samples were used to evaluate their cytotoxicity and interference on FAK and Src phosphorylations. Both Src and FAK were investigated by using specific antibody against specific phosphorylation sites. Principal Findings The results showed that both FAK and Src activations were differently modulated as a function of titanium surfaces physico/chemical configuration and protein adsorption. Conclusions It can be suggested that signaling pathways involving both FAK and Src could provide biomarkers to predict osteoblast adhesion onto different surfaces. PMID:24999733

  14. EMG-Driven Forward-Dynamic Estimation of Muscle Force and Joint Moment about Multiple Degrees of Freedom in the Human Lower Extremity

    PubMed Central

    Sartori, Massimo; Reggiani, Monica; Farina, Dario; Lloyd, David G.

    2012-01-01

    This work examined if currently available electromyography (EMG) driven models, that are calibrated to satisfy joint moments about one single degree of freedom (DOF), could provide the same musculotendon unit (MTU) force solution, when driven by the same input data, but calibrated about a different DOF. We then developed a novel and comprehensive EMG-driven model of the human lower extremity that used EMG signals from 16 muscle groups to drive 34 MTUs and satisfy the resulting joint moments simultaneously produced about four DOFs during different motor tasks. This also led to the development of a calibration procedure that allowed identifying a set of subject-specific parameters that ensured physiological behavior for the 34 MTUs. Results showed that currently available single-DOF models did not provide the same unique MTU force solution for the same input data. On the other hand, the MTU force solution predicted by our proposed multi-DOF model satisfied joint moments about multiple DOFs without loss of accuracy compared to single-DOF models corresponding to each of the four DOFs. The predicted MTU force solution was (1) a function of experimentally measured EMGs, (2) the result of physiological MTU excitation, (3) reflected different MTU contraction strategies associated to different motor tasks, (4) coordinated a greater number of MTUs with respect to currently available single-DOF models, and (5) was not specific to an individual DOF dynamics. Therefore, our proposed methodology has the potential of producing a more dynamically consistent and generalizable MTU force solution than was possible using single-DOF EMG-driven models. This will help better address the important scientific questions previously approached using single-DOF EMG-driven modeling. Furthermore, it might have applications in the development of human-machine interfaces for assistive devices. PMID:23300725

  15. Surface electromyogram for the control of anthropomorphic teleoperator fingers.

    PubMed

    Gupta, V; Reddy, N P

    1996-01-01

    Growing importance of telesurgery has led to the need for the development of synergistic control of anthropomorphic teleoperators. Synergistic systems can be developed using direct biological control. The purpose of this study was to develop techniques for direct biocontrol of anthropomorphic teleoperators using surface electromyogram (EMG). A computer model of a two finger teleoperator was developed and controlled using surface EMG from the flexor digitorum superficialis during flexion-extension of the index finger. The results of the study revealed a linear relationship between the RMS EMG and the flexion-extension of the finger model. Therefore, surface EMG can be used as a direct biocontrol for teleoperators and in VR applications.

  16. Comparison of sensor structures for the signal amplification of surface plasmon resonance immunoassay using enzyme precipitation

    NASA Astrophysics Data System (ADS)

    Yang, Chih-Tsung; Thierry, Benjamin

    2015-12-01

    Surface plasmon resonance (SPR) biosensing has been successfully applied for the label-free detection of a broad range of bioanalytes ranging from bacteria, cell, exosome, protein and nucleic acids. When it comes to the detection of small molecules or analytes found at low concentration, amplification schemes are desirable to enhance binding signals and in turn increase sensitivity. A number of SPR signal amplification schemes have been developed and validated; however, little effort has been devoted to understanding the effect of the SPR sensor structures on the amplification of binding signals and therefore on the overall sensing performance. The physical phenomenon of long-range SPR (LRSPR) relies on the propagation of coupled surface plasmonic waves on the opposite sides of a nanoscale-thick noble metal film suspended between two dielectrics with similar refractive indices. Importantly, as compared with commonly used conventional SPR (cSPR), LRSPR is not only characterized by a longer penetration depth of the plasmonic waves in the analyzed medium but also by a greater sensitivity to bulk refractive index changes. In this work, an immunoassay signal amplification platform based on horseradish peroxidase (HRP) catalyzed precipitation was utilized to investigate the sensing performance with regards to cSPR and LRSPR. The enzymatic precipitation of 3, 3'-diaminobenzidine tetrahydrochloride (DAB)/H2O2 was used to amplify SPR signals. The structure-function relationship of cSPR and LRSPR sensors is presented for both standard refractometric measurements and the enzymatic precipitation scheme. Experimental data shows that despite its inherent higher sensitivity to bulk refractive index changes and higher figure of merit, LRSPR was characterized by a lower angular sensitivity in the model enzymatic amplification scheme used here.

  17. A method to combine numerical optimization and EMG data for the estimation of joint moments under dynamic conditions.

    PubMed

    Amarantini, David; Martin, Luc

    2004-09-01

    To solve the problem of muscle redundancy at the level of opposing muscle groups, an alternative method to inverse dynamics must be employed. Considering the advantages of existing alternatives, the present study was aimed to compute knee joint moments under dynamic conditions using electromyographic (EMG) signals combined with non-linear constrained optimization in a single routine. The associated mathematical problems accounted for muscle behavior in an attempt to obtain accurate predictions of the resultant moment as well as physiologically realistic estimates of agonist and antagonist moments. The experiment protocol comprised (1) isometric trials to determine the most effective EMG processing for the prediction of the resultant moment and (2) stepping-in-place trials for the calculation of joint moments from processed EMG under dynamic conditions. Quantitative comparisons of the model predictions with the output of a biological-based model, showed that the proposed method (1) produced the most accurate estimates of the resultant moment and (2) avoided possible inconsistencies by enforcing appropriate constraints. As a possible solution for solving the redundancy problem under dynamic conditions, the proposed optimization formulation also led to realistic predictions of agonist and antagonist moments.

  18. The signaling phospholipid PIP3 creates a new interaction surface on the nuclear receptor SF-1

    DOE PAGESBeta

    Blind, Raymond D.; Sablin, Elena P.; Kuchenbecker, Kristopher M.; Chiu, Hsiu-Ju; Deacon, Ashley M.; Das, Debanu; Fletterick, Robert J.; Ingraham, Holly A.

    2014-10-06

    We previously reported that lipids PI(4,5)P2 (PIP2) and PI(3,4,5)P3 (PIP3) bind NR5A nuclear receptors to regulate their activity. Here, the crystal structures of PIP2 and PIP3 bound to NR5A1 (SF-1) define a new interaction surface that is organized by the solvent-exposed PIPn headgroups. We find that stabilization by the PIP3 ligand propagates a signal that increases coactivator recruitment to SF-1, consistent with our earlier work showing that PIP3 increases SF-1 activity. This newly created surface harbors a cluster of human mutations that lead to endocrine disorders, thus explaining how these puzzling mutations cripple SF-1 activity. Finally, we propose that thismore » new surface acts as a PIP3-regulated interface between SF-1 and coregulatory proteins, analogous to the function of membrane-bound phosphoinositides.« less

  19. Surface electromyography analysis in long-term recordings: application to head rest comfort in cars.

    PubMed

    Duchêne, J; Lamotte, T

    2001-02-20

    Analysis of long-term surface electromyographic (SEMG) signals has many applications in ergonomics when related to muscle fatigue. The present work proposes a set of processing methods reporting SEMG modifications during long-term driving tests in various situations (with or without head rest). A segmentation/classification algorithm allows signal splitting into homogeneous parts (postural activity and EMG bursts) and an efficient artefact suppression. Postural activity modifications are evaluated from time-varying amplitude probability density function (TAPDF) parameters. EMG burst analysis is achieved taking into account the relationships of these bursts with accelerometric events. This segmentation/classification procedure improves repeatability but does not significantly modify the overall results obtained before segmentation, as far as the analysis of head rest influence is concerned.

  20. Respiratory burst in human B lymphocytes. Triggering of surface Ig receptors induces modulation of chemiluminescence signal.

    PubMed

    Leca, G; Benichou, G; Bensussan, A; Mitenne, F; Galanaud, P; Vazquez, A

    1991-05-15

    B lymphocytes have been shown to proliferate and release oxygen metabolites when surface Ig is cross-linked and when stimulated with phorbol ester. Biochemical evidence has been provided for the presence of a superoxide generating system in B cells, which seems to be identical to the well-characterized NADPH-oxidase of phagocytes. In this report, we show that normal and EBV-transformed B cells produce superoxide anions after stimulation with phorbol ester and when surface Ig was cross-linked, as detected by lucigenin-dependent chemiluminescence. Anti-surface IgG antibodies induced a significant respiratory burst whereas those directed against surface IgM had no effect on B cell oxidative metabolism. Prestimulated B lymphocytes responded to further triggering by the same or another ligand. Pretreatment with Staphlococcus aureus Cowan I strain (SAC) or anti-IgM antibodies resulted in complete unresponsiveness to subsequent SAC or anti-IgG stimulation, but it did not affect PMA- and ionomycin-mediated B cell chemiluminescence. In contrast to preincubation with anti-IgM antibodies, the pretreatment of B cells with SAC induced a transient inhibitory effect on B cell signaling. In fact, SAC-pretreated B lymphocytes could be restimulated with the same ligand when blast cells were isolated. Furthermore, a 24-h incubation of the pretreated B cells in the absence of SAC completely restored the SAC-mediated respiratory burst. These results suggest that two distinct mechanisms may account for SAC- and anti-IgM-induced inhibition: a transient and reversible modulation of surface Ig, induced by SAC, and a long-lasting desensitization of the surface Ig receptors, respectively. These findings may have interesting implications for understanding the transduction of negative signals in B lymphocytes.

  1. Development of an implanted intramuscular EMG-triggered FES system for ambulation after incomplete spinal cord injury.

    PubMed

    Dutta, Anirban; Kobetic, Rudi; Triolo, Ronald

    2009-01-01

    Ambulation after spinal cord injury is possible with the aid of neuroprosthesis employing functional electrical stimulation (FES). Individuals with incomplete spinal cord injury (iSCI) retain partial volitional control of muscles below the level of injury, necessitating careful integration of FES with intact voluntary motor function for efficient walking. In this study, the intramuscular electromyogram (iEMG) was used to detect the intent to step and trigger FES-assisted walking in a volunteer with iSCI via an implanted neuroprosthesis consisting of two channels of bipolar iEMG signal acquisition and 12 independent channels of stimulation. The detection was performed with two types of classifiers- a threshold-based classifier that compared the running mean of the iEMG with a discrimination threshold to generate the trigger and a pattern recognition classifier that compared the time-history of the iEMG with a specified template of activity to generate the trigger whenever the cross-correlation coefficient exceeded a discrimination threshold. The pattern recognition classifier generally outperformed the threshold-based classifier, particularly with respect to minimizing False Positive triggers. The overall True Positive rates for the threshold-based classifier were 61.6% and 87.2% for the right and left steps with overall False Positive rates of 38.4% and 33.3%. The overall True Positive rates for the left and right step with the pattern recognition classifier were 57.2% and 93.3% and the overall False Positive rates were 11.9% and 24.4%. The subject showed no preference for either the threshold or pattern recognition-based classifier as determined by the Usability Rating Scale (URS) score collected after each trial and both the classifiers were perceived as moderately easy to use.

  2. In vivo EMG biofeedback in violin and viola pedagogy.

    PubMed

    LeVine, W R; Irvine, J K

    1984-06-01

    In vivo EMG biofeedback was found to be an effective pedagogical tool for removing unwanted left-hand tension in nine violin and viola players. Improvement occurred rapidly and persisted throughout a 5-month follow-up period. Further studies will be necessary to assess the effect of biofeedback independent of placebo effects. The brevity of the method and the magnitude of improvement warrant further investigation. PMID:6509108

  3. A comparison of two gluteus maximus EMG maximum voluntary isometric contraction positions

    PubMed Central

    Contreras, Bret; Schoenfeld, Brad J.; Beardsley, Chris; Cronin, John

    2015-01-01

    Background. The purpose of this study was to compare the peak electromyography (EMG) of the most commonly-used position in the literature, the prone bent-leg (90°) hip extension against manual resistance applied to the distal thigh (PRONE), to a novel position, the standing glute squeeze (SQUEEZE). Methods. Surface EMG electrodes were placed on the upper and lower gluteus maximus of thirteen recreationally active females (age = 28.9 years; height = 164 cm; body mass = 58.2 kg), before three maximum voluntary isometric contraction (MVIC) trials for each position were obtained in a randomized, counterbalanced fashion. Results. No statistically significant (p < 0.05) differences were observed between PRONE (upper: 91.94%; lower: 94.52%) and SQUEEZE (upper: 92.04%; lower: 85.12%) for both the upper and lower gluteus maximus. Neither the PRONE nor SQUEEZE was more effective between all subjects. Conclusions. In agreement with other studies, no single testing position is ideal for every participant. Therefore, it is recommended that investigators employ multiple MVIC positions, when possible, to ensure accuracy. Future research should investigate a variety of gluteus maximus MVIC positions in heterogeneous samples. PMID:26417543

  4. A comparison of two gluteus maximus EMG maximum voluntary isometric contraction positions.

    PubMed

    Contreras, Bret; Vigotsky, Andrew D; Schoenfeld, Brad J; Beardsley, Chris; Cronin, John

    2015-01-01

    Background. The purpose of this study was to compare the peak electromyography (EMG) of the most commonly-used position in the literature, the prone bent-leg (90°) hip extension against manual resistance applied to the distal thigh (PRONE), to a novel position, the standing glute squeeze (SQUEEZE). Methods. Surface EMG electrodes were placed on the upper and lower gluteus maximus of thirteen recreationally active females (age = 28.9 years; height = 164 cm; body mass = 58.2 kg), before three maximum voluntary isometric contraction (MVIC) trials for each position were obtained in a randomized, counterbalanced fashion. Results. No statistically significant (p < 0.05) differences were observed between PRONE (upper: 91.94%; lower: 94.52%) and SQUEEZE (upper: 92.04%; lower: 85.12%) for both the upper and lower gluteus maximus. Neither the PRONE nor SQUEEZE was more effective between all subjects. Conclusions. In agreement with other studies, no single testing position is ideal for every participant. Therefore, it is recommended that investigators employ multiple MVIC positions, when possible, to ensure accuracy. Future research should investigate a variety of gluteus maximus MVIC positions in heterogeneous samples.

  5. EMG profiles of knee joint musculature during walking: changes induced by anterior cruciate ligament deficiency.

    PubMed

    Limbird, T J; Shiavi, R; Frazer, M; Borra, H

    1988-01-01

    A tear of the anterior cruciate ligament (ACL) disrupts the delicate balance of static stabilizers of the knee, leading to significant alterations in joint kinematics. Little is known about the dynamic compensatory responses of the patient to these kinematic alterations. This lack of quantitative information on the muscle synergy patterns has limited the surgeon's ability to evaluate various operative and rehabilitative techniques. Twelve subjects with documented ACL deficiency for at least 1 year and 15 normal participants were studied. Each subject was asked to walk at free and fast speeds on a 12 m walkway. The right and left foot contact patterns and the linear envelopes from the surface electromyogram (EMG) patterns of the gastrocnemius, medial and lateral hamstrings, rectus femoris, and vastus lateralis were measured. Significant differences were found in the muscle synergy patterns during walking. During the swing-to-stance transition, the ACL-deficient subjects showed significantly less activity in the quadriceps and gastrocnemius muscles and more activity in the biceps femoris than in the normal group. During early swing, the vastus lateralis is more active than normal, and during midstance and terminal stance, the hamstrings appear to be less active than normal subjects. These dynamic compensatory mechanisms suggest that use of the hamstring tendons in reconstructive procedures may alter important compensatory mechanisms about the knee joint. Application of dynamic EMG techniques to the study of reconstructive procedures should provide additional information that will assist the clinician in the rational choice of a surgical procedure.

  6. Selection of Antibodies Interfering with Cell Surface Receptor Signaling Using Embryonic Stem Cell Differentiation.

    PubMed

    Melidoni, Anna N; Dyson, Michael R; McCafferty, John

    2016-01-01

    Antibodies able to bind and modify the function of cell surface signaling components in vivo are increasingly being used as therapeutic drugs. The identification of such "functional" antibodies from within large antibody pools is, therefore, the subject of intense research. Here we describe a novel cell-based expression and reporting system for the identification of functional antibodies from antigen-binding populations preselected with phage display. The system involves inducible expression of the antibody gene population from the Rosa-26 locus of embryonic stem (ES) cells, followed by secretion of the antibodies during ES cell differentiation. Target antigens are cell-surface signaling components (receptors or ligands) with a known effect on the direction of cell differentiation (FGFR1 mediating ES cell exit from self renewal in this particular protocol). Therefore, inhibition or activation of these components by functional antibodies in a few elite clones causes a shift in the differentiation outcomes of these clones, leading to their phenotypic selection. Functional antibody genes are then recovered from positive clones and used to produce the purified antibodies, which can be tested for their ability to affect cell fates exogenously. Identified functional antibody genes can be further introduced in different stem cell types. Inducible expression of functional antibodies has a temporally controlled protein-knockdown capability, which can be used to study the unknown role of the signaling pathway in different developmental contexts. Moreover, it provides a means for control of stem cell differentiation with potential in vivo applications.

  7. Usp12 stabilizes the T-cell receptor complex at the cell surface during signaling

    PubMed Central

    Jahan, Akhee S.; Lestra, Maxime; Swee, Lee Kim; Fan, Ying; Lamers, Mart M.; Tafesse, Fikadu G.; Theile, Christopher S.; Spooner, Eric; Bruzzone, Roberto; Ploegh, Hidde L.; Sanyal, Sumana

    2016-01-01

    Posttranslational modifications are central to the spatial and temporal regulation of protein function. Among others, phosphorylation and ubiquitylation are known to regulate proximal T-cell receptor (TCR) signaling. Here we used a systematic and unbiased approach to uncover deubiquitylating enzymes (DUBs) that participate during TCR signaling in primary mouse T lymphocytes. Using a C-terminally modified vinyl methyl ester variant of ubiquitin (HA-Ub-VME), we captured DUBs that are differentially recruited to the cytosol on TCR activation. We identified ubiquitin-specific peptidase (Usp) 12 and Usp46, which had not been previously described in this pathway. Stimulation with anti-CD3 resulted in phosphorylation and time-dependent translocation of Usp12 from the nucleus to the cytosol. Usp12−/− Jurkat cells displayed defective NFκB, NFAT, and MAPK activities owing to attenuated surface expression of TCR, which were rescued on reconstitution of wild type Usp12. Proximity-based labeling with BirA-Usp12 revealed several TCR adaptor proteins acting as interactors in stimulated cells, of which LAT and Trat1 displayed reduced expression in Usp12−/− cells. We demonstrate that Usp12 deubiquitylates and prevents lysosomal degradation of LAT and Trat1 to maintain the proximal TCR complex for the duration of signaling. Our approach benefits from the use of activity-based probes in primary cells without any previous genome modification, and underscores the importance of ubiquitin-mediated regulation to refine signaling cascades. PMID:26811477

  8. Role of TI-VAMP and CD82 in EGFR cell-surface dynamics and signaling.

    PubMed

    Danglot, Lydia; Chaineau, Mathilde; Dahan, Maxime; Gendron, Marie-Claude; Boggetto, Nicole; Perez, Franck; Galli, Thierry

    2010-03-01

    The v-SNARE TI-VAMP (VAMP7) mediates exocytosis during neuritogenesis, phagocytosis and lysosomal secretion. It localizes to endosomes and lysosomes but also to the trans-Golgi network. Here we show that depletion of TI-VAMP enhances the endocytosis of activated EGF receptor (EGFR) without affecting constitutive endocytosis of EGFR, or transferrin uptake. This increased EGFR internalization is mainly clathrin dependent. Searching for defects in EGFR regulators, we found that TI-VAMP depletion reduces the cell surface amount of CD82, a tetraspanin known to control EGFR localization in microdomains. We further show that TI-VAMP is required for secretion from the Golgi apparatus to the cell surface, and that TI-VAMP-positive vesicles transport CD82. Quantum dots video-microscopy indicates that depletion of TI-VAMP, or its cargo CD82, restrains EGFR diffusion and the area explored by EGFR at the cell surface. Both depletions also impair MAPK signaling and enhance endocytosis of activated EGFR by increased recruitment of AP-2. These results highlight the role of TI-VAMP in the secretory pathway of a tetraspanin, and support a model in which CD82 allows EGFR entry in microdomains that control its clathrin-dependent endocytosis and signaling.

  9. Elevation dependency of the surface climate change signal: A model study

    SciTech Connect

    Giorgi, F.; Hurrell, J.W.; Marinucci, M.R.

    1997-02-01

    Results are presented from a present-day and a doubled CO{sub 2} experiment over the Alpine region with a nested regional climate model. The simulated temperature change signal shows a substantial elevation dependency, mostly during the winter and spring seasons, resulting in more pronounced warming at high elevations than low elevations. This is caused by a depletion of snowpack in doubled CO{sub 2} conditions and further enhanced by the snow-albedo feedback. This result is consistent with some observed temperature trends for anomalously warm years over the Alpine region and suggests that high elevation temperature changes could be used as an early detection tool for global warming. Changes in precipitation, as well as other components of the surface energy and water budgets, also show an elevation signal, which may have important implications for impact assessments in high elevation regions. 22 refs., 10 figs., 2 tabs.

  10. Surface Time-Variable Gravity Signals and Possible Sources Including Core Mass Flow

    NASA Technical Reports Server (NTRS)

    Chao, Benjamin F.; Kuang, Weijia

    2003-01-01

    Over two decades of geodetic satellite-laser-ranging (SLR) data show that the variation of the Earth's oblateness parameter J2 has a clear seasonal signal of amplitude of about 3e-10 and a secular decrease of about -2.8e-11/year, superimposed on some interesting interannual fluctuations. Physically, any change in mass distribution or/inside the Earth will be reflected in the time-variable gravity signal obtained outside the Earth, according to Newton s gravitational law. Therefore, such signal contains contributions from all geophysical sources that redistribute mass, on all temporal and spatial scales, including those from the core. Besides Earth rotation and geomagnetic field variations, the time-variable gravity also contains information linking Earth surface observations with internal core dynamical processes. The time scales of the gravity signal are critical in helping differentiate different contributions. The atmosphere and hydrosphere are responsible for the seasonal and much of the interannual and intraseasoanl fluctuations, while the secular trend is due mainly to the post-glacial rebound but possibly core mass flow. To estimate the latter effect, we use our MoSST (Modular, Scalable, Self-consistent, Three-dimensional) core dynamics model to forward simulate the core flow, and density variation due to the core convection. Our results suggest that, when upward continued to the surface, the J2 component of the core mass redistribution can reach an overall amplitude of e-11/year, approaching the SLR detectability and significant in geophysical terms. We also find a general westward drift of the mass flow, with a speed comparable to that of the geomagnetic westward drift.

  11. Cell Surface Receptors for Signal Transduction and Ligand Transport: A Design Principles Study

    PubMed Central

    Shankaran, Harish; Resat, Haluk; Wiley, H. Steven

    2007-01-01

    Receptors constitute the interface of cells to their external environment. These molecules bind specific ligands involved in multiple processes, such as signal transduction and nutrient transport. Although a variety of cell surface receptors undergo endocytosis, the systems-level design principles that govern the evolution of receptor trafficking dynamics are far from fully understood. We have constructed a generalized mathematical model of receptor–ligand binding and internalization to understand how receptor internalization dynamics encodes receptor function and regulation. A given signaling or transport receptor system represents a particular implementation of this module with a specific set of kinetic parameters. Parametric analysis of the response of receptor systems to ligand inputs reveals that receptor systems can be characterized as being: i) avidity-controlled where the response control depends primarily on the extracellular ligand capture efficiency, ii) consumption-controlled where the ability to internalize surface-bound ligand is the primary control parameter, and iii) dual-sensitivity where both the avidity and consumption parameters are important. We show that the transferrin and low-density lipoprotein receptors are avidity-controlled, the vitellogenin receptor is consumption-controlled, and the epidermal growth factor receptor is a dual-sensitivity receptor. Significantly, we show that ligand-induced endocytosis is a mechanism to enhance the accuracy of signaling receptors rather than merely serving to attenuate signaling. Our analysis reveals that the location of a receptor system in the avidity-consumption parameter space can be used to understand both its function and its regulation. PMID:17542642

  12. Triboelectric sensor as self-powered signal reader for scanning probe surface topography imaging

    NASA Astrophysics Data System (ADS)

    Yu, Aifang; Chen, Libo; Chen, Xiangyu; Zhang, Aihua; Fan, Fengru; Zhan, Yan; Wang, Zhong Lin

    2015-04-01

    We report a self-powered signal reading mechanism for imaging surface topography using a triboelectric sensor (TES) without supplying an external power or light source. A membrane-structured triboelectric nanogenerator (TENG) is designed at the root of a whisker (probe); the deflection of the whisker causes the two contacting surfaces of the TENG to give an electric output current/voltage that responds to the bending degree of the whisker when it scans over a rough surface. A series of studies were carried out to characterize the performance of the TES, such as high sensitivity of 0.45 V mm-1, favorable repeating of standard deviation 8 mV, high Z-direction resolution of 18 μm, as well as lateral resolution of 250 μm by using a probe of size 11 mm in the length and 120 μm in radius. It not only can recognize the surface feature and size but also can perform a surface topography imaging in scanning mode. This work shows the potential of a TES as a self-powered tactile sensor for applications at relatively low spatial resolution.

  13. Can interannual land surface signal be discerned in composite AVHRR data?

    NASA Astrophysics Data System (ADS)

    Cihlar, J.; Chen, J. M.; Li, Z.; Huang, F.; Latifovic, R.; Dixon, R.

    1998-09-01

    The ability to make repeated measurements of the changing Earth's surface is the principal advantage of satellite remote sensing. To realize its potential, it is necessary that true surface changes be isolated in the satellite signal from other effects which also influence the signal. In this study, we explore the magnitude of such effects in composite NOAA advanced very high resolution radiometer (AVHRR) images with a pixel spacing of 1 km. A compositing procedure is frequently used in the preparation of data sets for land biosphere studies to minimize the effect of clouds. However, the composite images contain residual artifacts which make it difficult to compare measurements at various times. We have employed a 4-year (1993-1996) AVHRR data set from NOAA 11 and 14 covering the Canadian landmass and corrected these data for the influence of the remaining clouds (full pixel or subpixel), atmospheric attenuation, and bidirectional reflectance. We have found that such corrections are essential for studies of interannual variations. The magnitude of the interannual signal varied with the AVHRR channel, land cover type, and satellite sensor but it was reduced by a factor of 2 to 8 between top of the atmosphere and the normalized surface reflectance. The remaining variations consisted of true interannual signal and the residual noise in the data (including sensor calibration) which was not removed by the correction process. Assuming that barren or sparsely vegetated land in northern Canada has not changed over the 4-year period, the mean residual uncertainty in surface reflectance of the selected sites was 0.012 for AVHRR channel 1, 0.042 for channel 2, and 0.068 for the normalized difference vegetation index (NDVI). These values decreased to 0.011, 0.024 and 0.038, respectively, when excluding 1994 data because their atmospheric and bidirectional corrections were hampered by high solar zenith angles (mean values above 55° in all 1994 composite periods). The errors

  14. A sign-component-based framework for Chinese sign language recognition using accelerometer and sEMG data.

    PubMed

    Li, Yun; Chen, Xiang; Zhang, Xu; Wang, Kongqiao; Wang, Z Jane

    2012-10-01

    Identification of constituent components of each sign gesture can be beneficial to the improved performance of sign language recognition (SLR), especially for large-vocabulary SLR systems. Aiming at developing such a system using portable accelerometer (ACC) and surface electromyographic (sEMG) sensors, we propose a framework for automatic Chinese SLR at the component level. In the proposed framework, data segmentation, as an important preprocessing operation, is performed to divide a continuous sign language sentence into subword segments. Based on the features extracted from ACC and sEMG data, three basic components of sign subwords, namely the hand shape, orientation, and movement, are further modeled and the corresponding component classifiers are learned. At the decision level, a sequence of subwords can be recognized by fusing the likelihoods at the component level. The overall classification accuracy of 96.5% for a vocabulary of 120 signs and 86.7% for 200 sentences demonstrate the feasibility of interpreting sign components from ACC and sEMG data and clearly show the superior recognition performance of the proposed method when compared with the previous SLR method at the subword level. The proposed method seems promising for implementing large-vocabulary portable SLR systems. PMID:22438511

  15. An EMG analysis of the shoulder in pitching. A second report.

    PubMed

    Jobe, F W; Moynes, D R; Tibone, J E; Perry, J

    1984-01-01

    This is the second report in a series of projects dealing with electromyographic (EMG) analysis of the upper extremity during throwing. Better understanding of the muscle activation patterns could lead to more effective preseason conditioning regimens and rehabilitation programs. Indwelling wire electrodes recorded the output from the biceps, long and lateral heads of the triceps, pectoralis major, latissimus dorsi, serratus anterior, and brachialis for four professional baseball pitchers. These signals were synchronized electronically with high speed film records of a fast ball. The EMG signals were converted from analog to digital records. Results showed that wind-up and early cocking phases showed minimal activity in all muscles, and such firing which occurred was of low intensity. Late cocking, which occurred after the front foot was firmly planted, showed moderate activity in the biceps. Cocking was terminated by the pectoralis major and latissimus dorsi. At this point, the trunk began to rotate forward, while the arm remained elevated and the elbow flexed. Also, the shoulder was moving to maximum external rotation. During the acceleration phase, the biceps was notably quiescent, while the pectoralis major, latissimus dorsi, triceps, and serratus anterior were all active. Muscle action at this time terminated external rotation and elbow flexion; i.e., the muscles fired as decelerators and also initiated the opposite actions for ball acceleration, internal rotation and elbow extension. Follow-through was not only a time of eccentric contraction with muscle activity decelerating the upper extremity complex, it was also an active event with the shoulder moving across the body and the elbow into extension with forearm pronation.

  16. Surface electromyography as a tool to assess the responses of car passengers to lateral accelerations: Part I. Extraction of relevant muscular activities from noisy recordings.

    PubMed

    Farah, G; Hewson, D J; Duchêne, J

    2006-12-01

    The aim of this paper is to develop a method to extract relevant activities from surface electromyography (SEMG) recordings under difficult experimental conditions with a poor signal to noise ratio. High amplitude artifacts, the QRS complex, low frequency noise and white noise significantly alter EMG characteristics. The CEM algorithm proved to be useful for segmentation of SEMG signals into high amplitude artifacts (HAA), phasic activity (PA) and background postural activity (BA) classes. This segmentation was performed on signal energy, with classes belonging to a chi(2) distribution. Ninety-five percent of HAA events and 96.25% of BA events were detected, and the remaining noise was then identified using AR modeling, a classification based upon the position of the coordinates of the pole of highest module. This method eliminated 91.5% of noise and misclassified only 3.3% of EMG events when applied to SEMG recorded on passengers subjected to lateral accelerations.

  17. Radar signal return from near-shore surface and shallow subsurface features, Darien Province, Panama

    NASA Technical Reports Server (NTRS)

    Hanson, B. C.; Dellwig, L. F.

    1973-01-01

    The AN/APQ-97 radar imagery over eastern Panama is analyzed. The imagery was directed toward extraction of geologic and engineering data and the establishment of operational parameters. Subsequent investigations emphasized landform identification and vegetation distribution. The parameters affecting the observed return signal strength from such features are considered. Near-shore ocean phenomena were analyzed. Tidal zone features such as mud flats and reefs were identified in the near range, but were not detectable in the far range. Surface roughness dictated the nature of reflected energy (specular or diffuse). In surf zones, changes in wave train orientation relative to look direction, the slope of the surface, and the physical character of the wave must be considered. It is concluded that the establishment of the areal extent of the tidal flats, distributary channels, and reefs is practical only in the near to intermediate range under minimal low tide conditions.

  18. Mechanical loading of knee articular cartilage induced by muscle contraction can be assessed by measuring electrical potentials at the surface of the knee.

    PubMed

    Zhu, Lin; Buschmann, Michael D; Savard, Pierre

    2016-02-01

    Electroarthrography (EAG) consists of recording electrical potentials on the knee surface that originate from streaming potentials within articular cartilage while the joint is undergoing compressive loading. The aim was to investigate how the contraction of specific leg muscles affects the contact force of the knee joint and, in turn, the EAG values. For six normal subjects, voluntary isometric muscle contractions were repeatedly conducted to activate four leg muscle groups while the subject was lying on his back. Two EAG signals were recorded on the medial and lateral sides of the knee, as well as four EMG signals (gastrocnemius, hamstring, quadriceps, tensor fascia latae), and the signal from a force plate fixed against the foot according to the direction of the force. The EAG and force signals were very well correlated: the median of the correlation coefficients between an EAG signal and the corresponding force signal during each loading cycle was 0.91, and 86% of the correlation coefficients were statistically significant (p<5%). Isolated muscle contraction was possible for the gastrocnemius and hamstring, but not always for the quadriceps and tensor fascia latae. Using the clinical loading protocol which consists of a one-legged stance, the quadriceps and hamstring EMGs showed minimal activity; loading cycles with increased EAG amplitude were associated with higher EMG activity from the gastrocnemius, which is involved in antero-posterior balance. These results document the role of the EAG as a "sensor" of the knee contact force and contribute to the development of clinical loading protocols with improved reproducibility.

  19. Surface-wave-enabled darkfield aperture for background suppression during weak signal detection.

    PubMed

    Zheng, Guoan; Cui, Xiquan; Yang, Changhuei

    2010-05-18

    Sensitive optical signal detection can often be confounded by the presence of a significant background, and, as such, predetection background suppression is substantively important for weak signal detection. In this paper, we present a novel optical structure design, termed surface-wave-enabled darkfield aperture (SWEDA), which can be directly incorporated onto optical sensors to accomplish predetection background suppression. This SWEDA structure consists of a central hole and a set of groove pattern that channels incident light to the central hole via surface plasmon wave and surface-scattered wave coupling. We show that the surface wave component can mutually cancel the direct transmission component, resulting in near-zero net transmission under uniform normal incidence illumination. Here, we report the implementation of two SWEDA structures. The first structure, circular-groove-based SWEDA, is able to provide polarization-independent suppression of uniform illumination with a suppression factor of 1230. The second structure, linear-groove-based SWEDA, is able to provide a suppression factor of 5080 for transverse-magnetic wave and can serve as a highly compact (5.5 micrometer length) polarization sensor (the measured transmission ratio of two orthogonal polarizations is 6100). Because the exact destructive interference balance is highly delicate and can be easily disrupted by the nonuniformity of the localized light field or light field deviation from normal incidence, the SWEDA can therefore be used to suppress a bright background and allow for sensitive darkfield sensing and imaging (observed image contrast enhancement of 27 dB for the first SWEDA).

  20. The Activity of Surface Electromyographic Signal of Selected Muscles during Classic Rehabilitation Exercise.

    PubMed

    Xiao, Jinzhuang; Sun, Jinli; Gao, Junmin; Wang, Hongrui; Yang, Xincai

    2016-01-01

    Objectives. Prone bridge, unilateral bridge, supine bridge, and bird-dog are classic rehabilitation exercises, which have been advocated as effective ways to improve core stability among healthy individuals and patients with low back pain. The aim of this study was to investigate the activity of seven selected muscles during rehabilitation exercises through the signal of surface electromyographic. Approaches. We measured the surface electromyographic signals of four lower limb muscles, two abdominal muscles, and one back muscle during rehabilitation exercises of 30 healthy students and then analyzed its activity level using the median frequency method. Results. Different levels of muscle activity during the four rehabilitation exercises were observed. The prone bridge and unilateral bridge caused the greatest muscle fatigue; however, the supine bridge generated the lowest muscle activity. There was no significant difference (P > 0.05) between left and right body side muscles in the median frequency slope during the four rehabilitation exercises of seven muscles. Conclusions. The prone bridge can affect the low back and lower limb muscles of most people. The unilateral bridge was found to stimulate muscles much more active than the supine bridge. The bird-dog does not cause much fatigue to muscles but can make most selected muscles active. PMID:27195151

  1. The signaling phospholipid PIP3 creates a new interaction surface on the nuclear receptor SF-1.

    PubMed

    Blind, Raymond D; Sablin, Elena P; Kuchenbecker, Kristopher M; Chiu, Hsiu-Ju; Deacon, Ashley M; Das, Debanu; Fletterick, Robert J; Ingraham, Holly A

    2014-10-21

    The signaling phosphatidylinositol lipids PI(4,5)P2 (PIP2) and PI(3,4,5)P3 (PIP3) bind nuclear receptor 5A family (NR5As), but their regulatory mechanisms remain unknown. Here, the crystal structures of human NR5A1 (steroidogenic factor-1, SF-1) ligand binding domain (LBD) bound to PIP2 and PIP3 show the lipid hydrophobic tails sequestered in the hormone pocket, as predicted. However, unlike classic nuclear receptor hormones, the phosphoinositide head groups are fully solvent-exposed and complete the LBD fold by organizing the receptor architecture at the hormone pocket entrance. The highest affinity phosphoinositide ligand PIP3 stabilizes the coactivator binding groove and increases coactivator peptide recruitment. This receptor-ligand topology defines a previously unidentified regulatory protein-lipid surface on SF-1 with the phosphoinositide head group at its nexus and poised to interact with other proteins. This surface on SF-1 coincides with the predicted binding site of the corepressor DAX-1 (dosage-sensitive sex reversal, adrenal hypoplasia critical region on chromosome X), and importantly harbors missense mutations associated with human endocrine disorders. Our data provide the structural basis for this poorly understood cluster of human SF-1 mutations and demonstrates how signaling phosphoinositides function as regulatory ligands for NR5As. PMID:25288771

  2. The signaling phospholipid PIP3 creates a new interaction surface on the nuclear receptor SF-1

    PubMed Central

    Blind, Raymond D.; Sablin, Elena P.; Kuchenbecker, Kristopher M.; Chiu, Hsiu-Ju; Deacon, Ashley M.; Das, Debanu; Fletterick, Robert J.; Ingraham, Holly A.

    2014-01-01

    The signaling phosphatidylinositol lipids PI(4,5)P2 (PIP2) and PI(3,4,5)P3 (PIP3) bind nuclear receptor 5A family (NR5As), but their regulatory mechanisms remain unknown. Here, the crystal structures of human NR5A1 (steroidogenic factor-1, SF-1) ligand binding domain (LBD) bound to PIP2 and PIP3 show the lipid hydrophobic tails sequestered in the hormone pocket, as predicted. However, unlike classic nuclear receptor hormones, the phosphoinositide head groups are fully solvent-exposed and complete the LBD fold by organizing the receptor architecture at the hormone pocket entrance. The highest affinity phosphoinositide ligand PIP3 stabilizes the coactivator binding groove and increases coactivator peptide recruitment. This receptor-ligand topology defines a previously unidentified regulatory protein-lipid surface on SF-1 with the phosphoinositide head group at its nexus and poised to interact with other proteins. This surface on SF-1 coincides with the predicted binding site of the corepressor DAX-1 (dosage-sensitive sex reversal, adrenal hypoplasia critical region on chromosome X), and importantly harbors missense mutations associated with human endocrine disorders. Our data provide the structural basis for this poorly understood cluster of human SF-1 mutations and demonstrates how signaling phosphoinositides function as regulatory ligands for NR5As. PMID:25288771

  3. Lower arm electromyography (EMG) activity detection using local binary patterns.

    PubMed

    McCool, Paul; Chatlani, Navin; Petropoulakis, Lykourgos; Soraghan, John J; Menon, Radhika; Lakany, Heba

    2014-09-01

    This paper presents a new electromyography activity detection technique in which 1-D local binary pattern histograms are used to distinguish between periods of activity and inactivity in myoelectric signals. The algorithm is tested on forearm surface myoelectric signals occurring due to hand gestures. The novel features of the presented method are that: 1) activity detection is performed across multiple channels using few parameters and without the need for majority vote mechanisms, 2) there are no per-channel thresholds to be tuned, which makes the process of activity detection easier and simpler to implement and less prone to errors, 3) it is not necessary to measure the properties of the signal during a quiescent period before using the algorithm. The algorithm is compared to other offline single- and double-threshold activity detection methods and, for the data sets tested, it is shown to have a better overall performance with greater tolerance to the noise in the real data set used.

  4. A novel feature extraction for robust EMG pattern recognition.

    PubMed

    Veer, Karan; Sharma, Tanu

    2016-01-01

    This paper presents the detailed evaluation and classification of Surface Electromyogram (SEMG) signals at different upper arm muscles for different operations. After acquiring the data from selected locations, interpretation of signals was done for the estimation of parameters using simulated algorithm. First, different types of arm operations were analysed; then statistical techniques were implemented for investigating muscle force relationships in terms of amplitude estimation. The classification (Artificial Neural Network) based results have been presented for detecting different pre-defined arm motions in order to discriminate SEMG signals. The outcome of research indicates that a neural network classifier performs best with an average classification rate of 92.50%. Finally, the result also inferred the operations which were observed to be easy for arm recognition and the study is a step forward to develop powerful, flexible and efficient prosthetic designs. PMID:27004618

  5. Evolutionary and functional perspectives on signaling from neuronal surface to nucleus

    SciTech Connect

    Cohen, Samuel M.; Li, Boxing; Tsien, Richard W. Ma, Huan

    2015-04-24

    Reliance on Ca{sup 2+} signaling has been well-preserved through the course of evolution. While the complexity of Ca{sup 2+} signaling pathways has increased, activation of transcription factors including CREB by Ca{sup 2+}/CaM-dependent kinases (CaMKs) has remained critical for long-term plasticity. In C. elegans, the CaMK family is made up of only three members, and CREB phosphorylation is mediated by CMK-1, the homologue of CaMKI. CMK-1 nuclear translocation directly regulates adaptation of thermotaxis behavior in response to changes in the environment. In mammals, the CaMK family has been expanded from three to ten members, enabling specialization of individual elements of a signal transduction pathway and increased reliance on the CaMKII subfamily. This increased complexity enables private line communication between Ca{sup 2+} sources at the cell surface and specific cellular targets. Using both new and previously published data, we review the mechanism of a γCaMKII-CaM nuclear translocation. This intricate pathway depends on a specific role for multiple Ca{sup 2+}/CaM-dependent kinases and phosphatases: α/βCaMKII phosphorylates γCaMKII to trap CaM; CaN dephosphorylates γCaMKII to dispatch it to the nucleus; and PP2A induces CaM release from γCaMKII so that CaMKK and CaMKIV can trigger CREB phosphorylation. Thus, while certain basic elements have been conserved from C. elegans, evolutionary modifications offer opportunities for targeted communication, regulation of key nodes and checkpoints, and greater specificity and flexibility in signaling.

  6. Surface loading affects internal pressure source characteristics derived from volcano deformation signals

    NASA Astrophysics Data System (ADS)

    Grapenthin, Ronni; Sigmundsson, Freysteinn; Ofeigsson, Benedikt; Sturkell, Erik

    2010-05-01

    Deformation of the Earth's surface provides critical information about the migration of material beneath a volcano. The resulting displacements, recorded by geodetic techniques such as GPS or InSAR, are used to infer characteristics of the volcanic plumbing system which are critical for hazard mitigation in volcanic regions. Given some deformation data, we search for the source model that explains the data best. Discussions of the results usually focus on the validity of the chosen model and the underlying assumptions regarding crustal composition, e.g. the level of inhomogeneity, elastic versus plastic deformation, thermal effects, depth vs. volume trade offs of the applied analytical models, or the (in-)compressibility of materials. Surface loads such as lava flows, however, provide an additional source of deformation. The initial elastic response due to a load on the surface of the Earth is followed by a visco-elastic response of the ductile crust below the uppermost elastic layer. Thus, a deformation signal recorded in the vicinity of a volcano is often composed of at least two contributors: an internal pressure source (the magma chamber) and a surface load (e.g., a composition of previously erupted lava flows) - at the extreme the volcanic edifice and its glaciers. A test case for a circular lava flow on top of a deflating magma chamber shows that the crust will adjust to the load towards final relaxed response. During this relaxation process gradual subsidence occurs that may mistakenly be interpreted as due to pressure decrease in a magma chamber since the deformation pattern of both processes are very similar. This poses a problem when characteristics of a magma chamber are to be derived. Based on the ratio of horizontal and vertical displacement and a combination of model results (Green's functions and Mogi model), we can estimate the composition of observed deformation signals. This method is applied to the Icelandic volcano Mt. Hekla where we investigate

  7. Fas- and tumor necrosis factor-mediated apoptosis uses the same binding surface of FADD to trigger signal transduction. A typical model for convergent signal transduction.

    PubMed

    Bang, S; Jeong, E J; Kim, I K; Jung, Y K; Kim, K S

    2000-11-17

    FADD is known to function as a common signaling conduit in Fas- and tumor necrosis factor (TNF)-mediated apoptosis. The convergent death signals from the Fas receptor and TNF receptor 1 are transferred to FADD by death domain interactions triggering the same cellular event, caspase-8 activation. In this work, we investigated whether the same binding surface of FADD is used for both signaling pathways by using FADD death domain mutants. Mutations in helices alpha2 and alpha3 of the FADD death domain, the interacting surface with the Fas death domain, affected TNF-mediated apoptosis to various extents. This indicated that TNF-mediated apoptosis uses the same binding surface of the FADD death domain as Fas-mediated apoptosis. The binding specificity is not the same, however. Some mutations affected the binding affinity of the Fas death domain for the FADD death domain, but did not influence TNF-mediated apoptosis and vice versa. Interestingly, all mutants tested that affected TNF-mediated apoptosis have structural perturbations, implying that the structural integrity, involving helices alpha2 and alpha3 in particular, is critical in TNF-mediated apoptosis. Our results suggest that different signaling molecules use a similar structural interaction to trigger the same cellular event, such as caspase-8 recruitment, which could be typical in convergent signal transduction.

  8. Surface electromyography in animal biomechanics: A systematic review.

    PubMed

    Valentin, Stephanie; Zsoldos, Rebeka R

    2016-06-01

    The study of muscle activity using surface electromyography (sEMG) is commonly used for investigations of the neuromuscular system in man. Although sEMG has faced methodological challenges, considerable technical advances have been made in the last few decades. Similarly, the field of animal biomechanics, including sEMG, has grown despite being confronted with often complex experimental conditions. In human sEMG research, standardised protocols have been developed, however these are lacking in animal sEMG. Before standards can be proposed in this population group, the existing research in animal sEMG should be collated and evaluated. Therefore the aim of this review is to systematically identify and summarise the literature in animal sEMG focussing on (1) species, breeds, activities and muscles investigated, and (2) electrode placement and normalisation methods used. The databases PubMed, Web of Science, Scopus, and Vetmed Resource were searched systematically for sEMG studies in animals and 38 articles were included in the final review. Data on methodological quality was collected and summarised. The findings from this systematic review indicate the divergence in animal sEMG methodology and as a result, future steps required to develop standardisation in animal sEMG are proposed.

  9. Quadratus femoris: An EMG investigation during walking and running.

    PubMed

    Semciw, Adam I; Freeman, Michael; Kunstler, Breanne E; Mendis, M Dilani; Pizzari, Tania

    2015-09-18

    Dysfunction of hip stabilizing muscles such as quadratus femoris (QF) is identified as a potential source of lower extremity injury during functional tasks like running. Despite these assumptions, there are currently no electromyography (EMG) data that establish the burst activity profile of QF during any functional task like walking or running. The objectives of this study were to characterize and compare the EMG activity profile of QF while walking and running (primary aim) and describe the direction specific action of QF (secondary aim). A bipolar fine-wire intramuscular electrode was inserted via ultrasound guidance into the QF of 10 healthy participants (4 females). Ensemble curves were generated from four walking and running trials, and normalized to maximum voluntary isometric contractions (MVICs). Paired t-tests compared the temporal and amplitude EMG variables. The relative activity of QF in the MVICs was calculated. The QF displayed moderate to high amplitude activity in the stance phase of walking and very high activity during stance in running. During swing, there was minimal QF activity recorded during walking and high amplitudes were present while running (run vs walk effect size=4.23, P<0.001). For the MVICs, external rotation and clam produced the greatest QF activity, with the hip in the anatomical position. This study provides an understanding of the activity demands placed on QF while walking and running. The high activity in late swing during running may signify a synergistic role with other posterior thigh muscles to control deceleration of the limb in preparation for stance.

  10. A feedback model reproduces muscle activity during human postural responses to support-surface translations.

    PubMed

    Welch, Torrence D J; Ting, Lena H

    2008-02-01

    Although feedback models have been used to simulate body motions in human postural control, it is not known whether muscle activation patterns generated by the nervous system during postural responses can also be explained by a feedback control process. We investigated whether a simple feedback law could explain temporal patterns of muscle activation in response to support-surface translations in human subjects. Previously, we used a single-link inverted-pendulum model with a delayed feedback controller to reproduce temporal patterns of muscle activity during postural responses in cats. We scaled this model to human dimensions and determined whether it could reproduce human muscle activity during forward and backward support-surface perturbations. Through optimization, we found three feedback gains (on pendulum acceleration, velocity, and displacement) and a common time delay that allowed the model to best match measured electromyographic (EMG) signals. For each muscle and each subject, the entire time courses of EMG signals during postural responses were well reconstructed in muscles throughout the lower body and resembled the solution derived from an optimal control model. In ankle muscles, >75% of the EMG variability was accounted for by model reconstructions. Surprisingly, >67% of the EMG variability was also accounted for in knee, hip, and pelvis muscles, even though motion at these joints was minimal. Although not explicitly required by our optimization, pendulum kinematics were well matched to subject center-of-mass (CoM) kinematics. Together, these results suggest that a common set of feedback signals related to task-level control of CoM motion is used in the temporal formation of muscle activity during postural control.

  11. EMG BIOFEEDBACK II: THE DOSE—RESPONSE RELATIONSHIP

    PubMed Central

    Sargunaraj, D.; Kumaraiah, V.; Subbakrishna, D.K.

    1991-01-01

    SUMMARY 36 clients with anxiety neurosis were trained to reduce frontalis muscle tension over two phases of ten sessions each. They were assessed on psychological and physiological measures, before, during and after the phases. The data analysis indicated that the clients succeeded in lowering frontalis muscle tension levels during the feedback and no-feedback phases of the training sessions. The inter-correlations among the outcome measures indicated that with an increasing amount of control of muscle tensior, the clients perceived greater amounts of change in state anxiety and in anxiety symptoms. This implies that EMG biofeedback can effect cognitive changes in clients. PMID:21897456

  12. Adaptive neuro-fuzzy logic analysis based on myoelectric signals for multifunction prosthesis control.

    PubMed

    Favieiro, Gabriela W; Balbinot, Alexandre

    2011-01-01

    The myoelectric signal is a sign of control of the human body that contains the information of the user's intent to contract a muscle and, therefore, make a move. Studies shows that the Amputees are able to generate standardized myoelectric signals repeatedly before of the intention to perform a certain movement. This paper presents a study that investigates the use of forearm surface electromyography (sEMG) signals for classification of five distinguish movements of the arm using just three pairs of surface electrodes located in strategic places. The classification is done by an adaptive neuro-fuzzy inference system (ANFIS) to process signal features to recognize performed movements. The average accuracy reached for the classification of five motion classes was 86-98% for three subjects. PMID:22256169

  13. Analysis of upper arm muscle activation using surface electromyography signals during drum playing

    PubMed Central

    Chong, Hyun Ju; Kwon, Chun-Ki; Kang, Hyun-Joo; Kim, Soo Ji

    2016-01-01

    This study measured surface electromyography of the biceps brachii and triceps brachii during repeated drum playing with and without a drumstick to better understand activation of the upper arm muscles and inform the use of instrument playing for motor rehabilitation. A total of 40 healthy college students participated in this study. All participants were asked to strike a drum with their hand and with a drumstick at three different levels of stroke: soft, medium, and strong. The stroke order was randomly assigned to participants. A sound level meter was used to record the intensity of the drum playing. Surface electromyography signals were recorded at every hit during drum playing both with and without the drumstick in each of the three stroke conditions. The results demonstrated that the highest muscle activation was observed in both biceps brachii and triceps brachii with strong drum playing with and without the drumstick. A two-way repeated measures analysis of variance showed that there was a significant main effect for stroke intensity in muscle activation and produced sound level. While higher activation of the triceps brachii was observed for drum playing without a drumstick, no significant differences were found between the biceps brachii and sound level. This study demonstrated via surface electromyography data that greater muscle activation of the biceps brachii and triceps brachii does not occur with the use of drumsticks in drum playing. With the drum sound controlled, drum playing by hand can be an effective therapeutic intervention for the upper arm muscles. PMID:27419114

  14. Analysis of upper arm muscle activation using surface electromyography signals during drum playing.

    PubMed

    Chong, Hyun Ju; Kwon, Chun-Ki; Kang, Hyun-Joo; Kim, Soo Ji

    2016-06-01

    This study measured surface electromyography of the biceps brachii and triceps brachii during repeated drum playing with and without a drumstick to better understand activation of the upper arm muscles and inform the use of instrument playing for motor rehabilitation. A total of 40 healthy college students participated in this study. All participants were asked to strike a drum with their hand and with a drumstick at three different levels of stroke: soft, medium, and strong. The stroke order was randomly assigned to participants. A sound level meter was used to record the intensity of the drum playing. Surface electromyography signals were recorded at every hit during drum playing both with and without the drumstick in each of the three stroke conditions. The results demonstrated that the highest muscle activation was observed in both biceps brachii and triceps brachii with strong drum playing with and without the drumstick. A two-way repeated measures analysis of variance showed that there was a significant main effect for stroke intensity in muscle activation and produced sound level. While higher activation of the triceps brachii was observed for drum playing without a drumstick, no significant differences were found between the biceps brachii and sound level. This study demonstrated via surface electromyography data that greater muscle activation of the biceps brachii and triceps brachii does not occur with the use of drumsticks in drum playing. With the drum sound controlled, drum playing by hand can be an effective therapeutic intervention for the upper arm muscles. PMID:27419114

  15. Surface position, not signaling from surrounding maternal tissues, specifies aleurone epidermal cell fate in maize.

    PubMed

    Gruis, Darren Fred; Guo, Hena; Selinger, David; Tian, Qing; Olsen, Odd-Arne

    2006-07-01

    Maize (Zea mays) endosperm consists of an epidermal-like surface layer of aleurone cells, an underlying body of starchy endosperm cells, and a basal layer of transfer cells. To determine whether surrounding maternal tissues perform a role in specifying endosperm cell fates, a maize endosperm organ culture technique was established whereby the developing endosperm is completely removed from surrounding maternal tissues. Using cell type-specific fluorescence markers, we show that aleurone cell fate specification occurs exclusively in response to surface position and does not require specific, continued maternal signal input. The starchy endosperm and aleurone cell fates are freely interchangeable throughout the lifespan of the endosperm, with internalized aleurone cells converting to starchy endosperm cells and with starchy endosperm cells that become positioned at the surface converting to aleurone cells. In contrast to aleurone and starchy endosperm cells, transfer cells fail to develop in in vitro-grown endosperm, supporting earlier indications that maternal tissue interaction is required to fully differentiate this cell type. Several parameters confirm that the maize endosperm organ cultures described herein retain the main developmental features of in planta endosperm, including fidelity of aleurone mutant phenotypes, temporal and spatial control of cell type-specific fluorescent markers, specificity of cell type transcripts, and control of mitotic cell divisions.

  16. Estimation of the rain signal in the presence of large surface clutter

    NASA Technical Reports Server (NTRS)

    Ahamad, Atiq; Moore, Richard K.

    1994-01-01

    The principal limitation for the use of a spaceborne imaging SAR as a rain radar is the surface-clutter problem. Signals may be estimated in the presence of noise by averaging large numbers of independent samples. This method was applied to obtain an estimate of the rain echo by averaging a set of N(sub c) samples of the clutter in a separate measurement and subtracting the clutter estimate from the combined estimate. The number of samples required for successful estimation (within 10-20%) for off-vertical angles of incidence appears to be prohibitively large. However, by appropriately degrading the resolution in both range and azimuth, the required number of samples can be obtained. For vertical incidence, the number of samples required for successful estimation is reasonable. In estimating the clutter it was assumed that the surface echo is the same outside the rain volume as it is within the rain volume. This may be true for the forest echo, but for convective storms over the ocean the surface echo outside the rain volume is very different from that within. It is suggested that the experiment be performed with vertical incidence over forest to overcome this limitation.

  17. Analysis of upper arm muscle activation using surface electromyography signals during drum playing.

    PubMed

    Chong, Hyun Ju; Kwon, Chun-Ki; Kang, Hyun-Joo; Kim, Soo Ji

    2016-06-01

    This study measured surface electromyography of the biceps brachii and triceps brachii during repeated drum playing with and without a drumstick to better understand activation of the upper arm muscles and inform the use of instrument playing for motor rehabilitation. A total of 40 healthy college students participated in this study. All participants were asked to strike a drum with their hand and with a drumstick at three different levels of stroke: soft, medium, and strong. The stroke order was randomly assigned to participants. A sound level meter was used to record the intensity of the drum playing. Surface electromyography signals were recorded at every hit during drum playing both with and without the drumstick in each of the three stroke conditions. The results demonstrated that the highest muscle activation was observed in both biceps brachii and triceps brachii with strong drum playing with and without the drumstick. A two-way repeated measures analysis of variance showed that there was a significant main effect for stroke intensity in muscle activation and produced sound level. While higher activation of the triceps brachii was observed for drum playing without a drumstick, no significant differences were found between the biceps brachii and sound level. This study demonstrated via surface electromyography data that greater muscle activation of the biceps brachii and triceps brachii does not occur with the use of drumsticks in drum playing. With the drum sound controlled, drum playing by hand can be an effective therapeutic intervention for the upper arm muscles.

  18. Wavelet-based unsupervised learning method for electrocardiogram suppression in surface electromyograms.

    PubMed

    Niegowski, Maciej; Zivanovic, Miroslav

    2016-03-01

    We present a novel approach aimed at removing electrocardiogram (ECG) perturbation from single-channel surface electromyogram (EMG) recordings by means of unsupervised learning of wavelet-based intensity images. The general idea is to combine the suitability of certain wavelet decomposition bases which provide sparse electrocardiogram time-frequency representations, with the capacity of non-negative matrix factorization (NMF) for extracting patterns from images. In order to overcome convergence problems which often arise in NMF-related applications, we design a novel robust initialization strategy which ensures proper signal decomposition in a wide range of ECG contamination levels. Moreover, the method can be readily used because no a priori knowledge or parameter adjustment is needed. The proposed method was evaluated on real surface EMG signals against two state-of-the-art unsupervised learning algorithms and a singular spectrum analysis based method. The results, expressed in terms of high-to-low energy ratio, normalized median frequency, spectral power difference and normalized average rectified value, suggest that the proposed method enables better ECG-EMG separation quality than the reference methods. PMID:26774422

  19. Continuous monitoring of electromyography (EMG), mechanomyography (MMG), sonomyography (SMG) and torque output during ramp and step isometric contractions.

    PubMed

    Guo, Jing-Yi; Zheng, Yong-Ping; Xie, Hong-Bo; Chen, Xin

    2010-11-01

    In this study we simultaneously collected ultrasound images, EMG, MMG from the rectus femoris (RF) muscle and torque signal from the leg extensor muscle group of nine male subjects (mean±SD, age=30.7±.4.9 years; body weight=67.0±8.4kg; height=170.4±6.9cm) during step, ramp increasing, and decreasing at three different rates (50%, 25% and 17% MVC/s). The muscle architectural parameters extracted from ultrasound imaging, which reflect muscle contractions, were defined as sonomyography (SMG) in this study. The cross-sectional area (CSA) and aspect ratio between muscle width and thickness (width/thickness) were extracted from ultrasound images. The results showed that the CSA of RF muscles decreased by 7.25±4.07% when muscle torque output changed from 0% to 90% MVC, and the aspect ratio decreased by 41.66±7.96%. The muscle contraction level and SMG data were strongly correlated (R(2)=0.961, P=0.003, for CSA and R(2)=0.999, P<0.001, for width/thickness ratio). The data indicated a significant difference (P<0.05) in percentage changes for CSA and aspect ratio among step, ramp increasing, and decreasing contractions. The normalized EMG RMS in ramp increasing was 8.25±4.00% higher than step (P=0.002). The normalized MMG RMS of step contraction was significantly lower than ramp increasing and decreasing, with averaged differences of 12.22±3.37% (P=0.001) and 12.06±3.37% (P=0.001), respectively. The results of this study demonstrated that the CSA and aspect ratio, i.e., SMG signals, can provide useful information about muscle contractions. They may therefore complement EMG and MMG for studying muscle activation strategies under different conditions.

  20. Robust EMG sensing system based on data fusion for myoelectric control of a robotic arm

    PubMed Central

    López, Natalia M; di Sciascio, Fernando; Soria, Carlos M; Valentinuzzi, Max E

    2009-01-01

    Background Myoelectric control of a robotic manipulator may be disturbed by failures due to disconnected electrodes, interface impedance changes caused by movements, problems in the recording channel and other various noise sources. To correct these problems, this paper presents two fusing techniques, Variance Weighted Average (VWA) and Decentralized Kalman Filter (DKF), both based on the myoelectric signal variance as selecting criterion. Methods Tested in five volunteers, a redundant arrangement was obtained with two pairs of electrodes for each recording channel. The myoelectric signals were electronically amplified, filtered and digitalized, while the processing, fusion algorithms and control were implemented in a personal computer under MATLAB® environment and in a Digital Signal Processor (DSP). The experiments used an industrial robotic manipulator BOSCH SR-800, type SCARA, with four degrees of freedom; however, only the first joint was used to move the end effector to a desired position, the latter obtained as proportional to the EMG amplitude. Results Several trials, including disconnecting and reconnecting one electrode and disturbing the signal with synthetic noise, were performed to test the fusion techniques. The results given by VWA and DKF were transformed into joint coordinates and used as command signals to the robotic arm. Even though the resultant signal was not exact, the failure was ignored and the joint reference signal never exceeded the workspace limits. Conclusion The fault robustness and safety characteristics of a myoelectric controlled manipulator system were substantially improved. The proposed scheme prevents potential risks for the operator, the equipment and the environment. Both algorithms showed efficient behavior. This outline could be applied to myoelectric control of prosthesis, or assistive manipulators to better assure the system functionality when electrode faults or noisy environment are present. PMID:19243627

  1. Evidence from retractor bulbi EMG for linearized motor control of conditioned nictitating membrane responses.

    PubMed

    Lepora, N F; Mavritsaki, E; Porrill, J; Yeo, C H; Evinger, C; Dean, P

    2007-10-01

    Classical conditioning of nictitating membrane (NM) responses in rabbits is a robust model learning system, and experimental evidence indicates that conditioned responses (CRs) are controlled by the cerebellum. It is unknown whether cerebellar control signals deal directly with the complex nonlinearities of the plant (blink-related muscles and peripheral tissues) or whether the plant is linearized to ensure a simple relation between cerebellar neuronal firing and CR profile. To study this question, the retractor bulbi muscle EMG was recorded with implanted electrodes during NM conditioning. Pooled activity in accessory abducens motoneurons was estimated from spike trains extracted from the EMG traces, and its temporal profile was found to have an approximately Gaussian shape with peak amplitude linearly related to CR amplitude. The relation between motoneuron activity and CR profiles was accurately fitted by a first-order linear filter, with each spike input producing an exponentially decaying impulse response with time constant of order 0.1 s. Application of this first-order plant model to CR data from other laboratories suggested that, in these cases also, motoneuron activity had a Gaussian profile, with time-of-peak close to unconditioned stimulus (US) onset and SD proportional to the interval between conditioned stimulus and US onsets. These results suggest that for conditioned NM responses the cerebellum is presented with a simplified "virtual" plant that is a linearized version of the underlying nonlinear biological system. Analysis of a detailed plant model suggests that one method for linearising the plant would be appropriate recruitment of motor units.

  2. The Movement- and Load-Dependent Differences in the EMG Patterns of the Human Arm Muscles during Two-Joint Movements (A Preliminary Study)

    PubMed Central

    Tomiak, Tomasz; Abramovych, Tetiana I.; Gorkovenko, Andriy V.; Vereshchaka, Inna V.; Mishchenko, Viktor S.; Dornowski, Marcin; Kostyukov, Alexander I.

    2016-01-01

    Slow circular movements of the hand with a fixed wrist joint that were produced in a horizontal plane under visual guidance during conditions of action of the elastic load directed tangentially to the movement trajectory were studied. The positional dependencies of the averaged surface EMGs in the muscles of the elbow and shoulder joints were compared for four possible combinations in the directions of load and movements. The EMG intensities were largely correlated with the waves of the force moment computed for a corresponding joint in the framework of a simple geometrical model of the system: arm - experimental setup. At the same time, in some cases the averaged EMGs exit from the segments of the trajectory restricted by the force moment singular points (FMSPs), in which the moments exhibited altered signs. The EMG activities display clear differences for the eccentric and concentric zones of contraction that are separated by the joint angle singular points (JASPs), which present extreme at the joint angle traces. We assumed that the modeled patterns of FMSPs and JASPs may be applied for an analysis of the synergic interaction between the motor commands arriving at different muscles in arbitrary two-joint movements. PMID:27375496

  3. Individual-specific muscle maximum force estimation using ultrasound for ankle joint torque prediction using an EMG-driven Hill-type model.

    PubMed

    de Oliveira, Liliam Fernandes; Menegaldo, Luciano Luporini

    2010-10-19

    EMG-driven models can be used to estimate muscle force in biomechanical systems. Collected and processed EMG readings are used as the input of a dynamic system, which is integrated numerically. This approach requires the definition of a reasonably large set of parameters. Some of these vary widely among subjects, and slight inaccuracies in such parameters can lead to large model output errors. One of these parameters is the maximum voluntary contraction force (F(om)). This paper proposes an approach to find F(om) by estimating muscle physiological cross-sectional area (PCSA) using ultrasound (US), which is multiplied by a realistic value of maximum muscle specific tension. Ultrasound is used to measure muscle thickness, which allows for the determination of muscle volume through regression equations. Soleus, gastrocnemius medialis and gastrocnemius lateralis PCSAs are estimated using published volume proportions among leg muscles, which also requires measurements of muscle fiber length and pennation angle by US. F(om) obtained by this approach and from data widely cited in the literature was used to comparatively test a Hill-type EMG-driven model of the ankle joint. The model uses 3 EMGs (Soleus, gastrocnemius medialis and gastrocnemius lateralis) as inputs with joint torque as the output. The EMG signals were obtained in a series of experiments carried out with 8 adult male subjects, who performed an isometric contraction protocol consisting of 10s step contractions at 20% and 60% of the maximum voluntary contraction level. Isometric torque was simultaneously collected using a dynamometer. A statistically significant reduction in the root mean square error was observed when US-obtained F(om) was used, as compared to F(om) from the literature.

  4. Multiplex transmission system for gate drive signals of inverter circuit using surface acoustic wave filters

    NASA Astrophysics Data System (ADS)

    Suzuki, Akifumi; Ueda, Kensuke; Goka, Shigeyoshi; Wada, Keiji; Kakio, Shoji

    2016-07-01

    We propose and fabricate a multiplexed transmission system based on frequency-division multiple access (FDMA) with surface acoustic wave (SAW) filters. SAW filters are suitable for use in wide-gap switching devices and multilevel inverters because of their capability to operate at high temperatures, good electrical isolation, low cost, and high reliability. Our proposed system reduces the number of electrical signal wires needed to control each switching device and eliminates the need for isolation circuits, simplifying the transmission system and gate drive circuits. We successfully controlled two switching devices with a single coaxial line and confirmed the operation of a single-phase half-bridge inverter at a supply voltage of 100 V, and the total delay time to control the switching devices was less than 2.5 µs. Our experimental results validated our proposed system.

  5. Cell surface receptors for signal transduction and ligand transport - a design principles study

    SciTech Connect

    Shankaran, Harish; Resat, Haluk; Wiley, H. S.

    2007-06-01

    Although many different receptors undergo endocytosis, the system-level design principles that govern the evolution of receptor dynamics are far from fully understood. We have constructed a generalized mathematical model to understand how receptor internalization dynamics encodes receptor function and regulation. Parametric analysis of the response of receptor systems to ligand inputs reveals that receptors can be categorized a being: i) avidity-controlled where the response control depends primarily on the extracelluar ligand capture efficiency, ii) consumption-controlled where the ability to internalize surface-bound ligand is the primary control parameter, and iii) dual-sensitivity where both the avidity and consumption parameters are important. We show that the transferrin and low-density lipoprotein receptors are avidity-controlled, the vitellogenin receptor is consumption-controlled and epidermal growth factor receptor is a dual-sensitivity receptor. Significantly, we show that ligand-induced endocytosis is a mechanism to anhance the accuracy of signaling receptors rather than serving to attenuate signaling. Our analysis reveals that the location of a receptor system in the avidity-consumption parameter space can be used to understand both its function and its regulations.

  6. Application of the normalized surface magnetic charge model to UXO discrimination in cases with overlapping signals

    NASA Astrophysics Data System (ADS)

    Shubitidze, F.; O'Neill, K.; Barrowes, B. E.; Shamatava, I.; Fernández, J. P.; Sun, K.; Paulsen, K. D.

    2007-03-01

    This paper presents an application of the normalized surface magnetic charge (NSMC) model to discriminate objects of interest, such as unexploded ordnance (UXO), from innocuous items in cases when UXO electromagnetic induction (EMI) responses are contaminated by signals from other objects. Over the entire EMI spectrum considered here (tens of Hertz up to several hundreds of kHz), the scattered magnetic field outside the object can be produced mathematically by equivalent magnetic charges. The amplitudes of these charges are determined from measurement data and normalized by the excitation field. The model takes into account the scatterer's heterogeneity and near- and far-field effects. For classification algorithms, the frequency spectrum of the total NSMC is proposed and investigated as a discriminant. The NSMC is combined with the differential evolution (DE) algorithm in a two-step inversion procedure. To illustrate the applicability of the DE-NSMC algorithm, blind test data are processed and analyzed for cases in which signals from nearby objects frequently overlap. The method was highly successful in distinguishing UXO from accompanying clutter.

  7. Locomotor adaptation to a soleus EMG-controlled antagonistic exoskeleton.

    PubMed

    Gordon, Keith E; Kinnaird, Catherine R; Ferris, Daniel P

    2013-04-01

    Locomotor adaptation in humans is not well understood. To provide insight into the neural reorganization that occurs following a significant disruption to one's learned neuromuscular map relating a given motor command to its resulting muscular action, we tied the mechanical action of a robotic exoskeleton to the electromyography (EMG) profile of the soleus muscle during walking. The powered exoskeleton produced an ankle dorsiflexion torque proportional to soleus muscle recruitment thus limiting the soleus' plantar flexion torque capability. We hypothesized that neurologically intact subjects would alter muscle activation patterns in response to the antagonistic exoskeleton by decreasing soleus recruitment. Subjects practiced walking with the exoskeleton for two 30-min sessions. The initial response to the perturbation was to "fight" the resistive exoskeleton by increasing soleus activation. By the end of training, subjects had significantly reduced soleus recruitment resulting in a gait pattern with almost no ankle push-off. In addition, there was a trend for subjects to reduce gastrocnemius recruitment in proportion to the soleus even though only the soleus EMG was used to control the exoskeleton. The results from this study demonstrate the ability of the nervous system to recalibrate locomotor output in response to substantial changes in the mechanical output of the soleus muscle and associated sensory feedback. This study provides further evidence that the human locomotor system of intact individuals is highly flexible and able to adapt to achieve effective locomotion in response to a broad range of neuromuscular perturbations. PMID:23307949

  8. EMG activity during positive-pressure treadmill running.

    PubMed

    Hunter, Iain; Seeley, Matthew Kirk; Hopkins, Jon Ty; Carr, Cameron; Franson, Jared Judd

    2014-06-01

    Success has been demonstrated in rehabilitation from certain injuries while using positive-pressure treadmills. However, certain injuries progress even with the lighter vertical loads. Our purpose was to investigate changes in muscle activation for various lower limb muscles while running on a positive-pressure treadmill at different amounts of body weight support. We hypothesized that some muscles would show decreases in activation with greater body weight support while others would not. Eleven collegiate distance runners were recruited. EMG amplitude was measured over 12 lower limb muscles. After a short warm-up, subjects ran at 100%, 80%, 60%, and 40% of their body weight for two minutes each. EMG amplitudes were recorded during the final 30s of each stage. Most muscles demonstrated lower amplitudes as body weight was supported. For the hip adductors during the swing phase and the hamstrings during stance, no significant trend appeared. Positive-pressure treadmills may be useful interventions for certain injuries. However, some injuries, such as hip adductor and hamstring tendonitis or strains may require alternative cross-training to relieve stress on those areas. Runners should be careful in determining how much body weight should be supported for various injuries to return to normal activity in the shortest possible time. PMID:24613660

  9. EMG activity during positive-pressure treadmill running.

    PubMed

    Hunter, Iain; Seeley, Matthew Kirk; Hopkins, Jon Ty; Carr, Cameron; Franson, Jared Judd

    2014-06-01

    Success has been demonstrated in rehabilitation from certain injuries while using positive-pressure treadmills. However, certain injuries progress even with the lighter vertical loads. Our purpose was to investigate changes in muscle activation for various lower limb muscles while running on a positive-pressure treadmill at different amounts of body weight support. We hypothesized that some muscles would show decreases in activation with greater body weight support while others would not. Eleven collegiate distance runners were recruited. EMG amplitude was measured over 12 lower limb muscles. After a short warm-up, subjects ran at 100%, 80%, 60%, and 40% of their body weight for two minutes each. EMG amplitudes were recorded during the final 30s of each stage. Most muscles demonstrated lower amplitudes as body weight was supported. For the hip adductors during the swing phase and the hamstrings during stance, no significant trend appeared. Positive-pressure treadmills may be useful interventions for certain injuries. However, some injuries, such as hip adductor and hamstring tendonitis or strains may require alternative cross-training to relieve stress on those areas. Runners should be careful in determining how much body weight should be supported for various injuries to return to normal activity in the shortest possible time.

  10. Convective signals from surface measurements at ARM Tropical Western Pacific site: Manus

    SciTech Connect

    Wang, Yi; Long, Charles N.; Mather, James H.; Liu, Xiaodong

    2011-02-04

    Madden-Julian Oscillation (MJO) signals have been detected using highly sampled observations from the U.S. DOE ARM Climate Research Facility located at the Tropical Western Pacific Manus site. Using downwelling shortwave radiative fluxes and derived shortwave fractional sky cover, and the statistical tools of wavelet, cross wavelet, and Fourier spectrum power, we report finding major convective signals and their phase change from surface observations spanning from 1996 to 2006. Our findings are confirmed with the satellite-gauge combined values of precipitation from the NASA Global Precipitation Climatology Project and the NOAA interpolated outgoing longwave radiation for the same location. We find that the Manus MJO signal is weakest during the strongest 1997-1998 El Nin˜o Southern Oscillation (ENSO) year. A significant 3-5-month lead in boreal winter is identified further between Manus MJO and NOAA NINO3.4 sea surface temperature (former leads latter). A striking inverse relationship is found also between the instantaneous synoptic and intraseasonal phenomena over Manus. To further study the interaction between intraseasonal and diurnal scale variability, we composite the diurnal cycle of cloudiness for 21-MJO events that have passed over Manus. Our diurnal composite analysis of shortwave and longwave fractional sky covers indicates that during the MJO peak (strong convection), the diurnal amplitude of cloudiness is reduced substantially, while the diurnal mean cloudiness reaches the highest value and there are no significant phase changes. We argue that the increasing diurnal mean and decreasing diurnal amplitude are caused by the systematic convective cloud formation that is associated with the wet phase of the MJO, while the diurnal phase is still regulated by the well-defined solar forcing. This confirms our previous finding of the anti-phase relationship between the synoptic and intraseasonal phenomena. The detection of theMJOover the Manus site provides

  11. Convective signals from surface measurements at ARM Tropical Western Pacific site: Manus

    NASA Astrophysics Data System (ADS)

    Wang, Yi; Long, Charles N.; Mather, James H.; Liu, Xiaodong

    2011-02-01

    Madden-Julian Oscillation (MJO) signals have been detected using highly sampled observations from the U.S. DOE ARM Climate Research Facility located at the Tropical Western Pacific Manus site. Using downwelling shortwave radiative fluxes and derived shortwave fractional sky cover, and the statistical tools of wavelet, cross wavelet, and Fourier spectrum power, we report finding major convective signals and their phase change from surface observations spanning from 1996 to 2006. Our findings are confirmed with the satellite-gauge combined values of precipitation from the NASA Global Precipitation Climatology Project and the NOAA interpolated outgoing longwave radiation for the same location. We find that the Manus MJO signal is weakest during the strongest 1997-1998 El Niño Southern Oscillation (ENSO) year. A significant 3-5-month lead in boreal winter is identified further between Manus MJO and NOAA NINO3.4 sea surface temperature (former leads latter). A striking inverse relationship is found also between the instantaneous synoptic and intraseasonal phenomena over Manus. To further study the interaction between intraseasonal and diurnal scale variability, we composite the diurnal cycle of cloudiness for 21-MJO events that have passed over Manus. Our diurnal composite analysis of shortwave and longwave fractional sky covers indicates that during the MJO peak (strong convection), the diurnal amplitude of cloudiness is reduced substantially, while the diurnal mean cloudiness reaches the highest value and there are no significant phase changes. We argue that the increasing diurnal mean and decreasing diurnal amplitude are caused by the systematic convective cloud formation that is associated with the wet phase of the MJO, while the diurnal phase is still regulated by the well-defined solar forcing. This confirms our previous finding of the anti-phase relationship between the synoptic and intraseasonal phenomena. The detection of the MJO over the Manus site provides

  12. Agonist and Antagonist Muscle EMG Activity Pattern Changes with Skill Acquisition.

    ERIC Educational Resources Information Center

    Engelhorn, Richard

    1983-01-01

    Using electromyography (EMG), researchers studied changes in the control of biceps and triceps brachii muscles that occurred as women college students learned two elbow flexion tasks. Data on EMG activity, angular kinematics, training, and angular displacement were analyzed. (Author/PP)

  13. Preliminary Investigation of EMG Biofeedback Induced Relaxation with a Preschool Aged Stutterer.

    ERIC Educational Resources Information Center

    St. Louis, Kenneth O.; And Others

    1982-01-01

    Using comparative speech tasks and EMG recordings to assess the potential of EMG biofeedback-assisted relaxation to reduce stuttering, a preschool child was able to reduce larynegeal tension but not without some difficulty. The small effect of the training was in the direction of less stuttering. (Author/CM)

  14. The effect of neutral-surface iron oxide nanoparticles on cellular uptake and signaling pathways