Determining the optimal window length for pattern recognition-based myoelectric control: balancing the competing effects of classification error and controller delay.

PubMed

Smith, Lauren H; Hargrove, Levi J; Lock, Blair A; Kuiken, Todd A

2011-04-01

Pattern recognition-based control of myoelectric prostheses has shown great promise in research environments, but has not been optimized for use in a clinical setting. To explore the relationship between classification error, controller delay, and real-time controllability, 13 able-bodied subjects were trained to operate a virtual upper-limb prosthesis using pattern recognition of electromyogram (EMG) signals. Classification error and controller delay were varied by training different classifiers with a variety of analysis window lengths ranging from 50 to 550 ms and either two or four EMG input channels. Offline analysis showed that classification error decreased with longer window lengths (p < 0.01 ). Real-time controllability was evaluated with the target achievement control (TAC) test, which prompted users to maneuver the virtual prosthesis into various target postures. The results indicated that user performance improved with lower classification error (p < 0.01 ) and was reduced with longer controller delay (p < 0.01 ), as determined by the window length. Therefore, both of these effects should be considered when choosing a window length; it may be beneficial to increase the window length if this results in a reduced classification error, despite the corresponding increase in controller delay. For the system employed in this study, the optimal window length was found to be between 150 and 250 ms, which is within acceptable controller delays for conventional multistate amplitude controllers.

sEMG Sensor Using Polypyrrole-Coated Nonwoven Fabric Sheet for Practical Control of Prosthetic Hand

PubMed Central

Jiang, Yinlai; Togane, Masami; Lu, Baoliang; Yokoi, Hiroshi

2017-01-01

One of the greatest challenges of using a myoelectric prosthetic hand in daily life is to conveniently measure stable myoelectric signals. This study proposes a novel surface electromyography (sEMG) sensor using polypyrrole-coated nonwoven fabric sheet as electrodes (PPy electrodes) to allow people with disabilities to control prosthetic limbs. The PPy electrodes are sewn on an elastic band to guarantee close contact with the skin and thus reduce the contact electrical impedance between the electrodes and the skin. The sensor is highly customizable to fit the size and the shape of the stump so that people with disabilities can attach the sensor by themselves. The performance of the proposed sensor was investigated experimentally by comparing measurements of Ag/AgCl electrodes with electrolytic gel and the sEMG from the same muscle fibers. The high correlation coefficient (0.87) between the two types of sensors suggests the effectiveness of the proposed sensor. Another experiment of sEMG pattern recognition to control myoelectric prosthetic hands showed that the PPy electrodes are as effective as Ag/AgCl electrodes for measuring sEMG signals for practical myoelectric control. We also investigated the relation between the myoelectric signals' signal-to-noise ratio and the source impedances by simultaneously measuring the source impedances and the myoelectric signals with a switching circuit. The results showed that differences in both the norm and the phase of the source impedance greatly affect the common mode noise in the signal. PMID:28220058

Improving robustness against electrode shift of high density EMG for myoelectric control through common spatial patterns.

PubMed

Pan, Lizhi; Zhang, Dingguo; Jiang, Ning; Sheng, Xinjun; Zhu, Xiangyang

2015-12-02

Most prosthetic myoelectric control studies have concentrated on low density (less than 16 electrodes, LD) electromyography (EMG) signals, due to its better clinical applicability and low computation complexity compared with high density (more than 16 electrodes, HD) EMG signals. Since HD EMG electrodes have been developed more conveniently to wear with respect to the previous versions recently, HD EMG signals become an alternative for myoelectric prostheses. The electrode shift, which may occur during repositioning or donning/doffing of the prosthetic socket, is one of the main reasons for degradation in classification accuracy (CA). HD EMG signals acquired from the forearm of the subjects were used for pattern recognition-based myoelectric control in this study. Multiclass common spatial patterns (CSP) with two types of schemes, namely one versus one (CSP-OvO) and one versus rest (CSP-OvR), were used for feature extraction to improve the robustness against electrode shift for myoelectric control. Shift transversal (ST1 and ST2) and longitudinal (SL1 and SL2) to the direction of the muscle fibers were taken into consideration. We tested nine intact-limb subjects for eleven hand and wrist motions. The CSP features (CSP-OvO and CSP-OvR) were compared with three commonly used features, namely time-domain (TD) features, time-domain autoregressive (TDAR) features and variogram (Variog) features. Compared with the TD features, the CSP features significantly improved the CA over 10 % in all shift configurations (ST1, ST2, SL1 and SL2). Compared with the TDAR features, a. the CSP-OvO feature significantly improved the average CA over 5 % in all shift configurations; b. the CSP-OvR feature significantly improved the average CA in shift configurations ST1, SL1 and SL2. Compared with the Variog features, the CSP features significantly improved the average CA in longitudinal shift configurations (SL1 and SL2). The results demonstrated that the CSP features significantly improved the robustness against electrode shift for myoelectric control with respect to the commonly used features.

Combining two open source tools for neural computation (BioPatRec and Netlab) improves movement classification for prosthetic control.

PubMed

Prahm, Cosima; Eckstein, Korbinian; Ortiz-Catalan, Max; Dorffner, Georg; Kaniusas, Eugenijus; Aszmann, Oskar C

2016-08-31

Controlling a myoelectric prosthesis for upper limbs is increasingly challenging for the user as more electrodes and joints become available. Motion classification based on pattern recognition with a multi-electrode array allows multiple joints to be controlled simultaneously. Previous pattern recognition studies are difficult to compare, because individual research groups use their own data sets. To resolve this shortcoming and to facilitate comparisons, open access data sets were analysed using components of BioPatRec and Netlab pattern recognition models. Performances of the artificial neural networks, linear models, and training program components were compared. Evaluation took place within the BioPatRec environment, a Matlab-based open source platform that provides feature extraction, processing and motion classification algorithms for prosthetic control. The algorithms were applied to myoelectric signals for individual and simultaneous classification of movements, with the aim of finding the best performing algorithm and network model. Evaluation criteria included classification accuracy and training time. Results in both the linear and the artificial neural network models demonstrated that Netlab's implementation using scaled conjugate training algorithm reached significantly higher accuracies than BioPatRec. It is concluded that the best movement classification performance would be achieved through integrating Netlab training algorithms in the BioPatRec environment so that future prosthesis training can be shortened and control made more reliable. Netlab was therefore included into the newest release of BioPatRec (v4.0).

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

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.

Optimizing pattern recognition-based control for partial-hand prosthesis application.

PubMed

Earley, Eric J; Adewuyi, Adenike A; Hargrove, Levi J

2014-01-01

Partial-hand amputees often retain good residual wrist motion, which is essential for functional activities involving use of the hand. Thus, a crucial design criterion for a myoelectric, partial-hand prosthesis control scheme is that it allows the user to retain residual wrist motion. Pattern recognition (PR) of electromyographic (EMG) signals is a well-studied method of controlling myoelectric prostheses. However, wrist motion degrades a PR system's ability to correctly predict hand-grasp patterns. We studied the effects of (1) window length and number of hand-grasps, (2) static and dynamic wrist motion, and (3) EMG muscle source on the ability of a PR-based control scheme to classify functional hand-grasp patterns. Our results show that training PR classifiers with both extrinsic and intrinsic muscle EMG yields a lower error rate than training with either group by itself (p<0.001); and that training in only variable wrist positions, with only dynamic wrist movements, or with both variable wrist positions and movements results in lower error rates than training in only the neutral wrist position (p<0.001). Finally, our results show that both an increase in window length and a decrease in the number of grasps available to the classifier significantly decrease classification error (p<0.001). These results remained consistent whether the classifier selected or maintained a hand-grasp.

Comparative study of state-of-the-art myoelectric controllers for multigrasp prosthetic hands.

PubMed

Segil, Jacob L; Controzzi, Marco; Weir, Richard F ff; Cipriani, Christian

2014-01-01

A myoelectric controller should provide an intuitive and effective human-machine interface that deciphers user intent in real-time and is robust enough to operate in daily life. Many myoelectric control architectures have been developed, including pattern recognition systems, finite state machines, and more recently, postural control schemes. Here, we present a comparative study of two types of finite state machines and a postural control scheme using both virtual and physical assessment procedures with seven nondisabled subjects. The Southampton Hand Assessment Procedure (SHAP) was used in order to compare the effectiveness of the controllers during activities of daily living using a multigrasp artificial hand. Also, a virtual hand posture matching task was used to compare the controllers when reproducing six target postures. The performance when using the postural control scheme was significantly better (p < 0.05) than the finite state machines during the physical assessment when comparing within-subject averages using the SHAP percent difference metric. The virtual assessment results described significantly greater completion rates (97% and 99%) for the finite state machines, but the movement time tended to be faster (2.7 s) for the postural control scheme. Our results substantiate that postural control schemes rival other state-of-the-art myoelectric controllers.

Closed-Loop Control of Myoelectric Prostheses With Electrotactile Feedback: Influence of Stimulation Artifact and Blanking.

PubMed

Hartmann, Cornelia; Dosen, Strahinja; Amsuess, Sebastian; Farina, Dario

2015-09-01

Electrocutaneous stimulation is a promising approach to provide sensory feedback to amputees, and thus close the loop in upper limb prosthetic systems. However, the stimulation introduces artifacts in the recorded electromyographic (EMG) signals, which may be detrimental for the control of myoelectric prostheses. In this study, artifact blanking with three data segmentation approaches was investigated as a simple method to restore the performance of pattern recognition in prosthesis control (eight motions) when EMG signals are corrupted by stimulation artifacts. The methods were tested over a range of stimulation conditions and using four feature sets, comprising both time and frequency domain features. The results demonstrated that when stimulation artifacts were present, the classification performance improved with blanking in all tested conditions. In some cases, the classification performance with blanking was at the level of the benchmark (artifact-free data). The greatest pulse duration and frequency that allowed a full performance recovery were 400 μs and 150 Hz, respectively. These results show that artifact blanking can be used as a practical solution to eliminate the negative influence of the stimulation artifact on EMG pattern classification in a broad range of conditions, thus allowing to close the loop in myoelectric prostheses using electrotactile feedback.

Interface Prostheses With Classifier-Feedback-Based User Training.

PubMed

Fang, Yinfeng; Zhou, Dalin; Li, Kairu; Liu, Honghai

2017-11-01

It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.

Toward attenuating the impact of arm positions on electromyography pattern-recognition based motion classification in transradial amputees

PubMed Central

2012-01-01

Background Electromyography (EMG) pattern-recognition based control strategies for multifunctional myoelectric prosthesis systems have been studied commonly in a controlled laboratory setting. Before these myoelectric prosthesis systems are clinically viable, it will be necessary to assess the effect of some disparities between the ideal laboratory setting and practical use on the control performance. One important obstacle is the impact of arm position variation that causes the changes of EMG pattern when performing identical motions in different arm positions. This study aimed to investigate the impacts of arm position variation on EMG pattern-recognition based motion classification in upper-limb amputees and the solutions for reducing these impacts. Methods With five unilateral transradial (TR) amputees, the EMG signals and tri-axial accelerometer mechanomyography (ACC-MMG) signals were simultaneously collected from both amputated and intact arms when performing six classes of arm and hand movements in each of five arm positions that were considered in the study. The effect of the arm position changes was estimated in terms of motion classification error and compared between amputated and intact arms. Then the performance of three proposed methods in attenuating the impact of arm positions was evaluated. Results With EMG signals, the average intra-position and inter-position classification errors across all five arm positions and five subjects were around 7.3% and 29.9% from amputated arms, respectively, about 1.0% and 10% low in comparison with those from intact arms. While ACC-MMG signals could yield a similar intra-position classification error (9.9%) as EMG, they had much higher inter-position classification error with an average value of 81.1% over the arm positions and the subjects. When the EMG data from all five arm positions were involved in the training set, the average classification error reached a value of around 10.8% for amputated arms. Using a two-stage cascade classifier, the average classification error was around 9.0% over all five arm positions. Reducing ACC-MMG channels from 8 to 2 only increased the average position classification error across all five arm positions from 0.7% to 1.0% in amputated arms. Conclusions The performance of EMG pattern-recognition based method in classifying movements strongly depends on arm positions. This dependency is a little stronger in intact arm than in amputated arm, which suggests that the investigations associated with practical use of a myoelectric prosthesis should use the limb amputees as subjects instead of using able-body subjects. The two-stage cascade classifier mode with ACC-MMG for limb position identification and EMG for limb motion classification may be a promising way to reduce the effect of limb position variation on classification performance. PMID:23036049

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

PubMed Central

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-01-01

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition.

PubMed

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-06-13

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle).

Treatment of phantom limb pain (PLP) based on augmented reality and gaming controlled by myoelectric pattern recognition: a case study of a chronic PLP patient

PubMed Central

Ortiz-Catalan, Max; Sander, Nichlas; Kristoffersen, Morten B.; Håkansson, Bo; Brånemark, Rickard

2014-01-01

A variety of treatments have been historically used to alleviate phantom limb pain (PLP) with varying efficacy. Recently, virtual reality (VR) has been employed as a more sophisticated mirror therapy. Despite the advantages of VR over a conventional mirror, this approach has retained the use of the contralateral limb and is therefore restricted to unilateral amputees. Moreover, this strategy disregards the actual effort made by the patient to produce phantom motions. In this work, we investigate a treatment in which the virtual limb responds directly to myoelectric activity at the stump, while the illusion of a restored limb is enhanced through augmented reality (AR). Further, phantom motions are facilitated and encouraged through gaming. The proposed set of technologies was administered to a chronic PLP patient who has shown resistance to a variety of treatments (including mirror therapy) for 48 years. Individual and simultaneous phantom movements were predicted using myoelectric pattern recognition and were then used as input for VR and AR environments, as well as for a racing game. The sustained level of pain reported by the patient was gradually reduced to complete pain-free periods. The phantom posture initially reported as a strongly closed fist was gradually relaxed, interestingly resembling the neutral posture displayed by the virtual limb. The patient acquired the ability to freely move his phantom limb, and a telescopic effect was observed where the position of the phantom hand was restored to the anatomically correct distance. More importantly, the effect of the interventions was positively and noticeably perceived by the patient and his relatives. Despite the limitation of a single case study, the successful results of the proposed system in a patient for whom other medical and non-medical treatments have been ineffective justifies and motivates further investigation in a wider study. PMID:24616655

Treatment of phantom limb pain (PLP) based on augmented reality and gaming controlled by myoelectric pattern recognition: a case study of a chronic PLP patient.

PubMed

Ortiz-Catalan, Max; Sander, Nichlas; Kristoffersen, Morten B; Håkansson, Bo; Brånemark, Rickard

2014-01-01

A variety of treatments have been historically used to alleviate phantom limb pain (PLP) with varying efficacy. Recently, virtual reality (VR) has been employed as a more sophisticated mirror therapy. Despite the advantages of VR over a conventional mirror, this approach has retained the use of the contralateral limb and is therefore restricted to unilateral amputees. Moreover, this strategy disregards the actual effort made by the patient to produce phantom motions. In this work, we investigate a treatment in which the virtual limb responds directly to myoelectric activity at the stump, while the illusion of a restored limb is enhanced through augmented reality (AR). Further, phantom motions are facilitated and encouraged through gaming. The proposed set of technologies was administered to a chronic PLP patient who has shown resistance to a variety of treatments (including mirror therapy) for 48 years. Individual and simultaneous phantom movements were predicted using myoelectric pattern recognition and were then used as input for VR and AR environments, as well as for a racing game. The sustained level of pain reported by the patient was gradually reduced to complete pain-free periods. The phantom posture initially reported as a strongly closed fist was gradually relaxed, interestingly resembling the neutral posture displayed by the virtual limb. The patient acquired the ability to freely move his phantom limb, and a telescopic effect was observed where the position of the phantom hand was restored to the anatomically correct distance. More importantly, the effect of the interventions was positively and noticeably perceived by the patient and his relatives. Despite the limitation of a single case study, the successful results of the proposed system in a patient for whom other medical and non-medical treatments have been ineffective justifies and motivates further investigation in a wider study.

Analog Front-Ends comparison in the way of a portable, low-power and low-cost EMG controller based on pattern recognition EMBC 2015.

PubMed

Mastinu, Enzo; Ortiz-Catalan, Max; Hakansson, Bo

2015-01-01

Compact and low-noise Analog Front-Ends (AFEs) are becoming increasingly important for the acquisition of bioelectric signals in portable system. In this work, we compare two popular AFEs available on the market, namely the ADS1299 (Texas Instruments) and the RHA2216 (Intan Technologies). This work develops towards the identification of suitable acquisition modules to design an affordable, reliable and portable device for electromyography (EMG) acquisition and prosthetic control. Device features such as Common Mode Rejection (CMR), Input Referred Noise (IRN) and Signal to Noise Ratio (SNR) were evaluated, as well as the resulting accuracy in myoelectric pattern recognition (MPR) for the decoding of motion intention. Results reported better noise performances and higher MPR accuracy for the ADS1299 and similar SNR values for both devices.

The efficacy of using human myoelectric signals to control the limbs of robots in space

NASA Technical Reports Server (NTRS)

Clark, Jane E.; Phillips, Sally J.

1988-01-01

This project was designed to investigate the usefulness of the myoelectric signal as a control in robotics applications. More specifically, the neural patterns associated with human arm and hand actions were studied to determine the efficacy of using these myoelectric signals to control the manipulator arm of a robot. The advantage of this approach to robotic control was the use of well-defined and well-practiced neural patterns already available to the system, as opposed to requiring the human operator to learn new tasks and establish new neural patterns in learning to control a joystick or mechanical coupling device.

An upper-limb power-assist exoskeleton using proportional myoelectric control.

PubMed

Tang, Zhichuan; Zhang, Kejun; Sun, Shouqian; Gao, Zenggui; Zhang, Lekai; Yang, Zhongliang

2014-04-10

We developed an upper-limb power-assist exoskeleton actuated by pneumatic muscles. The exoskeleton included two metal links: a nylon joint, four size-adjustable carbon fiber bracers, a potentiometer and two pneumatic muscles. The proportional myoelectric control method was proposed to control the exoskeleton according to the user's motion intention in real time. With the feature extraction procedure and the classification (back-propagation neural network), an electromyogram (EMG)-angle model was constructed to be used for pattern recognition. Six healthy subjects performed elbow flexion-extension movements under four experimental conditions: (1) holding a 1-kg load, wearing the exoskeleton, but with no actuation and for different periods (2-s, 4-s and 8-s periods); (2) holding a 1-kg load, without wearing the exoskeleton, for a fixed period; (3) holding a 1-kg load, wearing the exoskeleton, but with no actuation, for a fixed period; (4) holding a 1-kg load, wearing the exoskeleton under proportional myoelectric control, for a fixed period. The EMG signals of the biceps brachii, the brachioradialis, the triceps brachii and the anconeus and the angle of the elbow were collected. The control scheme's reliability and power-assist effectiveness were evaluated in the experiments. The results indicated that the exoskeleton could be controlled by the user's motion intention in real time and that it was useful for augmenting arm performance with neurological signal control, which could be applied to assist in elbow rehabilitation after neurological injury.

Gastric myoelectrical and autonomic cardiac reactivity to laboratory stressors

PubMed Central

GIANAROS, PETER J.; QUIGLEY, KAREN S.; MORDKOFF, J. TOBY; STERN, ROBERT M.

2010-01-01

We evaluated the effects of two laboratory stressors (speech preparation and isometric handgrip) on gastric myoelectrical and autonomic cardiac activity, and the extent to which autonomic responses to these stressors and somatization predict reports of motion sickness during exposure to a rotating optokinetic drum. Both stressors prompted a decrease in preejection period (PEP) and respiratory sinus arrhythmia (RSA), and an increase in a dysrhythmic pattern of gastric myoelectrical activity, termed gastric tachyarrhythmia. Stressor-induced decreases in RSA and higher somatization scores predicted increased reports of motion sickness during drum rotation. These results demonstrate that laboratory stressors concurrently affect gastric myoelectrical activity and autonomic control of the heart, and that stressor-induced decreases in RSA and higher levels of somatization predict motion sickness susceptibility. PMID:11446577

Validation of a selective ensemble-based classification scheme for myoelectric control using a three-dimensional Fitts' Law test.

PubMed

Scheme, Erik J; Englehart, Kevin B

2013-07-01

When controlling a powered upper limb prosthesis it is important not only to know how to move the device, but also when not to move. A novel approach to pattern recognition control, using a selective multiclass one-versus-one classification scheme has been shown to be capable of rejecting unintended motions. This method was shown to outperform other popular classification schemes when presented with muscle contractions that did not correspond to desired actions. In this work, a 3-D Fitts' Law test is proposed as a suitable alternative to using virtual limb environments for evaluating real-time myoelectric control performance. The test is used to compare the selective approach to a state-of-the-art linear discriminant analysis classification based scheme. The framework is shown to obey Fitts' Law for both control schemes, producing linear regression fittings with high coefficients of determination (R(2) > 0.936). Additional performance metrics focused on quality of control are discussed and incorporated in the evaluation. Using this framework the selective classification based scheme is shown to produce significantly higher efficiency and completion rates, and significantly lower overshoot and stopping distances, with no significant difference in throughput.

Gesture recognition by instantaneous surface EMG images.

PubMed

Geng, Weidong; Du, Yu; Jin, Wenguang; Wei, Wentao; Hu, Yu; Li, Jiajun

2016-11-15

Gesture recognition in non-intrusive muscle-computer interfaces is usually based on windowed descriptive and discriminatory surface electromyography (sEMG) features because the recorded amplitude of a myoelectric signal may rapidly fluctuate between voltages above and below zero. Here, we present that the patterns inside the instantaneous values of high-density sEMG enables gesture recognition to be performed merely with sEMG signals at a specific instant. We introduce the concept of an sEMG image spatially composed from high-density sEMG and verify our findings from a computational perspective with experiments on gesture recognition based on sEMG images with a classification scheme of a deep convolutional network. Without any windowed features, the resultant recognition accuracy of an 8-gesture within-subject test reached 89.3% on a single frame of sEMG image and reached 99.0% using simple majority voting over 40 frames with a 1,000 Hz sampling rate. Experiments on the recognition of 52 gestures of NinaPro database and 27 gestures of CSL-HDEMG database also validated that our approach outperforms state-of-the-arts methods. Our findings are a starting point for the development of more fluid and natural muscle-computer interfaces with very little observational latency. For example, active prostheses and exoskeletons based on high-density electrodes could be controlled with instantaneous responses.

Motion Control of Drives for Prosthetic Hand Using Continuous Myoelectric Signals

NASA Astrophysics Data System (ADS)

Purushothaman, Geethanjali; Ray, Kalyan Kumar

2016-03-01

In this paper the authors present motion control of a prosthetic hand, through continuous myoelectric signal acquisition, classification and actuation of the prosthetic drive. A four channel continuous electromyogram (EMG) signal also known as myoelectric signals (MES) are acquired from the abled-body to classify the six unique movements of hand and wrist, viz, hand open (HO), hand close (HC), wrist flexion (WF), wrist extension (WE), ulnar deviation (UD) and radial deviation (RD). The classification technique involves in extracting the features/pattern through statistical time domain (TD) parameter/autoregressive coefficients (AR), which are reduced using principal component analysis (PCA). The reduced statistical TD features and or AR coefficients are used to classify the signal patterns through k nearest neighbour (kNN) as well as neural network (NN) classifier and the performance of the classifiers are compared. Performance comparison of the above two classifiers clearly shows that kNN classifier in identifying the hidden intended motion in the myoelectric signals is better than that of NN classifier. Once the classifier identifies the intended motion, the signal is amplified to actuate the three low power DC motor to perform the above mentioned movements.

Improved prosthetic hand control with concurrent use of myoelectric and inertial measurements.

PubMed

Krasoulis, Agamemnon; Kyranou, Iris; Erden, Mustapha Suphi; Nazarpour, Kianoush; Vijayakumar, Sethu

2017-07-11

Myoelectric pattern recognition systems can decode movement intention to drive upper-limb prostheses. Despite recent advances in academic research, the commercial adoption of such systems remains low. This limitation is mainly due to the lack of classification robustness and a simultaneous requirement for a large number of electromyogram (EMG) electrodes. We propose to address these two issues by using a multi-modal approach which combines surface electromyography (sEMG) with inertial measurements (IMs) and an appropriate training data collection paradigm. We demonstrate that this can significantly improve classification performance as compared to conventional techniques exclusively based on sEMG signals. We collected and analyzed a large dataset comprising recordings with 20 able-bodied and two amputee participants executing 40 movements. Additionally, we conducted a novel real-time prosthetic hand control experiment with 11 able-bodied subjects and an amputee by using a state-of-the-art commercial prosthetic hand. A systematic performance comparison was carried out to investigate the potential benefit of incorporating IMs in prosthetic hand control. The inclusion of IM data improved performance significantly, by increasing classification accuracy (CA) in the offline analysis and improving completion rates (CRs) in the real-time experiment. Our findings were consistent across able-bodied and amputee subjects. Integrating the sEMG electrodes and IM sensors within a single sensor package enabled us to achieve high-level performance by using on average 4-6 sensors. The results from our experiments suggest that IMs can form an excellent complimentary source signal for upper-limb myoelectric prostheses. We trust that multi-modal control solutions have the potential of improving the usability of upper-extremity prostheses in real-life applications.

Gesture recognition by instantaneous surface EMG images

PubMed Central

Geng, Weidong; Du, Yu; Jin, Wenguang; Wei, Wentao; Hu, Yu; Li, Jiajun

2016-01-01

Gesture recognition in non-intrusive muscle-computer interfaces is usually based on windowed descriptive and discriminatory surface electromyography (sEMG) features because the recorded amplitude of a myoelectric signal may rapidly fluctuate between voltages above and below zero. Here, we present that the patterns inside the instantaneous values of high-density sEMG enables gesture recognition to be performed merely with sEMG signals at a specific instant. We introduce the concept of an sEMG image spatially composed from high-density sEMG and verify our findings from a computational perspective with experiments on gesture recognition based on sEMG images with a classification scheme of a deep convolutional network. Without any windowed features, the resultant recognition accuracy of an 8-gesture within-subject test reached 89.3% on a single frame of sEMG image and reached 99.0% using simple majority voting over 40 frames with a 1,000 Hz sampling rate. Experiments on the recognition of 52 gestures of NinaPro database and 27 gestures of CSL-HDEMG database also validated that our approach outperforms state-of-the-arts methods. Our findings are a starting point for the development of more fluid and natural muscle-computer interfaces with very little observational latency. For example, active prostheses and exoskeletons based on high-density electrodes could be controlled with instantaneous responses. PMID:27845347

Motor unit recruitment patterns 2: the influence of myoelectric intensity and muscle fascicle strain rate.

PubMed

Hodson-Tole, Emma F; Wakeling, James M

2008-06-01

To effectively meet the force requirements of a given movement an appropriate number and combination of motor units must be recruited between and within muscles. Orderly recruitment of motor units has been shown to occur in a wide range of skeletal muscles, however, alternative strategies do occur. Faster motor units are better suited to developing force rapidly, and produce higher mechanical power with greater efficiency at faster shortening strain rates than slower motor units. As the frequency content of the myoelectric signal is related to the fibre type of the active motor units, we hypothesised that, in addition to an association between myoelectric frequency and intensity, there would be a significant association between muscle fascicle shortening strain rate and myoelectric frequency content. Myoelectric and sonomicrometric data were collected from the three ankle extensor muscles of the rat hind limb during walking and running. Myoelectric signals were analysed using wavelet transformation and principal component analysis to give a measure of the signal frequency content. Sonomicrometric signals were analysed to give measures of muscle fascicle strain and strain rate. The relationship between myoelectric frequency and both intensity and muscle fascicle strain rate was found to change across the time course of a stride, with differences also occurring in the strength of the associations between and within muscles. In addition to the orderly recruitment of motor units, a mechanical strategy of motor unit recruitment was therefore identified. Motor unit recruitment is therefore a multifactorial phenomenon, which is more complex than typically thought.

The migrating myoelectric complex of the small intestine

NASA Astrophysics Data System (ADS)

Telford, Gordon L.; Sarna, Sushil K.

1991-10-01

Gastric and small intestinal myoelectric and motor activity is divided into two main patterns, fed and fasted. During fasting, the predominant pattern of activity is the migrating myoelectric complex (MMC), a cyclically occurring pattern of electric and mechanical activity that is initiated in the stomach and duodenum almost simultaneously and, from there, propagates the length of the small intestine. Cyclic motor activity also occurs in the lower esophageal sphincter, the gallbladder, and the sphincter of Oddi with a duration that is related to the MMC in the small intestine. Of the possible mechanisms for initiation of the MMC in the small intestine (extrinsic neural control, intrinsic neural control, and hormonal control), intrinsic neural control via a series of coupled is the most likely. The keep this sentence in! hormone motilin also plays a role in the initiation of MMCs. After a meal, in man the MMC is disrupted and replaced by irregular contractions. The physiologic role of the MMC is to clear the stomach and small intestine of residual food, secretions, and desquamated cells and propel them to the colon. Disruption of the MMC cycle is associated with bacterial overgrowth in some patients, an observation that supports the proposed cleansing function of the MMC cycle.

Swarm-wavelet based extreme learning machine for finger movement classification on transradial amputees.

PubMed

Anam, Khairul; Al-Jumaily, Adel

2014-01-01

The use of a small number of surface electromyography (EMG) channels on the transradial amputee in a myoelectric controller is a big challenge. This paper proposes a pattern recognition system using an extreme learning machine (ELM) optimized by particle swarm optimization (PSO). PSO is mutated by wavelet function to avoid trapped in a local minima. The proposed system is used to classify eleven imagined finger motions on five amputees by using only two EMG channels. The optimal performance of wavelet-PSO was compared to a grid-search method and standard PSO. The experimental results show that the proposed system is the most accurate classifier among other tested classifiers. It could classify 11 finger motions with the average accuracy of about 94 % across five amputees.

A Prosthetic Hand Body Area Controller Based on Efficient Pattern Recognition Control Strategies.

PubMed

Benatti, Simone; Milosevic, Bojan; Farella, Elisabetta; Gruppioni, Emanuele; Benini, Luca

2017-04-15

Poliarticulated prosthetic hands represent a powerful tool to restore functionality and improve quality of life for upper limb amputees. Such devices offer, on the same wearable node, sensing and actuation capabilities, which are not equally supported by natural interaction and control strategies. The control in state-of-the-art solutions is still performed mainly through complex encoding of gestures in bursts of contractions of the residual forearm muscles, resulting in a non-intuitive Human-Machine Interface (HMI). Recent research efforts explore the use of myoelectric gesture recognition for innovative interaction solutions, however there persists a considerable gap between research evaluation and implementation into successful complete systems. In this paper, we present the design of a wearable prosthetic hand controller, based on intuitive gesture recognition and a custom control strategy. The wearable node directly actuates a poliarticulated hand and wirelessly interacts with a personal gateway (i.e., a smartphone) for the training and personalization of the recognition algorithm. Through the whole system development, we address the challenge of integrating an efficient embedded gesture classifier with a control strategy tailored for an intuitive interaction between the user and the prosthesis. We demonstrate that this combined approach outperforms systems based on mere pattern recognition, since they target the accuracy of a classification algorithm rather than the control of a gesture. The system was fully implemented, tested on healthy and amputee subjects and compared against benchmark repositories. The proposed approach achieves an error rate of 1.6% in the end-to-end real time control of commonly used hand gestures, while complying with the power and performance budget of a low-cost microcontroller.

A Prosthetic Hand Body Area Controller Based on Efficient Pattern Recognition Control Strategies

PubMed Central

Benatti, Simone; Milosevic, Bojan; Farella, Elisabetta; Gruppioni, Emanuele; Benini, Luca

2017-01-01

Poliarticulated prosthetic hands represent a powerful tool to restore functionality and improve quality of life for upper limb amputees. Such devices offer, on the same wearable node, sensing and actuation capabilities, which are not equally supported by natural interaction and control strategies. The control in state-of-the-art solutions is still performed mainly through complex encoding of gestures in bursts of contractions of the residual forearm muscles, resulting in a non-intuitive Human-Machine Interface (HMI). Recent research efforts explore the use of myoelectric gesture recognition for innovative interaction solutions, however there persists a considerable gap between research evaluation and implementation into successful complete systems. In this paper, we present the design of a wearable prosthetic hand controller, based on intuitive gesture recognition and a custom control strategy. The wearable node directly actuates a poliarticulated hand and wirelessly interacts with a personal gateway (i.e., a smartphone) for the training and personalization of the recognition algorithm. Through the whole system development, we address the challenge of integrating an efficient embedded gesture classifier with a control strategy tailored for an intuitive interaction between the user and the prosthesis. We demonstrate that this combined approach outperforms systems based on mere pattern recognition, since they target the accuracy of a classification algorithm rather than the control of a gesture. The system was fully implemented, tested on healthy and amputee subjects and compared against benchmark repositories. The proposed approach achieves an error rate of 1.6% in the end-to-end real time control of commonly used hand gestures, while complying with the power and performance budget of a low-cost microcontroller. PMID:28420135

Virtual Sensor of Surface Electromyography in a New Extensive Fault-Tolerant Classification System.

PubMed

de Moura, Karina de O A; Balbinot, Alexandre

2018-05-01

A few prosthetic control systems in the scientific literature obtain pattern recognition algorithms adapted to changes that occur in the myoelectric signal over time and, frequently, such systems are not natural and intuitive. These are some of the several challenges for myoelectric prostheses for everyday use. The concept of the virtual sensor, which has as its fundamental objective to estimate unavailable measures based on other available measures, is being used in other fields of research. The virtual sensor technique applied to surface electromyography can help to minimize these problems, typically related to the degradation of the myoelectric signal that usually leads to a decrease in the classification accuracy of the movements characterized by computational intelligent systems. This paper presents a virtual sensor in a new extensive fault-tolerant classification system to maintain the classification accuracy after the occurrence of the following contaminants: ECG interference, electrode displacement, movement artifacts, power line interference, and saturation. The Time-Varying Autoregressive Moving Average (TVARMA) and Time-Varying Kalman filter (TVK) models are compared to define the most robust model for the virtual sensor. Results of movement classification were presented comparing the usual classification techniques with the method of the degraded signal replacement and classifier retraining. The experimental results were evaluated for these five noise types in 16 surface electromyography (sEMG) channel degradation case studies. The proposed system without using classifier retraining techniques recovered of mean classification accuracy was of 4% to 38% for electrode displacement, movement artifacts, and saturation noise. The best mean classification considering all signal contaminants and channel combinations evaluated was the classification using the retraining method, replacing the degraded channel by the virtual sensor TVARMA model. This method recovered the classification accuracy after the degradations, reaching an average of 5.7% below the classification of the clean signal, that is the signal without the contaminants or the original signal. Moreover, the proposed intelligent technique minimizes the impact of the motion classification caused by signal contamination related to degrading events over time. There are improvements in the virtual sensor model and in the algorithm optimization that need further development to provide an increase the clinical application of myoelectric prostheses but already presents robust results to enable research with virtual sensors on biological signs with stochastic behavior.

Virtual Sensor of Surface Electromyography in a New Extensive Fault-Tolerant Classification System

PubMed Central

Balbinot, Alexandre

2018-01-01

A few prosthetic control systems in the scientific literature obtain pattern recognition algorithms adapted to changes that occur in the myoelectric signal over time and, frequently, such systems are not natural and intuitive. These are some of the several challenges for myoelectric prostheses for everyday use. The concept of the virtual sensor, which has as its fundamental objective to estimate unavailable measures based on other available measures, is being used in other fields of research. The virtual sensor technique applied to surface electromyography can help to minimize these problems, typically related to the degradation of the myoelectric signal that usually leads to a decrease in the classification accuracy of the movements characterized by computational intelligent systems. This paper presents a virtual sensor in a new extensive fault-tolerant classification system to maintain the classification accuracy after the occurrence of the following contaminants: ECG interference, electrode displacement, movement artifacts, power line interference, and saturation. The Time-Varying Autoregressive Moving Average (TVARMA) and Time-Varying Kalman filter (TVK) models are compared to define the most robust model for the virtual sensor. Results of movement classification were presented comparing the usual classification techniques with the method of the degraded signal replacement and classifier retraining. The experimental results were evaluated for these five noise types in 16 surface electromyography (sEMG) channel degradation case studies. The proposed system without using classifier retraining techniques recovered of mean classification accuracy was of 4% to 38% for electrode displacement, movement artifacts, and saturation noise. The best mean classification considering all signal contaminants and channel combinations evaluated was the classification using the retraining method, replacing the degraded channel by the virtual sensor TVARMA model. This method recovered the classification accuracy after the degradations, reaching an average of 5.7% below the classification of the clean signal, that is the signal without the contaminants or the original signal. Moreover, the proposed intelligent technique minimizes the impact of the motion classification caused by signal contamination related to degrading events over time. There are improvements in the virtual sensor model and in the algorithm optimization that need further development to provide an increase the clinical application of myoelectric prostheses but already presents robust results to enable research with virtual sensors on biological signs with stochastic behavior. PMID:29723994

Selection of suitable hand gestures for reliable myoelectric human computer interface.

PubMed

Castro, Maria Claudia F; Arjunan, Sridhar P; Kumar, Dinesh K

2015-04-09

Myoelectric controlled prosthetic hand requires machine based identification of hand gestures using surface electromyogram (sEMG) recorded from the forearm muscles. This study has observed that a sub-set of the hand gestures have to be selected for an accurate automated hand gesture recognition, and reports a method to select these gestures to maximize the sensitivity and specificity. Experiments were conducted where sEMG was recorded from the muscles of the forearm while subjects performed hand gestures and then was classified off-line. The performances of ten gestures were ranked using the proposed Positive-Negative Performance Measurement Index (PNM), generated by a series of confusion matrices. When using all the ten gestures, the sensitivity and specificity was 80.0% and 97.8%. After ranking the gestures using the PNM, six gestures were selected and these gave sensitivity and specificity greater than 95% (96.5% and 99.3%); Hand open, Hand close, Little finger flexion, Ring finger flexion, Middle finger flexion and Thumb flexion. This work has shown that reliable myoelectric based human computer interface systems require careful selection of the gestures that have to be recognized and without such selection, the reliability is poor.

Real-time and simultaneous control of artificial limbs based on pattern recognition algorithms.

PubMed

Ortiz-Catalan, Max; Håkansson, Bo; Brånemark, Rickard

2014-07-01

The prediction of simultaneous limb motions is a highly desirable feature for the control of artificial limbs. In this work, we investigate different classification strategies for individual and simultaneous movements based on pattern recognition of myoelectric signals. Our results suggest that any classifier can be potentially employed in the prediction of simultaneous movements if arranged in a distributed topology. On the other hand, classifiers inherently capable of simultaneous predictions, such as the multi-layer perceptron (MLP), were found to be more cost effective, as they can be successfully employed in their simplest form. In the prediction of individual movements, the one-vs-one (OVO) topology was found to improve classification accuracy across different classifiers and it was therefore used to benchmark the benefits of simultaneous control. As opposed to previous work reporting only offline accuracy, the classification performance and the resulting controllability are evaluated in real time using the motion test and target achievement control (TAC) test, respectively. We propose a simultaneous classification strategy based on MLP that outperformed a top classifier for individual movements (LDA-OVO), thus improving the state-of-the-art classification approach. Furthermore, all the presented classification strategies and data collected in this study are freely available in BioPatRec, an open source platform for the development of advanced prosthetic control strategies.

Task-specific recruitment of motor units for vibration damping.

PubMed

Wakeling, James M; Liphardt, Anna-Maria

2006-01-01

Vibrations occur within the soft tissues of the lower extremities due to the heel-strike impact during walking. Increases in muscle activity in the lower extremities result in increased damping to reduce this vibration. The myoelectric intensity spectra were compared using principal component analysis from the tibialis anterior and lateral gastrocnemius of 40 subjects walking with different shoe conditions. The soft insert condition resulted in a significant, simultaneous increase in muscle activity with a shift to higher myoelectric frequencies in the period 0-60 ms after heel-strike which is the period when the greater vibration damping occurred. These increases in myoelectric frequency match the spectral patterns which indicate increases in recruitment of faster motor units. It is concluded that fast motor units are recruited during the task of damping the soft-tissue resonance that occurs following heel-strike.

A synergy-driven approach to a myoelectric hand.

PubMed

Godfrey, S B; Ajoudani, A; Catalano, M; Grioli, G; Bicchi, A

2013-06-01

In this paper, we present the Pisa/IIT SoftHand with myoelectric control as a synergy-driven approach for a prosthetic hand. Commercially available myoelectric hands are more expensive, heavier, and less robust than their body-powered counterparts; however, they can offer greater freedom of motion and a more aesthetically pleasing appearance. The Pisa/IIT SoftHand is built on the motor control principle of synergies through which the immense complexity of the hand is simplified into distinct motor patterns. As the SoftHand grasps, it follows a synergistic path with built-in flexibility to allow grasping of a wide variety of objects with a single motor. Here we test, as a proof-of-concept, 4 myoelectric controllers: a standard controller in which the EMG signal is used only as a position reference, an impedance controller that determines both position and stiffness references from the EMG input, a standard controller with vibrotactile force feedback, and finally a combined vibrotactile-impedance (VI) controller. Four healthy subjects tested the control algorithms by grasping various objects. All controllers were sufficient for basic grasping, however the impedance and vibrotactile controllers reduced the physical and cognitive load on the user, while the combined VI mode was the easiest to use of the four. While these results need to be validated with amputees, they suggest a low-cost, robust hand employing hardware-based synergies is a viable alternative to traditional myoelectric prostheses.

Robotic Lower Limb Exoskeletons Using Proportional Myoelectric Control

PubMed Central

Ferris, Daniel P.; Lewis, Cara L.

2010-01-01

Robotic lower limb exoskeletons have been built for augmenting human performance, assisting with disabilities, studying human physiology, and re-training motor deficiencies. At the University of Michigan Human Neuromechanics Laboratory, we have built pneumatically-powered lower limb exoskeletons for the last two purposes. Most of our prior research has focused on ankle joint exoskeletons because of the large contribution from plantar flexors to the mechanical work performed during gait. One way we control the exoskeletons is with proportional myoelectric control, effectively increasing the strength of the wearer with a physiological mode of control. Healthy human subjects quickly adapt to walking with the robotic ankle exoskeletons, reducing their overall energy expenditure. Individuals with incomplete spinal cord injury have demonstrated rapid modification of muscle recruitment patterns with practice walking with the ankle exoskeletons. Evidence suggests that proportional myoelectric control may have distinct advantages over other types of control for robotic exoskeletons in basic science and rehabilitation. PMID:19964579

Variations in motor unit recruitment patterns occur within and between muscles in the running rat (Rattus norvegicus).

PubMed

Hodson-Tole, E F; Wakeling, J M

2007-07-01

Motor units are generally considered to follow a set, orderly pattern of recruitment within each muscle with activation occurring in the slowest through to the fastest units. A growing body of evidence, however, suggests that recruitment patterns may not always follow such an orderly sequence. Here we investigate whether motor unit recruitment patterns vary within and between the ankle extensor muscles of the rat running at 40 cm s(-1) on a level treadmill. In the past it has been difficult to quantify motor unit recruitment patterns during locomotion; however, recent application of wavelet analysis techniques has made such detailed analysis of motor unit recruitment possible. Here we present methods for quantifying the interplay of fast and slow motor unit recruitment based on their myoelectric signals. Myoelectric data were collected from soleus, plantaris and medial gastrocnemius muscles representing populations of slow, mixed and fast fibres, respectively, and providing a good opportunity to relate myoelectric frequency content to motor unit recruitment patterns. Following wavelet transformation, principal component analysis quantified signal intensity and relative frequency content. Significant differences in signal frequency content occurred between different time points within a stride (P<0.001). We optimised high- and low-frequency wavelets to the major signals from the fast and slow motor units. The goodness-of-fit of the optimised wavelets to the signal intensity was high for all three muscles (r2>0.98). The low-frequency band had a significantly better fit to signals from the soleus muscle (P<0.001), while the high-frequency band had a significantly better fit to the medial gastrocnemius (P<0.001).

A simple ERP method for quantitative analysis of cognitive workload in myoelectric prosthesis control and human-machine interaction.

PubMed

Deeny, Sean; Chicoine, Caitlin; Hargrove, Levi; Parrish, Todd; Jayaraman, Arun

2014-01-01

Common goals in the development of human-machine interface (HMI) technology are to reduce cognitive workload and increase function. However, objective and quantitative outcome measures assessing cognitive workload have not been standardized for HMI research. The present study examines the efficacy of a simple event-related potential (ERP) measure of cortical effort during myoelectric control of a virtual limb for use as an outcome tool. Participants trained and tested on two methods of control, direct control (DC) and pattern recognition control (PRC), while electroencephalographic (EEG) activity was recorded. Eighteen healthy participants with intact limbs were tested using DC and PRC under three conditions: passive viewing, easy, and hard. Novel auditory probes were presented at random intervals during testing, and significant task-difficulty effects were observed in the P200, P300, and a late positive potential (LPP), supporting the efficacy of ERPs as a cognitive workload measure in HMI tasks. LPP amplitude distinguished DC from PRC in the hard condition with higher amplitude in PRC, consistent with lower cognitive workload in PRC relative to DC for complex movements. Participants completed trials faster in the easy condition using DC relative to PRC, but completed trials more slowly using DC relative to PRC in the hard condition. The results provide promising support for ERPs as an outcome measure for cognitive workload in HMI research such as prosthetics, exoskeletons, and other assistive devices, and can be used to evaluate and guide new technologies for more intuitive HMI control.

Embedded System for Prosthetic Control Using Implanted Neuromuscular Interfaces Accessed Via an Osseointegrated Implant.

PubMed

Mastinu, Enzo; Doguet, Pascal; Botquin, Yohan; Hakansson, Bo; Ortiz-Catalan, Max

2017-08-01

Despite the technological progress in robotics achieved in the last decades, prosthetic limbs still lack functionality, reliability, and comfort. Recently, an implanted neuromusculoskeletal interface built upon osseointegration was developed and tested in humans, namely the Osseointegrated Human-Machine Gateway. Here, we present an embedded system to exploit the advantages of this technology. Our artificial limb controller allows for bioelectric signals acquisition, processing, decoding of motor intent, prosthetic control, and sensory feedback. It includes a neurostimulator to provide direct neural feedback based on sensory information. The system was validated using real-time tasks characterization, power consumption evaluation, and myoelectric pattern recognition performance. Functionality was proven in a first pilot patient from whom results of daily usage were obtained. The system was designed to be reliably used in activities of daily living, as well as a research platform to monitor prosthesis usage and training, machine-learning-based control algorithms, and neural stimulation paradigms.

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.

Neural network classification of myoelectric signal for prosthesis control.

PubMed

Kelly, M F; Parker, P A; Scott, R N

1991-12-01

An alternate approach to deriving control for multidegree of freedom prosthetic arms is considered. By analyzing a single-channel myoelectric signal (MES), we can extract information that can be used to identify different contraction patterns in the upper arm. These contraction patterns are generated by subjects without previous training and are naturally associated with specific functions. Using a set of normalized MES spectral features, we can identify contraction patterns for four arm functions, specifically extension and flexion of the elbow and pronation and supination of the forearm. Performing identification independent of signal power is advantageous because this can then be used as a means for deriving proportional rate control for a prosthesis. An artificial neural network implementation is applied in the classification task. By using three single-layer perceptron networks, the MES is classified, with the spectral representations as input features. Trials performed on five subjects with normal limbs resulted in an average classification performance level of 85% for the four functions. Copyright © 1991. Published by Elsevier Ltd.

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%.

Towards reducing the impacts of unwanted movements on identification of motion intentions.

PubMed

Li, Xiangxin; Chen, Shixiong; Zhang, Haoshi; Samuel, Oluwarotimi Williams; Wang, Hui; Fang, Peng; Zhang, Xiufeng; Li, Guanglin

2016-06-01

Surface electromyogram (sEMG) has been extensively used as a control signal in prosthesis devices. However, it is still a great challenge to make multifunctional myoelectric prostheses clinically available due to a number of critical issues associated with existing EMG based control strategy. One such issue would be the effect of unwanted movements (UMs) that are inadvertently done by users on the performance of movement classification in EMG pattern recognition based algorithms. Since UMs are not considered in training a classifier, they would decay the performance of a trained classifier in identifying the target movements (TMs), which would cause some undesired actions in control of multifunctional prostheses. In this study, the impact of UMs was systemically investigated in both able-bodied subjects and transradial amputees. Our results showed that the UMs would be unevenly classified into all classes of the TMs. To reduce the impact of the UMs on the performance of a classifier, a new training strategy that would categorize all possible UMs into a new movement class was proposed and a metric called Reject Ratio that is a measure of how many UMs is rejected by a trained classifier was adopted. The results showed that the average Reject Ratio across all the participants was greater than 91%, meanwhile the average classification accuracy of TMs was above 99% when UMs occurred. This suggests that the proposed training strategy could greatly reduce the impact of UMs on the performance of the trained classifier in identifying the TMs and may enhance the robustness of myoelectric control in clinical applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

Discrimination of Human Forearm Motions on the Basis of Myoelectric Signals by Using Adaptive Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Kiso, Atsushi; Seki, Hirokazu

This paper describes a method for discriminating of the human forearm motions based on the myoelectric signals using an adaptive fuzzy inference system. In conventional studies, the neural network is often used to estimate motion intention by the myoelectric signals and realizes the high discrimination precision. On the other hand, this study uses the fuzzy inference for a human forearm motion discrimination based on the myoelectric signals. This study designs the membership function and the fuzzy rules using the average value and the standard deviation of the root mean square of the myoelectric potential for every channel of each motion. In addition, the characteristics of the myoelectric potential gradually change as a result of the muscle fatigue. Therefore, the motion discrimination should be performed by taking muscle fatigue into consideration. This study proposes a method to redesign the fuzzy inference system such that dynamic change of the myoelectric potential because of the muscle fatigue will be taken into account. Some experiments carried out using a myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.

Relationship of gastric myoelectrical and cardiac parasympathetic activity to chemotherapy-induced nausea

PubMed Central

Gianaros, Peter J.; Stern, Robert M.; Morrow, Gary R.; Hickok, Jane T.

2010-01-01

Objectives We evaluated (a) whether pretreatment levels of gastric tachyarrhythmia, a dysrhythmic pattern of gastric myoelectrical activity, or cardiac parasympathetic activity are associated with the development of chemotherapy-induced nausea and (b) whether chemotherapy-induced nausea is preceded by an increase in gastric tachyarrhythmia and a decrease in cardiac parasympathetic activity, as has been observed during motion sickness. Methods Electrogastrograms and estimates of respiratory sinus arrhythmia (RSA) were obtained from cancer chemotherapy patients before treatment and for approximately 24 hours after treatment. Results Higher levels of pretreatment gastric tachyarrhythmia were observed on chemotherapy sessions that were followed by posttreatment reports of nausea. Pretreatment levels of RSA, however, did not differ between chemotherapy treatments that were and were not followed by nausea. No statistically significant changes in gastric tachyarrhythmia or RSA were observed prior to first reports of nausea following chemotherapy. Conclusions In contrast to motion sickness, chemotherapy-induced nausea may not be related to an increase in dysrhythmic gastric myoelectrical activity; however, higher levels of pretreatment gastric tachyarrhythmia may be related to posttreatment reports of chemotherapy-induced nausea. PMID:11399283

Real-time myoelectric control of a multi-fingered hand prosthesis using principal components analysis.

PubMed

Matrone, Giulia C; Cipriani, Christian; Carrozza, Maria Chiara; Magenes, Giovanni

2012-06-15

In spite of the advances made in the design of dexterous anthropomorphic hand prostheses, these sophisticated devices still lack adequate control interfaces which could allow amputees to operate them in an intuitive and close-to-natural way. In this study, an anthropomorphic five-fingered robotic hand, actuated by six motors, was used as a prosthetic hand emulator to assess the feasibility of a control approach based on Principal Components Analysis (PCA), specifically conceived to address this problem. Since it was demonstrated elsewhere that the first two principal components (PCs) can describe the whole hand configuration space sufficiently well, the controller here employed reverted the PCA algorithm and allowed to drive a multi-DoF hand by combining a two-differential channels EMG input with these two PCs. Hence, the novelty of this approach stood in the PCA application for solving the challenging problem of best mapping the EMG inputs into the degrees of freedom (DoFs) of the prosthesis. A clinically viable two DoFs myoelectric controller, exploiting two differential channels, was developed and twelve able-bodied participants, divided in two groups, volunteered to control the hand in simple grasp trials, using forearm myoelectric signals. Task completion rates and times were measured. The first objective (assessed through one group of subjects) was to understand the effectiveness of the approach; i.e., whether it is possible to drive the hand in real-time, with reasonable performance, in different grasps, also taking advantage of the direct visual feedback of the moving hand. The second objective (assessed through a different group) was to investigate the intuitiveness, and therefore to assess statistical differences in the performance throughout three consecutive days. Subjects performed several grasp, transport and release trials with differently shaped objects, by operating the hand with the myoelectric PCA-based controller. Experimental trials showed that the simultaneous use of the two differential channels paradigm was successful. This work demonstrates that the proposed two-DoFs myoelectric controller based on PCA allows to drive in real-time a prosthetic hand emulator into different prehensile patterns with excellent performance. These results open up promising possibilities for the development of intuitive, effective myoelectric hand controllers.

A Low-Cost, Open-Source, Compliant Hand for Enabling Sensorimotor Control for People with Transradial Amputations

PubMed Central

Akhtar, Aadeel; Choi, Kyung Yun; Fatina, Michael; Cornman, Jesse; Wu, Edward; Sombeck, Joseph; Yim, Chris; Slade, Patrick; Lee, Jason; Moore, Jack; Gonzales, Daniel; Wu, Alvin; Anderson, Garrett; Rotter, David; Shin, Cliff; Bretl, Timothy

2017-01-01

In this paper, we describe the design and implementation of a low-cost, open-source prosthetic hand that enables both motor control and sensory feedback for people with transradial amputations. We integrate electromyographic pattern recognition for motor control along with contact reflexes and sensory substitution to provide feedback to the user. Compliant joints allow for robustness to impacts. The entire hand can be built for around $550. This low cost makes research and development of sensorimotor prosthetic hands more accessible to researchers worldwide, while also being affordable for people with amputations in developing nations. We evaluate the sensorimotor capabilites of our hand with a subject with a transradial amputation. We show that using contact reflexes and sensory substitution, when compared to standard myoelectric prostheses that lack these features, improves grasping of delicate objects like an eggshell and a cup of water both with and without visual feedback. Our hand is easily integrated into standard sockets, facilitating long-term testing of sensorimotor capabilities. PMID:28261008

Evaluation of extreme learning machine for classification of individual and combined finger movements using electromyography on amputees and non-amputees.

PubMed

Anam, Khairul; Al-Jumaily, Adel

2017-01-01

The success of myoelectric pattern recognition (M-PR) mostly relies on the features extracted and classifier employed. This paper proposes and evaluates a fast classifier, extreme learning machine (ELM), to classify individual and combined finger movements on amputees and non-amputees. ELM is a single hidden layer feed-forward network (SLFN) that avoids iterative learning by determining input weights randomly and output weights analytically. Therefore, it can accelerate the training time of SLFNs. In addition to the classifier evaluation, this paper evaluates various feature combinations to improve the performance of M-PR and investigate some feature projections to improve the class separability of the features. Different from other studies on the implementation of ELM in the myoelectric controller, this paper presents a complete and thorough investigation of various types of ELMs including the node-based and kernel-based ELM. Furthermore, this paper provides comparisons of ELMs and other well-known classifiers such as linear discriminant analysis (LDA), k-nearest neighbour (kNN), support vector machine (SVM) and least-square SVM (LS-SVM). The experimental results show the most accurate ELM classifier is radial basis function ELM (RBF-ELM). The comparison of RBF-ELM and other well-known classifiers shows that RBF-ELM is as accurate as SVM and LS-SVM but faster than the SVM family; it is superior to LDA and kNN. The experimental results also indicate that the accuracy gap of the M-PR on the amputees and non-amputees is not too much with the accuracy of 98.55% on amputees and 99.5% on the non-amputees using six electromyography (EMG) channels. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Framework of Temporal-Spatial Descriptors-Based Feature Extraction for Improved Myoelectric Pattern Recognition.

PubMed

Khushaba, Rami N; Al-Timemy, Ali H; Al-Ani, Ahmed; Al-Jumaily, Adel

2017-10-01

The extraction of the accurate and efficient descriptors of muscular activity plays an important role in tackling the challenging problem of myoelectric control of powered prostheses. In this paper, we present a new feature extraction framework that aims to give an enhanced representation of muscular activities through increasing the amount of information that can be extracted from individual and combined electromyogram (EMG) channels. We propose to use time-domain descriptors (TDDs) in estimating the EMG signal power spectrum characteristics; a step that preserves the computational power required for the construction of spectral features. Subsequently, TDD is used in a process that involves: 1) representing the temporal evolution of the EMG signals by progressively tracking the correlation between the TDD extracted from each analysis time window and a nonlinearly mapped version of it across the same EMG channel and 2) representing the spatial coherence between the different EMG channels, which is achieved by calculating the correlation between the TDD extracted from the differences of all possible combinations of pairs of channels and their nonlinearly mapped versions. The proposed temporal-spatial descriptors (TSDs) are validated on multiple sparse and high-density (HD) EMG data sets collected from a number of intact-limbed and amputees performing a large number of hand and finger movements. Classification results showed significant reductions in the achieved error rates in comparison to other methods, with the improvement of at least 8% on average across all subjects. Additionally, the proposed TSDs achieved significantly well in problems with HD-EMG with average classification errors of <5% across all subjects using windows lengths of 50 ms only.

Application of dexterous space robotics technology to myoelectric prostheses

NASA Astrophysics Data System (ADS)

Hess, Clifford; Li, Larry C. H.; Farry, Kristin A.; Walker, Ian D.

1994-02-01

Future space missions will require robots equipped with highly dexterous robotic hands to perform a variety of tasks. A major technical challenge in making this possible is an improvement in the way these dexterous robotic hands are remotely controlled or teleoperated. NASA is currently investigating the feasibility of using myoelectric signals to teleoperate a dexterous robotic hand. In theory, myoelectric control of robotic hands will require little or no mechanical parts and will greatly reduce the bulk and weight usually found in dexterous robotic hand control devices. An improvement in myoelectric control of multifinger hands will also benefit prosthetics users. Therefore, as an effort to transfer dexterous space robotics technology to prosthetics applications and to benefit from existing myoelectric technology, NASA is collaborating with the Limbs of Love Foundation, the Institute for Rehabilitation and Research, and Rice University in developing improved myoelectric control multifinger hands and prostheses. In this paper, we will address the objectives and approaches of this collaborative effort and discuss the technical issues associated with myoelectric control of multifinger hands. We will also report our current progress and discuss plans for future work.

Application of dexterous space robotics technology to myoelectric prostheses

NASA Technical Reports Server (NTRS)

Hess, Clifford; Li, Larry C. H.; Farry, Kristin A.; Walker, Ian D.

1994-01-01

Future space missions will require robots equipped with highly dexterous robotic hands to perform a variety of tasks. A major technical challenge in making this possible is an improvement in the way these dexterous robotic hands are remotely controlled or teleoperated. NASA is currently investigating the feasibility of using myoelectric signals to teleoperate a dexterous robotic hand. In theory, myoelectric control of robotic hands will require little or no mechanical parts and will greatly reduce the bulk and weight usually found in dexterous robotic hand control devices. An improvement in myoelectric control of multifinger hands will also benefit prosthetics users. Therefore, as an effort to transfer dexterous space robotics technology to prosthetics applications and to benefit from existing myoelectric technology, NASA is collaborating with the Limbs of Love Foundation, the Institute for Rehabilitation and Research, and Rice University in developing improved myoelectric control multifinger hands and prostheses. In this paper, we will address the objectives and approaches of this collaborative effort and discuss the technical issues associated with myoelectric control of multifinger hands. We will also report our current progress and discuss plans for future work.

Voluntary Control of Residual Antagonistic Muscles in Transtibial Amputees: Feedforward Ballistic Contractions and Implications for Direct Neural Control of Powered Lower Limb Prostheses.

PubMed

Huang, Stephanie; Huang, He

2018-04-01

Discrete, rapid (i.e., ballistic like) muscle activation patterns have been observed in ankle muscles (i.e., plantar flexors and dorsiflexors) of able-bodied individuals during voluntary posture control. This observation motivated us to investigate whether transtibial amputees are capable of generating such a ballistic-like activation pattern accurately using their residual ankle muscles in order to assess whether the volitional postural control of a powered ankle prosthesis using proportional myoelectric control via residual muscles could be feasible. In this paper, we asked ten transtibial amputees to generate ballistic-like activation patterns using their residual lateral gastrocnemius and residual tibialis anterior to control a computer cursor via proportional myoelectric control to hit targets positioned at 20% and 40% of maximum voluntary contraction of the corresponding residual muscle. During practice conditions, we asked amputees to hit a single target repeatedly. During testing conditions, we asked amputees to hit a random sequence of targets. We compared movement time to target and end-point accuracy. We also examined motor recruitment synchronization via time-frequency representations of residual muscle activation. The result showed that median end-point error ranged from -0.6% to 1% maximum voluntary contraction across subjects during practice, which was significantly lower compared to testing ( ). Average movement time for all amputees was 242 ms during practice and 272 ms during testing. Motor recruitment synchronization varied across subjects, and amputees with the highest synchronization achieved the fastest movement times. End-point accuracy was independent of movement time. Results suggest that it is feasible for transtibial amputees to generate ballistic control signals using their residual muscles. Future work on volitional control of powered power ankle prostheses might consider anticipatory postural control based on ballistic-like residual muscle activation patterns and direct continuous proportional myoelectric control.

Myoelectric signal processing for control of powered limb prostheses.

PubMed

Parker, P; Englehart, K; Hudgins, B

2006-12-01

Progress in myoelectric control technology has over the years been incremental, due in part to the alternating focus of the R&D between control methodology and device hardware. The technology has over the past 50 years or so moved from single muscle control of a single prosthesis function to muscle group activity control of multifunction prostheses. Central to these changes have been developments in the means of extracting information from the myoelectric signal. This paper gives an overview of the myoelectric signal processing challenge, a brief look at the challenge from an historical perspective, the state-of-the-art in myoelectric signal processing for prosthesis control, and an indication of where this field is heading. The paper demonstrates that considerable progress has been made in providing clients with useful and reliable myoelectric communication channels, and that exciting work and developments are on the horizon.

The Development of a Myoelectric Training Tool for Above-Elbow Amputees

PubMed Central

Dawson, Michael R; Fahimi, Farbod; Carey, Jason P

2012-01-01

The objective of above-elbow myoelectric prostheses is to reestablish the functionality of missing limbs and increase the quality of life of amputees. By using electromyography (EMG) electrodes attached to the surface of the skin, amputees are able to control motors in myoelectric prostheses by voluntarily contracting the muscles of their residual limb. This work describes the development of an inexpensive myoelectric training tool (MTT) designed to help upper limb amputees learn how to use myoelectric technology in advance of receiving their actual myoelectric prosthesis. The training tool consists of a physical and simulated robotic arm, signal acquisition hardware, controller software, and a graphical user interface. The MTT improves over earlier training systems by allowing a targeted muscle reinnervation (TMR) patient to control up to two degrees of freedom simultaneously. The training tool has also been designed to function as a research prototype for novel myoelectric controllers. A preliminary experiment was performed in order to evaluate the effectiveness of the MTT as a learning tool and to identify any issues with the system. Five able-bodied participants performed a motor-learning task using the EMG controlled robotic arm with the goal of moving five balls from one box to another as quickly as possible. The results indicate that the subjects improved their skill in myoelectric control over the course of the trials. A usability survey was administered to the subjects after their trials. Results from the survey showed that the shoulder degree of freedom was the most difficult to control. PMID:22383905

The development of a myoelectric training tool for above-elbow amputees.

PubMed

Dawson, Michael R; Fahimi, Farbod; Carey, Jason P

2012-01-01

The objective of above-elbow myoelectric prostheses is to reestablish the functionality of missing limbs and increase the quality of life of amputees. By using electromyography (EMG) electrodes attached to the surface of the skin, amputees are able to control motors in myoelectric prostheses by voluntarily contracting the muscles of their residual limb. This work describes the development of an inexpensive myoelectric training tool (MTT) designed to help upper limb amputees learn how to use myoelectric technology in advance of receiving their actual myoelectric prosthesis. The training tool consists of a physical and simulated robotic arm, signal acquisition hardware, controller software, and a graphical user interface. The MTT improves over earlier training systems by allowing a targeted muscle reinnervation (TMR) patient to control up to two degrees of freedom simultaneously. The training tool has also been designed to function as a research prototype for novel myoelectric controllers. A preliminary experiment was performed in order to evaluate the effectiveness of the MTT as a learning tool and to identify any issues with the system. Five able-bodied participants performed a motor-learning task using the EMG controlled robotic arm with the goal of moving five balls from one box to another as quickly as possible. The results indicate that the subjects improved their skill in myoelectric control over the course of the trials. A usability survey was administered to the subjects after their trials. Results from the survey showed that the shoulder degree of freedom was the most difficult to control.

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).

Reduced biceps femoris myoelectrical activity influences eccentric knee flexor weakness after repeat sprint running.

PubMed

Timmins, R G; Opar, D A; Williams, M D; Schache, A G; Dear, N M; Shield, A J

2014-08-01

The aim of this study was to determine whether declines in knee flexor strength following overground repeat sprints were related to changes in hamstrings myoelectrical activity. Seventeen recreationally active men completed maximal isokinetic concentric and eccentric knee flexor strength assessments at 180°/s before and after repeat sprint running. Myoelectrical activity of the biceps femoris (BF) and medial hamstrings (MHs) was measured during all isokinetic contractions. Repeated measures mixed model [fixed factors = time (pre- and post-repeat sprint) and leg (dominant and nondominant), random factor = participants] design was fitted with the restricted maximal likelihood method. Repeat sprint running resulted in significant declines in eccentric, and concentric, knee flexor strength (eccentric = 26 ± 4 Nm, 15% P < 0.001; concentric 11 ± 2 Nm, 10% P < 0.001). Eccentric BF myoelectrical activity was significantly reduced (10%; P = 0.035). Concentric BF and all MH myoelectrical activity were not altered. The declines in maximal eccentric torque were associated with the change in eccentric BF myoelectrical activity (P = 0.013). Following repeat sprint running, there were preferential declines in the myoelectrical activity of the BF, which explained declines in eccentric knee flexor strength. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Effects of scopolamine on autonomic profiles underlying motion sickness susceptibility

NASA Technical Reports Server (NTRS)

Uijtdehaage, Sebastian H. J.; Stern, Robert M.; Koch, Kenneth L.

1993-01-01

The purpose of this study was to examine the effects of scopolamine on the physiological patterns occurring prior to and during motion sickness stimulation. In addition, the use of physiological profiles in the prediction of motion sickness was evaluated. Sixty subjects ingested either 0.6 mg scopolamine, 2.5 mg methoscopolamine, or a placebo. Heart rate (HR), respiratory sinus arrhythmia (an index of vagal tone), and electrogastrograms were measured prior to and during the exposure to a rotating optokinetic drum. Compared to the other groups, the scopolamine group reported fewer motion sickness symptoms, and displayed lower HR, higher vagal tone, enhanced normal gastric myoelectric activity, and depressed gastric dysrhythmias before and during motion sickness induction. Distinct physiological profiles prior to drum rotation could reliably differentiate individuals who would develop gastric discomfort from those who would not. Symptom-free subjects were characterized by high levels of vagal tone and low HR across conditions, and by maintaining normal (3 cpm) electrogastrographic activity during drum rotation. It was concluded that scopolamine offered motion sickness protection by initiating a pattern of increased vagal tone and gastric myoelectric stability.

Myoelectric control of prosthetic hands: state-of-the-art review

PubMed Central

Geethanjali, Purushothaman

2016-01-01

Myoelectric signals (MES) have been used in various applications, in particular, for identification of user intention to potentially control assistive devices for amputees, orthotic devices, and exoskeleton in order to augment capability of the user. MES are also used to estimate force and, hence, torque to actuate the assistive device. The application of MES is not limited to assistive devices, and they also find potential applications in teleoperation of robots, haptic devices, virtual reality, and so on. The myoelectric control-based prosthetic hand aids to restore activities of daily living of amputees in order to improve the self-esteem of the user. All myoelectric control-based prosthetic hands may not have similar operations and exhibit variation in sensing input, deciphering the signals, and actuating prosthetic hand. Researchers are focusing on improving the functionality of prosthetic hand in order to suit the user requirement with the different operating features. The myoelectric control differs in operation to accommodate various external factors. This article reviews the state of the art of myoelectric prosthetic hand, giving description of each control strategy. PMID:27555799

The effect of drugs and stimulants on gastric myoelectrical activity

PubMed Central

Kwiecień, Jarosław; Kasicka-Jonderko, Anna; Buschhaus, Magdalena

2014-01-01

Electrogastrography (EGG) is a non-invasive diagnostic method useful for the registration and analysis of gastric myoelectrical activity. Abnormalities within an electrogastrogram were found to correlate with a number of disorders and symptoms, like functional dyspepsia, diabetic gastroparesis and terminal hepatic or renal failure. The EGG is also a valuable diagnostic method enabling the evaluation of the effect of drugs on gastric myoelectrical activity, which can be intentional, as in the case of prokinetics, or can have an adverse character. Our review focuses on drugs with a proven impact on gastric myoelectrical activity and hence on the electrogastrogram. The paper assembles and discusses the results of investigations dealing with changes in the electrogastrograms evoked by various drugs. Moreover, the mechanisms of the influence on the gastric myoelectrical activity of drugs, curative substances and stimulants are presented. PMID:25097708

Powered ankle-foot prosthesis to assist level-ground and stair-descent gaits.

PubMed

Au, Samuel; Berniker, Max; Herr, Hugh

2008-05-01

The human ankle varies impedance and delivers net positive work during the stance period of walking. In contrast, commercially available ankle-foot prostheses are passive during stance, causing many clinical problems for transtibial amputees, including non-symmetric gait patterns, higher gait metabolism, and poorer shock absorption. In this investigation, we develop and evaluate a myoelectric-driven, finite state controller for a powered ankle-foot prosthesis that modulates both impedance and power output during stance. The system employs both sensory inputs measured local to the external prosthesis, and myoelectric inputs measured from residual limb muscles. Using local prosthetic sensing, we first develop two finite state controllers to produce biomimetic movement patterns for level-ground and stair-descent gaits. We then employ myoelectric signals as control commands to manage the transition between these finite state controllers. To transition from level-ground to stairs, the amputee flexes the gastrocnemius muscle, triggering the prosthetic ankle to plantar flex at terminal swing, and initiating the stair-descent state machine algorithm. To transition back to level-ground walking, the amputee flexes the tibialis anterior muscle, triggering the ankle to remain dorsiflexed at terminal swing, and initiating the level-ground state machine algorithm. As a preliminary evaluation of clinical efficacy, we test the device on a transtibial amputee with both the proposed controller and a conventional passive-elastic control. We find that the amputee can robustly transition between the finite state controllers through direct muscle activation, allowing rapid transitioning from level-ground to stair walking patterns. Additionally, we find that the proposed finite state controllers result in a more biomimetic ankle response, producing net propulsive work during level-ground walking and greater shock absorption during stair descent. The results of this study highlight the potential of prosthetic leg controllers that exploit neural signals to trigger terrain-appropriate, local prosthetic leg behaviors.

Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton.

PubMed

Koller, Jeffrey R; Jacobs, Daniel A; Ferris, Daniel P; Remy, C David

2015-11-04

Robotic ankle exoskeletons can provide assistance to users and reduce metabolic power during walking. Our research group has investigated the use of proportional myoelectric control for controlling robotic ankle exoskeletons. Previously, these controllers have relied on a constant gain to map user's muscle activity to actuation control signals. A constant gain may act as a constraint on the user, so we designed a controller that dynamically adapts the gain to the user's myoelectric amplitude. We hypothesized that an adaptive gain proportional myoelectric controller would reduce metabolic energy expenditure compared to walking with the ankle exoskeleton unpowered because users could choose their preferred control gain. We tested eight healthy subjects walking with the adaptive gain proportional myoelectric controller with bilateral ankle exoskeletons. The adaptive gain was updated each stride such that on average the user's peak muscle activity was mapped to maximal power output of the exoskeleton. All subjects participated in three identical training sessions where they walked on a treadmill for 50 minutes (30 minutes of which the exoskeleton was powered) at 1.2 ms(-1). We calculated and analyzed metabolic energy consumption, muscle recruitment, inverse kinematics, inverse dynamics, and exoskeleton mechanics. Using our controller, subjects achieved a metabolic reduction similar to that seen in previous work in about a third of the training time. The resulting controller gain was lower than that seen in previous work (β=1.50±0.14 versus a constant β=2). The adapted gain allowed users more total ankle joint power than that of unassisted walking, increasing ankle power in exchange for a decrease in hip power. Our findings indicate that humans prefer to walk with greater ankle mechanical power output than their unassisted gait when provided with an ankle exoskeleton using an adaptive controller. This suggests that robotic assistance from an exoskeleton can allow humans to adopt gait patterns different from their normal choices for locomotion. In our specific experiment, subjects increased ankle power and decreased hip power to walk with a reduction in metabolic cost. Future exoskeleton devices that rely on proportional myolectric control are likely to demonstrate improved performance by including an adaptive gain.

Model and experiments to optimize co-adaptation in a simplified myoelectric control system.

PubMed

Couraud, M; Cattaert, D; Paclet, F; Oudeyer, P Y; de Rugy, A

2018-04-01

To compensate for a limb lost in an amputation, myoelectric prostheses use surface electromyography (EMG) from the remaining muscles to control the prosthesis. Despite considerable progress, myoelectric controls remain markedly different from the way we normally control movements, and require intense user adaptation. To overcome this, our goal is to explore concurrent machine co-adaptation techniques that are developed in the field of brain-machine interface, and that are beginning to be used in myoelectric controls. We combined a simplified myoelectric control with a perturbation for which human adaptation is well characterized and modeled, in order to explore co-adaptation settings in a principled manner. First, we reproduced results obtained in a classical visuomotor rotation paradigm in our simplified myoelectric context, where we rotate the muscle pulling vectors used to reconstruct wrist force from EMG. Then, a model of human adaptation in response to directional error was used to simulate various co-adaptation settings, where perturbations and machine co-adaptation are both applied on muscle pulling vectors. These simulations established that a relatively low gain of machine co-adaptation that minimizes final errors generates slow and incomplete adaptation, while higher gains increase adaptation rate but also errors by amplifying noise. After experimental verification on real subjects, we tested a variable gain that cumulates the advantages of both, and implemented it with directionally tuned neurons similar to those used to model human adaptation. This enables machine co-adaptation to locally improve myoelectric control, and to absorb more challenging perturbations. The simplified context used here enabled to explore co-adaptation settings in both simulations and experiments, and to raise important considerations such as the need for a variable gain encoded locally. The benefits and limits of extending this approach to more complex and functional myoelectric contexts are discussed.

Recognition of Handwriting from Electromyography

PubMed Central

Linderman, Michael; Lebedev, Mikhail A.; Erlichman, Joseph S.

2009-01-01

Handwriting – one of the most important developments in human culture – is also a methodological tool in several scientific disciplines, most importantly handwriting recognition methods, graphology and medical diagnostics. Previous studies have relied largely on the analyses of handwritten traces or kinematic analysis of handwriting; whereas electromyographic (EMG) signals associated with handwriting have received little attention. Here we show for the first time, a method in which EMG signals generated by hand and forearm muscles during handwriting activity are reliably translated into both algorithm-generated handwriting traces and font characters using decoding algorithms. Our results demonstrate the feasibility of recreating handwriting solely from EMG signals – the finding that can be utilized in computer peripherals and myoelectric prosthetic devices. Moreover, this approach may provide a rapid and sensitive method for diagnosing a variety of neurogenerative diseases before other symptoms become clear. PMID:19707562

A pilot study on disturbed gastric myoelectric activity in obstructed defecation syndrome.

PubMed

Farid, Mohamed; Emile, Sameh Hany; Haleem, Magdy; El-Hak, Nabil Gad

2018-07-01

Electrogastrography (EGG) is a noninvasive technique for recording gastric myoelectric activity. The aim of this study was to measure and record gastric myoelectric activity in patients with obstructed defecation syndrome (ODS) and to compare their results with those of normal individuals. Forty-two patients (22 male) with ODS and a mean age of 41.02 y were enrolled in this prospective study after thorough clinical and physiologic assessment. Eleven normal subjects (six female) with a mean age of 39.2 ± 8.4 y were assigned to the control group. Both patients and controls were subjected to surface EGG in fasting and postprandial states. Data were recorded and analyzed via a computer system to reveal the EGG pattern in both groups. Abnormalities in the EGG were found in 24 (57.1%) of the 42 patients with ODS. EGG in ODS patients showed alterations in the fasting state in the form of a significant decrease of the normal gastric slow wave (P = 0.03) and a nonsignificant increase in gastric dysrhythmias. The EGG alterations of ODS patients were significantly improved in the postprandial state as the normal gastric slow waves significantly (P = 0.006) increased and the gastric bradycardia declined significantly (P = 0.02). No significant differences were observed in the power distribution between the ODS patients and the healthy controls. Patients with ODS showed an altered EGG pattern compared with that of healthy control subjects. The alterations in ODS patients were more clearly observed during the fasting state and improved significantly after eating. Copyright © 2018 Elsevier Inc. All rights reserved.

Cerebro-afferent vessel and pupillary basal diameter variation induced by stomatognathic trigeminal proprioception: a case report.

PubMed

De Cicco, Vincenzo

2012-09-03

A patient affected by asymmetric hemodynamics of cerebro-afferent vessels underwent duplex color scanner investigations in occlusal proprioceptive un- and rebalance conditions. Pupillometric video-oculographic examinations were performed in order to spot connected trigeminal proprioceptive motor patterns able to interfere on sympathetic autonomic activity. The aim of this case report is to verify if involuntary jaw closing during swallowing, executed in unbalance and rebalance myoelectric activity, would be able to modify cerebral hemodynamics. A 56-year-old Caucasian Italian woman affected by asymmetric blood flow of cerebro-afferent vessels underwent an electromyographic investigation of her occlusal muscles in order to assess their occlusal functional balance. The extreme asymmetry of myoelectric activity in dental occlusion evidenced by electromyographic values suggested the rebalancing of the functions of occlusal muscles through concurrent transcutaneous stimulation of the trigeminal nerve supra- and submandibular motor branches. The above-mentioned method allowed the detection of a symmetric craniomandibular muscular relation that can be kept constant through the use of a cusp bite modeled on the inferior dental arch: called orthotic-syntropic bite for its peculiar use of electrostimulation. A few days later, the patient underwent a duplex color scanner investigation and pupillometric video-oculographic examinations in occlusal unbalance and rebalance conditions. A comparative data analysis showed that an unbalanced dental occlusal function may represent an interferential pattern on cerebral hemodynamics velocity and pupillometric evaluations have proved useful both in the analysis of locus coeruleus functional modalities and as a diagnostic tool in the assessment of pathologies involving locus coeruleus and autonomic systems. The inclusion of myoelectric masseter examinations can be useful in patients with asymmetric hemodynamics of cerebro-afferent vessels and dental occlusal proprioceptive rebalance can integrate the complex therapy of patients with increased chronic sympathetic activity.

Botulinum toxin type A inhibits rat pyloric myoelectrical activity and substance P release in vivo.

PubMed

Hou, Yi-Ping; Zhang, Yong-Ping; Song, Yan-Feng; Zhu, Chun-Min; Wang, Yin-Chun; Xie, Gui-Lin

2007-02-01

The effect of botulinum toxin type A (BTX-A) on rat pyloric myoelectrical activity in vivo and the content and distribution of substance P (SP) in pylorus were investigated, respectively, with electromyography, radioimmunoassay, and immunohistochemistry. A pair of electrodes for recording pyloric myoelectrical activity and a guide cannula for drug injection were implanted into the pylorus. The changes of pyloric myoelectrical activity were recorded followed vehicle, 10, 20, and 40 U/kg body mass of BTX-A injection. Pyloric tissues were dissected for radioimmunoassay and immunohistochemistry after recording. The 3 dosages of BTX-A injections caused the reduction of slow wave of pyloric myoelectrical activity in amplitude but not in frequency and the diminishment of spike activity in amplitude and spike burst. The inhibitory effect of 20 U/kg BTX-A was significantly different from that of 10 U/kg (p<0.05), but not from the effect of 40 U/kg administration (p>0.05). After BTX-A intrasphincteric injection, SP content was reduced in the pylorus, and cell number of SP-immunoreactivity was decreased more in myenteric nerve plexus of circular muscle and in mucosa of pylori. In conclusion, BTX-A inhibits pyloric myoelectrical slow activity in amplitude and spike activity and weakens pyloric smooth muscle contractility depending on threshold of dose or concentration. BTX-A-induced inhibition of pyloric myoelectrical activity implies a mechanism of inhibiting SP release from the autonomic and enteric nervous terminals in the pylorus.

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. © 2011 IEEE

Differences in myoelectric and body-powered upper-limb prostheses: Systematic literature review.

PubMed

Carey, Stephanie L; Lura, Derek J; Highsmith, M Jason

2015-01-01

The choice of a myoelectric or body-powered upper-limb prosthesis can be determined using factors including control, function, feedback, cosmesis, and rejection. Although body-powered and myoelectric control strategies offer unique functions, many prosthesis users must choose one. A systematic review was conducted to determine differences between myoelectric and body-powered prostheses to inform evidence-based clinical practice regarding prescription of these devices and training of users. A search of 9 databases identified 462 unique publications. Ultimately, 31 of them were included and 11 empirical evidence statements were developed. Conflicting evidence has been found in terms of the relative functional performance of body-powered and myoelectric prostheses. Body-powered prostheses have been shown to have advantages in durability, training time, frequency of adjustment, maintenance, and feedback; however, they could still benefit from improvements of control. Myoelectric prostheses have been shown to improve cosmesis and phantom-limb pain and are more accepted for light=intensity work. Currently, evidence is insufficient to conclude that either system provides a significant general advantage. Prosthetic selection should be based on a patient's individual needs and include personal preferences, prosthetic experience, and functional needs. This work demonstrates that there is a lack of empirical evidence regarding functional differences in upper-limb prostheses.

Real-time robustness evaluation of regression based myoelectric control against arm position change and donning/doffing.

PubMed

Hwang, Han-Jeong; Hahne, Janne Mathias; Müller, Klaus-Robert

2017-01-01

There are some practical factors, such as arm position change and donning/doffing, which prevent robust myoelectric control. The objective of this study is to precisely characterize the impacts of the two representative factors on myoelectric controllability in practical control situations, thereby providing useful references that can be potentially used to find better solutions for clinically reliable myoelectric control. To this end, a real-time target acquisition task was performed by fourteen subjects including one individual with congenital upper-limb deficiency, where the impacts of arm position change, donning/doffing and a combination of both factors on control performance was systematically evaluated. The changes in online performance were examined with seven different performance metrics to comprehensively evaluate various aspects of myoelectric controllability. As a result, arm position change significantly affects offline prediction accuracy, but not online control performance due to real-time feedback, thereby showing no significant correlation between offline and online performance. Donning/doffing was still problematic in online control conditions. It was further observed that no benefit was attained when using a control model trained with multiple position data in terms of arm position change, and the degree of electrode shift caused by donning/doffing was not severely associated with the degree of performance loss under practical conditions (around 1 cm electrode shift). Since this study is the first to concurrently investigate the impacts of arm position change and donning/doffing in practical myoelectric control situations, all findings of this study provide new insights into robust myoelectric control with respect to arm position change and donning/doffing.

Real-time robustness evaluation of regression based myoelectric control against arm position change and donning/doffing

PubMed Central

Hahne, Janne Mathias; Müller, Klaus-Robert

2017-01-01

There are some practical factors, such as arm position change and donning/doffing, which prevent robust myoelectric control. The objective of this study is to precisely characterize the impacts of the two representative factors on myoelectric controllability in practical control situations, thereby providing useful references that can be potentially used to find better solutions for clinically reliable myoelectric control. To this end, a real-time target acquisition task was performed by fourteen subjects including one individual with congenital upper-limb deficiency, where the impacts of arm position change, donning/doffing and a combination of both factors on control performance was systematically evaluated. The changes in online performance were examined with seven different performance metrics to comprehensively evaluate various aspects of myoelectric controllability. As a result, arm position change significantly affects offline prediction accuracy, but not online control performance due to real-time feedback, thereby showing no significant correlation between offline and online performance. Donning/doffing was still problematic in online control conditions. It was further observed that no benefit was attained when using a control model trained with multiple position data in terms of arm position change, and the degree of electrode shift caused by donning/doffing was not severely associated with the degree of performance loss under practical conditions (around 1 cm electrode shift). Since this study is the first to concurrently investigate the impacts of arm position change and donning/doffing in practical myoelectric control situations, all findings of this study provide new insights into robust myoelectric control with respect to arm position change and donning/doffing. PMID:29095846

Model and experiments to optimize co-adaptation in a simplified myoelectric control system

NASA Astrophysics Data System (ADS)

Couraud, M.; Cattaert, D.; Paclet, F.; Oudeyer, P. Y.; de Rugy, A.

2018-04-01

Objective. To compensate for a limb lost in an amputation, myoelectric prostheses use surface electromyography (EMG) from the remaining muscles to control the prosthesis. Despite considerable progress, myoelectric controls remain markedly different from the way we normally control movements, and require intense user adaptation. To overcome this, our goal is to explore concurrent machine co-adaptation techniques that are developed in the field of brain-machine interface, and that are beginning to be used in myoelectric controls. Approach. We combined a simplified myoelectric control with a perturbation for which human adaptation is well characterized and modeled, in order to explore co-adaptation settings in a principled manner. Results. First, we reproduced results obtained in a classical visuomotor rotation paradigm in our simplified myoelectric context, where we rotate the muscle pulling vectors used to reconstruct wrist force from EMG. Then, a model of human adaptation in response to directional error was used to simulate various co-adaptation settings, where perturbations and machine co-adaptation are both applied on muscle pulling vectors. These simulations established that a relatively low gain of machine co-adaptation that minimizes final errors generates slow and incomplete adaptation, while higher gains increase adaptation rate but also errors by amplifying noise. After experimental verification on real subjects, we tested a variable gain that cumulates the advantages of both, and implemented it with directionally tuned neurons similar to those used to model human adaptation. This enables machine co-adaptation to locally improve myoelectric control, and to absorb more challenging perturbations. Significance. The simplified context used here enabled to explore co-adaptation settings in both simulations and experiments, and to raise important considerations such as the need for a variable gain encoded locally. The benefits and limits of extending this approach to more complex and functional myoelectric contexts are discussed.

Applying Space Technology to Enhance Control of an Artificial Arm for Children and Adults With Amputations

NASA Technical Reports Server (NTRS)

Atkins, Diane J.

1998-01-01

The first single function myoelectric prosthetic hand was introduced in the 1960's. This hand was controlled by the electric fields generated by muscle contractions in the residual limb of the amputee user. Electrodes and amplifiers, embedded in the prosthetic socket, measured these electric fields across the skin, which increase in amplitude as the individual contracts their muscle. When the myoelectric signal reached a certain threshold amplitude, the control unit activated a motor which opened or closed a hand-like prosthetic terminal device with a pincher grip. Late in the 1990's, little has changed. Most current myoelectric prostheses still operate in this same, single-function way. To better understand the limitations of the current single-function myoelectric hand and the needs of those who use them, The Institute for Rehabilitation and Research (TIRR), sponsored by the National Institutes of Health (NUH), surveyed approximately 2,500 individuals with upper limb loss [1]. When asked to identify specific features of their current myoelectric prostheses that needed improvement, the survey respondents overwhelmingly identified the lack of wrist and finger movement, as well as poor control capability. However, simply building a mechanism with individual finger and wrist motion is not enough. In the 1960's and 1970's, engineers built a number of more dexterous prosthetic hands. Unfortunately, these were rejected during clinical trials due to a difficult and distracting control interface. The goal of this project, "Applying Space Technology to Enhance Control of an Artificial Arm for Children and Adults with Amputations," was to lay the foundation for a multi-function, intuitive myoelectric control system which requires no conscious thought to move the hand. We built an extensive myoelectric signal database for six motions from ten amputee volunteers, We also tested a control system based on new artificial intelligence techniques on the data from two of these subjects. This data is available to anyone doing myoelectric control research. Its availability is an important contribution to the prosthetics research community, as many researchers do not have access to amputee subjects. Since we collected myoelectric data from subjects' sound arms as well as their residual arms, this database will also prove useful to virtual reality and robotics researchers who want to explore myoelectric-based interfaces between any user and a machine. Currently, one small company (Intelligenta, Inc.) and one university (University of New Brunswick, Canada) are using this myoelectric database under other funding to develop multifunction control systems for prostheses. A prosthetics manufacturer (Liberty Technology, Inc.) is making plans to incorporate the results of their work into an artificial hand capable of several different movements to provide functionality only dreamed of by current myoelectric users. Methods Six adults and four children, all with unilateral, below-elbow amputations served as subjects. Five of the adults (3 male, 2 female, average age 34 years) had amputations due to traumatic injury, while one adult (female, age 32 years) and the four children (3 male, 1 female, average age 13 years) had congenital (i.e. from birth) limb deficiencies.

[Influence of electrical stimulation of "hunger center" of the lateral hypothalamus and food reinforcements on myoelectrical activity of the gastro-esophageal sphincter and stomach in rabbits under the conditions of hunger and satiation].

PubMed

Kromin, A A; Zenina, O Iu

2013-01-01

To study the combined effect of electrostimulation of "hunger center" of the lateral hypothalamus (LH) and food-obtaining behavior arising from it on myoelectrical activity of gastro-esophageal sphincter (GES) and the stomach in pre-fed and subjected to food deprivation animals . MATERIAL AND METHODS. Registration of myoelectrical GES and the stomach activity was carried out under free-behavior conditions in rabbits subjected to food deprivation or pre-fed before the experiment. It was done by means of chronically implanted electrodes during LH electrostimulation in the presence of food. Simultaneously using the web-camera the animals behavior was recorded. LH stimulation was produced by STM-100C stimulator (USA) with implanted bipolar nichrome electrodes. Analysis of temporal parameters of myoelectrical activity of GES and the stomach were carried out by the program AcqKnowledge (USA), and statistical analysis of the data by the program Statistica 6. Significanse of differences between the samples was assessed by the U-Mann-Whitney test (p < 0.05). Electrostimulation of "hunger center" of the lateral hypothalamus in pre-fed rabbits and the rabbits subjected to daily food deprivation, in the presence of food causes resultant food behavior which is accompanied by regular generations of bursts of peak potentials, frequency of which is essentially different in hungry and satiated animals and depends on intensity of artificially induced and artificially reinforced food motivation. In the process of LH stimulation arising resultant food behavior in satiated animals is accompanied by regular generation of high-amplitude slow electrical waves (SEW) by the muscles of lesser curvature (LC), the body and antrum of the stomach (AS) and this is reflected in the structure of temporal organization of slow electrical activity (SEA) in the form of monomodal distributions of SEW periods, typical of satiation state. Despite the increase in food motivation level, due to LH stimulation, additional entry of food into the stomach of satiated rabbits completely eliminates inhibitory effect of starvational motivational excitation on SEA of the muscles of LC, the body and AS. SEA alterations of the stomach muscles in hungry rabbits in the presence of food and thus arising of food-obtaining behavior during LH stimulation have two-phase character. At the initial stage of food behavior in hungry animals during LH stimulation high extent of scaterring of the values of SEW periods generated by the body and AS muscles is preserved, as evidenced by the bimodal distribution of SEW periods characteristic of the state of hunger. In spite of food entry into the stomach at the 1-st phase of LH stimulation, inhibitory effect of artificially reinforced starvational motivational excitation on pacemaker activity of the stomach is retained. At the 2-nd phase of LH electrostimulation food reinforcement eliminates inhibitory effect of food motivational excitation on myoelectrical activity of pacemaker of the stomach that gives maximal rhythm of SEW generation to the body and AS, monomodal distributions of SEW periods indicate to it. lnteraction of artificially induced and artificially reinforced food motivational excitation with afferentation from food reinforcement on neurons of the central generator of deglutition pattern and dorsal vagal complex due to LH electrostimulation and thereby arising resultant food obtaining behavior is specifically reflected in patterns of myoelectrical activity of GES, LC, the body and AS.

A real-time comparison between direct control, sequential pattern recognition control and simultaneous pattern recognition control using a Fitts’ law style assessment procedure

PubMed Central

2014-01-01

Background Pattern recognition (PR) based strategies for the control of myoelectric upper limb prostheses are generally evaluated through offline classification accuracy, which is an admittedly useful metric, but insufficient to discuss functional performance in real time. Existing functional tests are extensive to set up and most fail to provide a challenging, objective framework to assess the strategy performance in real time. Methods Nine able-bodied and two amputee subjects gave informed consent and participated in the local Institutional Review Board approved study. We designed a two-dimensional target acquisition task, based on the principles of Fitts’ law for human motor control. Subjects were prompted to steer a cursor from the screen center of into a series of subsequently appearing targets of different difficulties. Three cursor control systems were tested, corresponding to three electromyography-based prosthetic control strategies: 1) amplitude-based direct control (the clinical standard of care), 2) sequential PR control, and 3) simultaneous PR control, allowing for a concurrent activation of two degrees of freedom (DOF). We computed throughput (bits/second), path efficiency (%), reaction time (second), and overshoot (%)) and used general linear models to assess significant differences between the strategies for each metric. Results We validated the proposed methodology by achieving very high coefficients of determination for Fitts’ law. Both PR strategies significantly outperformed direct control in two-DOF targets and were more intuitive to operate. In one-DOF targets, the simultaneous approach was the least precise. The direct control was efficient in one-DOF targets but cumbersome to operate in two-DOF targets through a switch-depended sequential cursor control. Conclusions We designed a test, capable of comprehensively describing prosthetic control strategies in real time. When implemented on control subjects, the test was able to capture statistically significant differences (p < 0.05) in control strategies when considering throughputs, path efficiencies and reaction times. Of particular note, we found statistically significant (p < 0.01) improvements in throughputs and path efficiencies with simultaneous PR when compared to direct control or sequential PR. Amputees could readily achieve the task; however a limited number of subjects was tested and a statistical analysis was not performed with that population. PMID:24886664

A real-time comparison between direct control, sequential pattern recognition control and simultaneous pattern recognition control using a Fitts' law style assessment procedure.

PubMed

Wurth, Sophie M; Hargrove, Levi J

2014-05-30

Pattern recognition (PR) based strategies for the control of myoelectric upper limb prostheses are generally evaluated through offline classification accuracy, which is an admittedly useful metric, but insufficient to discuss functional performance in real time. Existing functional tests are extensive to set up and most fail to provide a challenging, objective framework to assess the strategy performance in real time. Nine able-bodied and two amputee subjects gave informed consent and participated in the local Institutional Review Board approved study. We designed a two-dimensional target acquisition task, based on the principles of Fitts' law for human motor control. Subjects were prompted to steer a cursor from the screen center of into a series of subsequently appearing targets of different difficulties. Three cursor control systems were tested, corresponding to three electromyography-based prosthetic control strategies: 1) amplitude-based direct control (the clinical standard of care), 2) sequential PR control, and 3) simultaneous PR control, allowing for a concurrent activation of two degrees of freedom (DOF). We computed throughput (bits/second), path efficiency (%), reaction time (second), and overshoot (%)) and used general linear models to assess significant differences between the strategies for each metric. We validated the proposed methodology by achieving very high coefficients of determination for Fitts' law. Both PR strategies significantly outperformed direct control in two-DOF targets and were more intuitive to operate. In one-DOF targets, the simultaneous approach was the least precise. The direct control was efficient in one-DOF targets but cumbersome to operate in two-DOF targets through a switch-depended sequential cursor control. We designed a test, capable of comprehensively describing prosthetic control strategies in real time. When implemented on control subjects, the test was able to capture statistically significant differences (p < 0.05) in control strategies when considering throughputs, path efficiencies and reaction times. Of particular note, we found statistically significant (p < 0.01) improvements in throughputs and path efficiencies with simultaneous PR when compared to direct control or sequential PR. Amputees could readily achieve the task; however a limited number of subjects was tested and a statistical analysis was not performed with that population.

Applying Space Technology to Enhance Control of an Artificial Arm

NASA Technical Reports Server (NTRS)

Atkins, Diane; Donovan, William H.; Novy, Mara; Abramczyk, Robert

1997-01-01

At the present time, myoelectric prostheses perform only one function of the hand: open and close with the thumb, index and middle finger coming together to grasp various shaped objects. To better understand the limitations of the current single-function prostheses and the needs of the individuals who use them, The Institute for Rehabilitation and Research (TIRR), sponsored by the National Institutes of Health (August 1992 - November 1994), surveyed approximately 2500 individuals with upper limb loss. When asked to identify specific features of their current electric prosthesis that needed improvement, the survey respondents overwhelmingly identified the lack of wrist and finger movement as well as poor control capability. Simply building a mechanism with individual finger and wrist motion is not enough. Individuals with upper limb loss tend to reject prostheses that require continuous visual monitoring and concentration to control. Robotics researchers at NASA's Johnson Space Center (JSC) and Rice University have made substantial progress in myoelectric teleoperation. A myoelectric teleoperation system translates signals generated by an able-bodied robot operator's muscles during hand motions into commands that drive a robot's hand through identical motions. Farry's early work in myoelectric teleoperation used variations over time in the myoelectric spectrum as inputs to neural networks to discriminate grasp types and thumb motions. The resulting schemes yielded up to 93% correct classification on thumb motions. More recently, Fernandez achieved 100% correct non-realtime classification of thumb abduction, extension, and flexion on the same myoelectric data. Fernandez used genetic programming to develop functions that discriminate between thumb motions using myoelectric signal parameters. Genetic programming (GP) is an evolutionary programming method where the computer can modify the discriminating functions' form to improve its performance, not just adjust numerical coefficients or weights. Although the function development may require much computational time and many training cases, the resulting discrimination functions can run in realtime on modest computers. These results suggest that myoelectric signals might be a feasible teleoperation medium, allowing an operator to use his or her own hand and arm as a master to intuitively control an anthropomorphic robot in a remote location such as outer space.

A Myoelectric Hand Splint

ERIC Educational Resources Information Center

Silverstein, Frances; And Others

1974-01-01

Development of a myoelectrically controlled hand splint permitting ambulating mobility of the user is discussed. The role of occupational therapy in the research and design of the device and the training of the patient are emphasized. (Authors)

Vection-induced gastric dysrhythmias and motion sickness

NASA Technical Reports Server (NTRS)

Koch, K. L.; Stern, R. M.

1986-01-01

Gastric electrical and mechanical activity during vection-induced motion sickness was investigated. The contractile events of the antrum and gastric myoelectric activity in healthy subjects exposed to vection were measured simultaneously. Symptomatic and myoelectric responses of subjects with vagotomy and gastric resections during vection stimuli were determined. And laboratory based computer systems for analysis of the myoelectric signal were developed. Gastric myoelectric activity was recorded from cutaneous electrodes, i.e., electrogastrograms (EGGs), and antral contractions were measured with intraluminal pressure transducers. Vection was induced by a rotating drum. gastric electromechanical activity was recorded during three periods: 15 min baseline, 15 min drum rotation (vection), and 15 to 30 min recovery. Preliminary results showed that catecholamine responses in nauseated versus symptom-free subjects were divergent and pretreatment with metoclopramide HC1 (Reglan) prevented vection-induced nausea and reduced tachygastrias in two previously symptomatic subjects.

Human-Machine Interface for the Control of Multi-Function Systems Based on Electrocutaneous Menu: Application to Multi-Grasp Prosthetic Hands

PubMed Central

Gonzalez-Vargas, Jose; Dosen, Strahinja; Amsuess, Sebastian; Yu, Wenwei; Farina, Dario

2015-01-01

Modern assistive devices are very sophisticated systems with multiple degrees of freedom. However, an effective and user-friendly control of these systems is still an open problem since conventional human-machine interfaces (HMI) cannot easily accommodate the system’s complexity. In HMIs, the user is responsible for generating unique patterns of command signals directly triggering the device functions. This approach can be difficult to implement when there are many functions (necessitating many command patterns) and/or the user has a considerable impairment (limited number of available signal sources). In this study, we propose a novel concept for a general-purpose HMI where the controller and the user communicate bidirectionally to select the desired function. The system first presents possible choices to the user via electro-tactile stimulation; the user then acknowledges the desired choice by generating a single command signal. Therefore, the proposed approach simplifies the user communication interface (one signal to generate), decoding (one signal to recognize), and allows selecting from a number of options. To demonstrate the new concept the method was used in one particular application, namely, to implement the control of all the relevant functions in a state of the art commercial prosthetic hand without using any myoelectric channels. We performed experiments in healthy subjects and with one amputee to test the feasibility of the novel approach. The results showed that the performance of the novel HMI concept was comparable or, for some outcome measures, better than the classic myoelectric interfaces. The presented approach has a general applicability and the obtained results point out that it could be used to operate various assistive systems (e.g., prosthesis vs. wheelchair), or it could be integrated into other control schemes (e.g., myoelectric control, brain-machine interfaces) in order to improve the usability of existing low-bandwidth HMIs. PMID:26069961

Human-Machine Interface for the Control of Multi-Function Systems Based on Electrocutaneous Menu: Application to Multi-Grasp Prosthetic Hands.

PubMed

Gonzalez-Vargas, Jose; Dosen, Strahinja; Amsuess, Sebastian; Yu, Wenwei; Farina, Dario

2015-01-01

Modern assistive devices are very sophisticated systems with multiple degrees of freedom. However, an effective and user-friendly control of these systems is still an open problem since conventional human-machine interfaces (HMI) cannot easily accommodate the system's complexity. In HMIs, the user is responsible for generating unique patterns of command signals directly triggering the device functions. This approach can be difficult to implement when there are many functions (necessitating many command patterns) and/or the user has a considerable impairment (limited number of available signal sources). In this study, we propose a novel concept for a general-purpose HMI where the controller and the user communicate bidirectionally to select the desired function. The system first presents possible choices to the user via electro-tactile stimulation; the user then acknowledges the desired choice by generating a single command signal. Therefore, the proposed approach simplifies the user communication interface (one signal to generate), decoding (one signal to recognize), and allows selecting from a number of options. To demonstrate the new concept the method was used in one particular application, namely, to implement the control of all the relevant functions in a state of the art commercial prosthetic hand without using any myoelectric channels. We performed experiments in healthy subjects and with one amputee to test the feasibility of the novel approach. The results showed that the performance of the novel HMI concept was comparable or, for some outcome measures, better than the classic myoelectric interfaces. The presented approach has a general applicability and the obtained results point out that it could be used to operate various assistive systems (e.g., prosthesis vs. wheelchair), or it could be integrated into other control schemes (e.g., myoelectric control, brain-machine interfaces) in order to improve the usability of existing low-bandwidth HMIs.

Intermanual Transfer Effects in Below-Elbow Myoelectric Prosthesis Users.

PubMed

de Boer, Errit; Romkema, Sietske; Cutti, Andrea G; Brouwers, Michael A; Bongers, Raoul M; van der Sluis, Corry K

2016-11-01

To determine intermanual transfer effects in patients with a below-elbow amputation using a myoelectric prosthesis and to establish whether laterality affects these effects. Case-control. A standardized setting in a rehabilitation clinic. A convenience sample (N=44) of experienced myoelectric prosthesis users (n=22) and matched controls (n=22). Controls were matched on sex, age (±5y), and hand dominance. Both the experienced group and the control group performed several tasks using a prosthesis simulator attached to their nonaffected arm. Movement time, force control, Box and Block test (BBT) scores, and duration of hand opening. Movement times of myoelectric prosthesis users were shorter, and these users had significantly higher BBT scores and shorter hand opening durations than those of controls. No intermanual transfer effects on force control and no laterality effects were found. Intermanual transfer effects were present in experienced myoelectric prosthesis users with a below-elbow amputation, independent of laterality. These findings support the clinical relevance of intermanual transfer training, which may facilitate persons with an upper limb amputation to start training directly after the amputation. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Online human training of a myoelectric prosthesis controller via actor-critic reinforcement learning.

PubMed

Pilarski, Patrick M; Dawson, Michael R; Degris, Thomas; Fahimi, Farbod; Carey, Jason P; Sutton, Richard S

2011-01-01

As a contribution toward the goal of adaptable, intelligent artificial limbs, this work introduces a continuous actor-critic reinforcement learning method for optimizing the control of multi-function myoelectric devices. Using a simulated upper-arm robotic prosthesis, we demonstrate how it is possible to derive successful limb controllers from myoelectric data using only a sparse human-delivered training signal, without requiring detailed knowledge about the task domain. This reinforcement-based machine learning framework is well suited for use by both patients and clinical staff, and may be easily adapted to different application domains and the needs of individual amputees. To our knowledge, this is the first my-oelectric control approach that facilitates the online learning of new amputee-specific motions based only on a one-dimensional (scalar) feedback signal provided by the user of the prosthesis. © 2011 IEEE

Use of probabilistic weights to enhance linear regression myoelectric control

NASA Astrophysics Data System (ADS)

Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

2015-12-01

Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

Myoelectric control system and task-specific characteristics affect voluntary use of simultaneous control

PubMed Central

Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

2015-01-01

Clinically available myoelectric control does not enable simultaneous proportional control of prosthetic degrees of freedom. Multiple studies have proposed systems that provide simultaneous control, though few have investigated whether subjects voluntarily use simultaneous control or how they implement it. Additionally, few studies have explicitly evaluated the effect of providing proportional velocity control. The objective of this study was to evaluate factors influencing when and how subjects use simultaneous myoelectric control, including the ability to proportionally control the velocity and the required task precision. Five able-bodied subjects used simultaneous myoelectric control systems with and without proportional velocity control in a virtual Fitts’ Law task. Though subjects used simultaneous control to a substantial degree when proportional velocity control was present, they used very little simultaneous control when using constant-velocity control. Furthermore, use of simultaneous control varied significantly with target distance and width, reflecting a strategy of using simultaneous control for gross cursor positioning and sequential control for fine corrective movements. These results provide insight into how users take advantage of simultaneous control and highlight the need for real-time evaluation of simultaneous control algorithms, as the potential benefit of providing simultaneous control may be affected by other characteristics of the myoelectric control system. PMID:25769167

Biomechanics and energetics of walking in powered ankle exoskeletons using myoelectric control versus mechanically intrinsic control.

PubMed

Koller, Jeffrey R; Remy, C David; Ferris, Daniel P

2018-05-25

Controllers for assistive robotic devices can be divided into two main categories: controllers using neural signals and controllers using mechanically intrinsic signals. Both approaches are prevalent in research devices, but a direct comparison between the two could provide insight into their relative advantages and disadvantages. We studied subjects walking with robotic ankle exoskeletons using two different control modes: dynamic gain proportional myoelectric control based on soleus muscle activity (neural signal), and timing-based mechanically intrinsic control based on gait events (mechanically intrinsic signal). We hypothesized that subjects would have different measures of metabolic work rate between the two controllers as we predicted subjects would use each controller in a unique manner due to one being dependent on muscle recruitment and the other not. The two controllers had the same average actuation signal as we used the control signals from walking with the myoelectric controller to shape the mechanically intrinsic control signal. The difference being the myoelectric controller allowed step-to-step variation in the actuation signals controlled by the user's soleus muscle recruitment while the timing-based controller had the same actuation signal with each step regardless of muscle recruitment. We observed no statistically significant difference in metabolic work rate between the two controllers. Subjects walked with 11% less soleus activity during mid and late stance and significantly less peak soleus recruitment when using the timing-based controller than when using the myoelectric controller. While walking with the myoelectric controller, subjects walked with significantly higher average positive and negative total ankle power compared to walking with the timing-based controller. We interpret the reduced ankle power and muscle activity with the timing-based controller relative to the myoelectric controller to result from greater slacking effects. Subjects were able to be less engaged on a muscle level when using a controller driven by mechanically intrinsic signals than when using a controller driven by neural signals, but this had no affect on their metabolic work rate. These results suggest that the type of controller (neural vs. mechanical) is likely to affect how individuals use robotic exoskeletons for therapeutic rehabilitation or human performance augmentation.

A Biomechanical Comparison of Proportional Electromyography Control to Biological Torque Control Using a Powered Hip Exoskeleton.

PubMed

Young, Aaron J; Gannon, Hannah; Ferris, Daniel P

2017-01-01

Despite a large increase in robotic exoskeleton research, there are few studies that have examined human performance with different control strategies on the same exoskeleton device. Direct comparison studies are needed to determine how users respond to different types of control. The purpose of this study was to compare user performance using a robotic hip exoskeleton with two different controllers: a controller that targeted a biological hip torque profile and a proportional myoelectric controller. We tested both control approaches on 10 able-bodied subjects using a pneumatically powered hip exoskeleton. The state machine controller targeted a biological hip torque profile. The myoelectric controller used electromyography (EMG) of lower limb muscles to produce a proportional control signal for the hip exoskeleton. Each subject performed two 30-min exoskeleton walking trials (1.0 m/s) using each controller and a 10-min trial with the exoskeleton unpowered. During each trial, we measured subjects' metabolic cost of walking, lower limb EMG profiles, and joint kinematics and kinetics (torques and powers) using a force treadmill and motion capture. Compared to unassisted walking in the exoskeleton, myoelectric control significantly reduced metabolic cost by 13% ( p  = 0.005) and biological hip torque control reduced metabolic cost by 7% ( p  = 0.261). Subjects reduced muscle activity relative to the unpowered condition for a greater number of lower limb muscles using myoelectric control compared to the biological hip torque control. More subjects subjectively preferred the myoelectric controller to the biological hip torque control. Myoelectric control had more advantages (metabolic cost and muscle activity reduction) compared to a controller that targeted a biological torque profile for walking with a robotic hip exoskeleton. However, these results were obtained with a single exoskeleton device with specific control configurations while level walking at a single speed. Further testing on different exoskeleton hardware and with more varied experimental protocols, such as testing over multiple types of terrain, is needed to fully elucidate the potential benefits of myoelectric control for exoskeleton technology.

Real time microcontroller implementation of an adaptive myoelectric filter.

PubMed

Bagwell, P J; Chappell, P H

1995-03-01

This paper describes a real time digital adaptive filter for processing myoelectric signals. The filter time constant is automatically selected by the adaptation algorithm, giving a significant improvement over linear filters for estimating the muscle force and controlling a prosthetic device. Interference from mains sources often produces problems for myoelectric processing, and so 50 Hz and all harmonic frequencies are reduced by an averaging filter and differential process. This makes practical electrode placement and contact less critical and time consuming. An economic real time implementation is essential for a prosthetic controller, and this is achieved using an Intel 80C196KC microcontroller.

Prosthesis use in adult acquired major upper-limb amputees: patterns of wear, prosthetic skills and the actual use of prostheses in activities of daily life.

PubMed

Østlie, Kristin; Lesjø, Ingrid Marie; Franklin, Rosemary Joy; Garfelt, Beate; Skjeldal, Ola Hunsbeth; Magnus, Per

2012-11-01

To describe patterns of prosthesis wear and perceived prosthetic usefulness in adult acquired upper-limb amputees (ULAs). To describe prosthetic skills in activities of daily life (ADL) and the actual use of prostheses in the performance of ADL tasks. To estimate the influence of prosthetic skills on actual prosthesis use and the influence of background factors on prosthetic skills and actual prosthesis use. Cross-sectional study analysing population-based questionnaire data (n = 224) and data from interviews and clinical testing in a referred/convenience sample of prosthesis-wearing ULAs (n = 50). Effects were analysed using linear regression. 80.8% wore prostheses. 90.3% reported their most worn prosthesis as useful. Prosthetic usefulness profiles varied with prosthetic type. Despite demonstrating good prosthetic skills, the amputees reported actual prosthesis use in only about half of the ADL tasks performed in everyday life. In unilateral amputees, increased actual use was associated with sufficient prosthetic training and with the use of myoelectric vs cosmetic prostheses, regardless of amputation level. Prosthetic skills did not affect actual prosthesis use. No background factors showed significant effect on prosthetic skills. Most major ULAs wear prostheses. Individualised prosthetic training and fitting of myoelectric rather than passive prostheses may increase actual prosthesis use in ADL.

Online myoelectric control of a dexterous hand prosthesis by transradial amputees.

PubMed

Cipriani, Christian; Antfolk, Christian; Controzzi, Marco; Lundborg, Göran; Rosen, Birgitta; Carrozza, Maria Chiara; Sebelius, Fredrik

2011-06-01

A real-time pattern recognition algorithm based on k-nearest neighbors and lazy learning was used to classify, voluntary electromyography (EMG) signals and to simultaneously control movements of a dexterous artificial hand. EMG signals were superficially recorded by eight pairs of electrodes from the stumps of five transradial amputees and forearms of five able-bodied participants and used online to control a robot hand. Seven finger movements (not involving the wrist) were investigated in this study. The first objective was to understand whether and to which extent it is possible to control continuously and in real-time, the finger postures of a prosthetic hand, using superficial EMG, and a practical classifier, also taking advantage of the direct visual feedback of the moving hand. The second objective was to calculate statistical differences in the performance between participants and groups, thereby assessing the general applicability of the proposed method. The average accuracy of the classifier was 79% for amputees and 89% for able-bodied participants. Statistical analysis of the data revealed a difference in control accuracy based on the aetiology of amputation, type of prostheses regularly used and also between able-bodied participants and amputees. These results are encouraging for the development of noninvasive EMG interfaces for the control of dexterous prostheses.

An Analysis of EMG Electrode Configuration for Targeted Muscle Reinnervation Based Neural Machine Interface

PubMed Central

Huang, He; Zhou, Ping; Li, Guanglin; Kuiken, Todd A.

2015-01-01

Targeted muscle reinnervation (TMR) is a novel neural machine interface for improved myoelectric prosthesis control. Previous high-density (HD) surface electromyography (EMG) studies have indicated that tremendous neural control information can be extracted from the reinnervated muscles by EMG pattern recognition (PR). However, using a large number of EMG electrodes hinders clinical application of the TMR technique. This study investigated a reduced number of electrodes and the placement required to extract sufficient neural control information for accurate identification of user movement intents. An electrode selection algorithm was applied to the HD EMG recordings from each of 4 TMR amputee subjects. The results show that when using only 12 selected bipolar electrodes the average accuracy over subjects for classifying 16 movement intents was 93.0(±3.3)%, just 1.2% lower than when using the entire HD electrode complement. The locations of selected electrodes were consistent with the anatomical reinnervation sites. Additionally, a practical protocol for clinical electrode placement was developed, which does not rely on complex HD EMG experiment and analysis while maintaining a classification accuracy of 88.7±4.5%. These outcomes provide important guidelines for practical electrode placement that can promote future clinical application of TMR and EMG PR in the control of multifunctional prostheses. PMID:18303804

Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching.

PubMed

Edwards, Ann L; Dawson, Michael R; Hebert, Jacqueline S; Sherstan, Craig; Sutton, Richard S; Chan, K Ming; Pilarski, Patrick M

2016-10-01

Myoelectric prostheses currently used by amputees can be difficult to control. Machine learning, and in particular learned predictions about user intent, could help to reduce the time and cognitive load required by amputees while operating their prosthetic device. The goal of this study was to compare two switching-based methods of controlling a myoelectric arm: non-adaptive (or conventional) control and adaptive control (involving real-time prediction learning). Case series study. We compared non-adaptive and adaptive control in two different experiments. In the first, one amputee and one non-amputee subject controlled a robotic arm to perform a simple task; in the second, three able-bodied subjects controlled a robotic arm to perform a more complex task. For both tasks, we calculated the mean time and total number of switches between robotic arm functions over three trials. Adaptive control significantly decreased the number of switches and total switching time for both tasks compared with the conventional control method. Real-time prediction learning was successfully used to improve the control interface of a myoelectric robotic arm during uninterrupted use by an amputee subject and able-bodied subjects. Adaptive control using real-time prediction learning has the potential to help decrease both the time and the cognitive load required by amputees in real-world functional situations when using myoelectric prostheses. © The International Society for Prosthetics and Orthotics 2015.

Myoelectric stimulation on peroneal muscles resists simulated ankle sprain motion.

PubMed

Fong, Daniel Tik-Pui; Chu, Vikki Wing-Shan; Chan, Kai-Ming

2012-07-26

The inadequate reaction time of the peroneal muscles in response to an incorrect foot contact event has been proposed as one of the etiological factors contributing to ankle joint inversion injury. Thus, the current study aimed to investigate the efficacy of a myoelectric stimulation applied to the peroneal muscles in the prevention of a simulated ankle inversion trauma. Ten healthy male subjects performed simulated inversion and supination tests on a pair of mechanical sprain simulators. An electrical signal was delivered to the peroneal muscles of the subjects through a pair of electrode pads. The start of the stimulus was synchronized with the drop of the sprain simulator's platform. In order to determine the maximum delay time which the stimulus could still resist the simulated ankle sprain motion, different delay time were test (0, 5, 10, and 15ms). Together with the control trial (no stimulus), there were 5 testing conditions for both simulated inversion and supination test. The effect was quantified by the drop in maximum ankle tilting angle and angular velocity, as determined by a motion analysis system with a standard laboratory procedure. Results showed that the myoelectric stimulation was effective in all conditions except the one with myoelectric stimulus delayed for 15ms in simulated supination test. It is concluded that myoelectric stimulation on peroneal muscles could resist an ankle spraining motion. Copyright © 2012 Elsevier Ltd. All rights reserved.

Influence of soya antigen levels in milk replacers on the disruption of intestinal motility patterns in calves sensitive to soya.

PubMed

Lalles, J P; Benkredda, D; Toullec, R

1995-09-01

An experiment was designed to determine the soya antigen levels in milk replacers above which gastrointestinal disorders appeared in preruminant calves previously sensitized to antigenic soya by feeding a soya-based milk replacer for 3 months. These calves were then equipped with wire electrodes on the duodenum and the mid-jejunum. The sensitization was visualized using direct skin testing, plasma anti-soya antibody determination and intestinal myoelectric activity recording. After sensitization, the calves were occasionally fed liquid test meals containing various proportions of antigenic soya and whey. The soya-fed calves displayed larger 24 h skin reactions to beta-conglycinin and higher plasma anti-soya antibody titres than the controls maintained on a skim-milk based milk replacer. Disturbances of the myoelectric activity patterns were recorded on the duodenum and mid-jejunum after feeding antigenic soya, but not non-antigenic soya or milk protein, in the soya-sensitized calves. When the level of antigens was varied, disorders in the jejunal motility patterns appeared when antigenic soya provided one-third or more of the dietary protein in the test meals, although some abnormalities were evident at lower incorporation rates. The major change was a reduction in the mean duration of the jejunal migrating motor complexes which was essentially accounted for by a decrease in the mean duration of the phase I (quiescence). This level of antigens corresponded approximately to 14 and 12 mg of immunoreactive glycinin and beta-conglycinin respectively, per gram of protein intake, i.e. 80 and 70 mg/kg0.75 per test meal.

Identification of the Slow Wave of Small Bowel Myoelectrical Activity by Surface Recording

DTIC Science & Technology

2001-10-25

recording of myoelectrical activity (Fig. 1), which underlies intestinal smooth muscle contraction . In effect, the relation between intestinal mechanical...Martínez-de-Juan, J. Saiz, M. Meseguer, J.L. Ponce “Small bowel motility: relationship between smooth muscle contraction and electroenterogram signal”, Med

An implantable myoelectric sensor based prosthesis control system.

PubMed

DeMichele, Glenn A; Troyk, Philip R; Kerns, Douglas A; Weir, Richard

2006-01-01

We present progress on the design and testing of an upper-extremity prosthesis control system based on implantable myoelectric sensors. The implant consists of a single silicon chip packaged with transmit and receive coils. Forward control telemetry to, and reverse EMG data telemetry from multiple implants has been demonstrated.

Conditioning 1-6 Month Old Infants by Means of Myoelectrically Controlled Reinforcement.

ERIC Educational Resources Information Center

Stack, Dale M.; McDonnell, Paul M.

1995-01-01

In order to evaluate possibilities of fitting myoelectrically controlled prosthetic arms on infants, this study examined whether 32 infants (1-6 months) could learn to control environmental contingencies by means of contracting the forearm flexor muscle group. Results indicated that older subjects (age greater than 104 days) demonstrated learning,…

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

Assessment of Myoelectric Controller Performance and Kinematic Behavior of a Novel Soft Synergy-Inspired Robotic Hand for Prosthetic Applications

PubMed Central

Fani, Simone; Bianchi, Matteo; Jain, Sonal; Pimenta Neto, José Simões; Boege, Scott; Grioli, Giorgio; Bicchi, Antonio; Santello, Marco

2016-01-01

Myoelectric artificial limbs can significantly advance the state of the art in prosthetics, since they can be used to control mechatronic devices through muscular activity in a way that mimics how the subjects used to activate their muscles before limb loss. However, surveys indicate that dissatisfaction with the functionality of terminal devices underlies the widespread abandonment of prostheses. We believe that one key factor to improve acceptability of prosthetic devices is to attain human likeness of prosthesis movements, a goal which is being pursued by research on social and human–robot interactions. Therefore, to reduce early abandonment of terminal devices, we propose that controllers should be designed so as to ensure effective task accomplishment in a natural fashion. In this work, we have analyzed and compared the performance of three types of myoelectric controller algorithms based on surface electromyography to control an underactuated and multi-degrees of freedom prosthetic hand, the SoftHand Pro. The goal of the present study was to identify the myoelectric algorithm that best mimics the native hand movements. As a preliminary step, we first quantified the repeatability of the SoftHand Pro finger movements and identified the electromyographic recording sites for able-bodied individuals with the highest signal-to-noise ratio from two pairs of muscles, i.e., flexor digitorum superficialis/extensor digitorum communis, and flexor carpi radialis/extensor carpi ulnaris. Able-bodied volunteers were then asked to execute reach-to-grasp movements, while electromyography signals were recorded from flexor digitorum superficialis/extensor digitorum communis as this was identified as the muscle pair characterized by high signal-to-noise ratio and intuitive control. Subsequently, we tested three myoelectric controllers that mapped electromyography signals to position of the SoftHand Pro. We found that a differential electromyography-to-position mapping ensured the highest coherence with hand movements. Our results represent a first step toward a more effective and intuitive control of myoelectric hand prostheses. PMID:27799908

Electromyography data for non-invasive naturally-controlled robotic hand prostheses

PubMed Central

Atzori, Manfredo; Gijsberts, Arjan; Castellini, Claudio; Caputo, Barbara; Hager, Anne-Gabrielle Mittaz; Elsig, Simone; Giatsidis, Giorgio; Bassetto, Franco; Müller, Henning

2014-01-01

Recent advances in rehabilitation robotics suggest that it may be possible for hand-amputated subjects to recover at least a significant part of the lost hand functionality. The control of robotic prosthetic hands using non-invasive techniques is still a challenge in real life: myoelectric prostheses give limited control capabilities, the control is often unnatural and must be learned through long training times. Meanwhile, scientific literature results are promising but they are still far from fulfilling real-life needs. This work aims to close this gap by allowing worldwide research groups to develop and test movement recognition and force control algorithms on a benchmark scientific database. The database is targeted at studying the relationship between surface electromyography, hand kinematics and hand forces, with the final goal of developing non-invasive, naturally controlled, robotic hand prostheses. The validation section verifies that the data are similar to data acquired in real-life conditions, and that recognition of different hand tasks by applying state-of-the-art signal features and machine-learning algorithms is possible. PMID:25977804

Visceral perceptions and gastric myoelectrical activity in healthy women and in patients with bulimia nervosa.

PubMed

Koch, K L; Bingaman, S; Tan, L; Stern, R M

1998-02-01

Bulimia nervosa remains a common eating disorder in young women. Little is known about upper gastrointestinal symptoms or gastric motility in patients with bulimia nervosa. The aim of this study was to measure gastric myoelectrical activity and hunger/satiety and stomach emptiness/fullness before and after a non-nutrient water load and solid-phase gastric emptying in hospitalized patients with bulimia nervosa (n = 12) and in healthy women (n = 13). Gastric myoelectrical activity was measured by means of cutaneous electrodes; visual analogue scales were used to measure perceptions of hunger/satiety and stomach emptiness/fullness. Before and after a standard water load the bulimia patients reported significantly greater stomach fullness and satiety compared with control subjects (P < 0.01). The percentage of gastric myoelectrical power in the normal 3 cpm range was significantly less in bulimics compared with controls. Power in the 1-2 cpm bradygastria range was significantly greater in bulimia patients before and after the water load compared with the control subjects (P < 0.05). Solid-phase gastric emptying studies using radio-isotope-labelled scrambled eggs showed the lag phase was shortened in the bulimic patients (16 +/- 4 min vs 31 +/- 4 min in controls, P < 0.01), but the percentage of meal emptied at 2 h was similar to control values. bulimia patients had exaggerated perceptions of stomach fullness and satiety in response to water; and abnormal gastric myoelectrical activity and accelerated lag phase of gastric emptying were objective stomach abnormalities detected in hospitalized patients with bulimia nervosa.

The influence of autonomic interventions on the sleep-wake-related changes in gastric myoelectrical activity in rats.

PubMed

Huang, Y M; Yang, C C H; Lai, C J; Kuo, T B J

2011-06-01

Significant changes in autonomic activity occur at sleep-wake transitions and constitute an ideal setting for investigating the modulatory role of the autonomic nervous system on gastric myoelectrical activity (GMA). Using continuous power spectral analysis of electroencephalogram, electromyogram, and electrogastromyogram (EGMG) data from freely moving rats that had undergone chemical sympathetomy and/or truncal vagotomy, sleep-wake-related fluctuations in GMA were compared among the intervention groups. The pattern and extent of fluctuations in EGMG power across the sleep-wake states was blunted most significantly in rats undergoing both chemical sympathectomy and truncal vagotomy. The effect of these interventions also varied with respect to the transition between different sleep-wake states. The most prominent influences were observed between active waking and quiet sleep and between paradoxical sleep and quiet sleep. The sleep-wake-related fluctuations in EGMG power are a result of joint contributions from both sympathetic and vagal innervation. Vagotomy mainly resulted in a reduction in EGMG power, while the role of sympathetic innervation was unveiled by vagotomy and this was reflected most obviously in the extent of the fluctuations in EGMG power. © 2011 Blackwell Publishing Ltd.

Evaluating Internal Model Strength and Performance of Myoelectric Prosthesis Control Strategies.

PubMed

Shehata, Ahmed W; Scheme, Erik J; Sensinger, Jonathon W

2018-05-01

On-going developments in myoelectric prosthesis control have provided prosthesis users with an assortment of control strategies that vary in reliability and performance. Many studies have focused on improving performance by providing feedback to the user but have overlooked the effect of this feedback on internal model development, which is key to improve long-term performance. In this paper, the strength of internal models developed for two commonly used myoelectric control strategies: raw control with raw feedback (using a regression-based approach) and filtered control with filtered feedback (using a classifier-based approach), were evaluated using two psychometric measures: trial-by-trial adaptation and just-noticeable difference. The performance of both strategies was also evaluated using Schmidt's style target acquisition task. Results obtained from 24 able-bodied subjects showed that although filtered control with filtered feedback had better short-term performance in path efficiency ( ), raw control with raw feedback resulted in stronger internal model development ( ), which may lead to better long-term performance. Despite inherent noise in the control signals of the regression controller, these findings suggest that rich feedback associated with regression control may be used to improve human understanding of the myoelectric control system.

Robust extraction of basis functions for simultaneous and proportional myoelectric control via sparse non-negative matrix factorization

NASA Astrophysics Data System (ADS)

Lin, Chuang; Wang, Binghui; Jiang, Ning; Farina, Dario

2018-04-01

Objective. This paper proposes a novel simultaneous and proportional multiple degree of freedom (DOF) myoelectric control method for active prostheses. Approach. The approach is based on non-negative matrix factorization (NMF) of surface EMG signals with the inclusion of sparseness constraints. By applying a sparseness constraint to the control signal matrix, it is possible to extract the basis information from arbitrary movements (quasi-unsupervised approach) for multiple DOFs concurrently. Main Results. In online testing based on target hitting, able-bodied subjects reached a greater throughput (TP) when using sparse NMF (SNMF) than with classic NMF or with linear regression (LR). Accordingly, the completion time (CT) was shorter for SNMF than NMF or LR. The same observations were made in two patients with unilateral limb deficiencies. Significance. The addition of sparseness constraints to NMF allows for a quasi-unsupervised approach to myoelectric control with superior results with respect to previous methods for the simultaneous and proportional control of multi-DOF. The proposed factorization algorithm allows robust simultaneous and proportional control, is superior to previous supervised algorithms, and, because of minimal supervision, paves the way to online adaptation in myoelectric control.

A Method for the Control of Multigrasp Myoelectric Prosthetic Hands

PubMed Central

Dalley, Skyler Ashton; Varol, Huseyin Atakan; Goldfarb, Michael

2012-01-01

This paper presents the design and preliminary experimental validation of a multigrasp myoelectric controller. The described method enables direct and proportional control of multigrasp prosthetic hand motion among nine characteristic postures using two surface electromyography electrodes. To assess the efficacy of the control method, five nonamputee subjects utilized the multigrasp myoelectric controller to command the motion of a virtual prosthesis between random sequences of target hand postures in a series of experimental trials. For comparison, the same subjects also utilized a data glove, worn on their native hand, to command the motion of the virtual prosthesis for similar sequences of target postures during each trial. The time required to transition from posture to posture and the percentage of correctly completed transitions were evaluated to characterize the ability to control the virtual prosthesis using each method. The average overall transition times across all subjects were found to be 1.49 and 0.81 s for the multigrasp myoelectric controller and the native hand, respectively. The average transition completion rates for both were found to be the same (99.2%). Supplemental videos demonstrate the virtual prosthesis experiments, as well as a preliminary hardware implementation. PMID:22180515

Motor control and learning with lower-limb myoelectric control in amputees.

PubMed

Alcaide-Aguirre, Ramses E; Morgenroth, David C; Ferris, Daniel P

2013-01-01

Advances in robotic technology have recently enabled the development of powered lower-limb prosthetic limbs. A major hurdle in developing commercially successful powered prostheses is the control interface. Myoelectric signals are one way for prosthetic users to provide feedforward volitional control of prosthesis mechanics. The goal of this study was to assess motor learning in people with lower-limb amputation using proportional myoelectric control from residual-limb muscles. We examined individuals with transtibial amputation and nondisabled controls performing tracking tasks of a virtual object. We assessed how quickly the individuals with amputation improved their performance and whether years since amputation correlated with performance. At the beginning of training, subjects with amputation performed much worse than control subjects. By the end of a short training period, tracking error did not significantly differ between subjects with amputation and nondisabled subjects. Initial but not final performance correlated significantly with time since amputation. This study demonstrates that although subjects with amputation may initially have poor volitional control of their residual lower-limb muscles, training can substantially improve their volitional control. These findings are encouraging for the future use of proportional myoelectric control of powered lower-limb prostheses.

Changes in the flexion relaxation response induced by lumbar muscle fatigue.

PubMed

Descarreaux, Martin; Lafond, Danik; Jeffrey-Gauthier, Renaud; Centomo, Hugo; Cantin, Vincent

2008-01-24

The flexion relaxation phenomenon (FRP) is an interesting model to study the modulation of lumbar stability. Previous investigations have explored the effect of load, angular velocity and posture on this particular response. However, the influence of muscular fatigue on FRP parameters has not been thoroughly examined. The objective of the study is to identify the effect of erector spinae (ES) muscle fatigue and spine loading on myoelectric silence onset and cessation in healthy individuals during a flexion-extension task. Twenty healthy subjects participated in this study and performed blocks of 3 complete trunk flexions under 4 different experimental conditions: no fatigue/no load (1), no fatigue/load (2), fatigue/no load(3), and fatigue/load (4). Fatigue was induced according to the Sorenson protocol, and electromyographic (EMG) power spectral analysis confirmed that muscular fatigue was adequate in each subject. Trunk and pelvis angles and surface EMG of the ES L2 and L5 were recorded during a flexion-extension task. Trunk flexion angle corresponding to the onset and cessation of myoelectric silence was then compared across the different experimental conditions using 2 x 2 repeated-measures ANOVA. Onset of myoelectric silence during the flexion motion appeared earlier after the fatigue task. Additionally, the cessation of myoelectric silence was observed later during the extension after the fatigue task. Statistical analysis also yielded a main effect of load, indicating a persistence of ES myoelectric activity in flexion during the load condition. The results of this study suggest that the presence of fatigue of the ES muscles modifies the FRP. Superficial back muscle fatigue seems to induce a shift in load-sharing towards passive stabilizing structures. The loss of muscle contribution together with or without laxity in the viscoelastic tissues may have a substantial impact on post fatigue stability.

Myoelectric manifestations of jaw elevator muscle fatigue and recovery in healthy and TMD subjects.

PubMed

Castroflorio, T; Falla, D; Tartaglia, G M; Sforza, C; Deregibus, A

2012-09-01

The effects of muscle pain and fatigue on the control of jaw elevator muscles are not well known. Furthermore, the myoelectric manifestations of fatigue and recovery from fatigue in the masticatory muscles are not reported in literature. The main aims of this study were (i) to evaluate the possible use of surface electromyography (sEMG) as an objective measure of fatigue of the jaw elevator muscles, (ii) to compare the myoelectric manifestations of fatigue in the temporalis anterior and masseter muscles bilaterally, (iii) to assess recovery of the investigated muscles after an endurance test and (iv) to compare fatigue and recovery of the jaw elevator muscles in healthy subjects and patients with muscle-related temporomandibular disorders (TMD). The study was performed on twenty healthy volunteers and eighteen patients with muscle-related TMD. An intra-oral compressive-force sensor was used to measure the voluntary contraction forces close to the intercuspal position and to provide visual feedback of submaximal forces to the subject. Surface EMG signals were recorded with linear electrode arrays during isometric contractions at 20%, 40%, 60% and 80% of the maximum voluntary contraction force, during an endurance test and during the recovery phase. The results showed that (i) the slope of the mean power spectral frequency (MNF) and the initial average rectified value (ARV) could be used to monitor fatigue of the jaw elevators, (ii) the temporalis anterior and masseter muscle show the same myoelectric manifestations of fatigue and recovery and (iii) the initial values of MNF and ARV were lower in patients with muscle-related TMD. The assessment of myoelectric manifestations of fatigue in the masticatory muscles may assist in the clinical assessment of TMDs. © 2012 Blackwell Publishing Ltd.

Design and Implementation of an Intelligent Interface for Myoelectric Controlled Prosthesis

DTIC Science & Technology

2001-10-25

de Investigación y Desarrollo en Instrumentación y Control” 2EMBS student member Universidad Distrital Francisco José de Caldas - Facultad de ...discrimination of the myoelectrical signal by which the control over the impeded movement shall be performed. The Universidad Nacional de Colombia...Number Author(s) Project Number Task Number Work Unit Number Performing Organization Name(s) and Address(es) GIDIC - Grupo de Investigacion y

Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals

PubMed Central

Hodson-Tole, Emma F.; Wakeling, James M.

2017-01-01

Appropriate neuromuscular functioning is essential for survival and features underpinning motor control are present in myoelectric signals recorded from skeletal muscles. One approach to quantify control processes related to function is to assess signal variability using measures such as Sample Entropy. Here we developed a theoretical framework to simulate the effect of variability in burst duration, activation duty cycle, and intensity on the Entropic Half-Life (EnHL) in myoelectric signals. EnHLs were predicted to be <40 ms, and to vary with fluctuations in myoelectric signal amplitude and activation duty cycle. Comparison with myoelectic data from rats walking and running at a range of speeds and inclines confirmed the range of EnHLs, however, the direction of EnHL change in response to altered locomotor demand was not correctly predicted. The discrepancy reflected different associations between the ratio of the standard deviation and mean signal intensity (Ist:It¯) and duty factor in simulated and physiological data, likely reflecting additional information in the signals from the physiological data (e.g., quiescent phase content; variation in action potential shapes). EnHL could have significant value as a novel marker of neuromuscular responses to alterations in perceived locomotor task complexity and intensity. PMID:28974932

Electromyographic fatigue of orbicular oris muscles during exercises in mouth and nasal breathing children.

PubMed

Busanello-Stella, Angela Ruviaro; Blanco-Dutra, Ana Paula; Corrêa, Eliane Castilhos Rodrigues; Silva, Ana Maria Toniolo da

2015-01-01

To investigate the process of fatigue in orbicularis oris muscles by analyzing the median frequency of electromyographic signal and the referred fatigue time, according to the breathing mode and the facial pattern. The participants were 70 children, aged 6 to 12 years, who matched the established criteria. To be classified as 36 nasal-breathing and 34 mouth-breathing children, they underwent speech-language, otorhinolaryngologic, and cephalometric evaluation. For the electromyographic assessment, the children had to sustain lip dumbbells weighing 40, 60, and 100 g and a lip exerciser, until the feeling of fatigue. Median frequency was analyzed in 5, 10, 15, and 20 seconds of activity. The referred time of the feeling of fatigue was also recorded. Data were analyzed through the analysis of variance--repeated measures (post hoc Tukey's test), Kruskal-Wallis test, and Mann-Whitney U-test. A significant decrease in the median frequency from 5 seconds of activity was observed, independently from the comparison between the groups. On comparison, the muscles did not show significant decrease. The reported time for the feeling of fatigue was shorter for mouth-breathing individuals. This feeling occurred after the significant decrease in the median frequency. There were signals that indicated myoelectric fatigue for the orbicularis oris muscles, in both groups analyzed, from the first 5 seconds of activity. Myoelectric fatigue in the orbicularis oris muscles preceded the reported feeling of fatigue in all groups. The account for fatigue time was influenced by only the breathing pattern, occurring more precociously in mouth-breathing children.

Central motor control failure in fibromyalgia: a surface electromyography study

PubMed Central

Casale, Roberto; Sarzi-Puttini, Piercarlo; Atzeni, Fabiola; Gazzoni, Marco; Buskila, Dan; Rainoldi, Alberto

2009-01-01

Background Fibromyalgia (FM) is characterised by diffuse musculoskeletal pain and stiffness at multiple sites, tender points in characteristic locations, and the frequent presence of symptoms such as fatigue. The aim of this study was to assess whether the myoelectrical manifestations of fatigue in patients affected by FM are central or peripheral in origin. Methods Eight female patients aged 55.6 ± 13.6 years (FM group) and eight healthy female volunteers aged 50.3 ± 9.3 years (MCG) were studied by means of non-invasive surface electromyography (s-EMG) involving a linear array of 16 electrodes placed on the skin overlying the biceps brachii muscle, with muscle fatigue being evoked by means of voluntary and involuntary (electrically elicited) contractions. Maximal voluntary contractions (MVCs), motor unit action potential conduction velocity distributions (mean ± SD and skewness), and the mean power frequency of the spectrum (MNF) were estimated in order to assess whether there were any significant differences between the two groups and contraction types. Results The motor pattern of recruitment during voluntary contractions was altered in the FM patients, who also showed fewer myoelectrical manifestations of fatigue (normalised conduction velocity rate of changes: -0.074 ± 0.052%/s in FM vs -0.196 ± 0.133%/s in MCG; normalised MNF rate of changes: -0.29 ± 0.16%/s in FM vs -0.66 ± 0.34%/s in MCG). Mean conduction velocity distribution and skewnesses values were higher (p < 0.01) in the FM group. There were no between-group differences in the results obtained from the electrically elicited contractions. Conclusion The apparent paradox of fewer myoelectrical manifestations of fatigue in FM is the electrophysiological expression of muscle remodelling in terms of the prevalence of slow conducting fatigue-resistant type I fibres. As the only between-group differences concerned voluntary contractions, they are probably more related to central motor control failure than muscle membrane alterations, which suggests pathological muscle fibre remodelling related to altered suprasegmental control. PMID:19570214

Characteristics of phase 3-like activity and rebound excitation triggered by hexamethonium and atropine administration in the ovine small bowel.

PubMed

Romański, K W

2010-02-01

Administration of hexamethonium (Hx) and atropine inhibits myoelectric and motor activity and then evokes a stimulatory effect called rebound excitation (RE) in the ovine small bowel. RE has not been precisely characterized so far and it is possible that it is composed of different types of motility. This study was thus devoted to characterizing these excitatory changes in the myoelectric and motor activity of the small bowel, particularly in the duodenum in conscious sheep. These alterations occurred in response to different intravenous doses of Hx and atropine administered alone or in combinations during various phases of the migrating myoelectric or motor complex (MMC) in the fasted and non-fasted sheep. Initially two basic types of excitatory response to the cholinergic blockade were found. In the course of chronic experiments different doses of Hx and atropine evoked phase 3-like activity (unorganized phase 3 of the MMC or its fragments) alternating with the less regular RE and the duration of these changes was related to the drug dose. In the nonfasted sheep these changes were less pronounced than in the fasted animals. When the drug was given during phase 1 of the MMC, RE did not occur or was greatly reduced. Administration of Hx and atropine in the course of phase 2a and phase 2b of the MMC produced roughly similar effects. Hx triggered stronger phase 3-like activity and RE than atropine. Combinations of Hx and atropine induced an additive effect, more evident in the fasted animals. These actions of Hx and atropine, thus, appear to involve at least partly the same intramural pathways. It is concluded that Hx and atropine evoke phase 3-like activity alternating with RE as the secondary stimulatory response in conscious sheep and both these types of the intestinal motility represent two distinct motility patterns.

Learning from demonstration: Teaching a myoelectric prosthesis with an intact limb via reinforcement learning.

PubMed

Vasan, Gautham; Pilarski, Patrick M

2017-07-01

Prosthetic arms should restore and extend the capabilities of someone with an amputation. They should move naturally and be able to perform elegant, coordinated movements that approximate those of a biological arm. Despite these objectives, the control of modern-day prostheses is often nonintuitive and taxing. Existing devices and control approaches do not yet give users the ability to effect highly synergistic movements during their daily-life control of a prosthetic device. As a step towards improving the control of prosthetic arms and hands, we introduce an intuitive approach to training a prosthetic control system that helps a user achieve hard-to-engineer control behaviours. Specifically, we present an actor-critic reinforcement learning method that for the first time promises to allow someone with an amputation to use their non-amputated arm to teach their prosthetic arm how to move through a wide range of coordinated motions and grasp patterns. We evaluate our method during the myoelectric control of a multi-joint robot arm by non-amputee users, and demonstrate that by using our approach a user can train their arm to perform simultaneous gestures and movements in all three degrees of freedom in the robot's hand and wrist based only on information sampled from the robot and the user's above-elbow myoelectric signals. Our results indicate that this learning-from-demonstration paradigm may be well suited to use by both patients and clinicians with minimal technical knowledge, as it allows a user to personalize the control of his or her prosthesis without having to know the underlying mechanics of the prosthetic limb. These preliminary results also suggest that our approach may extend in a straightforward way to next-generation prostheses with precise finger and wrist control, such that these devices may someday allow users to perform fluid and intuitive movements like playing the piano, catching a ball, and comfortably shaking hands.

Design and testing of an advanced implantable neuroprosthesis with myoelectric control.

PubMed

Hart, Ronald L; Bhadra, Niloy; Montague, Fred W; Kilgore, Kevin L; Peckham, P Hunter

2011-02-01

An implantable stimulator-telemeter (IST-12) was developed for applications in neuroprosthetic restoration of limb function in paralyzed individuals. The IST-12 provides 12 stimulation channels and two myoelectric signal (MES) channels. The MES circuitry includes a two-channel multiplexer, preamplifier, variable gain amplifier/bandpass filter, full-wave rectifier, and bin integrator. Power and control signals are transmitted from an external control unit to the IST-12 through an inductive link. Recorded MES signals are telemetered back to the external control unit through the same inductive link. Following bench testing, one device was implanted chronically in a dog for 15 months and evaluated. Conditions were identified in which MES could be recorded with minimal stimulus artifact. The ability to record MES in the presence of stimulation was verified, confirming the potential of the IST-12 to be used as a myoelectric controlled neuroprosthesis.

Estimation of muscle strength during motion recognition using multichannel surface EMG signals.

PubMed

Nagata, Kentaro; Nakano, Takemi; Magatani, Kazushige; Yamada, Masafumi

2008-01-01

The use of kinesiological electromyography is established as an evaluation tool for various kinds of applied research, and surface electromyogram (SEMG) has been widely used as a control source for human interfaces such as in a myoelectric prosthetic hand (we call them 'SEMG interfaces'). It is desirable to be able to control the SEMG interfaces with the same feeling as body movement. The existing SEMG interface mainly focuses on how to achieve accurate recognition of the intended movement. However, detecting muscular strength and reduced number of electrodes are also an important factor in controlling them. Therefore, our objective in this study is the development of and the estimation method for muscular strength that maintains the accuracy of hand motion recognition to reflect the result of measured power in a controlled object. Although the muscular strength can be evaluated by various methods, in this study a grasp force index was applied to evaluate the muscular strength. In order to achieve our objective, we directed our attention to measuring all valuable information for SEMG. This work proposes an application method of two simple linear models, and the selection method of an optimal electrode configuration to use them effectively. Our system required four SEMG measurement electrodes in which locations differed for every subject depending on the individual's characteristics, and those were selected from a 96ch multi electrode using the Monte Carlo method. From the experimental results, the performance in six normal subjects indicated that the recognition rate of four motions were perfect and the grasp force estimated result fit well with the actual measurement result.

Evaluation of the myoelectrical activity of the equine ileum infected with Strongylus vulgaris larvae.

PubMed

Berry, C R; Merritt, A M; Burrows, C F; Campbell, M; Drudge, J H

1986-01-01

Five weanling ponies were subjected to an intensive 6-week deworming program after which 4 Ag-AgCl bipolar electrodes were implanted surgically on the distal ileum. For 3 hours each day for 5 consecutive days, ileal myoelectrical activity was recorded from fed ponies under 3 sequential conditions: preinoculation, after oral administration of 1,000 killed Strongylus vulgaris infective larvae (3 ponies), and after oral administration of 1,000 live S vulgaris infective larvae. Recordings were analyzed for slow wave frequency, percentage duration of phases I, II, and III of the migrating myoelectrical complex (MMC), and the frequency of distinct, rapidly migrating action-potential complexes within phase 2 of the MMC. After administration of live and killed infected 3rd-stage larvae, there was a marked increase in the number of disrupted phase III complexes, and a significant (P less than 0.001) increase in the number of migrating action-potential complexes. In addition, after inoculation of live 3rd-stage larvae, there was a significant increase (P less than 0.001) in the percentage of time that the MMC was occupied by prolonged periods devoid of spike activity (phase I). The results indicate that S vulgaris larval mucosal penetration and submucosal migration can cause changes in ileal myoelectrical activity that could cause colic, and that larval antigen alone within the lumen may disrupt ileal motility.

Effect of the acupoints ST-36 (Zusanli) and SP-6 (Sanyinjiao) on intestinal myoelectric activity of Wistar rats.

PubMed

Tabosa, A; Yamamura, Y; Forno, E R; Mello, L E A M

2002-06-01

Despite its ancient use as a therapeutic tool to treat several ailments, acupuncture still faces the challenge of scrutiny by Western science both in terms of its efficacy and in terms of the characterization of its effects and mechanisms of actions underlying these effects. We investigated under well-controlled and carefully characterized conditions the influence of electrical stimulation of acupuncture points ST-36 (Zusanli) and SP-6 (Sanyinjiao) on the myoelectric activity of the small intestine of 38 adult male Wistar rats. Electrical recordings obtained by means of four electrodes chronically implanted in the small intestine were used to assess the effects of acupuncture (electroacupuncture stimulation set at 2 Hz, intermittent stimulation, 1 V, for 30 min). Immobilization of the animals was associated with a consistent decrease (-8 +/- 7%) in the myoelectric activity of the small intestine as measured by means of the root mean square. Conversely, acupuncture was able to significantly increase (overshoot) this activity compared to baseline (+44 +/- 7%). In contrast, immobilized animals subjected to sham acupuncture had only modest (nonsignificant) increases in myoelectric activity (+9 +/- 6%). Using carefully controlled conditions we confirmed previous noncontrolled studies on the ability of acupuncture to alter intestinal motility. The characterization of the topographic and temporal profiles of the effects observed here represents a basis for future dissection of the physiological and pharmacological systems underlying these effects.

Myoelectrically controlled wrist robot for stroke rehabilitation

PubMed Central

2013-01-01

Background Robot-assisted rehabilitation is an advanced new technology in stroke rehabilitation to provide intensive training. Post-stroke motor recovery depends on active rehabilitation by voluntary participation of patient’s paretic motor system as early as possible in order to promote reorganization of brain. However, voluntary residual motor efforts to the affected limb have not been involved enough in most robot-assisted rehabilitation for patients after stroke. The objective of this study is to evaluate the feasibility of robot-assisted rehabilitation using myoelectric control on upper limb motor recovery. Methods In the present study, an exoskeleton-type rehabilitation robotic system was designed to provide voluntarily controlled assisted torque to the affected wrist. Voluntary intention was involved by using the residual surface electromyography (EMG) from flexor carpi radialis(FCR) and extensor carpi radialis (ECR)on the affected limb to control the mechanical assistance provided by the robotic system during wrist flexion and extension in a 20-session training. The system also applied constant resistant torque to the affected wrist during the training. Sixteen subjects after stroke had been recruited for evaluating the tracking performance and therapeutical effects of myoelectrically controlled robotic system. Results With the myoelectrically-controlled assistive torque, stroke survivors could reach a larger range of motion with a significant decrease in the EMG signal from the agonist muscles. The stroke survivors could be trained in the unreached range with their voluntary residual EMG on the paretic side. After 20-session rehabilitation training, there was a non-significant increase in the range of motion and a significant decrease in the root mean square error (RMSE) between the actual wrist angle and target angle. Significant improvements also could be found in muscle strength and clinical scales. Conclusions These results indicate that robot-aided therapy with voluntary participation of patient’s paretic motor system using myoelectric control might have positive effect on upper limb motor recovery. PMID:23758925

Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2017-12-01

The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrated and flexible multichannel interface for electrotactile stimulation

NASA Astrophysics Data System (ADS)

Štrbac, Matija; Belić, Minja; Isaković, Milica; Kojić, Vladimir; Bijelić, Goran; Popović, Igor; Radotić, Milutin; Došen, Strahinja; Marković, Marko; Farina, Dario; Keller, Thierry

2016-08-01

Objective. The aim of the present work was to develop and test a flexible electrotactile stimulation system to provide real-time feedback to the prosthesis user. The system requirements were to accommodate the capabilities of advanced multi-DOF myoelectric hand prostheses and transmit the feedback variables (proprioception and force) using intuitive coding, with high resolution and after minimal training. Approach. We developed a fully-programmable and integrated electrotactile interface supporting time and space distributed stimulation over custom designed flexible array electrodes. The system implements low-level access to individual stimulation channels as well as a set of high-level mapping functions translating the state of a multi-DoF prosthesis (aperture, grasping force, wrist rotation) into a set of predefined dynamic stimulation profiles. The system was evaluated using discrimination tests employing spatial and frequency coding (10 able-bodied subjects) and dynamic patterns (10 able-bodied and 6 amputee subjects). The outcome measure was the success rate (SR) in discrimination. Main results. The more practical electrode with the common anode configuration performed similarly to the more usual concentric arrangement. The subjects could discriminate six spatial and four frequency levels with SR >90% after a few minutes of training, whereas the performance significantly deteriorated for more levels. The dynamic patterns were intuitive for the subjects, although amputees showed lower SR than able-bodied individuals (86% ± 10% versus 99% ± 3%). Significance. The tests demonstrated that the system was easy to setup and apply. The design and resolution of the multipad electrode was evaluated. Importantly, the novel dynamic patterns, which were successfully tested, can be superimposed to transmit multiple feedback variables intuitively and simultaneously. This is especially relevant for closing the loop in modern multifunction prostheses. Therefore, the proposed system is convenient for practical applications and can be used to implement sensory perception training and/or closed-loop control of myoelectric prostheses, providing grasping force and proprioceptive feedback.

Myoelectric intuitive control and transcutaneous electrical stimulation of the forearm for vibrotactile sensation feedback applied to a 3D printed prosthetic hand.

PubMed

Germany, Enrique I; Pino, Esteban J; Aqueveque, Pablo E

2016-08-01

This paper presents the development of a myoelectric prosthetic hand based on a 3D printed model. A myoelectric control strategy based on artificial neural networks is implemented on a microcontroller for online position estimation. Position estimation performance achieves a correlation index of 0.78. Also a study involving transcutaneous electrical stimulation was performed to provide tactile feedback. A series of stimulations with controlled parameters were tested on five able-body subjects. A single channel stimulator was used, positioning the electrodes 8 cm on the wrist over the ulnar and median nerve. Controlling stimulation parameters such as intensity, frequency and pulse width, the subjects were capable of distinguishing different sensations over the palm of the hand. Three main sensations where achieved: tickling, pressure and pain. Tickling and pressure were discretized into low, moderate and high according to the magnitude of the feeling. The parameters at which each sensation was obtained are further discussed in this paper.

Using speech for mode selection in control of multifunctional myoelectric prostheses.

PubMed

Fang, Peng; Wei, Zheng; Geng, Yanjuan; Yao, Fuan; Li, Guanglin

2013-01-01

Electromyogram (EMG) recorded from residual muscles of limbs is considered as suitable control information for motorized prostheses. However, in case of high-level amputations, the residual muscles are usually limited, which may not provide enough EMG for flexible control of myoelectric prostheses with multiple degrees of freedom of movements. Here, we proposed a control strategy, where the speech signals were used as additional information and combined with the EMG signals to realize more flexible control of multifunctional prostheses. By replacing the traditional "sequential mode-switching (joint-switching)", the speech signals were used to select a mode (joint) of the prosthetic arm, and then the EMG signals were applied to determine a motion class involved in the selected joint and to execute the motion. Preliminary results from three able-bodied subjects and one transhumeral amputee demonstrated the proposed strategy could achieve a high mode-selection rate and enhance the operation efficiency, suggesting the strategy may improve the control performance of commercial myoelectric prostheses.

Paroxysmal anal hyperkinesis: a characteristic feature of proctalgia fugax.

PubMed

Rao, S S; Hatfield, R A

1996-10-01

Proctalgia fugax is a common problem, yet its pathophysiology is poorly understood. The objective was to characterise colorectal disturbances in a paraplegic patient with a 10 year history of proctalgia fugax that began two years after an attack of transverse myelitis. Standard anorectal manometry and prolonged 33 hour ambulatory colonic manometry at six sites in the colon were performed together with myoelectrical recording of the anus. Provocative tests designed to simulate psychological and physical stress and two types of meals were included. Anorectal manometry showed normal internal sphincter tone and normal rectoanal inhibitory reflex but an inability to squeeze or to bear down or to expel a simulated stool. Rectal sensation (up to 360 ml inflation) was absent. Pudendal nerve latency was prolonged (4.5 ms (normal < 2.2 ms). During colonic manometry, the patient reported 27 episodes of pain, of which 23 (85%) were associated with bursts (1-60 min) of a high amplitude (0.5 to > 3.2 mv), high frequency (5-50/min) anal myoelectrical activity, particularly after stress tests, meals, and at night. The myoelectrical disturbance only occurred with proctalgia. Intermittently, 16 bursts of 3 cycles/ min phasic rectal contractions were seen, but only six were associated with proctalgia. Colonic motility was reduced compared with normal subjects. The temporal association between a high amplitude, high frequency myoelectrical activity of the anal sphincter, and the occurrence of proctalgia suggests that paroxysmal hyperkinesis of the anus may cause proctalgia fugax.

Paroxysmal anal hyperkinesis: a characteristic feature of proctalgia fugax.

PubMed Central

Rao, S S; Hatfield, R A

1996-01-01

BACKGROUND AND AIMS: Proctalgia fugax is a common problem, yet its pathophysiology is poorly understood. The objective was to characterise colorectal disturbances in a paraplegic patient with a 10 year history of proctalgia fugax that began two years after an attack of transverse myelitis. METHODS: Standard anorectal manometry and prolonged 33 hour ambulatory colonic manometry at six sites in the colon were performed together with myoelectrical recording of the anus. Provocative tests designed to simulate psychological and physical stress and two types of meals were included. RESULTS: Anorectal manometry showed normal internal sphincter tone and normal rectoanal inhibitory reflex but an inability to squeeze or to bear down or to expel a simulated stool. Rectal sensation (up to 360 ml inflation) was absent. Pudendal nerve latency was prolonged (4.5 ms (normal < 2.2 ms). During colonic manometry, the patient reported 27 episodes of pain, of which 23 (85%) were associated with bursts (1-60 min) of a high amplitude (0.5 to > 3.2 mv), high frequency (5-50/min) anal myoelectrical activity, particularly after stress tests, meals, and at night. The myoelectrical disturbance only occurred with proctalgia. Intermittently, 16 bursts of 3 cycles/ min phasic rectal contractions were seen, but only six were associated with proctalgia. Colonic motility was reduced compared with normal subjects. CONCLUSIONS: The temporal association between a high amplitude, high frequency myoelectrical activity of the anal sphincter, and the occurrence of proctalgia suggests that paroxysmal hyperkinesis of the anus may cause proctalgia fugax. PMID:8944574

Improving Fine Control of Grasping Force during Hand–Object Interactions for a Soft Synergy-Inspired Myoelectric Prosthetic Hand

PubMed Central

Fu, Qiushi; Santello, Marco

2018-01-01

The concept of postural synergies of the human hand has been shown to potentially reduce complexity in the neuromuscular control of grasping. By merging this concept with soft robotics approaches, a multi degrees of freedom soft-synergy prosthetic hand [SoftHand-Pro (SHP)] was created. The mechanical innovation of the SHP enables adaptive and robust functional grasps with simple and intuitive myoelectric control from only two surface electromyogram (sEMG) channels. However, the current myoelectric controller has very limited capability for fine control of grasp forces. We addressed this challenge by designing a hybrid-gain myoelectric controller that switches control gains based on the sensorimotor state of the SHP. This controller was tested against a conventional single-gain (SG) controller, as well as against native hand in able-bodied subjects. We used the following tasks to evaluate the performance of grasp force control: (1) pick and place objects with different size, weight, and fragility levels using power or precision grasp and (2) squeezing objects with different stiffness. Sensory feedback of the grasp forces was provided to the user through a non-invasive, mechanotactile haptic feedback device mounted on the upper arm. We demonstrated that the novel hybrid controller enabled superior task completion speed and fine force control over SG controller in object pick-and-place tasks. We also found that the performance of the hybrid controller qualitatively agrees with the performance of native human hands. PMID:29375360

Optical Pattern Recognition

NASA Astrophysics Data System (ADS)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

Assessment of muscle fatigue during biking.

PubMed

Knaflitz, Marco; Molinari, Filippo

2003-03-01

The analysis of the surface myoelectric signal recorded while a muscle is performing a sustained contraction is a valuable tool for assessing the progression of localized fatigue. It is well known that the modifications of the spectral content of the myoelectric signal are mainly related to changes in the interstitial fluid pH, which, in turn, affect the membrane excitability of the active muscle fibers. This paper describes the effects of muscle fatigue on the surface myoelectric signal recorded from three thigh and leg muscles during biking, on a population consisting of 22 young healthy volunteers. The purpose of this study was to obtain normative data relative to an exercise protocol mild enough to be applicable, in the future, to pathological subjects as well. Each subject was asked to exercise 30 min on a cycloergometer at a constant velocity and against a constant torque. While subjects were biking, the surface myoelectric signal was recorded from the rectus femoris, the biceps femoris, and the gastrocnemius muscles. In this study, we considered two different aspects of muscle fatigue: first, the localized muscle fatigue as shown by the decrement of the instantaneous frequency of the myoelectric signal during the exercise; second, the modifications of the muscle ON-OFF timing, which could be explained as a strategy for increasing endurance by modifying the role of different muscles during the exercise. The first aspect was studied by obtaining the spectral characteristics of the signals by means of bilinear time-frequency transforms and by applying an original estimator of the instantaneous frequency of stochastic processes based on cross time-frequency transforms. Our results demonstrated that none of the subjects showed significant signs of localized muscle fatigue, since the decrement of the instantaneous frequency during the exercise was always lower than 5% of its initial value. Muscle ON-OFF timing was obtained by applying to the raw myoelectric signal a double threshold statistical detector to identify the time intervals during which the observed muscles were active. This demonstrated that the subjective feeling of fatigue each subject reported during the exercise did not cause a change of the activation strategy of the observed muscles. It is concluded that the experimental protocol herein described and the signal processing procedures adopted are appropriate for monitoring different effects of muscle fatigue during biking. Moreover, data obtained from our sample population can be considered as a reference for studying the manifestations of muscle fatigue in pathological subjects asked to follow a similar experimental protocol.

Targeted Muscle Reinnervation for Real-Time Myoelectric Control of Multifunction Artificial Arms

PubMed Central

Kuiken, Todd A.; Li, Guanglin; Lock, Blair A.; Lipschutz, Robert D.; Miller, Laura A.; Stubblefield, Kathy A.; Englehart, Kevin

2011-01-01

Context Improving the function of prosthetic arms remains a challenge, as access to the neural control information for the arm is lost during amputation. We have developed a surgical technique called targeted muscle reinnervation (TMR) which transfers residual arm nerves to alternative muscle sites. After reinnervation, these target muscles produce an electromyogram (EMG) on the surface of the skin that can be measured and used to control prosthetic arms. Objective Assess the performance of TMR upper-limb amputee patients using a pattern-recognition algorithm to decode EMG signals and control prosthetic arm motions. Design Surface EMG signals were recorded on participants and decoded using a pattern-recognition algorithm. The decoding program controlled the movement of a virtual prosthetic arm. Participants were instructed to perform various arm movements, and their abilities to control the virtual prosthetic arm were measured. In addition, TMR patients used the same control system to operate advanced arm prosthesis prototypes. Setting This study was conducted between January 2007 and January 2008 at the Rehabilitation Institute of Chicago. Participants This study included five patients with shoulder disarticulation or transhumeral amputations who received TMR surgery between February 2002 and October 2006. It also included five non-amputee (control) participants. Main Outcome Measure Performance metrics measured during virtual arm movements included motion-selection time, motion-completion time, and motion-completion (or `success') rate. Three of the TMR patients were also able to test advanced arm prostheses. Results TMR patients were able to repeatedly perform 10 different elbow, wrist and hand motions with the virtual prosthetic arm. For TMR patients, the average (standard deviation (SD)) motion-selection and motion-completion times for elbow and wrist movements were 0.22 s (0.06) and 1.29 s (0.15), respectively. These times were 0.06 s and 0.21 s longer than the average times of control participants. For TMR patients, the average (SD) motion-selection and motion-completion times for hand-grasp patterns were 0.38 s (0.12) and 1.54 s (0.27), respectively. TMR patients successfully completed an average (SD) of 96.3% (3.8) of elbow and wrist movements and 86.9% (13.9) of hand movements within 5 s, compared to 100% (0) and 96.7% (4.7) completed by controls. Three of the patients were able to demonstrate the use of this control system in advanced prostheses including motorized shoulders, elbows, wrists and hands. Conclusion These results suggest that reinnervated muscles can produce sufficient EMG information to control advanced artificial arms. PMID:19211469

Use of Biometrics within Sub-Saharan Refugee Communities

DTIC Science & Technology

2013-12-01

fingerprint patterns, iris pattern recognition, and facial recognition as a means of establishing an individual’s identity. Biometrics creates and...Biometrics typically comprises fingerprint patterns, iris pattern recognition, and facial recognition as a means of establishing an individual’s identity...authentication because it identifies an individual based on mathematical analysis of the random pattern visible within the iris. Facial recognition is

Deep learning-based artificial vision for grasp classification in myoelectric hands.

PubMed

Ghazaei, Ghazal; Alameer, Ali; Degenaar, Patrick; Morgan, Graham; Nazarpour, Kianoush

2017-06-01

Computer vision-based assistive technology solutions can revolutionise the quality of care for people with sensorimotor disorders. The goal of this work was to enable trans-radial amputees to use a simple, yet efficient, computer vision system to grasp and move common household objects with a two-channel myoelectric prosthetic hand. We developed a deep learning-based artificial vision system to augment the grasp functionality of a commercial prosthesis. Our main conceptual novelty is that we classify objects with regards to the grasp pattern without explicitly identifying them or measuring their dimensions. A convolutional neural network (CNN) structure was trained with images of over 500 graspable objects. For each object, 72 images, at [Formula: see text] intervals, were available. Objects were categorised into four grasp classes, namely: pinch, tripod, palmar wrist neutral and palmar wrist pronated. The CNN setting was first tuned and tested offline and then in realtime with objects or object views that were not included in the training set. The classification accuracy in the offline tests reached [Formula: see text] for the seen and [Formula: see text] for the novel objects; reflecting the generalisability of grasp classification. We then implemented the proposed framework in realtime on a standard laptop computer and achieved an overall score of [Formula: see text] in classifying a set of novel as well as seen but randomly-rotated objects. Finally, the system was tested with two trans-radial amputee volunteers controlling an i-limb Ultra TM prosthetic hand and a motion control TM prosthetic wrist; augmented with a webcam. After training, subjects successfully picked up and moved the target objects with an overall success of up to [Formula: see text]. In addition, we show that with training, subjects' performance improved in terms of time required to accomplish a block of 24 trials despite a decreasing level of visual feedback. The proposed design constitutes a substantial conceptual improvement for the control of multi-functional prosthetic hands. We show for the first time that deep-learning based computer vision systems can enhance the grip functionality of myoelectric hands considerably.

Deep learning-based artificial vision for grasp classification in myoelectric hands

NASA Astrophysics Data System (ADS)

Ghazaei, Ghazal; Alameer, Ali; Degenaar, Patrick; Morgan, Graham; Nazarpour, Kianoush

2017-06-01

Objective. Computer vision-based assistive technology solutions can revolutionise the quality of care for people with sensorimotor disorders. The goal of this work was to enable trans-radial amputees to use a simple, yet efficient, computer vision system to grasp and move common household objects with a two-channel myoelectric prosthetic hand. Approach. We developed a deep learning-based artificial vision system to augment the grasp functionality of a commercial prosthesis. Our main conceptual novelty is that we classify objects with regards to the grasp pattern without explicitly identifying them or measuring their dimensions. A convolutional neural network (CNN) structure was trained with images of over 500 graspable objects. For each object, 72 images, at {{5}\\circ} intervals, were available. Objects were categorised into four grasp classes, namely: pinch, tripod, palmar wrist neutral and palmar wrist pronated. The CNN setting was first tuned and tested offline and then in realtime with objects or object views that were not included in the training set. Main results. The classification accuracy in the offline tests reached 85 % for the seen and 75 % for the novel objects; reflecting the generalisability of grasp classification. We then implemented the proposed framework in realtime on a standard laptop computer and achieved an overall score of 84 % in classifying a set of novel as well as seen but randomly-rotated objects. Finally, the system was tested with two trans-radial amputee volunteers controlling an i-limb UltraTM prosthetic hand and a motion controlTM prosthetic wrist; augmented with a webcam. After training, subjects successfully picked up and moved the target objects with an overall success of up to 88 % . In addition, we show that with training, subjects’ performance improved in terms of time required to accomplish a block of 24 trials despite a decreasing level of visual feedback. Significance. The proposed design constitutes a substantial conceptual improvement for the control of multi-functional prosthetic hands. We show for the first time that deep-learning based computer vision systems can enhance the grip functionality of myoelectric hands considerably.

Myoelectrical Manifestation of Fatigue Less Prominent in Patients with Cancer Related Fatigue

PubMed Central

Kisiel-Sajewicz, Katarzyna; Siemionow, Vlodek; Seyidova-Khoshknabi, Dilara; Davis, Mellar P.; Wyant, Alexandria; Ranganathan, Vinoth K.; Walsh, Declan; Yan, Jin H.; Hou, Juliet; Yue, Guang H.

2013-01-01

Purpose A lack of fatigue-related muscle contractile property changes at time of perceived physical exhaustion and greater central than peripheral fatigue detected by twitch interpolation technique have recently been reported in cancer survivors with fatigue symptoms. Based on these observations, it was hypothesized that compared to healthy people, myoelectrical manifestation of fatigue in the performing muscles would be less significant in these individuals while sustaining a prolonged motor task to self-perceived exhaustion (SPE) since their central fatigue was more prominent. The purpose of this study was to test this hypothesis by examining electromyographic (EMG) signal changes during fatiguing muscle performance. Methods Twelve individuals who had advanced solid cancer and cancer-related fatigue (CRF), and 12 age- and gender-matched healthy controls performed a sustained elbow flexion at 30% maximal voluntary contraction till SPE. Amplitude and mean power frequency (MPF) of EMG signals of the biceps brachii, brachioradialis, and triceps brachii muscles were evaluated when the individuals experienced minimal, moderate, and severe fatigue. Results CRF patients perceived physical “exhaustion” significantly sooner than the controls. The myoelectrical manifestation of muscular fatigue assessed by EMG amplitude and MPF was less significant in CRF than controls. The lower MPF even at minimal fatigue stage in CRF may indicate pathophysiologic condition of the muscle. Conclusions CRF patients experience less myoelectrical manifestation of muscle fatigue than healthy individuals near the time of SPE. The data suggest that central nervous system fatigue plays a more important role in limiting endurance-type of motor performance in patients with CRF. PMID:24391800

Electrogastrography in experimental pigs: the influence of gastrointestinal injury induced by dextran sodium sulphate on porcine gastric erythromycin-stimulated myoelectric activity.

PubMed

Tachecí, Ilja; Kvetina, Jaroslav; Kunes, Martin; Edakkanambeth Varayil, Jithinraj; Ali, Shahzad Marghoob; Pavlik, Michal; Kopacova, Marcela; Rejchrt, Stanislav; Bures, Jan; Pleskot, Miloslav

2011-01-01

Electrogastrography (EGG) is a non-invasive investigation of gastric myoelectrical activity. The aim of study was to evaluate the impact of erythromycin on EGG in gastrointestinal toxic injury induced by dextran sodium sulphate (DSS) in experimental pigs. The experiments were carried out on 12 adult pigs (weighing 30-35 kg). EGG was recorded using Digitrapper equipment (Synectics Medical AB, Stockholm). Running spectrum activity was used for EGG evaluation. There were two groups of animals: Group I: 6 controls with erythromycin administration (1,600 mg intragastrically); Group II: 6 animals treated with DSS (for 5 days, 0.25 g/kg per day in a dietary bolus) followed by erythromycin administration. Baseline and subsequent six separate 30-minute EGG-recordings (from time 0 to 360 min) were accomplished in each animal. A total of 84 records were analysed. Baseline dominant frequency of slow waves was fully comparable in both groups. In Group I, there was a significant increase in dominant frequency after erythromycin administration (maximum between 240-360 min). There was a flat non-significant and delayed increase in dominant frequency after erythromycin administration in Group II. The difference between Group I and II at particular time intervals was not significant but a diverse trend was evident. EGG recording enables us to register a gastric myoelectrical effect of prokinetic drugs. Erythromycin induced a significant increase in the dominant frequency of slow waves. DSS caused toxic injury to the porcine gastrointestinal tract responsible for the delayed and weaker myoelectrical effect of erythromycin in experimental animals.

Rotation-invariant neural pattern recognition system with application to coin recognition.

PubMed

Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

1992-01-01

In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.

Implantable Myoelectric Sensors (IMESs) for Intramuscular Electromyogram Recording

PubMed Central

Weir, Richard F. ff.; Troyk, Phil R.; DeMichele, Glen A.; Kerns, Douglas A.; Schorsch, Jack F.; Maas, Huub

2011-01-01

We have developed a multichannel electrogmyography sensor system capable of receiving and processing signals from up to 32 implanted myoelectric sensors (IMES). The appeal of implanted sensors for myoelectric control is that electromyography (EMG) signals can be measured at their source providing relatively cross-talk-free signals that can be treated as independent control sites. An external telemetry controller receives telemetry sent over a transcutaneous magnetic link by the implanted electrodes. The same link provides power and commands to the implanted electrodes. Wireless telemetry of EMG signals from sensors implanted in the residual musculature eliminates the problems associated with percutaneous wires, such as infection, breakage, and marsupialization. Each implantable sensor consists of a custom-designed application-specified integrated circuit that is packaged into a bio-compatible RF BION capsule from the Alfred E. Mann Foundation. Implants are designed for permanent long-term implantation with no servicing requirements. We have a fully operational system. The system has been tested in animals. Implants have been chronically implanted in the legs of three cats and are still completely operational four months after implantation. PMID:19224729

Functional Assessment of the Vanderbilt Multigrasp Myoelectric Hand: A Continuing Case Study

PubMed Central

Dalley, Skyler A.; Bennett, Daniel A.; Goldfarb, Michael

2015-01-01

This paper presents a case study involving the functional assessment of the Vanderbilt Multigrasp (VMG) hand prosthesis on a single transradial amputee subject. In particular, a transradial amputee subject performed the Southampton Hand Assessment Procedure (SHAP) using the hand prosthesis and multigrasp myoelectric controller in a series of experimental sessions occurring over a multi-week time span. The subject’s index of function (IoF) improved with each session, although essentially plateaued after the fourth session, resulting in a IoF score of 87, which compares favorably to SHAP scores published in previous studies. PMID:25571412

Biomechanical Reconstruction Using the Tacit Learning System: Intuitive Control of Prosthetic Hand Rotation.

PubMed

Oyama, Shintaro; Shimoda, Shingo; Alnajjar, Fady S K; Iwatsuki, Katsuyuki; Hoshiyama, Minoru; Tanaka, Hirotaka; Hirata, Hitoshi

2016-01-01

Background: For mechanically reconstructing human biomechanical function, intuitive proportional control, and robustness to unexpected situations are required. Particularly, creating a functional hand prosthesis is a typical challenge in the reconstruction of lost biomechanical function. Nevertheless, currently available control algorithms are in the development phase. The most advanced algorithms for controlling multifunctional prosthesis are machine learning and pattern recognition of myoelectric signals. Despite the increase in computational speed, these methods cannot avoid the requirement of user consciousness and classified separation errors. "Tacit Learning System" is a simple but novel adaptive control strategy that can self-adapt its posture to environment changes. We introduced the strategy in the prosthesis rotation control to achieve compensatory reduction, as well as evaluated the system and its effects on the user. Methods: We conducted a non-randomized study involving eight prosthesis users to perform a bar relocation task with/without Tacit Learning System support. Hand piece and body motions were recorded continuously with goniometers, videos, and a motion-capture system. Findings: Reduction in the participants' upper extremity rotatory compensation motion was monitored during the relocation task in all participants. The estimated profile of total body energy consumption improved in five out of six participants. Interpretation: Our system rapidly accomplished nearly natural motion without unexpected errors. The Tacit Learning System not only adapts human motions but also enhances the human ability to adapt to the system quickly, while the system amplifies compensation generated by the residual limb. The concept can be extended to various situations for reconstructing lost functions that can be compensated.

Gastric myoelectrical activity in patients with inflammatory bowel disease

PubMed Central

Sharma, Purnima; Makharia, Govind; Yadav, Rajeev; Dwivedi, Sada Nand; Deepak, Kishore Kumar

2015-01-01

Aim: Inflammatory bowel disease is characterized by the presence of gastrointestinal motility disturbances; however alterations in the gastric myoelectrical activity have not been characterized. In this study we have recorded the gastric myoelectrical activity in patients with ulcerative colitis (UC) and Crohn's disease (CD) during their clinical remission. Materials and Methods: Gastric activity was assessed using electrogastrography (EGG) in patients with UC (n = 60), CD (n = 40) and healthy controls (n = 40). In each case, their response to water load test, as well as the dominant frequency (DF), dominant power (DP) and the power ratio (PR) of the electrical activity were recorded. Results: In healthy controls, the resting DF was 2.57 ± 1.05 cycles per minute (cpm), which decreased after water ingestion (2.34 ± 0.99 cpm; P = 0.001). Compared to healthy controls, patients with UC had low resting DF (bradygastria) (2.57 ± 1.05 vs. 1.86 ± 1.28 cpm; P = 0.01). The change in DF after water ingestion was insignificant in patients with UC and CD. Post-water ingestion, healthy controls exhibited an increase in the DP as compared to the resting state, (7.1 [2.93, 102.56] vs. 15.94 [3.92, 133.41] µV2; P = 0.02). Patients with UC (1.26 [0.14, 9.83] vs. 3.27 [0.61, 42.12] µV2) and CD (2.54 [0.44, 47.06] vs. 15.8 [0.1, 126.68] µV2) also showed a significant increase in the DP post-water ingestion. Conclusions: Patients with ulcerative colitis have altered resting gastric myoelectrical activity during the remission phase of the disease. PMID:26447103

Sensor fusion and computer vision for context-aware control of a multi degree-of-freedom prosthesis

NASA Astrophysics Data System (ADS)

Markovic, Marko; Dosen, Strahinja; Popovic, Dejan; Graimann, Bernhard; Farina, Dario

2015-12-01

Objective. Myoelectric activity volitionally generated by the user is often used for controlling hand prostheses in order to replicate the synergistic actions of muscles in healthy humans during grasping. Muscle synergies in healthy humans are based on the integration of visual perception, heuristics and proprioception. Here, we demonstrate how sensor fusion that combines artificial vision and proprioceptive information with the high-level processing characteristics of biological systems can be effectively used in transradial prosthesis control. Approach. We developed a novel context- and user-aware prosthesis (CASP) controller integrating computer vision and inertial sensing with myoelectric activity in order to achieve semi-autonomous and reactive control of a prosthetic hand. The presented method semi-automatically provides simultaneous and proportional control of multiple degrees-of-freedom (DOFs), thus decreasing overall physical effort while retaining full user control. The system was compared against the major commercial state-of-the art myoelectric control system in ten able-bodied and one amputee subject. All subjects used transradial prosthesis with an active wrist to grasp objects typically associated with activities of daily living. Main results. The CASP significantly outperformed the myoelectric interface when controlling all of the prosthesis DOF. However, when tested with less complex prosthetic system (smaller number of DOF), the CASP was slower but resulted with reaching motions that contained less compensatory movements. Another important finding is that the CASP system required minimal user adaptation and training. Significance. The CASP constitutes a substantial improvement for the control of multi-DOF prostheses. The application of the CASP will have a significant impact when translated to real-life scenarious, particularly with respect to improving the usability and acceptance of highly complex systems (e.g., full prosthetic arms) by amputees.

Sensor fusion and computer vision for context-aware control of a multi degree-of-freedom prosthesis.

PubMed

Markovic, Marko; Dosen, Strahinja; Popovic, Dejan; Graimann, Bernhard; Farina, Dario

2015-12-01

Myoelectric activity volitionally generated by the user is often used for controlling hand prostheses in order to replicate the synergistic actions of muscles in healthy humans during grasping. Muscle synergies in healthy humans are based on the integration of visual perception, heuristics and proprioception. Here, we demonstrate how sensor fusion that combines artificial vision and proprioceptive information with the high-level processing characteristics of biological systems can be effectively used in transradial prosthesis control. We developed a novel context- and user-aware prosthesis (CASP) controller integrating computer vision and inertial sensing with myoelectric activity in order to achieve semi-autonomous and reactive control of a prosthetic hand. The presented method semi-automatically provides simultaneous and proportional control of multiple degrees-of-freedom (DOFs), thus decreasing overall physical effort while retaining full user control. The system was compared against the major commercial state-of-the art myoelectric control system in ten able-bodied and one amputee subject. All subjects used transradial prosthesis with an active wrist to grasp objects typically associated with activities of daily living. The CASP significantly outperformed the myoelectric interface when controlling all of the prosthesis DOF. However, when tested with less complex prosthetic system (smaller number of DOF), the CASP was slower but resulted with reaching motions that contained less compensatory movements. Another important finding is that the CASP system required minimal user adaptation and training. The CASP constitutes a substantial improvement for the control of multi-DOF prostheses. The application of the CASP will have a significant impact when translated to real-life scenarious, particularly with respect to improving the usability and acceptance of highly complex systems (e.g., full prosthetic arms) by amputees.

Preclinical electrogastrography in experimental pigs

PubMed Central

Květina, Jaroslav; Varayil, Jithinraj Edakkanambeth; Ali, Shahzad Marghoob; Kuneš, Martin; Bureš, Jan; Tachecí, Ilja; Rejchrt, Stanislav; Kopáčová, Marcela

2010-01-01

Surface electrogastrography (EGG) is a non-invasive means of recording gastric myoelectric activity or slow waves from cutaneous leads placed over the stomach. This paper provides a comprehensive review of preclinical EGG. Our group recently set up and worked out the methods for EGG in experimental pigs. We gained our initial experience in the use of EGG in assessment of porcine gastric myoelectric activity after volume challenge and after intragastric administration of itopride and erythromycin. The mean dominant frequency in pigs is comparable with that found in humans. EGG in experimental pigs is feasible. Experimental EGG is an important basis for further preclinical projects in pharmacology and toxicology. PMID:21217873

Abstract and proportional myoelectric control for multi-fingered hand prostheses.

PubMed

Pistohl, Tobias; Cipriani, Christian; Jackson, Andrew; Nazarpour, Kianoush

2013-12-01

Powered hand prostheses with many degrees of freedom are moving from research into the market for prosthetics. In order to make use of the prostheses' full functionality, it is essential to study efficient ways of high dimensional myoelectric control. Human subjects can rapidly learn to employ electromyographic (EMG) activity of several hand and arm muscles to control the position of a cursor on a computer screen, even if the muscle-cursor map contradicts directions in which the muscles would act naturally. But can a similar control scheme be translated into real-time operation of a dexterous robotic hand? We found that despite different degrees of freedom in the effector output, the learning process for controlling a robotic hand was surprisingly similar to that for a virtual two-dimensional cursor. Control signals were derived from the EMG in two different ways, with a linear and a Bayesian filter, to test how stable user intentions could be conveyed through them. Our analysis indicates that without visual feedback, control accuracy benefits from filters that reject high EMG amplitudes. In summary, we conclude that findings on myoelectric control principles, studied in abstract, virtual tasks can be transferred to real-life prosthetic applications.

Development of an Implantable Myoelectric Sensor for Advanced Prosthesis Control

PubMed Central

Merrill, Daniel R.; Lockhart, Joseph; Troyk, Phil R.; Weir, Richard F.; Hankin, David L.

2013-01-01

Modern hand and wrist prostheses afford a high level of mechanical sophistication, but the ability to control them in an intuitive and repeatable manner lags. Commercially available systems using surface electromyographic (EMG) or myoelectric control can supply at best two degrees of freedom (DOF), most often sequentially controlled. This limitation is partially due to the nature of surface-recorded EMG, for which the signal contains components from multiple muscle sources. We report here on the development of an implantable myoelectric sensor using EMG sensors that can be chronically implanted into an amputee’s residual muscles. Because sensing occurs at the source of muscle contraction, a single principal component of EMG is detected by each sensor, corresponding to intent to move a particular effector. This system can potentially provide independent signal sources for control of individual effectors within a limb prosthesis. The use of implanted devices supports inter-day signal repeatability. We report on efforts in preparation for human clinical trials, including animal testing, and a first-in-human proof of principle demonstration where the subject was able to intuitively and simultaneously control two DOF in a hand and wrist prosthesis. PMID:21371058

Face recognition system and method using face pattern words and face pattern bytes

DOEpatents

Zheng, Yufeng

2014-12-23

The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

Pattern Recognition Using Artificial Neural Network: A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, artificial neural network techniques theory have been receiving increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes, sensing environment, pattern representation, feature extraction and selection, cluster analysis, classifier design and learning, selection of training and test samples, and performance evaluation. In spite of almost 50 years of research and development in this field, the general problem of recognizing complex patterns with arbitrary orientation, location, and scale remains unsolved. New and emerging applications, such as data mining, web searching, retrieval of multimedia data, face recognition, and cursive handwriting recognition, require robust and efficient pattern recognition techniques. The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system using ANN and identify research topics and applications which are at the forefront of this exciting and challenging field.

A Novel Percutaneous Electrode Implant for Improving Robustness in Advanced Myoelectric Control

PubMed Central

Hahne, Janne M.; Farina, Dario; Jiang, Ning; Liebetanz, David

2016-01-01

Despite several decades of research, electrically powered hand and arm prostheses are still controlled with very simple algorithms that process the surface electromyogram (EMG) of remnant muscles to achieve control of one prosthetic function at a time. More advanced machine learning methods have shown promising results under laboratory conditions. However, limited robustness has largely prevented the transfer of these laboratory advances to clinical applications. In this paper, we introduce a novel percutaneous EMG electrode to be implanted chronically with the aim of improving the reliability of EMG detection in myoelectric control. The proposed electrode requires a minimally invasive procedure for its implantation, similar to a cosmetic micro-dermal implant. Moreover, being percutaneous, it does not require power and data telemetry modules. Four of these electrodes were chronically implanted in the forearm of an able-bodied human volunteer for testing their characteristics. The implants showed significantly lower impedance and greater robustness against mechanical interference than traditional surface EMG electrodes used for myoelectric control. Moreover, the EMG signals detected by the proposed systems allowed more stable control performance across sessions in different days than that achieved with classic EMG electrodes. In conclusion, the proposed implants may be a promising interface for clinically available prostheses. PMID:27065783

Auditory Pattern Recognition and Brief Tone Discrimination of Children with Reading Disorders

ERIC Educational Resources Information Center

Walker, Marianna M.; Givens, Gregg D.; Cranford, Jerry L.; Holbert, Don; Walker, Letitia

2006-01-01

Auditory pattern recognition skills in children with reading disorders were investigated using perceptual tests involving discrimination of frequency and duration tonal patterns. A behavioral test battery involving recognition of the pattern of presentation of tone triads was used in which individual components differed in either frequency or…

Image pattern recognition supporting interactive analysis and graphical visualization

NASA Technical Reports Server (NTRS)

Coggins, James M.

1992-01-01

Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis.

Understanding eye movements in face recognition using hidden Markov models.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2014-09-16

We use a hidden Markov model (HMM) based approach to analyze eye movement data in face recognition. HMMs are statistical models that are specialized in handling time-series data. We conducted a face recognition task with Asian participants, and model each participant's eye movement pattern with an HMM, which summarized the participant's scan paths in face recognition with both regions of interest and the transition probabilities among them. By clustering these HMMs, we showed that participants' eye movements could be categorized into holistic or analytic patterns, demonstrating significant individual differences even within the same culture. Participants with the analytic pattern had longer response times, but did not differ significantly in recognition accuracy from those with the holistic pattern. We also found that correct and wrong recognitions were associated with distinctive eye movement patterns; the difference between the two patterns lies in the transitions rather than locations of the fixations alone. © 2014 ARVO.

Can We Achieve Intuitive Prosthetic Elbow Control Based on Healthy Upper Limb Motor Strategies?

PubMed Central

Merad, Manelle; de Montalivet, Étienne; Touillet, Amélie; Martinet, Noël; Roby-Brami, Agnès; Jarrassé, Nathanaël

2018-01-01

Most transhumeral amputees report that their prosthetic device lacks functionality, citing the control strategy as a major limitation. Indeed, they are required to control several degrees of freedom with muscle groups primarily used for elbow actuation. As a result, most of them choose to have a one-degree-of-freedom myoelectric hand for grasping objects, a myoelectric wrist for pronation/supination, and a body-powered elbow. Unlike healthy upper limb movements, the prosthetic elbow joint angle, adjusted prior to the motion, is not involved in the overall upper limb movements, causing the rest of the body to compensate for the lack of mobility of the prosthesis. A promising solution to improve upper limb prosthesis control exploits the residual limb mobility: like in healthy movements, shoulder and prosthetic elbow motions are coupled using inter-joint coordination models. The present study aims to test this approach. A transhumeral amputated individual used a prosthesis with a residual limb motion-driven elbow to point at targets. The prosthetic elbow motion was derived from IMU-based shoulder measurements and a generic model of inter-joint coordinations built from healthy individuals data. For comparison, the participant also performed the task while the prosthetic elbow was implemented with his own myoelectric control strategy. The results show that although the transhumeral amputated participant achieved the pointing task with a better precision when the elbow was myoelectrically-controlled, he had to develop large compensatory trunk movements. Automatic elbow control reduced trunk displacements, and enabled a more natural body behavior with synchronous shoulder and elbow motions. However, due to socket impairments, the residual limb amplitudes were not as large as those of healthy shoulder movements. Therefore, this work also investigates if a control strategy whereby prosthetic joints are automatized according to healthy individuals' coordination models can lead to an intuitive and natural prosthetic control. PMID:29456499

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mojaverian, P.; Ferguson, R.K.; Vlasses, P.H.

In animal and human studies, the gastric emptying of large (greater than 1 mm) indigestible solids is due to the activity of the interdigestive migrating myoelectric complex. The gastric residence time (GRT) of an orally administered, nondigestible, pH-sensitive, radiotelemetric device (Heidelberg capsule) was evaluated in three studies in healthy volunteers. In 6 subjects, the GRT of the Heidelberg capsule was compared with the half-emptying time (t1/2) of diethylenetriaminepentaacetic acid labeled with technetium 99m after a 4-ml/kg liquid fatty meal. The mean (+/-SD) GRT (4.3 +/- 1.4 h) was significantly (p less than 0.001) longer than the mean t1/2 (1.1 +/-more » 0.3 h); the GRT was prolonged compared with the t1/2 in each subject. In a randomized, crossover trial in 10 subjects, frequent feeding caused a dramatic prolongation in mean GRT of the capsule compared with the fasting state (greater than 14.5 vs. 0.5 h, p less than 0.005). In another crossover study in 6 subjects, the GRT of the capsule was evaluated after an overnight fast, a standard breakfast including solid food, and a liquid meal (i.e., 200 ml of diluted light cream). The mean GRT was 2.6 +/- 0.9 h after the liquid meal vs. 1.2 +/- 0.8 h after fasting (p less than 0.025). The mean GRT after the breakfast was 4.8 +/- 1.5 h, which was significantly greater than that after fasting (p less than 0.001) and after the liquid meal (p less than 0.01). These data suggest that the GRT of the Heidelberg capsule is a marker of the interdigestive migrating myoelectric complex in humans, the interdigestive migrating myoelectric complex can be markedly delayed by frequent feedings with solids, and the interdigestive migrating myoelectric complex is delayed by both liquid and solid meals.« less

Pattern activation/recognition theory of mind

PubMed Central

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a “Pattern Recognition Theory of Mind” that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call “Pattern Activation/Recognition Theory of Mind.” While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

Pattern activation/recognition theory of mind.

PubMed

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

A control system for a powered prosthesis using positional and myoelectric inputs from the shoulder complex.

PubMed

Losier, Y; Englehart, K; Hudgins, B

2007-01-01

The integration of multiple input sources within a control strategy for powered upper limb prostheses could provide smoother, more intuitive multi-joint reaching movements based on the user's intended motion. The work presented in this paper presents the results of using myoelectric signals (MES) of the shoulder area in combination with the position of the shoulder as input sources to multiple linear discriminant analysis classifiers. Such an approach may provide users with control signals capable of controlling three degrees of freedom (DOF). This work is another important step in the development of hybrid systems that will enable simultaneous control of multiple degrees of freedom used for reaching tasks in a prosthetic limb.

Research, design & development project Myoelectric Prosthesis of Upper Limb

NASA Astrophysics Data System (ADS)

Galiano, L.; Montaner, E.; Flecha, A.

2007-11-01

A Research Design and Development Project was developed of a myoelectric prosthesis for a pediatric patient presenting congenital amputation of the left forearm below the elbow. A multidisciplinary work-team was formed for this goal, in order to solve the several (/various) aspects regarding this project (mechanical, ergonomics, electronics, physical). The prosthesis as an electromechanical device was divided in several blocks, trying to achieve a focused development for each stage, acording to requisites. A mechanical prototype of the prothesis was designed and built along with the circuitry needed for EMG aquisition, control logic and drivers. Having acomplished the previuos stages, the project is now dealing with the definitions of the interface between the prosthesis and the patient, with promising perspectives.

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Editor)

1988-01-01

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

PubMed Central

Swartz, R. Andrew

2013-01-01

This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate. PMID:24191136

A Method for Recognizing State of Finger Flexure and Extension

NASA Astrophysics Data System (ADS)

Terado, Toshihiko; Fujiwara, Osamu

In our country, the handicapped and the elderly people in bed increase rapidly. In the bedridden person’s daily life, there may be limitations in the physical movement and the means of mutual communication. For the support of their comfortable daily lives, therefore, the development of human interface equipment becomes an important task. The equipment of this kind is being already developed by means of laser beam, eye-tracking, breathing motion and myo-electric signals, while the attachment and handling are normally not so easy. In this study, paying attention to finger motion, we have developed human interface equipment easily attached to the body, which enables one to measure the finger flexure and extension for mutual communication. The state of finger flexure and extension is identified by a threshold level analysis from the 3D-locus data for the finger movement, which can be measured through the infrared rays from the LED markers attached to a glove with the previously developed prototype system. We then have confirmed from an experiment that nearly 100% recognition for the finger movement can be achieved.

Recognition of hand movements in a trans-radial amputated subject by sEMG.

PubMed

Atzori, Manfredo; Muller, Henning; Baechler, Micheal

2013-06-01

Trans-radially amputated persons who own a myoelectric prosthesis have currently some control via surface electromyography (sEMG). However, the control systems are still limited (as they include very few movements) and not always natural (as the subject has to learn to associate movements of the muscles with the movements of the prosthesis). The Ninapro project tries helping the scientific community to overcome these limits through the creation of electromyography data sources to test machine learning algorithms. In this paper the results gained from first tests made on an amputated subject with the Ninapro acquisition protocol are detailed. In agreement with neurological studies on cortical plasticity and on the anatomy of the forearm, the amputee produced stable signals for each movement in the test. Using a k-NN classification algorithm, we obtain an average classification rate of 61.5% on all 53 movements. Successively, we simplify the task reducing the number of movements to 13, resulting in no misclassified movements. This shows that for fewer movements a very high classification accuracy is possible without the subject having to learn the movements specifically.

Advanced optical correlation and digital methods for pattern matching—50th anniversary of Vander Lugt matched filter

NASA Astrophysics Data System (ADS)

Millán, María S.

2012-10-01

On the verge of the 50th anniversary of Vander Lugt’s formulation for pattern matching based on matched filtering and optical correlation, we acknowledge the very intense research activity developed in the field of correlation-based pattern recognition during this period of time. The paper reviews some domains that appeared as emerging fields in the last years of the 20th century and have been developed later on in the 21st century. Such is the case of three-dimensional (3D) object recognition, biometric pattern matching, optical security and hybrid optical-digital processors. 3D object recognition is a challenging case of multidimensional image recognition because of its implications in the recognition of real-world objects independent of their perspective. Biometric recognition is essentially pattern recognition for which the personal identification is based on the authentication of a specific physiological characteristic possessed by the subject (e.g. fingerprint, face, iris, retina, and multifactor combinations). Biometric recognition often appears combined with encryption-decryption processes to secure information. The optical implementations of correlation-based pattern recognition processes still rely on the 4f-correlator, the joint transform correlator, or some of their variants. But the many applications developed in the field have been pushing the systems for a continuous improvement of their architectures and algorithms, thus leading towards merged optical-digital solutions.

Robust autoassociative memory with coupled networks of Kuramoto-type oscillators

NASA Astrophysics Data System (ADS)

Heger, Daniel; Krischer, Katharina

2016-08-01

Uncertain recognition success, unfavorable scaling of connection complexity, or dependence on complex external input impair the usefulness of current oscillatory neural networks for pattern recognition or restrict technical realizations to small networks. We propose a network architecture of coupled oscillators for pattern recognition which shows none of the mentioned flaws. Furthermore we illustrate the recognition process with simulation results and analyze the dynamics analytically: Possible output patterns are isolated attractors of the system. Additionally, simple criteria for recognition success are derived from a lower bound on the basins of attraction.

[Effect of atropine on the enhancing action of Fructus Aurantii Immaturus on the myoelectric activity of small intestine in dogs].

PubMed

Huang, Z H; Yang, D Z; Wei, Y Q

1996-05-01

Effect of Fructus Aurantii Immaturus (FAI) was observed by using the computerized electrophysiologic method with the interdigestive myoelectric complex (IDMEC) as criterion. 100% FAI was given to the healthy, awakened and fasting dogs by gastrogavage and as soon as the effect on electric activity of small intestine appeared, atropine was injected. Results showed that the enhancing effect of FAI could be inhibited significantly by atropine, an antagonist of cholinergic receptor. It revealed that although the duration of phase II and general cycle were prolonged, but the spike burst per cluster in the duration between phase II and phase III as well as that per minute were decreased. It suggested the effect of FAI might be relevant with muscarinic receptor.

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

NASA Astrophysics Data System (ADS)

Acciarri, R.; Adams, C.; An, R.; Anthony, J.; Asaadi, J.; Auger, M.; Bagby, L.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fadeeva, A. A.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; Hourlier, A.; Huang, E.-C.; James, C.; Jan de Vries, J.; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; Rudolf von Rohr, C.; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yates, L.; Zeller, G. P.; Zennamo, J.; Zhang, C.

2018-01-01

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.

The Pandora multi-algorithm approach to automated pattern recognition in LAr TPC detectors

NASA Astrophysics Data System (ADS)

Marshall, J. S.; Blake, A. S. T.; Thomson, M. A.; Escudero, L.; de Vries, J.; Weston, J.; MicroBooNE Collaboration

2017-09-01

The development and operation of Liquid Argon Time Projection Chambers (LAr TPCs) for neutrino physics has created a need for new approaches to pattern recognition, in order to fully exploit the superb imaging capabilities offered by this technology. The Pandora Software Development Kit provides functionality to aid the process of designing, implementing and running pattern recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition: individual algorithms each address a specific task in a particular topology; a series of many tens of algorithms then carefully builds-up a picture of the event. The input to the Pandora pattern recognition is a list of 2D Hits. The output from the chain of over 70 algorithms is a hierarchy of reconstructed 3D Particles, each with an identified particle type, vertex and direction.

Real Time Large Memory Optical Pattern Recognition.

DTIC Science & Technology

1984-06-01

AD-Ri58 023 REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION(U) - h ARMY MISSILE COMMAND REDSTONE ARSENAL AL RESEARCH DIRECTORATE D A GREGORY JUN...TECHNICAL REPORT RR-84-9 Ln REAL TIME LARGE MEMORY OPTICAL PATTERN RECOGNITION Don A. Gregory Research Directorate US Army Missile Laboratory JUNE 1984 L...RR-84-9 , ___/_ _ __ _ __ _ __ _ __"__ _ 4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED Real Time Large Memory Optical Pattern Technical

Classification and machine recognition of severe weather patterns

NASA Technical Reports Server (NTRS)

Wang, P. P.; Burns, R. C.

1976-01-01

Forecasting and warning of severe weather conditions are treated from the vantage point of pattern recognition by machine. Pictorial patterns and waveform patterns are distinguished. Time series data on sferics are dealt with by considering waveform patterns. A severe storm patterns recognition machine is described, along with schemes for detection via cross-correlation of time series (same channel or different channels). Syntactic and decision-theoretic approaches to feature extraction are discussed. Active and decayed tornados and thunderstorms, lightning discharges, and funnels and their related time series data are studied.

Fuzzy Logic-Based Audio Pattern Recognition

NASA Astrophysics Data System (ADS)

Malcangi, M.

2008-11-01

Audio and audio-pattern recognition is becoming one of the most important technologies to automatically control embedded systems. Fuzzy logic may be the most important enabling methodology due to its ability to rapidly and economically model such application. An audio and audio-pattern recognition engine based on fuzzy logic has been developed for use in very low-cost and deeply embedded systems to automate human-to-machine and machine-to-machine interaction. This engine consists of simple digital signal-processing algorithms for feature extraction and normalization, and a set of pattern-recognition rules manually tuned or automatically tuned by a self-learning process.

New Optical Transforms For Statistical Image Recognition

NASA Astrophysics Data System (ADS)

Lee, Sing H.

1983-12-01

In optical implementation of statistical image recognition, new optical transforms on large images for real-time recognition are of special interest. Several important linear transformations frequently used in statistical pattern recognition have now been optically implemented, including the Karhunen-Loeve transform (KLT), the Fukunaga-Koontz transform (FKT) and the least-squares linear mapping technique (LSLMT).1-3 The KLT performs principle components analysis on one class of patterns for feature extraction. The FKT performs feature extraction for separating two classes of patterns. The LSLMT separates multiple classes of patterns by maximizing the interclass differences and minimizing the intraclass variations.

Optimal pattern synthesis for speech recognition based on principal component analysis

NASA Astrophysics Data System (ADS)

Korsun, O. N.; Poliyev, A. V.

2018-02-01

The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

Myoelectric Response of Back Muscles to Vertical Random Whole-Body Vibration with Different Magnitudes at Different Postures

NASA Astrophysics Data System (ADS)

BLÜTHNER, R.; SEIDEL, H.; HINZ, B.

2002-05-01

Back muscle forces contribute essentially to the whole-body vibration-induced spinal load. The electromyogram (EMG) can help to estimate these forces during whole-body vibration (WBV). Thirty-eight subjects were exposed to identical random low-frequency WBV (0·7, 1·0 and 1·4 m/s-2 r.m.s. weighted acceleration) at a relaxed, erect and bent forward postures. The acceleration of the seat and the force between the seat and the buttocks were measured. Six EMGs were derived from the right side of the m. trapezius pars descendens, m. ileocostalis lumborum pars thoracis, m. ileocostalis lumborum pars lumborum; m. longissimus thoracis pars thoracis, m. longissimus thoracis pars lumborum, and lumbar multifidus muscle. All data were filtered for anti-aliasing and sampled with 1000 Hz. Artefacts caused by the ECG in the EMG were identified and eliminated in the time domain using wavelets. The individually rectified and normalized EMGs were averaged across subjects. The EMGs without WBV exhibited characteristic patterns for the three postures examined. The coherence and transfer functions indicated characteristic myoelectric responses to random WBV with several effects of posture and WBV magnitude. A comprehensive set of transfer functions from the seat acceleration or the mean normalized input force to the mean processed EMG was presented.The results can be used for the development of more sophisticated models with a separate control of various back muscle groups. However, the EMG-force relationship under dynamic conditions needs to be examined in more detail before the results can be implemented. Since different reflex mechanisms depending on the frequency of WBV are linked with different types of active muscle fibres, various time delays between the EMG and muscle force may be necessary.

Effects of taste stimulation on gastric myoelectrical activity and autonomic balance.

PubMed

Waluga, Marek; Jonderko, Krzysztof; Domosławska, Ewelina; Matwiejszyn, Anna; Dzielicki, Marek; Krusiec-Świdergoł, Beata; Kasicka-Jonderko, Anna

2018-01-01

Sham feeding, reproducing the cephalic phase of digestion, and involving combined visual, olfactory, and taste stimulation affects gastrointestinal motility and secretory functions of the digestive system, as well as the sympathetic/parasympathetic balance (SPB). In this study, we aimed to check if taste stimulation with a single flavor affects the gastric myoelectrical activity (GMA) and/or SPB. Eighteen healthy volunteers underwent, on four separate days, 30-min electrogastrographic and electrocardiographic recordings: basal, with stimulation - while keeping in the mouth an agar cube with taste-delivering substance, and postexposure. Concentrations of saccharose, NaCl, citric acid, and quinine hydrochloride within the cubes were adjusted to 100-fold the individual taste recognition thresholds. SPB was determined from the heart rate variability (HRV) analysis of the recorded electrocardiograms. A moderate but statistically significant increase in tachygastria and bradygastria percentage time share was observed, regardless of the type of taste applied. Bitter taste elicited a considerable decrease in the normogastria time share (from 82.8 ± 2.5% to 73.5 ± 3.5%, P = 0.00076) and a diminution of the dominant frequency (from 3.07 ± 0.08 to 2.90 ± 0.10 cycles per minute (cpm) postexposure, P = 0.01). Sour taste brought about a drop of the dominant power (from 42.5 ± 1.1 to 40.1 ± 1.4 dB, P = 0.0015). Two tastes hindered propagation of the gastric slow waves - the average percentage of slow wave coupling decreased from 77.9 ± 3.1% to 69.5 ± 3.1% (P = 0.0078) and from 74.6 ± 2.5% to 68.2 ± 2.8% (P = 0.0054) with the bitter and the salty taste, respectively. Stimulation with sweet, salty, or sour taste evoked a significant decrease in the high frequency component of the HRV, whereas bitter taste did not affect the SPB. Oral stimulation with tastes subjectively perceived as unpleasant brings about disturbances of the interdigestive GMA. This, however, does not coincide with its effect upon SPB.

Effects of noxious stimulation and pain expectations on neuromuscular control of the spine in patients with chronic low back pain.

PubMed

Henchoz, Yves; Tétreau, Charles; Abboud, Jacques; Piché, Mathieu; Descarreaux, Martin

2013-10-01

Alterations of the neuromuscular control of the lumbar spine have been reported in patients with chronic low back pain (LBP). During trunk flexion and extension tasks, the reduced myoelectric activity of the low back extensor musculature observed during full trunk flexion is typically absent in patients with chronic LBP. To determine whether pain expectations could modulate neuromuscular responses to experimental LBP to a higher extent in patients with chronic LBP compared with controls. A cross-sectional, case-control study. Twenty-two patients with nonspecific chronic LBP and 22 age- and sex-matched control participants. Trunk flexion-extension tasks were performed under three experimental conditions: innocuous heat, noxious stimulation with low pain expectation, and noxious stimulation with high pain expectation. Noxious stimulations were delivered using a contact heat thermode applied on the skin of the lumbar region (L4-L5), whereas low or high pain expectations were induced by verbal and visual instructions. Surface electromyography of erector spinae at L2-L3 and L4-L5, as well as lumbopelvic kinematic variables were collected during the tasks. Pain was evaluated using a numerical rating scale. Pain catastrophizing, disability, anxiety, and fear-avoidance beliefs were measured using validated questionnaires. Two-way mixed analysis of variance revealed that pain was significantly different among the three experimental conditions (F2,84=317.5; p<.001). Increased myoelectric activity of the low back extensor musculature during full trunk flexion was observed in the high compared with low pain expectations condition at the L2-L3 level (F2,84=9.5; p<.001) and at the L4-L5 level (F2,84=3.7; p=.030). At the L4-L5 level, this effect was significantly more pronounced for the control participants compared with patients with chronic LBP (F2,84=3.4; p=.045). Pearson correlation analysis revealed that increased lumbar muscle activity in full flexion induced by expectations was associated with higher pain catastrophizing in patients with chronic LBP (r=0.54; p=.012). Repeated exposure to pain appears to generate rigid and less variable patterns of muscle activation in patients with chronic LBP, which attenuate their response to pain expectations. Patients with high levels of pain catastrophizing show higher myoelectric activity of lumbar muscles in full flexion and exhibit greater neuromechanical changes when expecting strong pain. Copyright © 2013 Elsevier Inc. All rights reserved.

The Need for Careful Data Collection for Pattern Recognition in Digital Pathology.

PubMed

Marée, Raphaël

2017-01-01

Effective pattern recognition requires carefully designed ground-truth datasets. In this technical note, we first summarize potential data collection issues in digital pathology and then propose guidelines to build more realistic ground-truth datasets and to control their quality. We hope our comments will foster the effective application of pattern recognition approaches in digital pathology.

Pattern recognition: A basis for remote sensing data analysis

NASA Technical Reports Server (NTRS)

Swain, P. H.

1973-01-01

The theoretical basis for the pattern-recognition-oriented algorithms used in the multispectral data analysis software system is discussed. A model of a general pattern recognition system is presented. The receptor or sensor is usually a multispectral scanner. For each ground resolution element the receptor produces n numbers or measurements corresponding to the n channels of the scanner.

Optical Pattern Recognition With Self-Amplification

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1994-01-01

In optical pattern recognition system with self-amplification, no reference beam used in addressing mode. Polarization of laser beam and orientation of photorefractive crystal chosen to maximize photorefractive effect. Intensity of recognition signal is orders of magnitude greater than other optical correlators. Apparatus regarded as real-time or quasi-real-time optical pattern recognizer with memory and reprogrammability.

Sonar Recognition Training: An Investigation of Whole VS. Part and Analytic VS. Synthetic Procedures.

ERIC Educational Resources Information Center

Annett, John

An experienced person, in such tasks as sonar detection and recognition, has a considerable superiority over a machine recognition system in auditory pattern recognition. However, people require extensive exposure to auditory patterns before achieving a high level of performance. In an attempt to discover a method of training people to recognize…

Degraded character recognition based on gradient pattern

NASA Astrophysics Data System (ADS)

Babu, D. R. Ramesh; Ravishankar, M.; Kumar, Manish; Wadera, Kevin; Raj, Aakash

2010-02-01

Degraded character recognition is a challenging problem in the field of Optical Character Recognition (OCR). The performance of an optical character recognition depends upon printed quality of the input documents. Many OCRs have been designed which correctly identifies the fine printed documents. But, very few reported work has been found on the recognition of the degraded documents. The efficiency of the OCRs system decreases if the input image is degraded. In this paper, a novel approach based on gradient pattern for recognizing degraded printed character is proposed. The approach makes use of gradient pattern of an individual character for recognition. Experiments were conducted on character image that is either digitally written or a degraded character extracted from historical documents and the results are found to be satisfactory.

Automatic Target Recognition Based on Cross-Plot

PubMed Central

Wong, Kelvin Kian Loong; Abbott, Derek

2011-01-01

Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository. PMID:21980508

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Acciarri, R.; Adams, C.; An, R.

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens ofmore » algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.« less

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

DOE PAGES

Acciarri, R.; Adams, C.; An, R.; ...

2018-01-29

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens ofmore » algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.« less

Mechanisms and neural basis of object and pattern recognition: a study with chess experts.

PubMed

Bilalić, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-11-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and novices performing chess-related and -unrelated (visual) search tasks. As expected, the superiority of experts was limited to the chess-specific task, as there were no differences in a control task that used the same chess stimuli but did not require chess-specific recognition. The analysis of eye movements showed that experts immediately and exclusively focused on the relevant aspects in the chess task, whereas novices also examined irrelevant aspects. With random chess positions, when pattern knowledge could not be used to guide perception, experts nevertheless maintained an advantage. Experts' superior domain-specific parafoveal vision, a consequence of their knowledge about individual domain-specific symbols, enabled improved object recognition. Functional magnetic resonance imaging corroborated this differentiation between object and pattern recognition and showed that chess-specific object recognition was accompanied by bilateral activation of the occipitotemporal junction, whereas chess-specific pattern recognition was related to bilateral activations in the middle part of the collateral sulci. Using the expertise approach together with carefully chosen controls and multiple dependent measures, we identified object and pattern recognition as two essential cognitive processes in expert visual cognition, which may also help to explain the mechanisms of everyday perception.

Finger Vein Recognition Based on Local Directional Code

PubMed Central

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-01-01

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP. PMID:23202194

Finger vein recognition based on local directional code.

PubMed

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-11-05

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP.

Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition.

PubMed

Ming, Yue; Wang, Guangchao; Fan, Chunxiao

2015-01-01

With the rapid development of 3D somatosensory technology, human behavior recognition has become an important research field. Human behavior feature analysis has evolved from traditional 2D features to 3D features. In order to improve the performance of human activity recognition, a human behavior recognition method is proposed, which is based on a hybrid texture-edge local pattern coding feature extraction and integration of RGB and depth videos information. The paper mainly focuses on background subtraction on RGB and depth video sequences of behaviors, extracting and integrating historical images of the behavior outlines, feature extraction and classification. The new method of 3D human behavior recognition has achieved the rapid and efficient recognition of behavior videos. A large number of experiments show that the proposed method has faster speed and higher recognition rate. The recognition method has good robustness for different environmental colors, lightings and other factors. Meanwhile, the feature of mixed texture-edge uniform local binary pattern can be used in most 3D behavior recognition.

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Influence of Blurred Ways on Pattern Recognition of a Scale-Free Hopfield Neural Network

NASA Astrophysics Data System (ADS)

Chang, Wen-Li

2010-01-01

We investigate the influence of blurred ways on pattern recognition of a Barabási-Albert scale-free Hopfield neural network (SFHN) with a small amount of errors. Pattern recognition is an important function of information processing in brain. Due to heterogeneous degree of scale-free network, different blurred ways have different influences on pattern recognition with same errors. Simulation shows that among partial recognition, the larger loading ratio (the number of patterns to average degree P/langlekrangle) is, the smaller the overlap of SFHN is. The influence of directed (large) way is largest and the directed (small) way is smallest while random way is intermediate between them. Under the ratio of the numbers of stored patterns to the size of the network P/N is less than 0. 1 conditions, there are three families curves of the overlap corresponding to directed (small), random and directed (large) blurred ways of patterns and these curves are not associated with the size of network and the number of patterns. This phenomenon only occurs in the SFHN. These conclusions are benefit for understanding the relation between neural network structure and brain function.

Rehand: Realistic electric prosthetic hand created with a 3D printer.

PubMed

Yoshikawa, Masahiro; Sato, Ryo; Higashihara, Takanori; Ogasawara, Tsukasa; Kawashima, Noritaka

2015-01-01

Myoelectric prosthetic hands provide an appearance with five fingers and a grasping function to forearm amputees. However, they have problems in weight, appearance, and cost. This paper reports on the Rehand, a realistic electric prosthetic hand created with a 3D printer. It provides a realistic appearance that is same as the cosmetic prosthetic hand and a grasping function. A simple link mechanism with one linear actuator for grasping and 3D printed parts achieve low cost, light weight, and ease of maintenance. An operating system based on a distance sensor provides a natural operability equivalent to the myoelectric control system. A supporter socket allows them to wear the prosthetic hand easily. An evaluation using the Southampton Hand Assessment Procedure (SHAP) demonstrated that an amputee was able to operate various objects and do everyday activities with the Rehand.

Development of myoelectric control type speaking valve with low flow resistance

NASA Astrophysics Data System (ADS)

Ooe, Katsutoshi; Sakurai, Kohei; Mimaki, Shinya

2015-12-01

We aimed to develop welfare devices for patients with phonation disorder. One of these devices is the electrical controltype speaking valve system. The conventional speaking valves have one-way valve architecture, they open when the user breathes in, and they close when user breathes out and produce voices. This type is very simple and tough, but some users feel closeness in case of exhalation without phonation. This problem is caused by its mechanism what can not be controlled by user's will. Therefore, we proposed an electrical control-type speaking valve system to resolve this problem. This valve is controlled by neck myoelectric signal of sternohyoid muscle. From our previous report, it was clarified that this valve had better performance about easy-to-breath. Furthermore, we proposed the compact myoelectric control-type speaking valve system. The new-type speaking valve was enough small to attach the human body, and its opening area is larger than that of conventional one. Additionally, we described the improvement of flow channel shape by using of FEM analysis. According to the result of the analysis, it was clarified that the shape-improved speaking valve gets the low flow resistance channel in case of inspiration. In this report, we tried to make the flow resistance lower by the shape of current plates, in case of both inspiration and exhalation. From the result of FEM analysis, our speaking valve could get better flow channel than older one.

Use of multichannel electrogastrography for noninvasive assessment of gastric myoelectrical activity in dogs.

PubMed

Koenig, Judith B; Martin, Christina E W; Dobson, Howard; Mintchev, Martin P

2009-01-01

To evaluate whether changes in gastric myoelectrical activity in healthy, awake dogs can be detected via multichannel electrogastrography (EGG). 6 healthy hound-breed dogs. For each dog, 8-channel EGG was performed after food had been withheld for 12 hours and at 30 minutes after subsequent feeding; 60 minutes after feeding, atropine (0.04 mg/kg) was administered IM to induce ileus, and 30 minutes later, EGG was again performed. Mean cycles per minute (cpm) values of the dominant frequency (a measure of the rhythmicity of gastric electrical activity) and mean power ratios (ie, power measured after treatment divided by the power measured when food was withheld) were calculated. Motility of the gastric antrum was assessed via B-mode ultrasonography during the same phases; contractions determined ultrasonographically were correlated with EGG power for each channel in each phase. The criterion for stability (SD of the dominant frequency < 15% of the cpm value in at least 3 of the 8 EGG channels) was met in 4 of the 6 dogs (only in long-distance channels). The mean power ratios were significantly higher in the postprandial phase than in the ileus phase. Compared with the postprandial phase, significantly fewer contractions per minute were evident ultrasonographically in the ileus and food-withholding phases. There was a significant and good correlation between EGG power and ultrasonographic findings in all 8 channels. Electrogastrography may be useful in assessing gastric myoelectrical activities in awake dogs with naturally occurring gastrointestinal disease, including gastric dilatation-volvulus.

The effect of Strongylus vulgaris larvae on equine intestinal myoelectrical activity.

PubMed

Lester, G D; Bolton, J R; Cambridge, H; Thurgate, S

1989-06-01

The myoelectrical activity of the ileum, caecum and large colon was monitored from Ag-AgCl bipolar recording electrodes in four conscious 'parasite-naive' weanling foals. All foals were inoculated with 1000 infective 3rd-stage Strongylus vulgaris larvae and alterations to the myoelectrical activity observed. The frequencies of caecal and colonic spike bursts increased significantly in all post infection periods coinciding with assumed larval penetration into the intestinal mucosa and migration through the vasculature. Peaks in caecal and colonic activity occurred at Days 1 to 5 post infection. In the caecum, peaks occurred again at Days 15 and 31 post infection, preceding similar rises in colonic spike burst frequency at Days 19 and 35. Longer term changes indicated a return towards pre-infection levels of activity suggesting smooth muscle adaptation to decreased blood flow. The analysis of caecal and colonic spike burst propagation indicated that the increases in burst frequency were not attributable to an increase in the propagation of spike bursts in any particular direction, but rather to proportional increases in all directions of activity. There was a slight decrease in the simple ileal spike burst frequency immediately post-infection. None of the experimental animals exhibited signs of abdominal pain during the trial, and there was no evidence of bowel infarction at post mortem examination despite the presence of severe parasite-induced arterial lesions. The results suggest that increased caecal and colonic motility is an important host response in susceptible foals exposed to S. vulgaris larvae.

Development of PDMS-based flexible dry type SEMG electrodes by micromachining technologies

NASA Astrophysics Data System (ADS)

Jung, Jung Mo; Cha, Doo Yeol; Kim, Deok Su; Yang, Hee Jun; Choi, Kyo Sang; Choi, Jong Myoung; Chang, Sung Pil

2014-09-01

The authors developed PDMS (polydimethylsiloxane)-based dry type surface electromyography (SEMG) electrodes for myoelectric prosthetic hands. The SEMG electrodes were strongly recommended to be fabricated on a flexible substrate to be compatible with the surface of skin. In this study, the authors designed a bar-shaped dry-type flexible SEMG electrodes comprised of two input electrodes and a reference electrode on a flexible PDMS substrate to measure EMG signals. The space distance between each electrode with a size of 10 mm × 2 mm was chosen to 18 mm to get optimal result according to the simulation result with taking into consideration the conduction velocity and the median frequency of EMG signals. Raw EMG signals were measured from Brachioradialis, Biceps brachii, deltoideus, and pectoralis major muscles, to drive the application of the myoelectric hand prosthesis. Measured raw EMG signals were transformed to root mean square (RMS) EMG signals using Acqknowledge4.2. The experimental peak voltage values of RMS EMG signals from Brachioradialis, Biceps brachii, deltoideus, and pectoralis major muscles were 2.96 V, 4.45 V, 1.74 V, and 2.62 V, respectively. Values from the dry type flexible SEMG electrodes showed higher peak values than a commercially available wet type Ag-AgCl electrode. The study shows that the PDMS-based flexible electrode devised for measuring myoelectric signals from the surface of skin is more useful for prosthetic hands because of its greater sensitivity and flexibility.

The use of targeted muscle reinnervation for improved myoelectric prosthesis control in a bilateral shoulder disarticulation amputee.

PubMed

Kuiken, T A; Dumanian, G A; Lipschutz, R D; Miller, L A; Stubblefield, K A

2004-12-01

A novel method for the control of a myoelectric upper limb prosthesis was achieved in a patient with bilateral amputations at the shoulder disarticulation level. Four independently controlled nerve-muscle units were created by surgically anastomosing residual brachial plexus nerves to dissected and divided aspects of the pectoralis major and minor muscles. The musculocutaneous nerve was anastomosed to the upper pectoralis major; the median nerve was transferred to the middle pectoralis major region; the radial nerve was anastomosed to the lower pectoralis major region; and the ulnar nerve was transferred to the pectoralis minor muscle which was moved out to the lateral chest wall. After five months, three nerve-muscle units were successful (the musculocutaneous, median and radial nerves) in that a contraction could be seen, felt and a surface electromyogram (EMG) could be recorded. Sensory reinnervation also occurred on the chest in an area where the subcutaneous fat was removed. The patient was fitted with a new myoelectric prosthesis using the targeted muscle reinnervation. The patient could simultaneously control two degrees-of-freedom with the experimental prosthesis, the elbow and either the terminal device or wrist. Objective testing showed a doubling of blocks moved with a box and blocks test and a 26% increase in speed with a clothes pin moving test. Subjectively the patient clearly preferred the new prosthesis. He reported that it was easier and faster to use, and felt more natural.

The effect of brain death and coma on gastric myoelectrical activity.

PubMed

Bor, Canan; Bordin, Dmitry; Demirag, Kubilay; Uyar, Mehmet

2016-05-01

Gastrointestinal motility problems and delayed gastric emptying in patients admitted to intensive care units are important because they can contribute to different problems. Herein we aimed to measure the changes in gastric myoelectrical activity with electrogastrography (EGG) following brain death (BD) and compare the results to those from patients in a deep coma without BD. Fifteen patients with BD and nine in a deep coma with a Glasgow Coma Score from 3 to 8 were included. An enteral nutrition solution was given via a nasogastric tube between 45 min of fasting and the postprandial periods. The mean dominant frequency (MnDF), normal gastric slow wave ratio (%), tachygastria and bradygastria (%), power ratio (PR: dominant power after test meal/fasting), and dominant frequency instability coefficient were evaluated. The median of MnDF was determined 3.20±0.6 (BD) vs 3.05±0.5 (control), p>0.05. Patients with BD displayed tachygastria, particularly during the fasting state, with this disturbance decreasing during the postprandial period (from 41% to 15%). However, none of the differences between the groups were statistically significant. PR was pathologic in 4/15 (26.7%) patients in the BD group and 4/9 (44.4%) patients in the control group (p=0.288). Patients with coma or BD bouth might have gastric myoelectrical activity disturbances. BD does not show more severe disturbance than coma wihouth BD. EGG might be useful as a non-invasive and easy-to-use technology; however, it needs further improvement.

The recognition of graphical patterns invariant to geometrical transformation of the models

NASA Astrophysics Data System (ADS)

Ileană, Ioan; Rotar, Corina; Muntean, Maria; Ceuca, Emilian

2010-11-01

In case that a pattern recognition system is used for images recognition (in robot vision, handwritten recognition etc.), the system must have the capacity to identify an object indifferently of its size or position in the image. The problem of the invariance of recognition can be approached in some fundamental modes. One may apply the similarity criterion used in associative recall. The original pattern is replaced by a mathematical transform that assures some invariance (e.g. the value of two-dimensional Fourier transformation is translation invariant, the value of Mellin transformation is scale invariant). In a different approach the original pattern is represented through a set of features, each of them being coded indifferently of the position, orientation or position of the pattern. Generally speaking, it is easy to obtain invariance in relation with one transformation group, but is difficult to obtain simultaneous invariance at rotation, translation and scale. In this paper we analyze some methods to achieve invariant recognition of images, particularly for digit images. A great number of experiments are due and the conclusions are underplayed in the paper.

Pattern recognition technique

NASA Technical Reports Server (NTRS)

Hong, J. P.

1971-01-01

Technique operates regardless of pattern rotation, translation or magnification and successfully detects out-of-register patterns. It improves accuracy and reduces cost of various optical character recognition devices and page readers and provides data input to computer.

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

Vomiting and gastric electrical dysrhythmia in dogs.

PubMed

Ueno, T; Chen, J D Z

2004-04-01

The correlation between gastric myoelectrical activity (GMA) and gastrointestinal symptoms such as nausea and vomiting is poorly understood. The aim of this study was to assess the association of GMA with vomiting induced by retrograde gastric electrical stimulation or duodenal balloon distention. Ten dogs were involved in this study. Vomiting was induced by retrograde gastric electrical stimulation in 6 dogs and by duodenal balloon distention in 4 dogs. Computerized spectral analysis and visual analysis were applied to detect the GMA change during various periods before and after vomiting. Gastric dysrhythmia preceded vomiting but was of brief duration. The major pattern of dysrhythmia immediately before vomiting was tachyarrhythmia and gastric slow wave was completely uncoupled before vomiting. Gastric dysrhythmia and slow wave uncoupling were also noticed immediately after vomiting but the dogs recovered quickly. The major pattern of dysrhythmia after vomiting was arrhythmia. GMA was normal during the periods other than 5 min before and during vomiting and 5 min after vomiting. Gastric dysrhythmia seems to be the cause of vomiting induced by retrograde gastric electrical stimulation or duodenal balloon distention. It is brief and characterized with tachyarrhythmia and uncoupling.

On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information

NASA Astrophysics Data System (ADS)

Stathopoulou, I.-O.; Alepis, E.; Tsihrintzis, G. A.; Virvou, M.

Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.

Basics of identification measurement technology

NASA Astrophysics Data System (ADS)

Klikushin, Yu N.; Kobenko, V. Yu; Stepanov, P. P.

2018-01-01

All available algorithms and suitable for pattern recognition do not give 100% guarantee, therefore there is a field of scientific night activity in this direction, studies are relevant. It is proposed to develop existing technologies for pattern recognition in the form of application of identification measurements. The purpose of the study is to identify the possibility of recognizing images using identification measurement technologies. In solving problems of pattern recognition, neural networks and hidden Markov models are mainly used. A fundamentally new approach to the solution of problems of pattern recognition based on the technology of identification signal measurements (IIS) is proposed. The essence of IIS technology is the quantitative evaluation of the shape of images using special tools and algorithms.

Pattern recognition neural-net by spatial mapping of biology visual field

NASA Astrophysics Data System (ADS)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

33 CFR 106.215 - Company or OCS facility personnel with security duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

... appropriate: (a) Knowledge of current and anticipated security threats and patterns. (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Recognition of techniques used to circumvent security...

33 CFR 106.215 - Company or OCS facility personnel with security duties.

Code of Federal Regulations, 2010 CFR

2010-07-01

... appropriate: (a) Knowledge of current and anticipated security threats and patterns. (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Recognition of techniques used to circumvent security...

Facial expression recognition based on improved local ternary pattern and stacked auto-encoder

NASA Astrophysics Data System (ADS)

Wu, Yao; Qiu, Weigen

2017-08-01

In order to enhance the robustness of facial expression recognition, we propose a method of facial expression recognition based on improved Local Ternary Pattern (LTP) combined with Stacked Auto-Encoder (SAE). This method uses the improved LTP extraction feature, and then uses the improved depth belief network as the detector and classifier to extract the LTP feature. The combination of LTP and improved deep belief network is realized in facial expression recognition. The recognition rate on CK+ databases has improved significantly.

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Theoretical Aspects of the Patterns Recognition Statistical Theory Used for Developing the Diagnosis Algorithms for Complicated Technical Systems

NASA Astrophysics Data System (ADS)

Obozov, A. A.; Serpik, I. N.; Mihalchenko, G. S.; Fedyaeva, G. A.

2017-01-01

In the article, the problem of application of the pattern recognition (a relatively young area of engineering cybernetics) for analysis of complicated technical systems is examined. It is shown that the application of a statistical approach for hard distinguishable situations could be the most effective. The different recognition algorithms are based on Bayes approach, which estimates posteriori probabilities of a certain event and an assumed error. Application of the statistical approach to pattern recognition is possible for solving the problem of technical diagnosis complicated systems and particularly big powered marine diesel engines.

ICPR-2016 - International Conference on Pattern Recognition

Science.gov Websites

Learning for Scene Understanding" Speakers ICPR2016 PAPER AWARDS Best Piero Zamperoni Student Paper -Paced Dictionary Learning for Cross-Domain Retrieval and Recognition Xu, Dan; Song, Jingkuan; Alameda discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and

"Bionic Man" Showcases Medical Research | NIH MedlinePlus the Magazine

MedlinePlus

... Wisconsin Implantable Sensors for Prosthesis Control Implantable myoelectric (electrical properties of muscle) sensors detect nerve signals above ... treatments reach the brain. Spinal Stimulation for Paralysis Electrical stimulation of the spinal cord is being used ...

Changes in gastric myoelectric activity during space flight

NASA Technical Reports Server (NTRS)

Harm, Deborah L.; Sandoz, Gwenn R.; Stern, Robert M.

2002-01-01

The purpose of the present study was to examine postprandial myoelectric activity of the stomach and gastric activity associated with space motion sickness using electrogastrography. Three crewmembers participated in this investigation. Preflight, subjects exhibited normal postprandial responses to the ingestion of a meal. Inflight, crewmembers exhibited an abnormal decrease in the power of the normal gastric slow wave after eating on flight day 1, but had a normal postprandial response by flight day 3. Prior to and during episodes of nausea and vomiting, the electrical activity of the stomach became dysrhythmic with 60-80% of the spectral power in the bradygastric and tachygastric frequency ranges. These findings indicate that gastric motility may be decreased during the first few days of space flight. In addition, changes in the frequency of the gastric slow wave associated with space motion sickness symptoms are consistent with those reported for laboratory-induced motion sickness.

The Spatial Vision Tree: A Generic Pattern Recognition Engine- Scientific Foundations, Design Principles, and Preliminary Tree Design

NASA Technical Reports Server (NTRS)

Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

2010-01-01

New foundational ideas are used to define a novel approach to generic visual pattern recognition. These ideas proceed from the starting point of the intrinsic equivalence of noise reduction and pattern recognition when noise reduction is taken to its theoretical limit of explicit matched filtering. This led us to think of the logical extension of sparse coding using basis function transforms for both de-noising and pattern recognition to the full pattern specificity of a lexicon of matched filter pattern templates. A key hypothesis is that such a lexicon can be constructed and is, in fact, a generic visual alphabet of spatial vision. Hence it provides a tractable solution for the design of a generic pattern recognition engine. Here we present the key scientific ideas, the basic design principles which emerge from these ideas, and a preliminary design of the Spatial Vision Tree (SVT). The latter is based upon a cryptographic approach whereby we measure a large aggregate estimate of the frequency of occurrence (FOO) for each pattern. These distributions are employed together with Hamming distance criteria to design a two-tier tree. Then using information theory, these same FOO distributions are used to define a precise method for pattern representation. Finally the experimental performance of the preliminary SVT on computer generated test images and complex natural images is assessed.

Hopfield's Model of Patterns Recognition and Laws of Artistic Perception

NASA Astrophysics Data System (ADS)

Yevin, Igor; Koblyakov, Alexander

The model of patterns recognition or attractor network model of associative memory, offered by J.Hopfield 1982, is the most known model in theoretical neuroscience. This paper aims to show, that such well-known laws of art perception as the Wundt curve, perception of visual ambiguity in art, and also the model perception of musical tonalities are nothing else than special cases of the Hopfield’s model of patterns recognition.

Computer discrimination procedures applicable to aerial and ERTS multispectral data

NASA Technical Reports Server (NTRS)

Richardson, A. J.; Torline, R. J.; Allen, W. A.

1970-01-01

Two statistical models are compared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.

Sub-pattern based multi-manifold discriminant analysis for face recognition

NASA Astrophysics Data System (ADS)

Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

2018-04-01

In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

Research on the feature extraction and pattern recognition of the distributed optical fiber sensing signal

NASA Astrophysics Data System (ADS)

Wang, Bingjie; Sun, Qi; Pi, Shaohua; Wu, Hongyan

2014-09-01

In this paper, feature extraction and pattern recognition of the distributed optical fiber sensing signal have been studied. We adopt Mel-Frequency Cepstral Coefficient (MFCC) feature extraction, wavelet packet energy feature extraction and wavelet packet Shannon entropy feature extraction methods to obtain sensing signals (such as speak, wind, thunder and rain signals, etc.) characteristic vectors respectively, and then perform pattern recognition via RBF neural network. Performances of these three feature extraction methods are compared according to the results. We choose MFCC characteristic vector to be 12-dimensional. For wavelet packet feature extraction, signals are decomposed into six layers by Daubechies wavelet packet transform, in which 64 frequency constituents as characteristic vector are respectively extracted. In the process of pattern recognition, the value of diffusion coefficient is introduced to increase the recognition accuracy, while keeping the samples for testing algorithm the same. Recognition results show that wavelet packet Shannon entropy feature extraction method yields the best recognition accuracy which is up to 97%; the performance of 12-dimensional MFCC feature extraction method is less satisfactory; the performance of wavelet packet energy feature extraction method is the worst.

Abnormal gastric myoelectrical activity in postural tachycardia syndrome.

PubMed

Seligman, William H; Low, David A; Asahina, Masato; Mathias, Christopher J

2013-04-01

Postural tachycardia syndrome (PoTS) is an important cause of orthostatic intolerance resulting from cardiovascular autonomic dysfunction. In addition to postural symptoms, PoTS patients may have allied features, including gastrointestinal (GI) symptoms, which have not yet been thoroughly investigated. We evaluated gastric myoelectrical activity in PoTS patients. Using cutaneous electrogastrography (EGG), we recorded gastric myoelectrical activity before and after standard liquid meal ingestion in 15 PoTS patients (age 27 ± 4 years); including 7 with and 8 without GI symptoms, and in 11 healthy individuals (age 23 ± 7 years). We performed spectral analysis of EGG recordings to obtain the dominant frequency of gastric pacemaker rhythm (DF), instability coefficient of DF (ICDF), and low (LFR%), normal (NFR%), and high (HFR%) range power percentages of the total power. Instability coefficient of DF, an index of variability of gastric pacemaker rhythm, was significantly elevated both pre- and post-prandially (30-45 min after the meal) in the PoTS group (8.8 ± 6, 10.0 ± 8 %) compared with controls (4.0 ± 3, 4.0 ± 3 %; both p < 0.05). Patients with GI symptoms had significantly higher post-prandial ICDF (15.0 ± 5 %) than those without GI symptoms (5.6 ± 4 %; p < 0.05). There were no significant differences in DF, LFR%, NFR% and HFR% before and after the meal between the PoTS and control groups, or between PoTS patients with and without GI symptoms. Our study revealed increased variability of gastric pacemaker rhythm in PoTS, and these findings might be related to pathophysiology of functional GI symptoms in PoTS.

First-in-man demonstration of a fully implanted myoelectric sensors system to control an advanced electromechanical prosthetic hand.

PubMed

Pasquina, Paul F; Evangelista, Melissa; Carvalho, A J; Lockhart, Joseph; Griffin, Sarah; Nanos, George; McKay, Patricia; Hansen, Morten; Ipsen, Derek; Vandersea, James; Butkus, Josef; Miller, Matthew; Murphy, Ian; Hankin, David

2015-04-15

Advanced motorized prosthetic devices are currently controlled by EMG signals generated by residual muscles and recorded by surface electrodes on the skin. These surface recordings are often inconsistent and unreliable, leading to high prosthetic abandonment rates for individuals with upper limb amputation. Surface electrodes are limited because of poor skin contact, socket rotation, residual limb sweating, and their ability to only record signals from superficial muscles, whose function frequently does not relate to the intended prosthetic function. More sophisticated prosthetic devices require a stable and reliable interface between the user and robotic hand to improve upper limb prosthetic function. Implantable Myoelectric Sensors (IMES(®)) are small electrodes intended to detect and wirelessly transmit EMG signals to an electromechanical prosthetic hand via an electro-magnetic coil built into the prosthetic socket. This system is designed to simultaneously capture EMG signals from multiple residual limb muscles, allowing the natural control of multiple degrees of freedom simultaneously. We report the status of the first FDA-approved clinical trial of the IMES(®) System. This study is currently in progress, limiting reporting to only preliminary results. Our first subject has reported the ability to accomplish a greater variety and complexity of tasks in his everyday life compared to what could be achieved with his previous myoelectric prosthesis. The interim results of this study indicate the feasibility of utilizing IMES(®) technology to reliably sense and wirelessly transmit EMG signals from residual muscles to intuitively control a three degree-of-freedom prosthetic arm. Copyright © 2014 Elsevier B.V. All rights reserved.

First-in-Man Demonstration of Fully Implanted Myoelectric Sensors for Control of an Advanced Electromechanical Arm by Transradial Amputees

PubMed Central

Pasquina, Paul F.; Evangelista, Melissa; Carvalho, Antonio J.; Lockhart, Joseph; Griffin, Sarah; Nanos, George; McKay, Patricia; Hansen, Morten; Ipsen, Derek; Vandersea, James; Butkus, Josef; Miller, Matthew; Murphy, Ian; Hankin, David

2014-01-01

Background Advanced motorized prosthetic devices are currently controlled by EMG signals generated by residual muscles and recorded by surface electrodes on the skin. These surface recordings are often inconsistent and unreliable, leading to high prosthetic abandonment rates for individuals with upper limb amputation. Surface electrodes are limited because of poor skin contact, socket rotation, residual limb sweating, and their ability to only record signals from superficial muscles, whose function frequently does not relate to the intended prosthetic function. More sophisticated prosthetic devices require a stable and reliable interface between the user and robotic hand to improve upper limb prosthetic function. New Method Implantable Myoelectric Sensors (IMES®) are small electrodes intended to detect and wirelessly transmit EMG signals to an electromechanical prosthetic hand via an electromagnetic coil built into the prosthetic socket. This system is designed to simultaneously capture EMG signals from multiple residual limb muscles, allowing the natural control of multiple degrees of freedom simultaneously. Results We report the status of the first FDA-approved clinical trial of the IMES® System. This study is currently in progress, limiting reporting to only preliminary results. Comparison with Existing Methods Our first subject has reported the ability to accomplish a greater variety and complexity of tasks in his everyday life compared to what could be achieved with his previous myoelectric prosthesis. Conclusion The interim results of this study indicate the feasibility of utilizing IMES® technology to reliably sense and wirelessly transmit EMG signals from residual muscles to intuitively control a three degree-of-freedom prosthetic arm. PMID:25102286

Surveying the interest of individuals with upper limb loss in novel prosthetic control techniques.

PubMed

Engdahl, Susannah M; Christie, Breanne P; Kelly, Brian; Davis, Alicia; Chestek, Cynthia A; Gates, Deanna H

2015-06-13

Novel techniques for the control of upper limb prostheses may allow users to operate more complex prostheses than those that are currently available. Because many of these techniques are surgically invasive, it is important to understand whether individuals with upper limb loss would accept the associated risks in order to use a prosthesis. An online survey of individuals with upper limb loss was conducted. Participants read descriptions of four prosthetic control techniques. One technique was noninvasive (myoelectric) and three were invasive (targeted muscle reinnervation, peripheral nerve interfaces, cortical interfaces). Participants rated how likely they were to try each technique if it offered each of six different functional features. They also rated their general interest in each of the six features. A two-way repeated measures analysis of variance with Greenhouse-Geisser corrections was used to examine the effect of the technique type and feature on participants' interest in each technique. Responses from 104 individuals were analyzed. Many participants were interested in trying the techniques - 83 % responded positively toward myoelectric control, 63 % toward targeted muscle reinnervation, 68 % toward peripheral nerve interfaces, and 39 % toward cortical interfaces. Common concerns about myoelectric control were weight, cost, durability, and difficulty of use, while the most common concern about the invasive techniques was surgical risk. Participants expressed greatest interest in basic prosthesis features (e.g., opening and closing the hand slowly), as opposed to advanced features like fine motor control and touch sensation. The results of these investigations may be used to inform the development of future prosthetic technologies that are appealing to individuals with upper limb loss.

Vibrotactile grasping force and hand aperture feedback for myoelectric forearm prosthesis users.

PubMed

Witteveen, Heidi J B; Rietman, Hans S; Veltink, Peter H

2015-06-01

User feedback about grasping force and hand aperture is very important in object handling with myoelectric forearm prostheses but is lacking in current prostheses. Vibrotactile feedback increases the performance of healthy subjects in virtual grasping tasks, but no extensive validation on potential users has been performed. Investigate the performance of upper-limb loss subjects in grasping tasks with vibrotactile stimulation, providing hand aperture, and grasping force feedback. Cross-over trial. A total of 10 subjects with upper-limb loss performed virtual grasping tasks while perceiving vibrotactile feedback. Hand aperture feedback was provided through an array of coin motors and grasping force feedback through a single miniature stimulator or an array of coin motors. Objects with varying sizes and weights had to be grasped by a virtual hand. Percentages correctly applied hand apertures and correct grasping force levels were all higher for the vibrotactile feedback condition compared to the no-feedback condition. With visual feedback, the results were always better compared to the vibrotactile feedback condition. Task durations were comparable for all feedback conditions. Vibrotactile grasping force and hand aperture feedback improves grasping performance of subjects with upper-limb loss. However, it should be investigated whether this is of additional value in daily-life tasks. This study is a first step toward the implementation of sensory vibrotactile feedback for users of myoelectric forearm prostheses. Grasping force feedback is crucial for optimal object handling, and hand aperture feedback is essential for reduction of required visual attention. Grasping performance with feedback is evaluated for the potential users. © The International Society for Prosthetics and Orthotics 2014.

The effect of motor learning and fatigue on pre-activation of the lower extremity muscles during different jumps.

PubMed

Kamelska, Anna M; Kot, Bartosz

2017-09-22

The first step in identifying risk factors for injuries is to characterize the myoelectric activity of different muscles after ground contact, especially when fatigue is a limiting factor. This study aimed at: (a) recording the myoelectric activity of calf muscles after ground contact during different types of jumps and (b) investigating the effect of motor learning and fatigue on muscle pre-activation. Twenty four male students aged 24.3 ± 1.2 years old performed three different motor activities: (a) Jump from a box with counter landing (JCL) on 30x30 cm plate (b) Drop jump with bounce drop jump (BDJ) and (c) BDJ followed by a jump on 51-cm step. The surface EMG was used to examine the following muscles: m. tibialis anterior (TA), m. gastrocnemius medialis (GM), m. gastrocnemius lateralis (GL), and m. soleus (S). The measurements were taken during different jumps before and after motor learning and fatigue stimulus. There were significant differences in pre-activation for TA between JCL and BDJ followed by a jump under the influence of fatigue (p<0.05). The differences were observed also during BDJ between non-fatigued and fatigued conditions. There was a statistically significant difference for GL between BDJ pre- and post-movement motor learning and BDJ pre- and post-fatigue influence. Current results indicate that myoelectric activity of muscles during motor activities is different, and the effect of motor learning and fatigue was shown. Thus, it could be important in the injury prevention in sport.

Reversible autonomic dysfunction in hyperthyroid patients affects gastric myoelectrical activity and emptying.

PubMed

Barczyński, M; Thor, P

2001-08-01

The autonomic nervous system (ANS) function in hyperthyroidism has been so far investigated mainly from the cardiovascular point of view. The aim of this study is to show that the ANS dysfunction in hyperthyroidism is also expressed in gastric myoelectrical activity disturbances and gastric emptying disorders and to search for a correlation between the severity of clinical manifestation and free thyroid hormone levels and the degree of the ANS dysfunction. The analyzed group included 50 recently diagnosed patients with hyperthyroidism who were examined twice: before and after 3 months of thyrostatic treatment. Results were compared with those of a sex-, age- and BMI-matched control group of 50 healthy volunteers. The study included: heart rate variability analysis in time and frequency domain, at rest and during a deep-breathing test, surface electrogastrography in preprandial and postprandial periods measured simultaneously with the ultrasound assessment of gastric emptying time by Bolondi method. In patients with hyperthyroidism in comparison with the control group, the following significant differences were observed: a sharp reduction of the high-frequency component and a decrease of heart rate variability, a high incidence of dysrhythmia with dominant bradyarrhythmia, and a delay of gastric emptying. The degree of disorders related to the degree of clinical manifestation of hyperthyroidism's symptoms and free triiodothyronine serum concentration both. All the disorders were functional and disappeared in a stable euthyroidism. To conclude, the ANS dysfunction in hyperthyroidism results not only in withdrawal of vagal inhibitory effect on sinoatrial node, but in impaired mutual neuro-hormonal regulation (decrease of vagal influence) of gastric myoelectrical activity followed by delay of gastric emptying.

Pattern association--a key to recognition of shark attacks.

PubMed

Cirillo, G; James, H

2004-12-01

Investigation of a number of shark attacks in South Australian waters has lead to recognition of pattern similarities on equipment recovered from the scene of such attacks. Six cases are presented in which a common pattern of striations has been noted.

Recognition vs Reverse Engineering in Boolean Concepts Learning

ERIC Educational Resources Information Center

Shafat, Gabriel; Levin, Ilya

2012-01-01

This paper deals with two types of logical problems--recognition problems and reverse engineering problems, and with the interrelations between these types of problems. The recognition problems are modeled in the form of a visual representation of various objects in a common pattern, with a composition of represented objects in the pattern.…

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

PubMed

Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

2017-06-01

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

Finger vein recognition based on personalized weight maps.

PubMed

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-09-10

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition.

Finger Vein Recognition Based on Personalized Weight Maps

PubMed Central

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-01-01

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition. PMID:24025556

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks.

PubMed

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-22

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

PubMed Central

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-01-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability. PMID:27874024

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

NASA Astrophysics Data System (ADS)

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Tactile feedback is an effective instrument for the training of grasping with a prosthesis at low- and medium-force levels.

PubMed

De Nunzio, Alessandro Marco; Dosen, Strahinja; Lemling, Sabrina; Markovic, Marko; Schweisfurth, Meike Annika; Ge, Nan; Graimann, Bernhard; Falla, Deborah; Farina, Dario

2017-08-01

Grasping is a complex task routinely performed in an anticipatory (feedforward) manner, where sensory feedback is responsible for learning and updating the internal model of grasp dynamics. This study aims at evaluating whether providing a proportional tactile force feedback during the myoelectric control of a prosthesis facilitates learning a stable internal model of the prosthesis force control. Ten able-bodied subjects controlled a sensorized myoelectric prosthesis performing four blocks of consecutive grasps at three levels of target force (30, 50, and 70%), repeatedly closing the fully opened hand. In the first and third block, the subjects received tactile and visual feedback, respectively, while during the second and fourth block, the feedback was removed. The subjects also performed an additional block with no feedback 1 day after the training (Retest). The median and interquartile range of the generated forces was computed to assess the accuracy and precision of force control. The results demonstrated that the feedback was indeed an effective instrument for the training of prosthesis control. After the training, the subjects were still able to accurately generate the desired force for the low and medium target (30 and 50% of maximum force available in a prosthesis), despite the feedback being removed within the session and during the retest (low target force). However, the training was substantially less successful for high forces (70% of prosthesis maximum force), where subjects exhibited a substantial loss of accuracy as soon as the feedback was removed. The precision of control decreased with higher forces and it was consistent across conditions, determined by an intrinsic variability of repeated myoelectric grasping. This study demonstrated that the subject could rely on the tactile feedback to adjust the motor command to the prosthesis across trials. The subjects adjusted the mean level of muscle activation (accuracy), whereas the precision could not be modulated as it depends on the intrinsic myoelectric variability. They were also able to maintain the feedforward command even after the feedback was removed, demonstrating thereby a stable learning, but the retention depended on the level of the target force. This is an important insight into the role of feedback as an instrument for learning of anticipatory prosthesis force control.

A bacterial tyrosine phosphatase inhibits plant pattern recognition receptor activation

USDA-ARS?s Scientific Manuscript database

Perception of pathogen-associated molecular patterns (PAMPs) by surface-localised pattern-recognition receptors (PRRs) is a key component of plant innate immunity. Most known plant PRRs are receptor kinases and initiation of PAMP-triggered immunity (PTI) signalling requires phosphorylation of the PR...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2011 CFR

2011-07-01

... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (xi...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2010 CFR

2010-07-01

... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (xi...

Infrared face recognition based on LBP histogram and KW feature selection

NASA Astrophysics Data System (ADS)

Xie, Zhihua

2014-07-01

The conventional LBP-based feature as represented by the local binary pattern (LBP) histogram still has room for performance improvements. This paper focuses on the dimension reduction of LBP micro-patterns and proposes an improved infrared face recognition method based on LBP histogram representation. To extract the local robust features in infrared face images, LBP is chosen to get the composition of micro-patterns of sub-blocks. Based on statistical test theory, Kruskal-Wallis (KW) feature selection method is proposed to get the LBP patterns which are suitable for infrared face recognition. The experimental results show combination of LBP and KW features selection improves the performance of infrared face recognition, the proposed method outperforms the traditional methods based on LBP histogram, discrete cosine transform(DCT) or principal component analysis(PCA).

2D DOST based local phase pattern for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new two dimensional (2-D) Discrete Orthogonal Stcokwell Transform (DOST) based Local Phase Pattern (LPP) technique has been proposed for efficient face recognition. The proposed technique uses 2-D DOST as preliminary preprocessing and local phase pattern to form robust feature signature which can effectively accommodate various 3D facial distortions and illumination variations. The S-transform, is an extension of the ideas of the continuous wavelet transform (CWT), is also known for its local spectral phase properties in time-frequency representation (TFR). It provides a frequency dependent resolution of the time-frequency space and absolutely referenced local phase information while maintaining a direct relationship with the Fourier spectrum which is unique in TFR. After utilizing 2-D Stransform as the preprocessing and build local phase pattern from extracted phase information yield fast and efficient technique for face recognition. The proposed technique shows better correlation discrimination compared to alternate pattern recognition techniques such as wavelet or Gabor based face recognition. The performance of the proposed method has been tested using the Yale and extended Yale facial database under different environments such as illumination variation and 3D changes in facial expressions. Test results show that the proposed technique yields better performance compared to alternate time-frequency representation (TFR) based face recognition techniques.

Optical Pattern Recognition for Missile Guidance.

DTIC Science & Technology

1982-11-15

directed to novel pattern recognition algo- rithms (that allow pattern recognition and object classification in the face of various geometrical and...I wats EF5 = 50) p.j/t’ni 2 (for btith image pat tern recognitio itas a preproicessing oiperatiton. Ini devices). TIhe rt’ad light intensity (0.33t mW...electrodes on its large faces . This Priz light modulator and the motivation for its devel- SLM is known as the Prom (Pockels real-time optical opment. In Sec

Recognition as Support for Reasoning about Horizontal Motion: A Further Resource for School Science?

ERIC Educational Resources Information Center

Howe, Christine; Taylor Tavares, Joana; Devine, Amy

2016-01-01

Background: Even infants can recognize whether patterns of motion are or are not natural, yet an acknowledged challenge for science education is to promote adequate reasoning about such patterns. Since research indicates linkage between the conceptual bases of recognition and reasoning, it seems possible that recognition can be engaged to support…

33 CFR 105.210 - Facility personnel with security duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

...: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely...

33 CFR 105.210 - Facility personnel with security duties.

Code of Federal Regulations, 2010 CFR

2010-07-01

...: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely...

From The Cover: Induction of antiviral immunity requires Toll-like receptor signaling in both stromal and dendritic cell compartments

NASA Astrophysics Data System (ADS)

Sato, Ayuko; Iwasaki, Akiko

2004-11-01

Pattern recognition by Toll-like receptors (TLRs) is known to be important for the induction of dendritic cell (DC) maturation. DCs, in turn, are critically important in the initiation of T cell responses. However, most viruses do not infect DCs. This recognition system poses a biological problem in ensuring that most viral infections be detected by pattern recognition receptors. Furthermore, it is unknown what, if any, is the contribution of TLRs expressed by cells that are infected by a virus, versus TLRs expressed by DCs, in the initiation of antiviral adaptive immunity. Here we address these issues using a physiologically relevant model of mucosal infection with herpes simplex virus type 2. We demonstrate that innate immune recognition of viral infection occurs in two distinct stages, one at the level of the infected epithelial cells and the other at the level of the noninfected DCs. Importantly, both TLR-mediated recognition events are required for the induction of effector T cells. Our results demonstrate that virally infected tissues instruct DCs to initiate the appropriate class of effector T cell responses and reveal the critical importance of the stromal cells in detecting infectious agents through their own pattern recognition receptors. mucosal immunity | pattern recognition | viral infection

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

Repetition and lag effects in movement recognition.

PubMed

Hall, C R; Buckolz, E

1982-03-01

Whether repetition and lag improve the recognition of movement patterns was investigated. Recognition memory was tested for one repetition, two-repetitions massed, and two-repetitions distributed with movement patterns at lags of 3, 5, 7, and 13. Recognition performance was examined both immediately afterwards and following a 48 hour delay. Both repetition and lag effects failed to be demonstrated, providing some support for the claim that memory is unaffected by repetition at a constant level of processing (Craik & Lockhart, 1972). There was, as expected, a significant decrease in recognition memory following the retention interval, but this appeared unrelated to repetition or lag.

Dentate gyrus supports slope recognition memory, shades of grey-context pattern separation and recognition memory, and CA3 supports pattern completion for object memory.

PubMed

Kesner, Raymond P; Kirk, Ryan A; Yu, Zhenghui; Polansky, Caitlin; Musso, Nick D

2016-03-01

In order to examine the role of the dorsal dentate gyrus (dDG) in slope (vertical space) recognition and possible pattern separation, various slope (vertical space) degrees were used in a novel exploratory paradigm to measure novelty detection for changes in slope (vertical space) recognition memory and slope memory pattern separation in Experiment 1. The results of the experiment indicate that control rats displayed a slope recognition memory function with a pattern separation process for slope memory that is dependent upon the magnitude of change in slope between study and test phases. In contrast, the dDG lesioned rats displayed an impairment in slope recognition memory, though because there was no significant interaction between the two groups and slope memory, a reliable pattern separation impairment for slope could not be firmly established in the DG lesioned rats. In Experiment 2, in order to determine whether, the dDG plays a role in shades of grey spatial context recognition and possible pattern separation, shades of grey were used in a novel exploratory paradigm to measure novelty detection for changes in the shades of grey context environment. The results of the experiment indicate that control rats displayed a shades of grey-context pattern separation effect across levels of separation of context (shades of grey). In contrast, the DG lesioned rats displayed a significant interaction between the two groups and levels of shades of grey suggesting impairment in a pattern separation function for levels of shades of grey. In Experiment 3 in order to determine whether the dorsal CA3 (dCA3) plays a role in object pattern completion, a new task requiring less training and using a choice that was based on choosing the correct set of objects on a two-choice discrimination task was used. The results indicated that control rats displayed a pattern completion function based on the availability of one, two, three or four cues. In contrast, the dCA3 lesioned rats displayed a significant interaction between the two groups and the number of available objects suggesting impairment in a pattern completion function for object cues. Copyright © 2015 Elsevier Inc. All rights reserved.

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

PubMed Central

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-01-01

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. PMID:29172273

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

PubMed

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-11-26

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. Creative Commons Attribution License

Solution NMR studies provide structural basis for endotoxin pattern recognition by the innate immune receptor CD14

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albright, Seth; Chen Bin; Holbrook, Kristen

CD14 functions as a key pattern recognition receptor for a diverse array of Gram-negative and Gram-positive cell-wall components in the host innate immune response by binding to pathogen-associated molecular patterns (PAMPs) at partially overlapping binding site(s). To determine the potential contribution of CD14 residues in this pattern recognition, we have examined using solution NMR spectroscopy, the binding of three different endotoxin ligands, lipopolysaccharide, lipoteichoic acid, and a PGN-derived compound, muramyl dipeptide to a {sup 15}N isotopically labeled 152-residue N-terminal fragment of sCD14 expressed in Pichia pastoris. Mapping of NMR spectral changes upon addition of ligands revealed that the pattern ofmore » residues affected by binding of each ligand is partially similar and partially different. This first direct structural observation of the ability of specific residue combinations of CD14 to differentially affect endotoxin binding may help explain the broad specificity of CD14 in ligand recognition and provide a structural basis for pattern recognition. Another interesting finding from the observed spectral changes is that the mode of binding may be dynamically modulated and could provide a mechanism for binding endotoxins with structural diversity through a common binding site.« less

Forecasting of hourly load by pattern recognition in a small area power system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dehdashti-Shahrokh, A.

1982-01-01

An intuitive, logical, simple and efficient method of forecasting hourly load in a small area power system is presented. A pattern recognition approach is used in developing the forecasting model. Pattern recognition techniques are powerful tools in the field of artificial intelligence (cybernetics) and simulate the way the human brain operates to make decisions. Pattern recognition is generally used in analysis of processes where the total physical nature behind the process variation is unkown but specific kinds of measurements explain their behavior. In this research basic multivariate analyses, in conjunction with pattern recognition techniques, are used to develop a linearmore » deterministic model to forecast hourly load. This method assumes that load patterns in the same geographical area are direct results of climatological changes (weather sensitive load), and have occurred in the past as a result of similar climatic conditions. The algorithm described in here searches for the best possible pattern from a seasonal library of load and weather data in forecasting hourly load. To accommodate the unpredictability of weather and the resulting load, the basic twenty-four load pattern was divided into eight three-hour intervals. This division was made to make the model adaptive to sudden climatic changes. The proposed method offers flexible lead times of one to twenty-four hours. The results of actual data testing had indicated that this proposed method is computationally efficient, highly adaptive, with acceptable data storage size and accuracy that is comparable to many other existing methods.« less

Optical character recognition based on nonredundant correlation measurements.

PubMed

Braunecker, B; Hauck, R; Lohmann, A W

1979-08-15

The essence of character recognition is a comparison between the unknown character and a set of reference patterns. Usually, these reference patterns are all possible characters themselves, the whole alphabet in the case of letter characters. Obviously, N analog measurements are highly redundant, since only K = log(2)N binary decisions are enough to identify one out of N characters. Therefore, we devised K reference patterns accordingly. These patterns, called principal components, are found by digital image processing, but used in an optical analog computer. We will explain the concept of principal components, and we will describe experiments with several optical character recognition systems, based on this concept.

Self-organizing neural network models for visual pattern recognition.

PubMed

Fukushima, K

1987-01-01

Two neural network models for visual pattern recognition are discussed. The first model, called a "neocognitron", is a hierarchical multilayered network which has only afferent synaptic connections. It can acquire the ability to recognize patterns by "learning-without-a-teacher": the repeated presentation of a set of training patterns is sufficient, and no information about the categories of the patterns is necessary. The cells of the highest stage eventually become "gnostic cells", whose response shows the final result of the pattern-recognition of the network. Pattern recognition is performed on the basis of similarity in shape between patterns, and is not affected by deformation, nor by changes in size, nor by shifts in the position of the stimulus pattern. The second model has not only afferent but also efferent synaptic connections, and is endowed with the function of selective attention. The afferent and the efferent signals interact with each other in the hierarchical network: the efferent signals, that is, the signals for selective attention, have a facilitating effect on the afferent signals, and at the same time, the afferent signals gate efferent signal flow. When a complex figure, consisting of two patterns or more, is presented to the model, it is segmented into individual patterns, and each pattern is recognized separately. Even if one of the patterns to which the models is paying selective attention is affected by noise or defects, the model can "recall" the complete pattern from which the noise has been eliminated and the defects corrected.

Effect of physical workload and modality of information presentation on pattern recognition and navigation task performance by high-fit young males.

PubMed

Zahabi, Maryam; Zhang, Wenjuan; Pankok, Carl; Lau, Mei Ying; Shirley, James; Kaber, David

2017-11-01

Many occupations require both physical exertion and cognitive task performance. Knowledge of any interaction between physical demands and modalities of cognitive task information presentation can provide a basis for optimising performance. This study examined the effect of physical exertion and modality of information presentation on pattern recognition and navigation-related information processing. Results indicated males of equivalent high fitness, between the ages of 18 and 34, rely more on visual cues vs auditory or haptic for pattern recognition when exertion level is high. We found that navigation response time was shorter under low and medium exertion levels as compared to high intensity. Navigation accuracy was lower under high level exertion compared to medium and low levels. In general, findings indicated that use of the haptic modality for cognitive task cueing decreased accuracy in pattern recognition responses. Practitioner Summary: An examination was conducted on the effect of physical exertion and information presentation modality in pattern recognition and navigation. In occupations requiring information presentation to workers, who are simultaneously performing a physical task, the visual modality appears most effective under high level exertion while haptic cueing degrades performance.

A strip chart recorder pattern recognition tool kit for Shuttle operations

NASA Technical Reports Server (NTRS)

Hammen, David G.; Moebes, Travis A.; Shelton, Robert O.; Savely, Robert T.

1993-01-01

During Space Shuttle operations, Mission Control personnel monitor numerous mission-critical systems such as electrical power; guidance, navigation, and control; and propulsion by means of paper strip chart recorders. For example, electrical power controllers monitor strip chart recorder pen traces to identify onboard electrical equipment activations and deactivations. Recent developments in pattern recognition technologies coupled with new capabilities that distribute real-time Shuttle telemetry data to engineering workstations make it possible to develop computer applications that perform some of the low-level monitoring now performed by controllers. The number of opportunities for such applications suggests a need to build a pattern recognition tool kit to reduce software development effort through software reuse. We are building pattern recognition applications while keeping such a tool kit in mind. We demonstrated the initial prototype application, which identifies electrical equipment activations, during three recent Shuttle flights. This prototype was developed to test the viability of the basic system architecture, to evaluate the performance of several pattern recognition techniques including those based on cross-correlation, neural networks, and statistical methods, to understand the interplay between an advanced automation application and human controllers to enhance utility, and to identify capabilities needed in a more general-purpose tool kit.

A dynamical pattern recognition model of gamma activity in auditory cortex

PubMed Central

Zavaglia, M.; Canolty, R.T.; Schofield, T.M.; Leff, A.P.; Ursino, M.; Knight, R.T.; Penny, W.D.

2012-01-01

This paper describes a dynamical process which serves both as a model of temporal pattern recognition in the brain and as a forward model of neuroimaging data. This process is considered at two separate levels of analysis: the algorithmic and implementation levels. At an algorithmic level, recognition is based on the use of Occurrence Time features. Using a speech digit database we show that for noisy recognition environments, these features rival standard cepstral coefficient features. At an implementation level, the model is defined using a Weakly Coupled Oscillator (WCO) framework and uses a transient synchronization mechanism to signal a recognition event. In a second set of experiments, we use the strength of the synchronization event to predict the high gamma (75–150 Hz) activity produced by the brain in response to word versus non-word stimuli. Quantitative model fits allow us to make inferences about parameters governing pattern recognition dynamics in the brain. PMID:22327049

Visual cluster analysis and pattern recognition methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

2001-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator)

1984-01-01

Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

Proceedings of the NASA/MPRIA Workshop: Pattern Recognition

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1983-01-01

Outlines of talks presented at the workshop conducted at Texas A & M University on February 3 and 4, 1983 are presented. Emphasis was given to the application of Mathematics to image processing and pattern recognition.

Factors associated with interest in novel interfaces for upper limb prosthesis control

PubMed Central

Engdahl, Susannah M.; Chestek, Cynthia A.; Kelly, Brian; Davis, Alicia

2017-01-01

Background Surgically invasive interfaces for upper limb prosthesis control may allow users to operate advanced, multi-articulated devices. Given the potential medical risks of these invasive interfaces, it is important to understand what factors influence an individual’s decision to try one. Methods We conducted an anonymous online survey of individuals with upper limb loss. A total of 232 participants provided personal information (such as age, amputation level, etc.) and rated how likely they would be to try noninvasive (myoelectric) and invasive (targeted muscle reinnervation, peripheral nerve interfaces, cortical interfaces) interfaces for prosthesis control. Bivariate relationships between interest in each interface and 16 personal descriptors were examined. Significant variables from the bivariate analyses were then entered into multiple logistic regression models to predict interest in each interface. Results While many of the bivariate relationships were significant, only a few variables remained significant in the regression models. The regression models showed that participants were more likely to be interested in all interfaces if they had unilateral limb loss (p ≤ 0.001, odds ratio ≥ 2.799). Participants were more likely to be interested in the three invasive interfaces if they were younger (p < 0.001, odds ratio ≤ 0.959) and had acquired limb loss (p ≤ 0.012, odds ratio ≥ 3.287). Participants who used a myoelectric device were more likely to be interested in myoelectric control than those who did not (p = 0.003, odds ratio = 24.958). Conclusions Novel prosthesis control interfaces may be accepted most readily by individuals who are young, have unilateral limb loss, and/or have acquired limb loss However, this analysis did not include all possible factors that may have influenced participant’s opinions on the interfaces, so additional exploration is warranted. PMID:28767716

Factors associated with interest in novel interfaces for upper limb prosthesis control.

PubMed

Engdahl, Susannah M; Chestek, Cynthia A; Kelly, Brian; Davis, Alicia; Gates, Deanna H

2017-01-01

Surgically invasive interfaces for upper limb prosthesis control may allow users to operate advanced, multi-articulated devices. Given the potential medical risks of these invasive interfaces, it is important to understand what factors influence an individual's decision to try one. We conducted an anonymous online survey of individuals with upper limb loss. A total of 232 participants provided personal information (such as age, amputation level, etc.) and rated how likely they would be to try noninvasive (myoelectric) and invasive (targeted muscle reinnervation, peripheral nerve interfaces, cortical interfaces) interfaces for prosthesis control. Bivariate relationships between interest in each interface and 16 personal descriptors were examined. Significant variables from the bivariate analyses were then entered into multiple logistic regression models to predict interest in each interface. While many of the bivariate relationships were significant, only a few variables remained significant in the regression models. The regression models showed that participants were more likely to be interested in all interfaces if they had unilateral limb loss (p ≤ 0.001, odds ratio ≥ 2.799). Participants were more likely to be interested in the three invasive interfaces if they were younger (p < 0.001, odds ratio ≤ 0.959) and had acquired limb loss (p ≤ 0.012, odds ratio ≥ 3.287). Participants who used a myoelectric device were more likely to be interested in myoelectric control than those who did not (p = 0.003, odds ratio = 24.958). Novel prosthesis control interfaces may be accepted most readily by individuals who are young, have unilateral limb loss, and/or have acquired limb loss However, this analysis did not include all possible factors that may have influenced participant's opinions on the interfaces, so additional exploration is warranted.

Myoelectric activation and kinetics of different plyometric push-up exercises.

PubMed

García-Massó, Xavier; Colado, Juan C; González, Luis M; Salvá, Pau; Alves, Joao; Tella, Víctor; Triplett, N Travis

2011-07-01

The kinetic and myoelectric differences between 3 types of plyometric push-ups were investigated. Twenty-seven healthy, physically active men served as subjects and completed both familiarization and testing sessions. During these sessions, subjects performed 2 series of 3 plyometric push-up variations in a counterbalanced order according to the following techniques: Countermovement push-ups (CPUs) were push-ups performed with the maximum speed of movement; jump push-ups (JPUs) were similar to clapping push-ups; and fall push-ups (FPUs) required kneeling subjects to drop and then attempt to return to their initial position. Vertical ground reaction forces were determined by using a force plate. Myoelectric activity was recorded by means of electromyography. Impact force and impact rate of force development were significantly (p < 0.05) higher for FPUs than for JPUs. The maximum rate of force development was higher for CPUs (p < 0.05) than for JPUs, and the maximum force was higher for the CPUs than for the FPUs (p < 0.05). There were differences among exercises for the mean muscle activation of the pectoralis major (PM; p < 0.001), triceps brachii (p < 0.001), external oblique (p < 0.005) and anterior deltoid (p < 0.001), and in the maximum muscle activation of the PM (p < 0.001). Plyometric push-ups with countermovement achieved a higher maximum force and rate of force and did not cause impact forces. Thus, this type of push-up exercise may be regarded as the best for improving explosive force. The FPU exercise achieved higher levels of muscular activation in the agonist and synergist muscle groups, and greater impact forces and impact force development rates.

Using pattern recognition as a method for predicting extreme events in natural and socio-economic systems

NASA Astrophysics Data System (ADS)

Intriligator, M.

2011-12-01

Vladimir (Volodya) Keilis-Borok has pioneered the use of pattern recognition as a technique for analyzing and forecasting developments in natural as well as socio-economic systems. Keilis-Borok's work on predicting earthquakes and landslides using this technique as a leading geophysicist has been recognized around the world. Keilis-Borok has also been a world leader in the application of pattern recognition techniques to the analysis and prediction of socio-economic systems. He worked with Allan Lichtman of American University in using such techniques to predict presidential elections in the U.S. Keilis-Borok and I have worked together with others on the use of pattern recognition techniques to analyze and to predict socio-economic systems. We have used this technique to study the pattern of macroeconomic indicators that would predict the end of an economic recession in the U.S. We have also worked with officers in the Los Angeles Police Department to use this technique to predict surges of homicides in Los Angeles.

Running Improves Pattern Separation during Novel Object Recognition.

PubMed

Bolz, Leoni; Heigele, Stefanie; Bischofberger, Josef

2015-10-09

Running increases adult neurogenesis and improves pattern separation in various memory tasks including context fear conditioning or touch-screen based spatial learning. However, it is unknown whether pattern separation is improved in spontaneous behavior, not emotionally biased by positive or negative reinforcement. Here we investigated the effect of voluntary running on pattern separation during novel object recognition in mice using relatively similar or substantially different objects.We show that running increases hippocampal neurogenesis but does not affect object recognition memory with 1.5 h delay after sample phase. By contrast, at 24 h delay, running significantly improves recognition memory for similar objects, whereas highly different objects can be distinguished by both, running and sedentary mice. These data show that physical exercise improves pattern separation, independent of negative or positive reinforcement. In sedentary mice there is a pronounced temporal gradient for remembering object details. In running mice, however, increased neurogenesis improves hippocampal coding and temporally preserves distinction of novel objects from familiar ones.

A Compact Prototype of an Optical Pattern Recognition System

NASA Technical Reports Server (NTRS)

Jin, Y.; Liu, H. K.; Marzwell, N. I.

1996-01-01

In the Technology 2006 Case Studies/Success Stories presentation, we will describe and demonstrate a prototype of a compact optical pattern recognition system as an example of a successful technology transfer and continuuing development of state-of-the-art know-how by the close collaboration among government, academia, and small business via the NASA SBIR program. The prototype consists of a complete set of optical pattern recognition hardware with multi-channel storage and retrieval capability that is compactly configured inside a portable 1'X 2'X 3' aluminum case.

In vivo characterization of regenerative peripheral nerve interface function

NASA Astrophysics Data System (ADS)

Ursu, Daniel C.; Urbanchek, Melanie G.; Nedic, Andrej; Cederna, Paul S.; Gillespie, R. Brent

2016-04-01

Objective. Regenerative peripheral nerve interfaces (RPNIs) are neurotized free autologous muscle grafts equipped with electrodes to record myoelectric signals for prosthesis control. Viability of rat RPNI constructs have been demonstrated using evoked responses. In vivo RPNI characterization is the next critical step for assessment as a control modality for prosthetic devices. Approach. Two RPNIs were created in each of two rats by grafting portions of free muscle to the ends of divided peripheral nerves (peroneal in the left and tibial in the right hind limb) and placing bipolar electrodes on the graft surface. After four months, we examined in vivo electromyographic signal activity and compared these signals to muscular electromyographic signals recorded from autologous muscles in two rats serving as controls. An additional group of two rats in which the autologous muscles were denervated served to quantify cross-talk in the electrode recordings. Recordings were made while rats walked on a treadmill and a motion capture system tracked the hind limbs. Amplitude and periodicity of signals relative to gait were quantified, correlation between electromyographic and motion recording were assessed, and a decoder was trained to predict joint motion. Main Results. Raw RPNI signals were active during walking, with amplitudes of 1 mVPP, and quiet during standing, with amplitudes less than 0.1 mVPP. RPNI signals were periodic and entrained with gait. A decoder predicted bilateral ankle motion with greater than 80% reliability. Control group signal activity agreed with literature. Denervated group signals remained quiescent throughout all evaluations. Significance. In vivo myoelectric RPNI activity encodes neural activation patterns associated with gait. Signal contamination from muscles adjacent to the RPNI is minimal, as demonstrated by the low amplitude signals obtained from the Denervated group. The periodicity and entrainment to gait of RPNI recordings suggests the transduced signals were generated via central nervous system control.

Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, Gordon Cecil; Martinez, Rubel Francisco

1999-01-01

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Photonic correlator pattern recognition: Application to autonomous docking

NASA Technical Reports Server (NTRS)

Sjolander, Gary W.

1991-01-01

Optical correlators for real-time automatic pattern recognition applications have recently become feasible due to advances in high speed devices and filter formulation concepts. The devices are discussed in the context of their use in autonomous docking.

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

Finger Vein Recognition Based on a Personalized Best Bit Map

PubMed Central

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition. PMID:22438735

Finger vein recognition based on a personalized best bit map.

PubMed

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition.

Large-memory real-time multichannel multiplexed pattern recognition

NASA Technical Reports Server (NTRS)

Gregory, D. A.; Liu, H. K.

1984-01-01

The principle and experimental design of a real-time multichannel multiplexed optical pattern recognition system via use of a 25-focus dichromated gelatin holographic lens (hololens) are described. Each of the 25 foci of the hololens may have a storage and matched filtering capability approaching that of a single-lens correlator. If the space-bandwidth product of an input image is limited, as is true in most practical cases, the 25-focus hololens system has 25 times the capability of a single lens. Experimental results have shown that the interfilter noise is not serious. The system has already demonstrated the storage and recognition of over 70 matched filters - which is a larger capacity than any optical pattern recognition system reported to date.

Sensory feedback add-on for upper-limb prostheses.

PubMed

Fallahian, Nader; Saeedi, Hassan; Mokhtarinia, Hamidreza; Tabatabai Ghomshe, Farhad

2017-06-01

Sensory feedback systems have been of great interest in upper-limb prosthetics. Despite tremendous research, there are no commercial modality-matched feedback systems. This article aims to introduce the first detachable and feedback add-on option that can be attached to in-use prostheses. A sensory feedback system was tested on a below-elbow myoelectric prosthesis. The aim was to have the amputee grasp fragile objects without crushing while other accidental feedback sources were blocked. A total of 8 successful trials (out of 10) showed that sensory feedback system decreased the amputee's visual dependency by improving awareness of his prosthesis. Sensory feedback system can be used either as post-fabrication (prosthetic add-on option) or para-fabrication (incorporated into prosthetic design). The use of these direct feedback systems can be explored with a current prosthesis before ordering new high-tech prosthesis. Clinical relevance This technical note introduces the first attach/detach-able sensory feedback system that can simply be added to in-use (myo)electric prosthesis, with no obligation to change prosthesis design or components.

Masseter muscle fatigue during sustained clenching in subjects with complete dentures, implant-supported prostheses, and natural teeth.

PubMed

Jacobs, R; van Steenberghe, D

1993-03-01

A sustained submaximal (50%) clenching effort was performed in four patient groups to establish whether implant-supported prosthetic reconstructions influence myoelectrical signal parameters. The first group consisted of patients with natural teeth in both jaws. The other three groups consisted of patients who were edentulous in both jaws: one group had complete dentures; one had an overdenture in the mandible on two implants connected by a bar; and the third had an implant-supported fixed prosthesis in either the maxilla or the mandible. Surface electromyography indicated an increased myoelectrical output level that paralleled a higher bite force level for implant-supported reconstructions compared with complete dentures. Power spectrum analysis revealed a downward shift of the mean power frequency during sustained clenching in all groups except the implant-supported fixed prosthesis. The absence of a spectral shift in the latter group probably reflected a fear of biting too hard and fracturing the prosthesis.

Development of wrist rehabilitation robot and interface system.

PubMed

Yamamoto, Ikuo; Matsui, Miki; Inagawa, Naohiro; Hachisuka, Kenji; Wada, Futoshi; Hachisuka, Akiko; Saeki, Satoru

2015-01-01

The authors have developed a practical wrist rehabilitation robot for hemiplegic patients. It consists of a mechanical rotation unit, sensor, grip, and computer system. A myoelectric sensor is used to monitor the extensor carpi radialis longus/brevis muscle and flexor carpi radialis muscle activity during training. The training robot can provoke training through myoelectric sensors, a biological signal detector and processor in advance, so that patients can undergo effective training of extention and flexion in an excited condition. In addition, both-wrist system has been developed for mirror effect training, which is the most effective function of the system, so that autonomous training using both wrists is possible. Furthermore, a user-friendly screen interface with easily recognizable touch panels has been developed to give effective training for patients. The developed robot is small size and easy to carry. The developed aspiring interface system is effective to motivate the training of patients. The effectiveness of the robot system has been verified in hospital trails.

Feature Extraction and Selection for Myoelectric Control Based on Wearable EMG Sensors.

PubMed

Phinyomark, Angkoon; N Khushaba, Rami; Scheme, Erik

2018-05-18

Specialized myoelectric sensors have been used in prosthetics for decades, but, with recent advancements in wearable sensors, wireless communication and embedded technologies, wearable electromyographic (EMG) armbands are now commercially available for the general public. Due to physical, processing, and cost constraints, however, these armbands typically sample EMG signals at a lower frequency (e.g., 200 Hz for the Myo armband) than their clinical counterparts. It remains unclear whether existing EMG feature extraction methods, which largely evolved based on EMG signals sampled at 1000 Hz or above, are still effective for use with these emerging lower-bandwidth systems. In this study, the effects of sampling rate (low: 200 Hz vs. high: 1000 Hz) on the classification of hand and finger movements were evaluated for twenty-six different individual features and eight sets of multiple features using a variety of datasets comprised of both able-bodied and amputee subjects. The results show that, on average, classification accuracies drop significantly ( p.

Listening for Recollection: A Multi-Voxel Pattern Analysis of Recognition Memory Retrieval Strategies

PubMed Central

Quamme, Joel R.; Weiss, David J.; Norman, Kenneth A.

2010-01-01

Recent studies of recognition memory indicate that subjects can strategically vary how much they rely on recollection of specific details vs. feelings of familiarity when making recognition judgments. One possible explanation of these results is that subjects can establish an internally directed attentional state (“listening for recollection”) that enhances retrieval of studied details; fluctuations in this attentional state over time should be associated with fluctuations in subjects’ recognition behavior. In this study, we used multi-voxel pattern analysis of fMRI data to identify brain regions that are involved in listening for recollection. We looked for brain regions that met the following criteria: (1) Distinct neural patterns should be present when subjects are instructed to rely on recollection vs. familiarity, and (2) fluctuations in these neural patterns should be related to recognition behavior in the manner predicted by dual-process theories of recognition: Specifically, the presence of the recollection pattern during the pre-stimulus interval (indicating that subjects are “listening for recollection” at that moment) should be associated with a selective decrease in false alarms to related lures. We found that pre-stimulus activity in the right supramarginal gyrus met all of these criteria, suggesting that this region proactively establishes an internally directed attentional state that fosters recollection. We also found other regions (e.g., left middle temporal gyrus) where the pattern of neural activity was related to subjects’ responding to related lures after stimulus onset (but not before), suggesting that these regions implement processes that are engaged in a reactive fashion to boost recollection. PMID:20740073

Auditory orientation in crickets: Pattern recognition controls reactive steering

NASA Astrophysics Data System (ADS)

Poulet, James F. A.; Hedwig, Berthold

2005-10-01

Many groups of insects are specialists in exploiting sensory cues to locate food resources or conspecifics. To achieve orientation, bees and ants analyze the polarization pattern of the sky, male moths orient along the females' odor plume, and cicadas, grasshoppers, and crickets use acoustic signals to locate singing conspecifics. In comparison with olfactory and visual orientation, where learning is involved, auditory processing underlying orientation in insects appears to be more hardwired and genetically determined. In each of these examples, however, orientation requires a recognition process identifying the crucial sensory pattern to interact with a localization process directing the animal's locomotor activity. Here, we characterize this interaction. Using a sensitive trackball system, we show that, during cricket auditory behavior, the recognition process that is tuned toward the species-specific song pattern controls the amplitude of auditory evoked steering responses. Females perform small reactive steering movements toward any sound patterns. Hearing the male's calling song increases the gain of auditory steering within 2-5 s, and the animals even steer toward nonattractive sound patterns inserted into the speciesspecific pattern. This gain control mechanism in the auditory-to-motor pathway allows crickets to pursue species-specific sound patterns temporarily corrupted by environmental factors and may reflect the organization of recognition and localization networks in insects. localization | phonotaxis

Receptor-like cytoplasmic kinases are pivotal components in pattern recognition receptor-mediated signaling in plant immunity.

PubMed

Yamaguchi, Koji; Yamada, Kenta; Kawasaki, Tsutomu

2013-10-01

Innate immunity is generally initiated with recognition of conserved pathogen-associated molecular patterns (PAMPs). PAMPs are perceived by pattern recognition receptors (PRRs), leading to activation of a series of immune responses, including the expression of defense genes, ROS production and activation of MAP kinase. Recent progress has indicated that receptor-like cytoplasmic kinases (RLCKs) are directly activated by ligand-activated PRRs and initiate pattern-triggered immunity (PTI) in both Arabidopsis and rice. To suppress PTI, pathogens inhibit the RLCKs by many types of effectors, including AvrAC, AvrPphB and Xoo1488. In this review, we summarize recent advances in RLCK-mediated PTI in plants.

Proceedings of the NASA Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1983-01-01

The application of mathematical and statistical analyses techniques to imagery obtained by remote sensors is described by Principal Investigators. Scene-to-map registration, geometric rectification, and image matching are among the pattern recognition aspects discussed.

Students' Dichotomous Experiences of the Illuminating and Illusionary Nature of Pattern Recognition in Mathematics

ERIC Educational Resources Information Center

Mhlolo, Michael Kainose

2016-01-01

The concept of pattern recognition lies at the heart of numerous deliberations concerned with new mathematics curricula, because it is strongly linked to improved generalised thinking. However none of these discussions has made the deceptive nature of patterns an object of exploration and understanding. Yet there is evidence showing that pattern…

Methods and means of diagnostics of oncological diseases on the basis of pattern recognition: intelligent morphological systems - problems and solutions

NASA Astrophysics Data System (ADS)

Nikitaev, V. G.

2017-01-01

The development of methods of pattern recognition in modern intelligent systems of clinical cancer diagnosis are discussed. The histological (morphological) diagnosis - primary diagnosis for medical setting with cancer are investigated. There are proposed: interactive methods of recognition and structure of intellectual morphological complexes based on expert training-diagnostic and telemedicine systems. The proposed approach successfully implemented in clinical practice.

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models

PubMed Central

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner’s faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals. PMID:27191162

Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models.

PubMed

Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori

2016-01-01

A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner's faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals.

Postprocessing for character recognition using pattern features and linguistic information

NASA Astrophysics Data System (ADS)

Yoshikawa, Takatoshi; Okamoto, Masayosi; Horii, Hiroshi

1993-04-01

We propose a new method of post-processing for character recognition using pattern features and linguistic information. This method corrects errors in the recognition of handwritten Japanese sentences containing Kanji characters. This post-process method is characterized by having two types of character recognition. Improving the accuracy of the character recognition rate of Japanese characters is made difficult by the large number of characters, and the existence of characters with similar patterns. Therefore, it is not practical for a character recognition system to recognize all characters in detail. First, this post-processing method generates a candidate character table by recognizing the simplest features of characters. Then, it selects words corresponding to the character from the candidate character table by referring to a word and grammar dictionary before selecting suitable words. If the correct character is included in the candidate character table, this process can correct an error, however, if the character is not included, it cannot correct an error. Therefore, if this method can presume a character does not exist in a candidate character table by using linguistic information (word and grammar dictionary). It then can verify a presumed character by character recognition using complex features. When this method is applied to an online character recognition system, the accuracy of character recognition improves 93.5% to 94.7%. This proved to be the case when it was used for the editorials of a Japanese newspaper (Asahi Shinbun).

Facial emotion recognition in patients with focal and diffuse axonal injury.

PubMed

Yassin, Walid; Callahan, Brandy L; Ubukata, Shiho; Sugihara, Genichi; Murai, Toshiya; Ueda, Keita

2017-01-01

Facial emotion recognition impairment has been well documented in patients with traumatic brain injury. Studies exploring the neural substrates involved in such deficits have implicated specific grey matter structures (e.g. orbitofrontal regions), as well as diffuse white matter damage. Our study aims to clarify whether different types of injuries (i.e. focal vs. diffuse) will lead to different types of impairments on facial emotion recognition tasks, as no study has directly compared these patients. The present study examined performance and response patterns on a facial emotion recognition task in 14 participants with diffuse axonal injury (DAI), 14 with focal injury (FI) and 22 healthy controls. We found that, overall, participants with FI and DAI performed more poorly than controls on the facial emotion recognition task. Further, we observed comparable emotion recognition performance in participants with FI and DAI, despite differences in the nature and distribution of their lesions. However, the rating response pattern between the patient groups was different. This is the first study to show that pure DAI, without gross focal lesions, can independently lead to facial emotion recognition deficits and that rating patterns differ depending on the type and location of trauma.

33 CFR 106.205 - Company Security Officer (CSO).

Code of Federal Regulations, 2011 CFR

2011-07-01

... security related communications; (7) Knowledge of current security threats and patterns; (8) Recognition and detection of dangerous substances and devices; (9) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (10) Techniques used to circumvent security...

33 CFR 106.205 - Company Security Officer (CSO).

Code of Federal Regulations, 2010 CFR

2010-07-01

... security related communications; (7) Knowledge of current security threats and patterns; (8) Recognition and detection of dangerous substances and devices; (9) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (10) Techniques used to circumvent security...

Visual cluster analysis and pattern recognition template and methods

DOEpatents

Osbourn, G.C.; Martinez, R.F.

1999-05-04

A method of clustering using a novel template to define a region of influence is disclosed. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques. 30 figs.

Multiple degree of freedom optical pattern recognition

NASA Technical Reports Server (NTRS)

Casasent, D.

1987-01-01

Three general optical approaches to multiple degree of freedom object pattern recognition (where no stable object rest position exists) are advanced. These techniques include: feature extraction, correlation, and artificial intelligence. The details of the various processors are advanced together with initial results.

Ultrasonography of ovarian masses using a pattern recognition approach

PubMed Central

Jung, Sung Il

2015-01-01

As a primary imaging modality, ultrasonography (US) can provide diagnostic information for evaluating ovarian masses. Using a pattern recognition approach through gray-scale transvaginal US, ovarian masses can be diagnosed with high specificity and sensitivity. Doppler US may allow ovarian masses to be diagnosed as benign or malignant with even greater confidence. In order to differentiate benign and malignant ovarian masses, it is necessary to categorize ovarian masses into unilocular cyst, unilocular solid cyst, multilocular cyst, multilocular solid cyst, and solid tumor, and then to detect typical US features that demonstrate malignancy based on pattern recognition approach. PMID:25797108

Application of pattern recognition techniques to crime analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bender, C.F.; Cox, L.A. Jr.; Chappell, G.A.

1976-08-15

The initial goal was to evaluate the capabilities of current pattern recognition techniques when applied to existing computerized crime data. Performance was to be evaluated both in terms of the system's capability to predict crimes and to optimize police manpower allocation. A relation was sought to predict the crime's susceptibility to solution, based on knowledge of the crime type, location, time, etc. The preliminary results of this work are discussed. They indicate that automatic crime analysis involving pattern recognition techniques is feasible, and that efforts to determine optimum variables and techniques are warranted. 47 figures (RWR)

DESIGN OF A PATTERN RECOGNITION DIGITAL COMPUTER WITH APPLICATION TO THE AUTOMATIC SCANNING OF BUBBLE CHAMBER NEGATIVES

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCormick, B.H.; Narasimhan, R.

1963-01-01

The overall computer system contains three main parts: an input device, a pattern recognition unit (PRU), and a control computer. The bubble chamber picture is divided into a grid of st run. Concent 1-mm squares on the film. It is then processed in parallel in a two-dimensional array of 1024 identical processing modules (stalactites) of the PRU. The array can function as a two- dimensional shift register in which results of successive shifting operations can be accumulated. The pattern recognition process is generally controlled by a conventional arithmetic computer. (A.G.W.)

Directing an appropriate immune response: the role of defense collagens and other soluble pattern recognition molecules.

PubMed

Fraser, D A; Tenner, A J

2008-02-01

Defense collagens and other soluble pattern recognition receptors contain the ability to recognize and bind molecular patterns associated with pathogens (PAMPs) or apoptotic cells (ACAMPs) and signal appropriate effector-function responses. PAMP recognition by defense collagens C1q, MBL and ficolins leads to rapid containment of infection via complement activation. However, in the absence of danger, such as during the clearance of apoptotic cells, defense collagens such as C1q, MBL, ficolins, SP-A, SP-D and even adiponectin have all been shown to facilitate enhanced phagocytosis and modulate induction of cytokines towards an anti-inflammatory profile. In this way, cellular debris can be removed without provoking an inflammatory immune response which may be important in the prevention of autoimmunity and/or resolving inflammation. Indeed, deficiencies and/or knock-out mouse studies have highlighted critical roles for soluble pattern recognition receptors in the clearance of apoptotic bodies and protection from autoimmune diseases along with mediating protection from specific infections. Understanding the mechanisms involved in defense collagen and other soluble pattern recognition receptor modulation of the immune response may provide important novel insights into therapeutic targets for infectious and/or autoimmune diseases and additionally may identify avenues for more effective vaccine design.

Visual scanning behavior is related to recognition performance for own- and other-age faces

PubMed Central

Proietti, Valentina; Macchi Cassia, Viola; dell’Amore, Francesca; Conte, Stefania; Bricolo, Emanuela

2015-01-01

It is well-established that our recognition ability is enhanced for faces belonging to familiar categories, such as own-race faces and own-age faces. Recent evidence suggests that, for race, the recognition bias is also accompanied by different visual scanning strategies for own- compared to other-race faces. Here, we tested the hypothesis that these differences in visual scanning patterns extend also to the comparison between own and other-age faces and contribute to the own-age recognition advantage. Participants (young adults with limited experience with infants) were tested in an old/new recognition memory task where they encoded and subsequently recognized a series of adult and infant faces while their eye movements were recorded. Consistent with findings on the other-race bias, we found evidence of an own-age bias in recognition which was accompanied by differential scanning patterns, and consequently differential encoding strategies, for own-compared to other-age faces. Gaze patterns for own-age faces involved a more dynamic sampling of the internal features and longer viewing time on the eye region compared to the other regions of the face. This latter strategy was extensively employed during learning (vs. recognition) and was positively correlated to discriminability. These results suggest that deeply encoding the eye region is functional for recognition and that the own-age bias is evident not only in differential recognition performance, but also in the employment of different sampling strategies found to be effective for accurate recognition. PMID:26579056

CNNs flag recognition preprocessing scheme based on gray scale stretching and local binary pattern

NASA Astrophysics Data System (ADS)

Gong, Qian; Qu, Zhiyi; Hao, Kun

2017-07-01

Flag is a rather special recognition target in image recognition because of its non-rigid features with the location, scale and rotation characteristics. The location change can be handled well by the depth learning algorithm Convolutional Neural Networks (CNNs), but the scale and rotation changes are quite a challenge for CNNs. Since it has good rotation and gray scale invariance, the local binary pattern (LBP) is combined with grayscale stretching and CNNs to make LBP and grayscale stretching as CNNs pretreatment, which can not only significantly improve the efficiency of flag recognition, but can also evaluate the recognition effect through ROC, accuracy, MSE and quality factor.

HWDA: A coherence recognition and resolution algorithm for hybrid web data aggregation

NASA Astrophysics Data System (ADS)

Guo, Shuhang; Wang, Jian; Wang, Tong

2017-09-01

Aiming at the object confliction recognition and resolution problem for hybrid distributed data stream aggregation, a distributed data stream object coherence solution technology is proposed. Firstly, the framework was defined for the object coherence conflict recognition and resolution, named HWDA. Secondly, an object coherence recognition technology was proposed based on formal language description logic and hierarchical dependency relationship between logic rules. Thirdly, a conflict traversal recognition algorithm was proposed based on the defined dependency graph. Next, the conflict resolution technology was prompted based on resolution pattern matching including the definition of the three types of conflict, conflict resolution matching pattern and arbitration resolution method. At last, the experiment use two kinds of web test data sets to validate the effect of application utilizing the conflict recognition and resolution technology of HWDA.

An isometric muscle force estimation framework based on a high-density surface EMG array and an NMF algorithm

NASA Astrophysics Data System (ADS)

Huang, Chengjun; Chen, Xiang; Cao, Shuai; Qiu, Bensheng; Zhang, Xu

2017-08-01

Objective. To realize accurate muscle force estimation, a novel framework is proposed in this paper which can extract the input of the prediction model from the appropriate activation area of the skeletal muscle. Approach. Surface electromyographic (sEMG) signals from the biceps brachii muscle during isometric elbow flexion were collected with a high-density (HD) electrode grid (128 channels) and the external force at three contraction levels was measured at the wrist synchronously. The sEMG envelope matrix was factorized into a matrix of basis vectors with each column representing an activation pattern and a matrix of time-varying coefficients by a nonnegative matrix factorization (NMF) algorithm. The activation pattern with the highest activation intensity, which was defined as the sum of the absolute values of the time-varying coefficient curve, was considered as the major activation pattern, and its channels with high weighting factors were selected to extract the input activation signal of a force estimation model based on the polynomial fitting technique. Main results. Compared with conventional methods using the whole channels of the grid, the proposed method could significantly improve the quality of force estimation and reduce the electrode number. Significance. The proposed method provides a way to find proper electrode placement for force estimation, which can be further employed in muscle heterogeneity analysis, myoelectric prostheses and the control of exoskeleton devices.

Emotional Faces in Context: Age Differences in Recognition Accuracy and Scanning Patterns

PubMed Central

Noh, Soo Rim; Isaacowitz, Derek M.

2014-01-01

While age-related declines in facial expression recognition are well documented, previous research relied mostly on isolated faces devoid of context. We investigated the effects of context on age differences in recognition of facial emotions and in visual scanning patterns of emotional faces. While their eye movements were monitored, younger and older participants viewed facial expressions (i.e., anger, disgust) in contexts that were emotionally congruent, incongruent, or neutral to the facial expression to be identified. Both age groups had highest recognition rates of facial expressions in the congruent context, followed by the neutral context, and recognition rates in the incongruent context were worst. These context effects were more pronounced for older adults. Compared to younger adults, older adults exhibited a greater benefit from congruent contextual information, regardless of facial expression. Context also influenced the pattern of visual scanning characteristics of emotional faces in a similar manner across age groups. In addition, older adults initially attended more to context overall. Our data highlight the importance of considering the role of context in understanding emotion recognition in adulthood. PMID:23163713

Comparing the visual spans for faces and letters

PubMed Central

He, Yingchen; Scholz, Jennifer M.; Gage, Rachel; Kallie, Christopher S.; Liu, Tingting; Legge, Gordon E.

2015-01-01

The visual span—the number of adjacent text letters that can be reliably recognized on one fixation—has been proposed as a sensory bottleneck that limits reading speed (Legge, Mansfield, & Chung, 2001). Like reading, searching for a face is an important daily task that involves pattern recognition. Is there a similar limitation on the number of faces that can be recognized in a single fixation? Here we report on a study in which we measured and compared the visual-span profiles for letter and face recognition. A serial two-stage model for pattern recognition was developed to interpret the data. The first stage is characterized by factors limiting recognition of isolated letters or faces, and the second stage represents the interfering effect of nearby stimuli on recognition. Our findings show that the visual span for faces is smaller than that for letters. Surprisingly, however, when differences in first-stage processing for letters and faces are accounted for, the two visual spans become nearly identical. These results suggest that the concept of visual span may describe a common sensory bottleneck that underlies different types of pattern recognition. PMID:26129858

Addressing the issue of insufficient information in data-based bridge health monitoring : final report.

DOT National Transportation Integrated Search

2015-11-01

One of the most efficient ways to solve the damage detection problem using the statistical pattern recognition : approach is that of exploiting the methods of outlier analysis. Cast within the pattern recognition framework, : damage detection assesse...

Fast traffic sign recognition with a rotation invariant binary pattern based feature.

PubMed

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-19

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

PubMed Central

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-01

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed. PMID:25608217

Iris recognition based on key image feature extraction.

PubMed

Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

2008-01-01

In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

Quantum pattern recognition with multi-neuron interactions

NASA Astrophysics Data System (ADS)

Fard, E. Rezaei; Aghayar, K.; Amniat-Talab, M.

2018-03-01

We present a quantum neural network with multi-neuron interactions for pattern recognition tasks by a combination of extended classic Hopfield network and adiabatic quantum computation. This scheme can be used as an associative memory to retrieve partial patterns with any number of unknown bits. Also, we propose a preprocessing approach to classifying the pattern space S to suppress spurious patterns. The results of pattern clustering show that for pattern association, the number of weights (η ) should equal the numbers of unknown bits in the input pattern ( d). It is also remarkable that associative memory function depends on the location of unknown bits apart from the d and load parameter α.

Investigation of the medical applications of the unique biocarbons developed by NASA. [compatibility of percutaneous prosthetic carbon devices

NASA Technical Reports Server (NTRS)

Mooney, V.

1973-01-01

The biocompatibility of percutaneous endoskeletal fixation devices made from carbon compounds, and their applications are considered. The clinical application of these carbons to solve human problems is demonstrated and the nature of myoelectric simulation by carbon implants is studied.

Optimal Selection of Time Series Coefficients for Wrist Myoelectric Control Based on Intramuscular Recordings

DTIC Science & Technology

2001-10-25

considered static or invariant because the spectral behavior of EMG data is dependent on the specific muscle , contraction level, and limb function. However...produced at the onset of the muscle contraction . Because the units with lower conduction velocity (lower frequency components) are recruited first, the

Word Recognition in Auditory Cortex

ERIC Educational Resources Information Center

DeWitt, Iain D. J.

2013-01-01

Although spoken word recognition is more fundamental to human communication than text recognition, knowledge of word-processing in auditory cortex is comparatively impoverished. This dissertation synthesizes current models of auditory cortex, models of cortical pattern recognition, models of single-word reading, results in phonetics and results in…

Incoherent optical generalized Hough transform: pattern recognition and feature extraction applications

NASA Astrophysics Data System (ADS)

Fernández, Ariel; Ferrari, José A.

2017-05-01

Pattern recognition and feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital-only methods. We explore an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a pupil mask implemented on a high-contrast spatial light modulator for orientation/shape variation of the template. Real-time can also be achieved. In addition, by thresholding of the GHT and optically inverse transforming, the previously detected features of interest can be extracted.

33 CFR 104.220 - Company or vessel personnel with security duties.

Code of Federal Regulations, 2010 CFR

2010-07-01

... the following, as appropriate: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Techniques used to circumvent security...

33 CFR 104.220 - Company or vessel personnel with security duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

... the following, as appropriate: (a) Knowledge of current security threats and patterns; (b) Recognition and detection of dangerous substances and devices; (c) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; (d) Techniques used to circumvent security...

Genetic dissection of the maize (Zea mays L.) MAMP response

USDA-ARS?s Scientific Manuscript database

Microbe-associated molecular patterns (MAMPs) are highly conserved molecules commonly found in microbes which can be recognized by plant pattern recognition receptors (PRRs). Recognition triggers a suite of responses including production of reactive oxygen species (ROS) and nitric oxide (NO) and ex...

The Functional Architecture of Visual Object Recognition

DTIC Science & Technology

1991-07-01

different forms of agnosia can provide clues to the representations underlying normal object recognition (Farah, 1990). For example, the pair-wise...patterns of deficit and sparing occur. In a review of 99 published cases of agnosia , the observed patterns of co- occurrence implicated two underlying

Utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information

DOT National Transportation Integrated Search

2009-01-01

This report describes a study conducted to explore the utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information. The study gathered data from a large number of pilots who conduct all type...

Spatial pattern recognition of seismic events in South West Colombia

NASA Astrophysics Data System (ADS)

Benítez, Hernán D.; Flórez, Juan F.; Duque, Diana P.; Benavides, Alberto; Lucía Baquero, Olga; Quintero, Jiber

2013-09-01

Recognition of seismogenic zones in geographical regions supports seismic hazard studies. This recognition is usually based on visual, qualitative and subjective analysis of data. Spatial pattern recognition provides a well founded means to obtain relevant information from large amounts of data. The purpose of this work is to identify and classify spatial patterns in instrumental data of the South West Colombian seismic database. In this research, clustering tendency analysis validates whether seismic database possesses a clustering structure. A non-supervised fuzzy clustering algorithm creates groups of seismic events. Given the sensitivity of fuzzy clustering algorithms to centroid initial positions, we proposed a methodology to initialize centroids that generates stable partitions with respect to centroid initialization. As a result of this work, a public software tool provides the user with the routines developed for clustering methodology. The analysis of the seismogenic zones obtained reveals meaningful spatial patterns in South-West Colombia. The clustering analysis provides a quantitative location and dispersion of seismogenic zones that facilitates seismological interpretations of seismic activities in South West Colombia.

Multivariate pattern recognition for diagnosis and prognosis in clinical neuroimaging: state of the art, current challenges and future trends.

PubMed

Haller, Sven; Lovblad, Karl-Olof; Giannakopoulos, Panteleimon; Van De Ville, Dimitri

2014-05-01

Many diseases are associated with systematic modifications in brain morphometry and function. These alterations may be subtle, in particular at early stages of the disease progress, and thus not evident by visual inspection alone. Group-level statistical comparisons have dominated neuroimaging studies for many years, proving fascinating insight into brain regions involved in various diseases. However, such group-level results do not warrant diagnostic value for individual patients. Recently, pattern recognition approaches have led to a fundamental shift in paradigm, bringing multivariate analysis and predictive results, notably for the early diagnosis of individual patients. We review the state-of-the-art fundamentals of pattern recognition including feature selection, cross-validation and classification techniques, as well as limitations including inter-individual variation in normal brain anatomy and neurocognitive reserve. We conclude with the discussion of future trends including multi-modal pattern recognition, multi-center approaches with data-sharing and cloud-computing.

Computer Vision for Artificially Intelligent Robotic Systems

NASA Astrophysics Data System (ADS)

Ma, Chialo; Ma, Yung-Lung

1987-04-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Improved Performance Characteristics For Indium Antimonide Photovoltaic Detector Arrays Using A FET-Switched Multiplexing Technique

NASA Astrophysics Data System (ADS)

Ma, Yung-Lung; Ma, Chialo

1987-03-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts _ position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed by the main control unit. In Pulse-Echo Signal Process Unit, we utilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by p law coding method, and this data together with delay time T, angle information eH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Models, we use a narrow beam transducer and it's input voltage is 50V p-p. A Robot equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Study and response time for the visual recognition of 'similarity' and identity

NASA Technical Reports Server (NTRS)

Derks, P. L.; Bauer, T. M.

1974-01-01

Four subjects compared successively presented pairs of line patterns for a match between any lines in the pattern (similarity) and for a match between all lines (identity). The encoding or study times for pattern recognition from immediate memory and the latency in responses to comparison stimuli were examined. Qualitative differences within and between subjects were most evident in study times.

Hypothesis Support Mechanism for Mid-Level Visual Pattern Recognition

NASA Technical Reports Server (NTRS)

Amador, Jose J (Inventor)

2007-01-01

A method of mid-level pattern recognition provides for a pose invariant Hough Transform by parametrizing pairs of points in a pattern with respect to at least two reference points, thereby providing a parameter table that is scale- or rotation-invariant. A corresponding inverse transform may be applied to test hypothesized matches in an image and a distance transform utilized to quantify the level of match.

The chemical structure of DNA sequence signals for RNA transcription

NASA Technical Reports Server (NTRS)

George, D. G.; Dayhoff, M. O.

1982-01-01

The proposed recognition sites for RNA transcription for E. coli NRA polymerase, bacteriophage T7 RNA polymerase, and eukaryotic RNA polymerase Pol II are evaluated in the light of the requirements for efficient recognition. It is shown that although there is good experimental evidence that specific nucleic acid sequence patterns are involved in transcriptional regulation in bacteria and bacterial viruses, among the sequences now available, only in the case of the promoters recognized by bacteriophage T7 polymerase does it seem likely that the pattern is sufficient. It is concluded that the eukaryotic pattern that is investigated is not restrictive enough to serve as a recognition site.

An Efficient and Robust Singular Value Method for Star Pattern Recognition and Attitude Determination

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Kim, Hye-Young; Junkins, John L.

2003-01-01

A new star pattern recognition method is developed using singular value decomposition of a measured unit column vector matrix in a measurement frame and the corresponding cataloged vector matrix in a reference frame. It is shown that singular values and right singular vectors are invariant with respect to coordinate transformation and robust under uncertainty. One advantage of singular value comparison is that a pairing process for individual measured and cataloged stars is not necessary, and the attitude estimation and pattern recognition process are not separated. An associated method for mission catalog design is introduced and simulation results are presented.

Fourier transform magnitudes are unique pattern recognition templates.

PubMed

Gardenier, P H; McCallum, B C; Bates, R H

1986-01-01

Fourier transform magnitudes are commonly used in the generation of templates in pattern recognition applications. We report on recent advances in Fourier phase retrieval which are relevant to pattern recognition. We emphasise in particular that the intrinsic form of a finite, positive image is, in general, uniquely related to the magnitude of its Fourier transform. We state conditions under which the Fourier phase can be reconstructed from samples of the Fourier magnitude, and describe a method of achieving this. Computational examples of restoration of Fourier phase (and hence, by Fourier transformation, the intrinsic form of the image) from samples of the Fourier magnitude are also presented.

Detection and recognition of analytes based on their crystallization patterns

DOEpatents

Morozov, Victor [Manassas, VA; Bailey, Charles L [Cross Junction, VA; Vsevolodov, Nikolai N [Kensington, MD; Elliott, Adam [Manassas, VA

2008-05-06

The invention contemplates a method for recognition of proteins and other biological molecules by imaging morphology, size and distribution of crystalline and amorphous dry residues in droplets (further referred to as "crystallization pattern") containing predetermined amount of certain crystal-forming organic compounds (reporters) to which protein to be analyzed is added. It has been shown that changes in the crystallization patterns of a number of amino-acids can be used as a "signature" of a protein added. It was also found that both the character of changer in the crystallization patter and the fact of such changes can be used as recognition elements in analysis of protein molecules.

Recognition of neural brain activity patterns correlated with complex motor activity

NASA Astrophysics Data System (ADS)

Kurkin, Semen; Musatov, Vyacheslav Yu.; Runnova, Anastasia E.; Grubov, Vadim V.; Efremova, Tatyana Yu.; Zhuravlev, Maxim O.

2018-04-01

In this paper, based on the apparatus of artificial neural networks, a technique for recognizing and classifying patterns corresponding to imaginary movements on electroencephalograms (EEGs) obtained from a group of untrained subjects was developed. The works on the selection of the optimal type, topology, training algorithms and neural network parameters were carried out from the point of view of the most accurate and fast recognition and classification of patterns on multi-channel EEGs associated with the imagination of movements. The influence of the number and choice of the analyzed channels of a multichannel EEG on the quality of recognition of imaginary movements was also studied, and optimal configurations of electrode arrangements were obtained. The effect of pre-processing of EEG signals is analyzed from the point of view of improving the accuracy of recognition of imaginary movements.

Perception of pathogenic or beneficial bacteria and their evasion of host immunity: pattern recognition receptors in the frontline

PubMed Central

Trdá, Lucie; Boutrot, Freddy; Claverie, Justine; Brulé, Daphnée; Dorey, Stephan; Poinssot, Benoit

2015-01-01

Plants are continuously monitoring the presence of microorganisms to establish an adapted response. Plants commonly use pattern recognition receptors (PRRs) to perceive microbe- or pathogen-associated molecular patterns (MAMPs/PAMPs) which are microorganism molecular signatures. Located at the plant plasma membrane, the PRRs are generally receptor-like kinases (RLKs) or receptor-like proteins (RLPs). MAMP detection will lead to the establishment of a plant defense program called MAMP-triggered immunity (MTI). In this review, we overview the RLKs and RLPs that assure early recognition and control of pathogenic or beneficial bacteria. We also highlight the crucial function of PRRs during plant-microbe interactions, with a special emphasis on the receptors of the bacterial flagellin and peptidoglycan. In addition, we discuss the multiple strategies used by bacteria to evade PRR-mediated recognition. PMID:25904927

Peptidoglycan recognition proteins in Drosophila immunity.

PubMed

Kurata, Shoichiro

2014-01-01

Innate immunity is the front line of self-defense against infectious non-self in vertebrates and invertebrates. The innate immune system is mediated by germ-line encoding pattern recognition molecules (pathogen sensors) that recognize conserved molecular patterns present in the pathogens but absent in the host. Peptidoglycans (PGN) are essential cell wall components of almost all bacteria, except mycoplasma lacking a cell wall, which provides the host immune system an advantage for detecting invading bacteria. Several families of pattern recognition molecules that detect PGN and PGN-derived compounds have been indentified, and the role of PGRP family members in host defense is relatively well-characterized in Drosophila. This review focuses on the role of PGRP family members in the recognition of invading bacteria and the activation and modulation of immune responses in Drosophila. Copyright © 2013 Elsevier Ltd. All rights reserved.

Automatic micropropagation of plants--the vision-system: graph rewriting as pattern recognition

NASA Astrophysics Data System (ADS)

Schwanke, Joerg; Megnet, Roland; Jensch, Peter F.

1993-03-01

The automation of plant-micropropagation is necessary to produce high amounts of biomass. Plants have to be dissected on particular cutting-points. A vision-system is needed for the recognition of the cutting-points on the plants. With this background, this contribution is directed to the underlying formalism to determine cutting-points on abstract-plant models. We show the usefulness of pattern recognition by graph-rewriting along with some examples in this context.

Age-related increases in false recognition: the role of perceptual and conceptual similarity.

PubMed

Pidgeon, Laura M; Morcom, Alexa M

2014-01-01

Older adults (OAs) are more likely to falsely recognize novel events than young adults, and recent behavioral and neuroimaging evidence points to a reduced ability to distinguish overlapping information due to decline in hippocampal pattern separation. However, other data suggest a critical role for semantic similarity. Koutstaal et al. [(2003) false recognition of abstract vs. common objects in older and younger adults: testing the semantic categorization account, J. Exp. Psychol. Learn. 29, 499-510] reported that OAs were only vulnerable to false recognition of items with pre-existing semantic representations. We replicated Koutstaal et al.'s (2003) second experiment and examined the influence of independently rated perceptual and conceptual similarity between stimuli and lures. At study, young and OAs judged the pleasantness of pictures of abstract (unfamiliar) and concrete (familiar) items, followed by a surprise recognition test including studied items, similar lures, and novel unrelated items. Experiment 1 used dichotomous "old/new" responses at test, while in Experiment 2 participants were also asked to judge lures as "similar," to increase explicit demands on pattern separation. In both experiments, OAs showed a greater increase in false recognition for concrete than abstract items relative to the young, replicating Koutstaal et al.'s (2003) findings. However, unlike in the earlier study, there was also an age-related increase in false recognition of abstract lures when multiple similar images had been studied. In line with pattern separation accounts of false recognition, OAs were more likely to misclassify concrete lures with high and moderate, but not low degrees of rated similarity to studied items. Results are consistent with the view that OAs are particularly susceptible to semantic interference in recognition memory, and with the possibility that this reflects age-related decline in pattern separation.

Age-related increases in false recognition: the role of perceptual and conceptual similarity

PubMed Central

Pidgeon, Laura M.; Morcom, Alexa M.

2014-01-01

Older adults (OAs) are more likely to falsely recognize novel events than young adults, and recent behavioral and neuroimaging evidence points to a reduced ability to distinguish overlapping information due to decline in hippocampal pattern separation. However, other data suggest a critical role for semantic similarity. Koutstaal et al. [(2003) false recognition of abstract vs. common objects in older and younger adults: testing the semantic categorization account, J. Exp. Psychol. Learn. 29, 499–510] reported that OAs were only vulnerable to false recognition of items with pre-existing semantic representations. We replicated Koutstaal et al.’s (2003) second experiment and examined the influence of independently rated perceptual and conceptual similarity between stimuli and lures. At study, young and OAs judged the pleasantness of pictures of abstract (unfamiliar) and concrete (familiar) items, followed by a surprise recognition test including studied items, similar lures, and novel unrelated items. Experiment 1 used dichotomous “old/new” responses at test, while in Experiment 2 participants were also asked to judge lures as “similar,” to increase explicit demands on pattern separation. In both experiments, OAs showed a greater increase in false recognition for concrete than abstract items relative to the young, replicating Koutstaal et al.’s (2003) findings. However, unlike in the earlier study, there was also an age-related increase in false recognition of abstract lures when multiple similar images had been studied. In line with pattern separation accounts of false recognition, OAs were more likely to misclassify concrete lures with high and moderate, but not low degrees of rated similarity to studied items. Results are consistent with the view that OAs are particularly susceptible to semantic interference in recognition memory, and with the possibility that this reflects age-related decline in pattern separation. PMID:25368576

Image-based automatic recognition of larvae

NASA Astrophysics Data System (ADS)

Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

2010-08-01

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

Enemy at the gates: traffic at the plant cell pathogen interface.

PubMed

Hoefle, Caroline; Hückelhoven, Ralph

2008-12-01

The plant apoplast constitutes a space for early recognition of potentially harmful non-self. Basal pathogen recognition operates via dynamic sensing of conserved microbial patterns by pattern recognition receptors or of elicitor-active molecules released from plant cell walls during infection. Recognition elicits defence reactions depending on cellular export via SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) complex-mediated vesicle fusion or plasma membrane transporter activity. Lipid rafts appear also involved in focusing immunity-associated proteins to the site of pathogen contact. Simultaneously, pathogen effectors target recognition, apoplastic host proteins and transport for cell wall-associated defence. This microreview highlights most recent reports on the arms race for plant disease and immunity at the cell surface.

Utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information

DOT National Transportation Integrated Search

2009-04-28

A study was conducted to explore the utility and recognition of lines and linear patterns on electronic displays depicting aeronautical charting information, such as electronic charts and moving map displays. The goal of this research is to support t...

Analysis of chemical signals in red fire ants by gas chromatography and pattern recognition techniques

USDA-ARS?s Scientific Manuscript database

The combination of gas chromatography and pattern recognition (GC/PR) analysis is a powerful tool for investigating complicated biological problems. Clustering, mapping, discriminant development, etc. are necessary to analyze realistically large chromatographic data sets and to seek meaningful relat...

Long Term Memory for Noise: Evidence of Robust Encoding of Very Short Temporal Acoustic Patterns.

PubMed

Viswanathan, Jayalakshmi; Rémy, Florence; Bacon-Macé, Nadège; Thorpe, Simon J

2016-01-01

Recent research has demonstrated that humans are able to implicitly encode and retain repeating patterns in meaningless auditory noise. Our study aimed at testing the robustness of long-term implicit recognition memory for these learned patterns. Participants performed a cyclic/non-cyclic discrimination task, during which they were presented with either 1-s cyclic noises (CNs) (the two halves of the noise were identical) or 1-s plain random noises (Ns). Among CNs and Ns presented once, target CNs were implicitly presented multiple times within a block, and implicit recognition of these target CNs was tested 4 weeks later using a similar cyclic/non-cyclic discrimination task. Furthermore, robustness of implicit recognition memory was tested by presenting participants with looped (shifting the origin) and scrambled (chopping sounds into 10- and 20-ms bits before shuffling) versions of the target CNs. We found that participants had robust implicit recognition memory for learned noise patterns after 4 weeks, right from the first presentation. Additionally, this memory was remarkably resistant to acoustic transformations, such as looping and scrambling of the sounds. Finally, implicit recognition of sounds was dependent on participant's discrimination performance during learning. Our findings suggest that meaningless temporal features as short as 10 ms can be implicitly stored in long-term auditory memory. Moreover, successful encoding and storage of such fine features may vary between participants, possibly depending on individual attention and auditory discrimination abilities. Significance Statement Meaningless auditory patterns could be implicitly encoded and stored in long-term memory.Acoustic transformations of learned meaningless patterns could be implicitly recognized after 4 weeks.Implicit long-term memories can be formed for meaningless auditory features as short as 10 ms.Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities.

Long Term Memory for Noise: Evidence of Robust Encoding of Very Short Temporal Acoustic Patterns

PubMed Central

Viswanathan, Jayalakshmi; Rémy, Florence; Bacon-Macé, Nadège; Thorpe, Simon J.

2016-01-01

Recent research has demonstrated that humans are able to implicitly encode and retain repeating patterns in meaningless auditory noise. Our study aimed at testing the robustness of long-term implicit recognition memory for these learned patterns. Participants performed a cyclic/non-cyclic discrimination task, during which they were presented with either 1-s cyclic noises (CNs) (the two halves of the noise were identical) or 1-s plain random noises (Ns). Among CNs and Ns presented once, target CNs were implicitly presented multiple times within a block, and implicit recognition of these target CNs was tested 4 weeks later using a similar cyclic/non-cyclic discrimination task. Furthermore, robustness of implicit recognition memory was tested by presenting participants with looped (shifting the origin) and scrambled (chopping sounds into 10− and 20-ms bits before shuffling) versions of the target CNs. We found that participants had robust implicit recognition memory for learned noise patterns after 4 weeks, right from the first presentation. Additionally, this memory was remarkably resistant to acoustic transformations, such as looping and scrambling of the sounds. Finally, implicit recognition of sounds was dependent on participant's discrimination performance during learning. Our findings suggest that meaningless temporal features as short as 10 ms can be implicitly stored in long-term auditory memory. Moreover, successful encoding and storage of such fine features may vary between participants, possibly depending on individual attention and auditory discrimination abilities. Significance Statement Meaningless auditory patterns could be implicitly encoded and stored in long-term memory.Acoustic transformations of learned meaningless patterns could be implicitly recognized after 4 weeks.Implicit long-term memories can be formed for meaningless auditory features as short as 10 ms.Successful encoding and long-term implicit recognition of meaningless patterns may strongly depend on individual attention and auditory discrimination abilities. PMID:27932941

The Psychophysics of Algebra Expertise: Mathematics Perceptual Learning Interventions Produce Durable Encoding Changes

ERIC Educational Resources Information Center

Bufford, Carolyn A.; Mettler, Everett; Geller, Emma H.; Kellman, Philip J.

2014-01-01

Mathematics requires thinking but also pattern recognition. Recent research indicates that perceptual learning (PL) interventions facilitate discovery of structure and recognition of patterns in mathematical domains, as assessed by tests of mathematical competence. Here we sought direct evidence that a brief perceptual learning module (PLM)…

Summary of 1971 pattern recognition program development

NASA Technical Reports Server (NTRS)

Whitley, S. L.

1972-01-01

Eight areas related to pattern recognition analysis at the Earth Resources Laboratory are discussed: (1) background; (2) Earth Resources Laboratory goals; (3) software problems/limitations; (4) operational problems/limitations; (5) immediate future capabilities; (6) Earth Resources Laboratory data analysis system; (7) general program needs and recommendations; and (8) schedule and milestones.

Pattern Recognition by Retina-Like Devices.

ERIC Educational Resources Information Center

Weiman, Carl F. R.; Rothstein, Jerome

This study has investigated some pattern recognition capabilities of devices consisting of arrays of cooperating elements acting in parallel. The problem of recognizing straight lines in general position on the quadratic lattice has been completely solved by applying parallel acting algorithms to a special code for lines on the lattice. The…

Cognitive Development and Reading Processes. Developmental Program Report Number 76.

ERIC Educational Resources Information Center

West, Richard F.

In discussing the relationship between cognitive development (perception, pattern recognition, and memory) and reading processes, this paper especially emphasizes developmental factors. After an overview of some issues that bear on how written language is processed, the paper presents a discussion of pattern recognition, including general pattern…

Optical and digital pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 13-15, 1987

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Editor); Schenker, Paul (Editor)

1987-01-01

The papers presented in this volume provide an overview of current research in both optical and digital pattern recognition, with a theme of identifying overlapping research problems and methodologies. Topics discussed include image analysis and low-level vision, optical system design, object analysis and recognition, real-time hybrid architectures and algorithms, high-level image understanding, and optical matched filter design. Papers are presented on synthetic estimation filters for a control system; white-light correlator character recognition; optical AI architectures for intelligent sensors; interpreting aerial photographs by segmentation and search; and optical information processing using a new photopolymer.

Recognition and classification of oscillatory patterns of electric brain activity using artificial neural network approach

NASA Astrophysics Data System (ADS)

Pchelintseva, Svetlana V.; Runnova, Anastasia E.; Musatov, Vyacheslav Yu.; Hramov, Alexander E.

2017-03-01

In the paper we study the problem of recognition type of the observed object, depending on the generated pattern and the registered EEG data. EEG recorded at the time of displaying cube Necker characterizes appropriate state of brain activity. As an image we use bistable image Necker cube. Subject selects the type of cube and interpret it either as aleft cube or as the right cube. To solve the problem of recognition, we use artificial neural networks. In our paper to create a classifier we have considered a multilayer perceptron. We examine the structure of the artificial neural network and define cubes recognition accuracy.

Performance Study of the First 2D Prototype of Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deptuch, Gregory; Hoff, James; Jindariani, Sergo

Extremely fast pattern recognition capabilities are necessary to find and fit billions of tracks at the hardware trigger level produced every second anticipated at high luminosity LHC (HL-LHC) running conditions. Associative Memory (AM) based approaches for fast pattern recognition have been proposed as a potential solution to the tracking trigger. However, at the HL-LHC, there is much less time available and speed performance must be improved over previous systems while maintaining a comparable number of patterns. The Vertically Integrated Pattern Recognition Associative Memory (VIPRAM) Project aims to achieve the target pattern density and performance goal using 3DIC technology. The firstmore » step taken in the VIPRAM work was the development of a 2D prototype (protoVIPRAM00) in which the associative memory building blocks were designed to be compatible with the 3D integration. In this paper, we present the results from extensive performance studies of the protoVIPRAM00 chip in both realistic HL-LHC and extreme conditions. Results indicate that the chip operates at the design frequency of 100 MHz with perfect correctness in realistic conditions and conclude that the building blocks are ready for 3D stacking. We also present performance boundary characterization of the chip under extreme conditions.« less

Do pattern recognition skills transfer across sports? A preliminary analysis.

PubMed

Smeeton, Nicholas J; Ward, Paul; Williams, A Mark

2004-02-01

The ability to recognize patterns of play is fundamental to performance in team sports. While typically assumed to be domain-specific, pattern recognition skills may transfer from one sport to another if similarities exist in the perceptual features and their relations and/or the strategies used to encode and retrieve relevant information. A transfer paradigm was employed to compare skilled and less skilled soccer, field hockey and volleyball players' pattern recognition skills. Participants viewed structured and unstructured action sequences from each sport, half of which were randomly represented with clips not previously seen. The task was to identify previously viewed action sequences quickly and accurately. Transfer of pattern recognition skill was dependent on the participant's skill, sport practised, nature of the task and degree of structure. The skilled soccer and hockey players were quicker than the skilled volleyball players at recognizing structured soccer and hockey action sequences. Performance differences were not observed on the structured volleyball trials between the skilled soccer, field hockey and volleyball players. The skilled field hockey and soccer players were able to transfer perceptual information or strategies between their respective sports. The less skilled participants' results were less clear. Implications for domain-specific expertise, transfer and diversity across domains are discussed.

An Indoor Pedestrian Positioning Method Using HMM with a Fuzzy Pattern Recognition Algorithm in a WLAN Fingerprint System

PubMed Central

Ni, Yepeng; Liu, Jianbo; Liu, Shan; Bai, Yaxin

2016-01-01

With the rapid development of smartphones and wireless networks, indoor location-based services have become more and more prevalent. Due to the sophisticated propagation of radio signals, the Received Signal Strength Indicator (RSSI) shows a significant variation during pedestrian walking, which introduces critical errors in deterministic indoor positioning. To solve this problem, we present a novel method to improve the indoor pedestrian positioning accuracy by embedding a fuzzy pattern recognition algorithm into a Hidden Markov Model. The fuzzy pattern recognition algorithm follows the rule that the RSSI fading has a positive correlation to the distance between the measuring point and the AP location even during a dynamic positioning measurement. Through this algorithm, we use the RSSI variation trend to replace the specific RSSI value to achieve a fuzzy positioning. The transition probability of the Hidden Markov Model is trained by the fuzzy pattern recognition algorithm with pedestrian trajectories. Using the Viterbi algorithm with the trained model, we can obtain a set of hidden location states. In our experiments, we demonstrate that, compared with the deterministic pattern matching algorithm, our method can greatly improve the positioning accuracy and shows robust environmental adaptability. PMID:27618053

STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

DTIC Science & Technology

ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

Prediction of acoustic feature parameters using myoelectric signals.

PubMed

Lee, Ki-Seung

2010-07-01

It is well-known that a clear relationship exists between human voices and myoelectric signals (MESs) from the area of the speaker's mouth. In this study, we utilized this information to implement a speech synthesis scheme in which MES alone was used to predict the parameters characterizing the vocal-tract transfer function of specific speech signals. Several feature parameters derived from MES were investigated to find the optimal feature for maximization of the mutual information between the acoustic and the MES features. After the optimal feature was determined, an estimation rule for the acoustic parameters was proposed, based on a minimum mean square error (MMSE) criterion. In a preliminary study, 60 isolated words were used for both objective and subjective evaluations. The results showed that the average Euclidean distance between the original and predicted acoustic parameters was reduced by about 30% compared with the average Euclidean distance of the original parameters. The intelligibility of the synthesized speech signals using the predicted features was also evaluated. A word-level identification ratio of 65.5% and a syllable-level identification ratio of 73% were obtained through a listening test.

Estimation of Muscle Force Based on Neural Drive in a Hemispheric Stroke Survivor.

PubMed

Dai, Chenyun; Zheng, Yang; Hu, Xiaogang

2018-01-01

Robotic assistant-based therapy holds great promise to improve the functional recovery of stroke survivors. Numerous neural-machine interface techniques have been used to decode the intended movement to control robotic systems for rehabilitation therapies. In this case report, we tested the feasibility of estimating finger extensor muscle forces of a stroke survivor, based on the decoded descending neural drive through population motoneuron discharge timings. Motoneuron discharge events were obtained by decomposing high-density surface electromyogram (sEMG) signals of the finger extensor muscle. The neural drive was extracted from the normalized frequency of the composite discharge of the motoneuron pool. The neural-drive-based estimation was also compared with the classic myoelectric-based estimation. Our results showed that the neural-drive-based approach can better predict the force output, quantified by lower estimation errors and higher correlations with the muscle force, compared with the myoelectric-based estimation. Our findings suggest that the neural-drive-based approach can potentially be used as a more robust interface signal for robotic therapies during the stroke rehabilitation.

Two-dimensional myoelectric control of a robotic arm for upper limb amputees

NASA Astrophysics Data System (ADS)

López Celani, Natalia M.; Soria, Carlos M.; Orosco, Eugenio C.; di Sciascio, Fernando A.; Valentinuzzi, Max E.

2007-11-01

Rehabilitation engineering and medicine have become integral and significant parts of health care services, particularly and unfortunately in the last three or four decades, because of wars, terrorism and large number of car accidents. Amputees show a high rate of rejection to wear prosthetic devices, often because of lack of an adequate period of adaptation. A robotic arm may appear as a good preliminary stage. To test the hypothesis, myoelectric signals from two upper limb amputees and from four normal volunteers were fed, via adequate electronic conditioning and using MATLAB, to an industrial robotic arm. Proportional strength control was used for two degrees of freedom (x-y plane) by means of eight signal features of control (four traditional statistics plus energy, integral of the absolute value, Willison's amplitude, waveform length and envelope) for comparison purposes, and selecting the best of them as final reference. Patients easily accepted the system and learned in short time how to operate it. Results were encouraging so that valuable training, before prosthesis is implanted, appears as good feedback; besides, these patients can be hired as specialized operators in semi-automatized industry.

Using EMG to anticipate head motion for virtual-environment applications

NASA Technical Reports Server (NTRS)

Barniv, Yair; Aguilar, Mario; Hasanbelliu, Erion

2005-01-01

In virtual environment (VE) applications, where virtual objects are presented in a see-through head-mounted display, virtual images must be continuously stabilized in space in response to user's head motion. Time delays in head-motion compensation cause virtual objects to "swim" around instead of being stable in space which results in misalignment errors when overlaying virtual and real objects. Visual update delays are a critical technical obstacle for implementing head-mounted displays in applications such as battlefield simulation/training, telerobotics, and telemedicine. Head motion is currently measurable by a head-mounted 6-degrees-of-freedom inertial measurement unit. However, even given this information, overall VE-system latencies cannot be reduced under about 25 ms. We present a novel approach to eliminating latencies, which is premised on the fact that myoelectric signals from a muscle precede its exertion of force, thereby limb or head acceleration. We thus suggest utilizing neck-muscles' myoelectric signals to anticipate head motion. We trained a neural network to map such signals onto equivalent time-advanced inertial outputs. The resulting network can achieve time advances of up to 70 ms.

Using EMG to anticipate head motion for virtual-environment applications.

PubMed

Barniv, Yair; Aguilar, Mario; Hasanbelliu, Erion

2005-06-01

In virtual environment (VE) applications, where virtual objects are presented in a see-through head-mounted display, virtual images must be continuously stabilized in space in response to user's head motion. Time delays in head-motion compensation cause virtual objects to "swim" around instead of being stable in space which results in misalignment errors when overlaying virtual and real objects. Visual update delays are a critical technical obstacle for implementing head-mounted displays in applications such as battlefield simulation/training, telerobotics, and telemedicine. Head motion is currently measurable by a head-mounted 6-degrees-of-freedom inertial measurement unit. However, even given this information, overall VE-system latencies cannot be reduced under about 25 ms. We present a novel approach to eliminating latencies, which is premised on the fact that myoelectric signals from a muscle precede its exertion of force, thereby limb or head acceleration. We thus suggest utilizing neck-muscles' myoelectric signals to anticipate head motion. We trained a neural network to map such signals onto equivalent time-advanced inertial outputs. The resulting network can achieve time advances of up to 70 ms.

Face Recognition Using Local Quantized Patterns and Gabor Filters

NASA Astrophysics Data System (ADS)

Khryashchev, V.; Priorov, A.; Stepanova, O.; Nikitin, A.

2015-05-01

The problem of face recognition in a natural or artificial environment has received a great deal of researchers' attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to accurately recognize the person in difficult scenarios, e.g. low resolution, low contrast, pose variations, etc. We therefore propose an approach for accurate and robust face recognition by using local quantized patterns and Gabor filters. The estimation of the eye centers is used as a preprocessing stage. The evaluation of our algorithm on different samples from a standardized FERET database shows that our method is invariant to the general variations of lighting, expression, occlusion and aging. The proposed approach allows about 20% correct recognition accuracy increase compared with the known face recognition algorithms from the OpenCV library. The additional use of Gabor filters can significantly improve the robustness to changes in lighting conditions.

Speaker normalization for chinese vowel recognition in cochlear implants.

PubMed

Luo, Xin; Fu, Qian-Jie

2005-07-01

Because of the limited spectra-temporal resolution associated with cochlear implants, implant patients often have greater difficulty with multitalker speech recognition. The present study investigated whether multitalker speech recognition can be improved by applying speaker normalization techniques to cochlear implant speech processing. Multitalker Chinese vowel recognition was tested with normal-hearing Chinese-speaking subjects listening to a 4-channel cochlear implant simulation, with and without speaker normalization. For each subject, speaker normalization was referenced to the speaker that produced the best recognition performance under conditions without speaker normalization. To match the remaining speakers to this "optimal" output pattern, the overall frequency range of the analysis filter bank was adjusted for each speaker according to the ratio of the mean third formant frequency values between the specific speaker and the reference speaker. Results showed that speaker normalization provided a small but significant improvement in subjects' overall recognition performance. After speaker normalization, subjects' patterns of recognition performance across speakers changed, demonstrating the potential for speaker-dependent effects with the proposed normalization technique.

Visual Scanning Patterns and Executive Function in Relation to Facial Emotion Recognition in Aging

PubMed Central

Circelli, Karishma S.; Clark, Uraina S.; Cronin-Golomb, Alice

2012-01-01

Objective The ability to perceive facial emotion varies with age. Relative to younger adults (YA), older adults (OA) are less accurate at identifying fear, anger, and sadness, and more accurate at identifying disgust. Because different emotions are conveyed by different parts of the face, changes in visual scanning patterns may account for age-related variability. We investigated the relation between scanning patterns and recognition of facial emotions. Additionally, as frontal-lobe changes with age may affect scanning patterns and emotion recognition, we examined correlations between scanning parameters and performance on executive function tests. Methods We recorded eye movements from 16 OA (mean age 68.9) and 16 YA (mean age 19.2) while they categorized facial expressions and non-face control images (landscapes), and administered standard tests of executive function. Results OA were less accurate than YA at identifying fear (p<.05, r=.44) and more accurate at identifying disgust (p<.05, r=.39). OA fixated less than YA on the top half of the face for disgust, fearful, happy, neutral, and sad faces (p’s<.05, r’s≥.38), whereas there was no group difference for landscapes. For OA, executive function was correlated with recognition of sad expressions and with scanning patterns for fearful, sad, and surprised expressions. Conclusion We report significant age-related differences in visual scanning that are specific to faces. The observed relation between scanning patterns and executive function supports the hypothesis that frontal-lobe changes with age may underlie some changes in emotion recognition. PMID:22616800

Recognition of surface lithologic and topographic patterns in southwest Colorado with ADP techniques

NASA Technical Reports Server (NTRS)

Melhorn, W. N.; Sinnock, S.

1973-01-01

Analysis of ERTS-1 multispectral data by automatic pattern recognition procedures is applicable toward grappling with current and future resource stresses by providing a means for refining existing geologic maps. The procedures used in the current analysis already yield encouraging results toward the eventual machine recognition of extensive surface lithologic and topographic patterns. Automatic mapping of a series of hogbacks, strike valleys, and alluvial surfaces along the northwest flank of the San Juan Basin in Colorado can be obtained by minimal man-machine interaction. The determination of causes for separable spectral signatures is dependent upon extensive correlation of micro- and macro field based ground truth observations and aircraft underflight data with the satellite data.

Infrared Ship Classification Using A New Moment Pattern Recognition Concept

NASA Astrophysics Data System (ADS)

Casasent, David; Pauly, John; Fetterly, Donald

1982-03-01

An analysis of the statistics of the moments and the conventional invariant moments shows that the variance of the latter become quite large as the order of the moments and the degree of invariance increases. Moreso, the need to whiten the error volume increases with the order and degree, but so does the computational load associated with computing the whitening operator. We thus advance a new estimation approach to the use of moments in pattern recog-nition that overcomes these problems. This work is supported by experimental verification and demonstration on an infrared ship pattern recognition problem. The computational load associated with our new algorithm is also shown to be very low.

Intelligent data processing of an ultrasonic sensor system for pattern recognition improvements

NASA Astrophysics Data System (ADS)

Na, Seung You; Park, Min-Sang; Hwang, Won-Gul; Kee, Chang-Doo

1999-05-01

Though conventional time-of-flight ultrasonic sensor systems are popular due to the advantages of low cost and simplicity, the usage of the sensors is rather narrowly restricted within object detection and distance readings. There is a strong need to enlarge the amount of environmental information for mobile applications to provide intelligent autonomy. Wide sectors of such neighboring object recognition problems can be satisfactorily handled with coarse vision data such as sonar maps instead of accurate laser or optic measurements. For the usage of object pattern recognition, ultrasonic senors have inherent shortcomings of poor directionality and specularity which result in low spatial resolution and indistinctiveness of object patterns. To resolve these problems an array of increased number of sensor elements has been used for large objects. In this paper we propose a method of sensor array system with improved recognition capability using electronic circuits accompanying the sensor array and neuro-fuzzy processing of data fusion. The circuit changes transmitter output voltages of array elements in several steps. Relying upon the known sensor characteristics, a set of different return signals from neighboring senors is manipulated to provide an enhanced pattern recognition in the aspects of inclination angle, size and shift as well as distance of objects. The results show improved resolution of the measurements for smaller targets.

Foundations for a syntatic pattern recognition system for genomic DNA sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

Immediate effects of acupuncture on biceps brachii muscle function in healthy and post-stroke subjects

PubMed Central

2012-01-01

Background The effects of acupuncture on muscle function in healthy subjects are contradictory and cannot be extrapolated to post-stroke patients. This study evaluated the immediate effects of manual acupuncture on myoelectric activity and isometric force in healthy and post-stroke patients. Methods A randomized clinical trial, with parallel groups, single-blinded study design, was conducted with 32 healthy subjects and 15 post-stroke patients with chronic hemiparesis. Surface electromyography from biceps brachii during maximal isometric voluntary tests was performed before and after 20-min intermittent, and manual stimulation of acupoints Quchi (LI11) or Tianquan (PC2). Pattern differentiation was performed by an automated method based on logistic regression equations. Results Healthy subjects showed a decrease in the root mean-squared (RMS) values after the stimulation of LI11 (pre: 1.392 ± 0.826 V; post: 0.612 ± 0.0.320 V; P = 0.002) and PC2 (pre: 1.494 ± 0.826 V; post: 0.623 ± 0.320 V; P = 0.001). Elbow flexion maximal isometric voluntary contraction (MIVC) was not significantly different after acupuncture stimulation of LI11 (pre: 22.2 ± 10.7 kg; post: 21.7 ± 9.5 kg; P = 0.288) or PC2 (pre: 18.8 ± 4.6 kg; post: 18.7 ± 6.0 kg; P = 0.468). Post-stroke patients did not exhibit any significant decrease in the RMS values after the stimulation of LI11 (pre: 0.627 ± 0.335 V; post: 0.530 ± 0.272 V; P = 0.187) and PC2 (pre: 0.601 ± 0.258 V; post: 0.591 ± 0.326 V; P = 0.398). Also, no significant decrease in the MIVC value was observed after the stimulation of LI11 (pre: 9.6 ± 3.9 kg; post: 9.6 ± 4.7 kg; P = 0.499) or PC2 (pre: 10.7 ± 5.6 kg; post: 10.2 ± 5.3 kg; P = 0.251). Different frequency of patterns was observed among healthy subjects and post-stroke patients groups (χ2 = 9.759; P = 0.021). Conclusion Manual acupuncture provides sufficient neuromuscular stimuli to promote immediate changes in motor unit gross recruitment without repercussion in maximal force output in healthy subjects. Post-stroke patients did not exhibit significant reduction on the myoelectric activity and maximal force output after manual acupuncture and needs further evaluation with a larger sample. Trial registration Brazilian Clinical Trials Registry RBR-5g7xqh. PMID:22417176

Intermanual transfer in training with an upper-limb myoelectric prosthesis simulator: a mechanistic, randomized, pretest-posttest study.

PubMed

Romkema, Sietske; Bongers, Raoul M; van der Sluis, Corry K

2013-01-01

Intermanual transfer may improve prosthetic handling and acceptance if used in training soon after an amputation. The purpose of this study was to determine whether intermanual transfer effects can be detected after training with a myoelectric upper-limb prosthesis simulator. A mechanistic, randomized, pretest-posttest design was used. A total of 48 right-handed participants (25 women, 23 men) who were able-bodied were randomly assigned to an experimental group or a control group. The experimental group performed a training program of 5 days' duration using the prosthesis simulator. To determine the improvement in skill, a test was administered before, immediately after, and 6 days after training. The control group only performed the tests. Training was performed with the unaffected arm, and tests were performed with the affected arm (the affected arm simulating an amputated limb). Half of the participants were tested with the dominant arm and half with the nondominant arm. Initiation time was defined as the time from starting signal until start of the movement, movement time was defined as the time from the beginning of the movement until completion of the task, and force control was defined as the maximal applied force on a deformable object. The movement time decreased significantly more in the experimental group (F₂,₉₂=7.42, P=.001, η²(G)=.028) when compared with the control group. This finding is indicative of faster handling of the prosthesis. No statistically significant differences were found between groups with regard to initiation time and force control. We did not find a difference in intermanual transfer between the dominant and nondominant arms. The training utilized participants who were able-bodied in a laboratory setting and focused only on transradial amputations. Intermanual transfer was present in the affected arm after training the unaffected arm with a myoelectric prosthesis simulator, and this effect did not depend on laterality. This effect may improve rehabilitation of patients with an upper-limb amputation.

Case-study of a user-driven prosthetic arm design: bionic hand versus customized body-powered technology in a highly demanding work environment.

PubMed

Schweitzer, Wolf; Thali, Michael J; Egger, David

2018-01-03

Prosthetic arm research predominantly focuses on "bionic" but not body-powered arms. However, any research orientation along user needs requires sufficiently precise workplace specifications and sufficiently hard testing. Forensic medicine is a demanding environment, also physically, also for non-disabled people, on several dimensions (e.g., distances, weights, size, temperature, time). As unilateral below elbow amputee user, the first author is in a unique position to provide direct comparison of a "bionic" myoelectric iLimb Revolution (Touch Bionics) and a customized body-powered arm which contains a number of new developments initiated or developed by the user: (1) quick lock steel wrist unit; (2) cable mount modification; (3) cast shape modeled shoulder anchor; (4) suspension with a soft double layer liner (Ohio Willowwood) and tube gauze (Molnlycke) combination. The iLimb is mounted on an epoxy socket; a lanyard fixed liner (Ohio Willowwood) contains magnetic electrodes (Liberating Technologies). An on the job usage of five years was supplemented with dedicated and focused intensive two-week use tests at work for both systems. The side-by-side comparison showed that the customized body-powered arm provides reliable, comfortable, effective, powerful as well as subtle service with minimal maintenance; most notably, grip reliability, grip force regulation, grip performance, center of balance, component wear down, sweat/temperature independence and skin state are good whereas the iLimb system exhibited a number of relevant serious constraints. Research and development of functional prostheses may want to focus on body-powered technology as it already performs on manually demanding and heavy jobs whereas eliminating myoelectric technology's constraints seems out of reach. Relevant testing could be developed to help expediting this. This is relevant as Swiss disability insurance specifically supports prostheses that enable actual work integration. Myoelectric and cosmetic arm improvement may benefit from a less forgiving focus on perfecting anthropomorphic appearance.

Effect of bowel decontamination with metronidazole and vancomycin on gastroduodenal myoelectric activity.

PubMed

Królczyk, Grzegorz; Czupryna, Antoni; Sobocki, Jacek; Nowak, Lukasz; Zurowski, Daniel; Szatyłowiczi, Jadwiga; Strus, Magdalena; Thor, Piotr J

2004-01-01

It is well recognized that prolonged antibiotic therapy leading to gut decontamination often results in side effects and may lead to colonization of gut with pathologic bacteria. Changes of a gut microflora could play a role in dysmotility of gastrointestinal tract. The aim of the study was to evaluate influence of intraluminal colon anaerobic and aerobic bacterial flora on myoelectric activity of duodenum and stomach. A myoelectric activity recordings using electrodes implanted on small bowel of the conscious rats were performed. Group I was scheduled for control recording, group II for recordings in 4th day after metronidazole (M) administration (30 mg/kg) and group III for recordings after vancomycin (V) administration (15 mg/kg) respectively. Rat's stools were cultured for confirmation of changes in colon flora composition. Recordings were previously filtered digitally with bandwidth filter 0.01-0.1 Hz and 0.1-1.0 Hz to extract gastric and duodenal slow wave respectively and than analyzed with Fast Fourier Transformation. Baseline duodenal slow wave frequency in control group revealed 0.60 +/- 0.05 Hz. M increased slow waves frequency to 0.64 +/- 0.13 Hz and V did not 0.58 +/- 0.09 Hz (p > 0.05). Slow wave dominant frequency of the stomach showed decrease of frequency from control 0.035 +/- 0.04 to 0.025 +/- 0.06 Hz after M (p < 0.05). Pretreatment with V also did not influence slow wave dominant frequency in comparison to control group (0.036 +/- 0.07 Hz, p > 0.05). Only pretreatment with M significantly decreased gastric slow wave frequency. One can speculate that M effects are related not only to gut decontamination but also directly affects ENS. We propose hypothesis that M influence on slow wave frequency may be related not only to its antimicrobial activity but to its potential neurotoxic action on intramural ENS neurons.

Case Report on the Use of a Custom Myoelectric Elbow-Wrist-Hand Orthosis for the Remediation of Upper Extremity Paresis and Loss of Function in Chronic Stroke.

PubMed

Dunaway, Stefanie; Dezsi, D Brianna; Perkins, Jessica; Tran, Daniel; Naft, Jonathan

2017-07-01

This case study describes the application of a commercially available, custom myoelectric elbow-wrist-hand orthosis (MEWHO), on a veteran diagnosed with chronic stroke with residual left hemiparesis. The MEWHO provides powered active assistance for elbow flexion/extension and 3 jaw chuck grip. It is a noninvasive orthosis that is driven by the user's electromyographic signal. Experience with the MEWHO and associated outcomes are reported. The participant completed 21 outpatient occupational therapy sessions that incorporated the use of a custom MEWHO without grasp capability into traditional occupational therapy interventions. He then upgraded to an advanced version of that MEWHO that incorporated grasp capability and completed an additional 14 sessions. Range of motion, strength, spasticity (Modified Ashworth Scale [MAS]), the Box and Blocks test, the Fugl-Meyer assessment and observation of functional tasks were used to track progress. The participant also completed a home log and a manufacturers' survey to track usage and user satisfaction over a 6-month period. Active left upper extremity range of motion and strength increased significantly (both with and without the MEWHO) and tone decreased, demonstrating both a training and an assistive effect. The participant also demonstrated an improved ability to incorporate his affected extremity (with the MEWHO) into a wide variety of bilateral, gross motor activities of daily living such as carrying a laundry basket, lifting heavy objects (e.g. a chair), using a tape measure, meal preparation, and opening doors. Custom myoelectric orthoses offer an exciting opportunity for individuals diagnosed with a variety of neurological conditions to make advancements toward their recovery and independence, and warrant further research into their training effects as well as their use as assistive devices. Reprint & Copyright © 2017 Association of Military Surgeons of the U.S.

The time course of individual face recognition: A pattern analysis of ERP signals.

PubMed

Nemrodov, Dan; Niemeier, Matthias; Mok, Jenkin Ngo Yin; Nestor, Adrian

2016-05-15

An extensive body of work documents the time course of neural face processing in the human visual cortex. However, the majority of this work has focused on specific temporal landmarks, such as N170 and N250 components, derived through univariate analyses of EEG data. Here, we take on a broader evaluation of ERP signals related to individual face recognition as we attempt to move beyond the leading theoretical and methodological framework through the application of pattern analysis to ERP data. Specifically, we investigate the spatiotemporal profile of identity recognition across variation in emotional expression. To this end, we apply pattern classification to ERP signals both in time, for any single electrode, and in space, across multiple electrodes. Our results confirm the significance of traditional ERP components in face processing. At the same time though, they support the idea that the temporal profile of face recognition is incompletely described by such components. First, we show that signals associated with different facial identities can be discriminated from each other outside the scope of these components, as early as 70ms following stimulus presentation. Next, electrodes associated with traditional ERP components as well as, critically, those not associated with such components are shown to contribute information to stimulus discriminability. And last, the levels of ERP-based pattern discrimination are found to correlate with recognition accuracy across subjects confirming the relevance of these methods for bridging brain and behavior data. Altogether, the current results shed new light on the fine-grained time course of neural face processing and showcase the value of novel methods for pattern analysis to investigating fundamental aspects of visual recognition. Copyright © 2016 Elsevier Inc. All rights reserved.

Three-Way Analysis of Spectrospatial Electromyography Data: Classification and Interpretation

PubMed Central

Kauppi, Jukka-Pekka; Hahne, Janne; Müller, Klaus-Robert; Hyvärinen, Aapo

2015-01-01

Classifying multivariate electromyography (EMG) data is an important problem in prosthesis control as well as in neurophysiological studies and diagnosis. With modern high-density EMG sensor technology, it is possible to capture the rich spectrospatial structure of the myoelectric activity. We hypothesize that multi-way machine learning methods can efficiently utilize this structure in classification as well as reveal interesting patterns in it. To this end, we investigate the suitability of existing three-way classification methods to EMG-based hand movement classification in spectrospatial domain, as well as extend these methods by sparsification and regularization. We propose to use Fourier-domain independent component analysis as preprocessing to improve classification and interpretability of the results. In high-density EMG experiments on hand movements across 10 subjects, three-way classification yielded higher average performance compared with state-of-the art classification based on temporal features, suggesting that the three-way analysis approach can efficiently utilize detailed spectrospatial information of high-density EMG. Phase and amplitude patterns of features selected by the classifier in finger-movement data were found to be consistent with known physiology. Thus, our approach can accurately resolve hand and finger movements on the basis of detailed spectrospatial information, and at the same time allows for physiological interpretation of the results. PMID:26039100

Muscle activities used by young and old adults when stepping to regain balance during a forward fall.

PubMed

Thelen, D G; Muriuki, M; James, J; Schultz, A B; Ashton-Miller, J A; Alexander, N B

2000-04-01

The current study was undertaken to determine if age-related differences in muscle activities might relate to older adults being significantly less able than young adults to recover balance during a forward fall. Fourteen young and twelve older healthy males were released from forward leans of various magnitudes and asked to regain standing balance by taking a single forward step. Myoelectric signals were recorded from 12 lower extremity muscles and processed to compare the muscle activation patterns of young and older adults. Young adults successfully recovered from significantly larger leans than older adults using a single step (32.2 degrees vs. 23.5 degrees ). Muscular latency times, the time between release and activity onset, ranged from 73 to 114 ms with no significant age-related differences in the shortest muscular latency times. The overall response muscular activation patterns were similar for young and older adults. However older adults were slower to deactivate three stance leg muscles and also demonstrated delays in activating the step leg hip flexors and knee extensors prior to and during the swing phase. In the forward fall paradigm studied, age-differences in balance recovery performance do not seem due to slowness in response onset but may relate to differences in muscle activation timing during the stepping movement.

Mechanisms and Neural Basis of Object and Pattern Recognition: A Study with Chess Experts

ERIC Educational Resources Information Center

Bilalic, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-01-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and…

Designing Clinical Examples To Promote Pattern Recognition: Nursing Education-Based Research and Practical Applications.

ERIC Educational Resources Information Center

Welk, Dorette Sugg

2002-01-01

Sophomore nursing students (n=162) examined scenarios depicting typical and atypical signs of heart attack. Examples were structured to include essential and nonessential symptoms, enabling pattern recognition and improved performance. The method provides a way to prepare students to anticipate and recognize life-threatening situations. (Contains…

PATTERN RECOGNITION APPROACH TO MEDICAL DIAGNOSIS,

DTIC Science & Technology

A sequential method of pattern recognition was used to recognize hyperthyroidism in a sample of 2219 patients being treated at the Straub Clinic in...the most prominent class features are selected. Thus, the symptoms which best distinguish hyperthyroidism are extracted at every step and the number of tests required to reach a diagnosis is reduced. (Author)

Aptamer Recognition of Multiplexed Small-Molecule-Functionalized Substrates.

PubMed

Nakatsuka, Nako; Cao, Huan H; Deshayes, Stephanie; Melkonian, Arin Lucy; Kasko, Andrea M; Weiss, Paul S; Andrews, Anne M

2018-05-31

Aptamers are chemically synthesized oligonucleotides or peptides with molecular recognition capabilities. We investigated recognition of substrate-tethered small-molecule targets, using neurotransmitters as examples, and fluorescently labeled DNA aptamers. Substrate regions patterned via microfluidic channels with dopamine or L-tryptophan were selectively recognized by previously identified dopamine or L-tryptophan aptamers, respectively. The on-substrate dissociation constant determined for the dopamine aptamer was comparable to, though slightly greater than the previously determined solution dissociation constant. Using pre-functionalized neurotransmitter-conjugated oligo(ethylene glycol) alkanethiols and microfluidics patterning, we produced multiplexed substrates to capture and to sort aptamers. Substrates patterned with L-DOPA, L-DOPS, and L-5-HTP enabled comparison of the selectivity of the dopamine aptamer for different targets via simultaneous determination of in situ binding constants. Thus, beyond our previous demonstrations of recognition by protein binding partners (i.e., antibodies and G-protein-coupled receptors), strategically optimized small-molecule-functionalized substrates show selective recognition of nucleic acid binding partners. These substrates are useful for side-by-side target comparisons, and future identification and characterization of novel aptamers targeting neurotransmitters or other important small-molecules.

Classifier dependent feature preprocessing methods

NASA Astrophysics Data System (ADS)

Rodriguez, Benjamin M., II; Peterson, Gilbert L.

2008-04-01

In mobile applications, computational complexity is an issue that limits sophisticated algorithms from being implemented on these devices. This paper provides an initial solution to applying pattern recognition systems on mobile devices by combining existing preprocessing algorithms for recognition. In pattern recognition systems, it is essential to properly apply feature preprocessing tools prior to training classification models in an attempt to reduce computational complexity and improve the overall classification accuracy. The feature preprocessing tools extended for the mobile environment are feature ranking, feature extraction, data preparation and outlier removal. Most desktop systems today are capable of processing a majority of the available classification algorithms without concern of processing while the same is not true on mobile platforms. As an application of pattern recognition for mobile devices, the recognition system targets the problem of steganalysis, determining if an image contains hidden information. The measure of performance shows that feature preprocessing increases the overall steganalysis classification accuracy by an average of 22%. The methods in this paper are tested on a workstation and a Nokia 6620 (Symbian operating system) camera phone with similar results.

Complex auditory behaviour emerges from simple reactive steering

NASA Astrophysics Data System (ADS)

Hedwig, Berthold; Poulet, James F. A.

2004-08-01

The recognition and localization of sound signals is fundamental to acoustic communication. Complex neural mechanisms are thought to underlie the processing of species-specific sound patterns even in animals with simple auditory pathways. In female crickets, which orient towards the male's calling song, current models propose pattern recognition mechanisms based on the temporal structure of the song. Furthermore, it is thought that localization is achieved by comparing the output of the left and right recognition networks, which then directs the female to the pattern that most closely resembles the species-specific song. Here we show, using a highly sensitive method for measuring the movements of female crickets, that when walking and flying each sound pulse of the communication signal releases a rapid steering response. Thus auditory orientation emerges from reactive motor responses to individual sound pulses. Although the reactive motor responses are not based on the song structure, a pattern recognition process may modulate the gain of the responses on a longer timescale. These findings are relevant to concepts of insect auditory behaviour and to the development of biologically inspired robots performing cricket-like auditory orientation.

Memory Distortion and Its Avoidance: An Event-Related Potentials Study on False Recognition and Correct Rejection

PubMed Central

Beato, Maria Soledad

2016-01-01

Memory researchers have long been captivated by the nature of memory distortions and have made efforts to identify the neural correlates of true and false memories. However, the underlying mechanisms of avoiding false memories by correctly rejecting related lures remains underexplored. In this study, we employed a variant of the Deese/Roediger-McDermott paradigm to explore neural signatures of committing and avoiding false memories. ERP were obtained for True recognition, False recognition, Correct rejection of new items, and, more importantly, Correct rejection of related lures. With these ERP data, early-frontal, left-parietal, and late right-frontal old/new effects (associated with familiarity, recollection, and monitoring processes, respectively) were analysed. Results indicated that there were similar patterns for True and False recognition in all three old/new effects analysed in our study. Also, False recognition and Correct rejection of related lures activities seemed to share common underlying familiarity-based processes. The ERP similarities between False recognition and Correct rejection of related lures disappeared when recollection processes were examined because only False recognition presented a parietal old/new effect. This finding supported the view that actual false recollections underlie false memories, providing evidence consistent with previous behavioural research and with most ERP and neuroimaging studies. Later, with the onset of monitoring processes, False recognition and Correct rejection of related lures waveforms presented, again, clearly dissociated patterns. Specifically, False recognition and True recognition showed more positive going patterns than Correct rejection of related lures signal and Correct rejection of new items signature. Since False recognition and Correct rejection of related lures triggered familiarity-recognition processes, our results suggest that deciding which items are studied is based more on recollection processes, which are later supported by monitoring processes. Results are discussed in terms of Activation-Monitoring Framework and Fuzzy Trace-Theory, the most prominent explanatory theories of false memory raised with the Deese/Roediger-McDermott paradigm. PMID:27711125

Memory Distortion and Its Avoidance: An Event-Related Potentials Study on False Recognition and Correct Rejection.

PubMed

Cadavid, Sara; Beato, Maria Soledad

2016-01-01

Memory researchers have long been captivated by the nature of memory distortions and have made efforts to identify the neural correlates of true and false memories. However, the underlying mechanisms of avoiding false memories by correctly rejecting related lures remains underexplored. In this study, we employed a variant of the Deese/Roediger-McDermott paradigm to explore neural signatures of committing and avoiding false memories. ERP were obtained for True recognition, False recognition, Correct rejection of new items, and, more importantly, Correct rejection of related lures. With these ERP data, early-frontal, left-parietal, and late right-frontal old/new effects (associated with familiarity, recollection, and monitoring processes, respectively) were analysed. Results indicated that there were similar patterns for True and False recognition in all three old/new effects analysed in our study. Also, False recognition and Correct rejection of related lures activities seemed to share common underlying familiarity-based processes. The ERP similarities between False recognition and Correct rejection of related lures disappeared when recollection processes were examined because only False recognition presented a parietal old/new effect. This finding supported the view that actual false recollections underlie false memories, providing evidence consistent with previous behavioural research and with most ERP and neuroimaging studies. Later, with the onset of monitoring processes, False recognition and Correct rejection of related lures waveforms presented, again, clearly dissociated patterns. Specifically, False recognition and True recognition showed more positive going patterns than Correct rejection of related lures signal and Correct rejection of new items signature. Since False recognition and Correct rejection of related lures triggered familiarity-recognition processes, our results suggest that deciding which items are studied is based more on recollection processes, which are later supported by monitoring processes. Results are discussed in terms of Activation-Monitoring Framework and Fuzzy Trace-Theory, the most prominent explanatory theories of false memory raised with the Deese/Roediger-McDermott paradigm.

Talker variability in audio-visual speech perception

PubMed Central

Heald, Shannon L. M.; Nusbaum, Howard C.

2014-01-01

A change in talker is a change in the context for the phonetic interpretation of acoustic patterns of speech. Different talkers have different mappings between acoustic patterns and phonetic categories and listeners need to adapt to these differences. Despite this complexity, listeners are adept at comprehending speech in multiple-talker contexts, albeit at a slight but measurable performance cost (e.g., slower recognition). So far, this talker variability cost has been demonstrated only in audio-only speech. Other research in single-talker contexts have shown, however, that when listeners are able to see a talker’s face, speech recognition is improved under adverse listening (e.g., noise or distortion) conditions that can increase uncertainty in the mapping between acoustic patterns and phonetic categories. Does seeing a talker’s face reduce the cost of word recognition in multiple-talker contexts? We used a speeded word-monitoring task in which listeners make quick judgments about target word recognition in single- and multiple-talker contexts. Results show faster recognition performance in single-talker conditions compared to multiple-talker conditions for both audio-only and audio-visual speech. However, recognition time in a multiple-talker context was slower in the audio-visual condition compared to audio-only condition. These results suggest that seeing a talker’s face during speech perception may slow recognition by increasing the importance of talker identification, signaling to the listener a change in talker has occurred. PMID:25076919

Talker variability in audio-visual speech perception.

PubMed

Heald, Shannon L M; Nusbaum, Howard C

2014-01-01

A change in talker is a change in the context for the phonetic interpretation of acoustic patterns of speech. Different talkers have different mappings between acoustic patterns and phonetic categories and listeners need to adapt to these differences. Despite this complexity, listeners are adept at comprehending speech in multiple-talker contexts, albeit at a slight but measurable performance cost (e.g., slower recognition). So far, this talker variability cost has been demonstrated only in audio-only speech. Other research in single-talker contexts have shown, however, that when listeners are able to see a talker's face, speech recognition is improved under adverse listening (e.g., noise or distortion) conditions that can increase uncertainty in the mapping between acoustic patterns and phonetic categories. Does seeing a talker's face reduce the cost of word recognition in multiple-talker contexts? We used a speeded word-monitoring task in which listeners make quick judgments about target word recognition in single- and multiple-talker contexts. Results show faster recognition performance in single-talker conditions compared to multiple-talker conditions for both audio-only and audio-visual speech. However, recognition time in a multiple-talker context was slower in the audio-visual condition compared to audio-only condition. These results suggest that seeing a talker's face during speech perception may slow recognition by increasing the importance of talker identification, signaling to the listener a change in talker has occurred.

Classifying performance impairment in response to sleep loss using pattern recognition algorithms on single session testing

PubMed Central

St. Hilaire, Melissa A.; Sullivan, Jason P.; Anderson, Clare; Cohen, Daniel A.; Barger, Laura K.; Lockley, Steven W.; Klerman, Elizabeth B.

2012-01-01

There is currently no “gold standard” marker of cognitive performance impairment resulting from sleep loss. We utilized pattern recognition algorithms to determine which features of data collected under controlled laboratory conditions could most reliably identify cognitive performance impairment in response to sleep loss using data from only one testing session, such as would occur in the “real world” or field conditions. A training set for testing the pattern recognition algorithms was developed using objective Psychomotor Vigilance Task (PVT) and subjective Karolinska Sleepiness Scale (KSS) data collected from laboratory studies during which subjects were sleep deprived for 26 – 52 hours. The algorithm was then tested in data from both laboratory and field experiments. The pattern recognition algorithm was able to identify performance impairment with a single testing session in individuals studied under laboratory conditions using PVT, KSS, length of time awake and time of day information with sensitivity and specificity as high as 82%. When this algorithm was tested on data collected under real-world conditions from individuals whose data were not in the training set, accuracy of predictions for individuals categorized with low performance impairment were as high as 98%. Predictions for medium and severe performance impairment were less accurate. We conclude that pattern recognition algorithms may be a promising method for identifying performance impairment in individuals using only current information about the individual’s behavior. Single testing features (e.g., number of PVT lapses) with high correlation with performance impairment in the laboratory setting may not be the best indicators of performance impairment under real-world conditions. Pattern recognition algorithms should be further tested for their ability to be used in conjunction with other assessments of sleepiness in real-world conditions to quantify performance impairment in response to sleep loss. PMID:22959616

Imaging in gynaecology: How good are we in identifying endometriomas?

PubMed Central

Van Holsbeke, C.; Van Calster, B.; Guerriero, S.; Savelli, L.; Leone, F.; Fischerova, D; Czekierdowski, A.; Fruscio, R.; Veldman, J.; Van de Putte, G.; Testa, A.C.; Bourne, T.; Valentin, L.; Timmerman, D.

2009-01-01

Aim: To evaluate the performance of subjective evaluation of ultrasound findings (pattern recognition) to discriminate endometriomas from other types of adnexal masses and to compare the demographic and ultrasound characteristics of the true positive cases with those cases that were presumed to be an endometrioma but proved to have a different histology (false positive cases) and the endometriomas missed by pattern recognition (false negative cases). Methods: All patients in the International Ovarian Tumor Analysis (IOTA ) studies were included for analysis. In the IOTA studies, patients with an adnexal mass that were preoperatively examined by expert sonologists following the same standardized ultrasound protocol were prospectively included in 21 international centres. Sensitivity and specificity to discriminate endometriomas from other types of adnexal masses using pattern recognition were calculated. Ultrasound and some demographic variables of the masses presumed to be an endometrioma were analysed (true positives and false positives) and compared with the variables of the endometriomas missed by pattern recognition (false negatives) as well as the true negatives. Results: IOTA phase 1, 1b and 2 included 3511 patients of which 2560 were benign (73%) and 951 malignant (27%). The dataset included 713 endometriomas. Sensitivity and specificity for pattern recognition were 81% (577/713) and 97% (2723/2798). The true positives were more often unilocular with ground glass echogenicity than the masses in any other category. Among the 75 false positive cases, 66 were benign but 9 were malignant (5 borderline tumours, 1 rare primary invasive tumour and 3 endometrioid adenocarcinomas). The presumed diagnosis suggested by the sonologist in case of a missed endometrioma was mostly functional cyst or cystadenoma. Conclusion: Expert sonologists can quite accurately discriminate endometriomas from other types of adnexal masses, but in this dataset 1% of the masses that were classified as endometrioma by pattern recognition proved to be malignancies. PMID:25478066

Remote Video Monitor of Vehicles in Cooperative Information Platform

NASA Astrophysics Data System (ADS)

Qin, Guofeng; Wang, Xiaoguo; Wang, Li; Li, Yang; Li, Qiyan

Detection of vehicles plays an important role in the area of the modern intelligent traffic management. And the pattern recognition is a hot issue in the area of computer vision. An auto- recognition system in cooperative information platform is studied. In the cooperative platform, 3G wireless network, including GPS, GPRS (CDMA), Internet (Intranet), remote video monitor and M-DMB networks are integrated. The remote video information can be taken from the terminals and sent to the cooperative platform, then detected by the auto-recognition system. The images are pretreated and segmented, including feature extraction, template matching and pattern recognition. The system identifies different models and gets vehicular traffic statistics. Finally, the implementation of the system is introduced.

The Characteristics of Binary Spike-Time-Dependent Plasticity in HfO2-Based RRAM and Applications for Pattern Recognition

NASA Astrophysics Data System (ADS)

Zhou, Zheng; Liu, Chen; Shen, Wensheng; Dong, Zhen; Chen, Zhe; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng

2017-04-01

A binary spike-time-dependent plasticity (STDP) protocol based on one resistive-switching random access memory (RRAM) device was proposed and experimentally demonstrated in the fabricated RRAM array. Based on the STDP protocol, a novel unsupervised online pattern recognition system including RRAM synapses and CMOS neurons is developed. Our simulations show that the system can efficiently compete the handwritten digits recognition task, which indicates the feasibility of using the RRAM-based binary STDP protocol in neuromorphic computing systems to obtain good performance.

Defect Localization Capabilities of a Global Detection Scheme: Spatial Pattern Recognition Using Full-field Vibration Test Data in Plates

NASA Technical Reports Server (NTRS)

Saleeb, A. F.; Prabhu, M.; Arnold, S. M. (Technical Monitor)

2002-01-01

Recently, a conceptually simple approach, based on the notion of defect energy in material space has been developed and extensively studied (from the theoretical and computational standpoints). The present study focuses on its evaluation from the viewpoint of damage localization capabilities in case of two-dimensional plates; i.e., spatial pattern recognition on surfaces. To this end, two different experimental modal test results are utilized; i.e., (1) conventional modal testing using (white noise) excitation and accelerometer-type sensors and (2) pattern recognition using Electronic speckle pattern interferometry (ESPI), a full field method capable of analyzing the mechanical vibration of complex structures. Unlike the conventional modal testing technique (using contacting accelerometers), these emerging ESPI technologies operate in a non-contacting mode, can be used even under hazardous conditions with minimal or no presence of noise and can simultaneously provide measurements for both translations and rotations. Results obtained have clearly demonstrated the robustness and versatility of the global NDE scheme developed. The vectorial character of the indices used, which enabled the extraction of distinct patterns for localizing damages proved very useful. In the context of the targeted pattern recognition paradigm, two algorithms were developed for the interrogation of test measurements; i.e., intensity contour maps for the damaged index, and the associated defect energy vector field plots.

Conformal Predictions in Multimedia Pattern Recognition

ERIC Educational Resources Information Center

Nallure Balasubramanian, Vineeth

2010-01-01

The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…

Behavioral and Physiological Neural Network Analyses: A Common Pathway toward Pattern Recognition and Prediction

ERIC Educational Resources Information Center

Ninness, Chris; Lauter, Judy L.; Coffee, Michael; Clary, Logan; Kelly, Elizabeth; Rumph, Marilyn; Rumph, Robin; Kyle, Betty; Ninness, Sharon K.

2012-01-01

Using 3 diversified datasets, we explored the pattern-recognition ability of the Self-Organizing Map (SOM) artificial neural network as applied to diversified nonlinear data distributions in the areas of behavioral and physiological research. Experiment 1 employed a dataset obtained from the UCI Machine Learning Repository. Data for this study…

Pattern Recognition Receptors in Innate Immunity, Host Defense, and Immunopathology

ERIC Educational Resources Information Center

Suresh, Rahul; Mosser, David M.

2013-01-01

Infection by pathogenic microbes initiates a set of complex interactions between the pathogen and the host mediated by pattern recognition receptors. Innate immune responses play direct roles in host defense during the early stages of infection, and they also exert a profound influence on the generation of the adaptive immune responses that ensue.…

Machine Learning Through Signature Trees. Applications to Human Speech.

ERIC Educational Resources Information Center

White, George M.

A signature tree is a binary decision tree used to classify unknown patterns. An attempt was made to develop a computer program for manipulating signature trees as a general research tool for exploring machine learning and pattern recognition. The program was applied to the problem of speech recognition to test its effectiveness for a specific…

Spectral pattern recognition of controlled substances in street samples using artificial neural network system

NASA Astrophysics Data System (ADS)

Poryvkina, Larisa; Aleksejev, Valeri; Babichenko, Sergey M.; Ivkina, Tatjana

2011-04-01

The NarTest fluorescent technique is aimed at the detection of analyte of interest in street samples by recognition of its specific spectral patterns in 3-dimentional Spectral Fluorescent Signatures (SFS) measured with NTX2000 analyzer without chromatographic or other separation of controlled substances from a mixture with cutting agents. The illicit drugs have their own characteristic SFS features which can be used for detection and identification of narcotics, however typical street sample consists of a mixture with cutting agents: adulterants and diluents. Many of them interfere the spectral shape of SFS. The expert system based on Artificial Neural Networks (ANNs) has been developed and applied for such pattern recognition in SFS of street samples of illicit drugs.

Real-Time Pattern Recognition - An Industrial Example

NASA Astrophysics Data System (ADS)

Fitton, Gary M.

1981-11-01

Rapid advancements in cost effective sensors and micro computers are now making practical the on-line implementation of pattern recognition based systems for a variety of industrial applications requiring high processing speeds. One major application area for real time pattern recognition is in the sorting of packaged/cartoned goods at high speed for automated warehousing and return goods cataloging. While there are many OCR and bar code readers available to perform these functions, it is often impractical to use such codes (package too small, adverse esthetics, poor print quality) and an approach which recognizes an item by its graphic content alone is desirable. This paper describes a specific application within the tobacco industry, that of sorting returned cigarette goods by brand and size.

Spatially Invariant Vector Quantization: A pattern matching algorithm for multiple classes of image subject matter including pathology.

PubMed

Hipp, Jason D; Cheng, Jerome Y; Toner, Mehmet; Tompkins, Ronald G; Balis, Ulysses J

2011-02-26

HISTORICALLY, EFFECTIVE CLINICAL UTILIZATION OF IMAGE ANALYSIS AND PATTERN RECOGNITION ALGORITHMS IN PATHOLOGY HAS BEEN HAMPERED BY TWO CRITICAL LIMITATIONS: 1) the availability of digital whole slide imagery data sets and 2) a relative domain knowledge deficit in terms of application of such algorithms, on the part of practicing pathologists. With the advent of the recent and rapid adoption of whole slide imaging solutions, the former limitation has been largely resolved. However, with the expectation that it is unlikely for the general cohort of contemporary pathologists to gain advanced image analysis skills in the short term, the latter problem remains, thus underscoring the need for a class of algorithm that has the concurrent properties of image domain (or organ system) independence and extreme ease of use, without the need for specialized training or expertise. In this report, we present a novel, general case pattern recognition algorithm, Spatially Invariant Vector Quantization (SIVQ), that overcomes the aforementioned knowledge deficit. Fundamentally based on conventional Vector Quantization (VQ) pattern recognition approaches, SIVQ gains its superior performance and essentially zero-training workflow model from its use of ring vectors, which exhibit continuous symmetry, as opposed to square or rectangular vectors, which do not. By use of the stochastic matching properties inherent in continuous symmetry, a single ring vector can exhibit as much as a millionfold improvement in matching possibilities, as opposed to conventional VQ vectors. SIVQ was utilized to demonstrate rapid and highly precise pattern recognition capability in a broad range of gross and microscopic use-case settings. With the performance of SIVQ observed thus far, we find evidence that indeed there exist classes of image analysis/pattern recognition algorithms suitable for deployment in settings where pathologists alone can effectively incorporate their use into clinical workflow, as a turnkey solution. We anticipate that SIVQ, and other related class-independent pattern recognition algorithms, will become part of the overall armamentarium of digital image analysis approaches that are immediately available to practicing pathologists, without the need for the immediate availability of an image analysis expert.

Receptor Kinases in Plant-Pathogen Interactions: More Than Pattern Recognition[OPEN

PubMed Central

2017-01-01

Receptor-like kinases (RLKs) and Receptor-like proteins (RLPs) play crucial roles in plant immunity, growth, and development. Plants deploy a large number of RLKs and RLPs as pattern recognition receptors (PRRs) that detect microbe- and host-derived molecular patterns as the first layer of inducible defense. Recent advances have uncovered novel PRRs, their corresponding ligands, and mechanisms underlying PRR activation and signaling. In general, PRRs associate with other RLKs and function as part of multiprotein immune complexes at the cell surface. Innovative strategies have emerged for the rapid identification of microbial patterns and their cognate PRRs. Successful pathogens can evade or block host recognition by secreting effector proteins to “hide” microbial patterns or inhibit PRR-mediated signaling. Furthermore, newly identified pathogen effectors have been shown to manipulate RLKs controlling growth and development by mimicking peptide hormones of host plants. The ongoing studies illustrate the importance of diverse plant RLKs in plant disease resistance and microbial pathogenesis. PMID:28302675

Developing Signal-Pattern-Recognition Programs

NASA Technical Reports Server (NTRS)

Shelton, Robert O.; Hammen, David

2006-01-01

Pattern Interpretation and Recognition Application Toolkit Environment (PIRATE) is a block-oriented software system that aids the development of application programs that analyze signals in real time in order to recognize signal patterns that are indicative of conditions or events of interest. PIRATE was originally intended for use in writing application programs to recognize patterns in space-shuttle telemetry signals received at Johnson Space Center's Mission Control Center: application programs were sought to (1) monitor electric currents on shuttle ac power busses to recognize activations of specific power-consuming devices, (2) monitor various pressures and infer the states of affected systems by applying a Kalman filter to the pressure signals, (3) determine fuel-leak rates from sensor data, (4) detect faults in gyroscopes through analysis of system measurements in the frequency domain, and (5) determine drift rates in inertial measurement units by regressing measurements against time. PIRATE can also be used to develop signal-pattern-recognition software for different purposes -- for example, to monitor and control manufacturing processes.

Document Form and Character Recognition using SVM

NASA Astrophysics Data System (ADS)

Park, Sang-Sung; Shin, Young-Geun; Jung, Won-Kyo; Ahn, Dong-Kyu; Jang, Dong-Sik

2009-08-01

Because of development of computer and information communication, EDI (Electronic Data Interchange) has been developing. There is OCR (Optical Character Recognition) of Pattern recognition technology for EDI. OCR contributed to changing many manual in the past into automation. But for the more perfect database of document, much manual is needed for excluding unnecessary recognition. To resolve this problem, we propose document form based character recognition method in this study. Proposed method is divided into document form recognition part and character recognition part. Especially, in character recognition, change character into binarization by using SVM algorithm and extract more correct feature value.

Intelligent Process Abnormal Patterns Recognition and Diagnosis Based on Fuzzy Logic.

PubMed

Hou, Shi-Wang; Feng, Shunxiao; Wang, Hui

2016-01-01

Locating the assignable causes by use of the abnormal patterns of control chart is a widely used technology for manufacturing quality control. If there are uncertainties about the occurrence degree of abnormal patterns, the diagnosis process is impossible to be carried out. Considering four common abnormal control chart patterns, this paper proposed a characteristic numbers based recognition method point by point to quantify the occurrence degree of abnormal patterns under uncertain conditions and a fuzzy inference system based on fuzzy logic to calculate the contribution degree of assignable causes with fuzzy abnormal patterns. Application case results show that the proposed approach can give a ranked causes list under fuzzy control chart abnormal patterns and support the abnormity eliminating.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals.

PubMed

Zhuang, Ning; Zeng, Ying; Yang, Kai; Zhang, Chi; Tong, Li; Yan, Bin

2018-03-12

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

PubMed Central

Zeng, Ying; Yang, Kai; Tong, Li; Yan, Bin

2018-01-01

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods. PMID:29534515

Associative Pattern Recognition In Analog VLSI Circuits

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1995-01-01

Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

Quantum Mechanics, Pattern Recognition, and the Mammalian Brain

NASA Astrophysics Data System (ADS)

Chapline, George

2008-10-01

Although the usual way of representing Markov processes is time asymmetric, there is a way of describing Markov processes, due to Schrodinger, which is time symmetric. This observation provides a link between quantum mechanics and the layered Bayesian networks that are often used in automated pattern recognition systems. In particular, there is a striking formal similarity between quantum mechanics and a particular type of Bayesian network, the Helmholtz machine, which provides a plausible model for how the mammalian brain recognizes important environmental situations. One interesting aspect of this relationship is that the "wake-sleep" algorithm for training a Helmholtz machine is very similar to the problem of finding the potential for the multi-channel Schrodinger equation. As a practical application of this insight it may be possible to use inverse scattering techniques to study the relationship between human brain wave patterns, pattern recognition, and learning. We also comment on whether there is a relationship between quantum measurements and consciousness.

Mining sequential patterns for protein fold recognition.

PubMed

Exarchos, Themis P; Papaloukas, Costas; Lampros, Christos; Fotiadis, Dimitrios I

2008-02-01

Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. In this work sequential pattern mining (SPM) is utilized for sequence-based fold recognition. Protein classification in terms of fold recognition plays an important role in computational protein analysis, since it can contribute to the determination of the function of a protein whose structure is unknown. Specifically, one of the most efficient SPM algorithms, cSPADE, is employed for the analysis of protein sequence. A classifier uses the extracted sequential patterns to classify proteins in the appropriate fold category. For training and evaluating the proposed method we used the protein sequences from the Protein Data Bank and the annotation of the SCOP database. The method exhibited an overall accuracy of 25% in a classification problem with 36 candidate categories. The classification performance reaches up to 56% when the five most probable protein folds are considered.

Autoregressive statistical pattern recognition algorithms for damage detection in civil structures

NASA Astrophysics Data System (ADS)

Yao, Ruigen; Pakzad, Shamim N.

2012-08-01

Statistical pattern recognition has recently emerged as a promising set of complementary methods to system identification for automatic structural damage assessment. Its essence is to use well-known concepts in statistics for boundary definition of different pattern classes, such as those for damaged and undamaged structures. In this paper, several statistical pattern recognition algorithms using autoregressive models, including statistical control charts and hypothesis testing, are reviewed as potentially competitive damage detection techniques. To enhance the performance of statistical methods, new feature extraction techniques using model spectra and residual autocorrelation, together with resampling-based threshold construction methods, are proposed. Subsequently, simulated acceleration data from a multi degree-of-freedom system is generated to test and compare the efficiency of the existing and proposed algorithms. Data from laboratory experiments conducted on a truss and a large-scale bridge slab model are then used to further validate the damage detection methods and demonstrate the superior performance of proposed algorithms.

Fuel spill identification using solid-phase extraction and solid-phase microextraction. 1. Aviation turbine fuels.

PubMed

Lavine, B K; Brzozowski, D M; Ritter, J; Moores, A J; Mayfield, H T

2001-12-01

The water-soluble fraction of aviation jet fuels is examined using solid-phase extraction and solid-phase microextraction. Gas chromatographic profiles of solid-phase extracts and solid-phase microextracts of the water-soluble fraction of kerosene- and nonkerosene-based jet fuels reveal that each jet fuel possesses a unique profile. Pattern recognition analysis reveals fingerprint patterns within the data characteristic of fuel type. By using a novel genetic algorithm (GA) that emulates human pattern recognition through machine learning, it is possible to identify features characteristic of the chromatographic profile of each fuel class. The pattern recognition GA identifies a set of features that optimize the separation of the fuel classes in a plot of the two largest principal components of the data. Because principal components maximize variance, the bulk of the information encoded by the selected features is primarily about the differences between the fuel classes.

Fuzzy tree automata and syntactic pattern recognition.

PubMed

Lee, E T

1982-04-01

An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ¿-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ¿-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,'' ``approximate elongated isosceles triangle,'' ``approximate rectangle,'' and ``approximate cross'' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,'' ``houses with high roofs,'' and ``fuzzy churches,'' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems.

Complex Event Recognition Architecture

NASA Technical Reports Server (NTRS)

Fitzgerald, William A.; Firby, R. James

2009-01-01

Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.

Facial emotion recognition deficits in relatives of children with autism are not associated with 5HTTLPR.

PubMed

Neves, Maila de Castro Lourenço das; Tremeau, Fabien; Nicolato, Rodrigo; Lauar, Hélio; Romano-Silva, Marco Aurélio; Correa, Humberto

2011-09-01

A large body of evidence suggests that several aspects of face processing are impaired in autism and that this impairment might be hereditary. This study was aimed at assessing facial emotion recognition in parents of children with autism and its associations with a functional polymorphism of the serotonin transporter (5HTTLPR). We evaluated 40 parents of children with autism and 41 healthy controls. All participants were administered the Penn Emotion Recognition Test (ER40) and were genotyped for 5HTTLPR. Our study showed that parents of children with autism performed worse in the facial emotion recognition test than controls. Analyses of error patterns showed that parents of children with autism over-attributed neutral to emotional faces. We found evidence that 5HTTLPR polymorphism did not influence the performance in the Penn Emotion Recognition Test, but that it may determine different error patterns. Facial emotion recognition deficits are more common in first-degree relatives of autistic patients than in the general population, suggesting that facial emotion recognition is a candidate endophenotype for autism.

An investigation of potential applications of OP-SAPS: Operational Sampled Analog Processors

NASA Technical Reports Server (NTRS)

Parrish, E. A.; Mcvey, E. S.

1977-01-01

The application of OP-SAP's (operational sampled analog processors) in pattern recognition system is summarized. Areas investigated include: (1) human face recognition; (2) a high-speed programmable transversal filter system; (3) discrete word (speech) recognition; and (4) a resolution enhancement system.

Foundations for a syntatic pattern recognition system for genomic DNA sequences. [Annual] report, 1 December 1991--31 March 1993

DOE Office of Scientific and Technical Information (OSTI.GOV)

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

SNR-adaptive stream weighting for audio-MES ASR.

PubMed

Lee, Ki-Seung

2008-08-01

Myoelectric signals (MESs) from the speaker's mouth region have been successfully shown to improve the noise robustness of automatic speech recognizers (ASRs), thus promising to extend their usability in implementing noise-robust ASR. In the recognition system presented herein, extracted audio and facial MES features were integrated by a decision fusion method, where the likelihood score of the audio-MES observation vector was given by a linear combination of class-conditional observation log-likelihoods of two classifiers, using appropriate weights. We developed a weighting process adaptive to SNRs. The main objective of the paper involves determining the optimal SNR classification boundaries and constructing a set of optimum stream weights for each SNR class. These two parameters were determined by a method based on a maximum mutual information criterion. Acoustic and facial MES data were collected from five subjects, using a 60-word vocabulary. Four types of acoustic noise including babble, car, aircraft, and white noise were acoustically added to clean speech signals with SNR ranging from -14 to 31 dB. The classification accuracy of the audio ASR was as low as 25.5%. Whereas, the classification accuracy of the MES ASR was 85.2%. The classification accuracy could be further improved by employing the proposed audio-MES weighting method, which was as high as 89.4% in the case of babble noise. A similar result was also found for the other types of noise.

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

NASA Technical Reports Server (NTRS)

Mellstrom, J. A.; Smyth, P.

1991-01-01

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Primary Stability Recognition of the Newly Designed Cementless Femoral Stem Using Digital Signal Processing

PubMed Central

Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A.; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing. PMID:24800230

Primary stability recognition of the newly designed cementless femoral stem using digital signal processing.

PubMed

Baharuddin, Mohd Yusof; Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing.

Crowding by a single bar: probing pattern recognition mechanisms in the visual periphery.

PubMed

Põder, Endel

2014-11-06

Whereas visual crowding does not greatly affect the detection of the presence of simple visual features, it heavily inhibits combining them into recognizable objects. Still, crowding effects have rarely been directly related to general pattern recognition mechanisms. In this study, pattern recognition mechanisms in visual periphery were probed using a single crowding feature. Observers had to identify the orientation of a rotated T presented briefly in a peripheral location. Adjacent to the target, a single bar was presented. The bar was either horizontal or vertical and located in a random direction from the target. It appears that such a crowding bar has very strong and regular effects on the identification of the target orientation. The observer's responses are determined by approximate relative positions of basic visual features; exact image-based similarity to the target is not important. A version of the "standard model" of object recognition with second-order features explains the main regularities of the data. © 2014 ARVO.

Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features

PubMed Central

Huo, Guanying

2017-01-01

As a typical deep-learning model, Convolutional Neural Networks (CNNs) can be exploited to automatically extract features from images using the hierarchical structure inspired by mammalian visual system. For image classification tasks, traditional CNN models employ the softmax function for classification. However, owing to the limited capacity of the softmax function, there are some shortcomings of traditional CNN models in image classification. To deal with this problem, a new method combining Biomimetic Pattern Recognition (BPR) with CNNs is proposed for image classification. BPR performs class recognition by a union of geometrical cover sets in a high-dimensional feature space and therefore can overcome some disadvantages of traditional pattern recognition. The proposed method is evaluated on three famous image classification benchmarks, that is, MNIST, AR, and CIFAR-10. The classification accuracies of the proposed method for the three datasets are 99.01%, 98.40%, and 87.11%, respectively, which are much higher in comparison with the other four methods in most cases. PMID:28316614

Apparatus for detecting and recognizing analytes based on their crystallization patterns

DOEpatents

Morozov, Victor; Bailey, Charles L.; Vsevolodov, Nikolai N.; Elliott, Adam

2010-12-14

The invention contemplates apparatuses for recognition of proteins and other biological molecules by imaging morphology, size and distribution of crystalline and amorphous dry residues in droplets (further referred to as "crystallization patterns") containing predetermined amount of certain crystal-forming organic compounds (reporters) to which protein to be analyzed is added. Changes in the crystallization patterns of a number of amino-acids can be used as a "signature" of a protein added. Also, changes in the crystallization patterns, as well as the character of such changes, can be used as recognition elements in analysis of protein molecules.

Intraspecific Variation in Learning: Worker Wasps Are Less Able to Learn and Remember Individual Conspecific Faces than Queen Wasps.

PubMed

Tibbetts, Elizabeth A; Injaian, Allison; Sheehan, Michael J; Desjardins, Nicole

2018-05-01

Research on individual recognition often focuses on species-typical recognition abilities rather than assessing intraspecific variation in recognition. As individual recognition is cognitively costly, the capacity for recognition may vary within species. We test how individual face recognition differs between nest-founding queens (foundresses) and workers in Polistes fuscatus paper wasps. Individual recognition mediates dominance interactions among foundresses. Three previously published experiments have shown that foundresses (1) benefit by advertising their identity with distinctive facial patterns that facilitate recognition, (2) have robust memories of individuals, and (3) rapidly learn to distinguish between face images. Like foundresses, workers have variable facial patterns and are capable of individual recognition. However, worker dominance interactions are muted. Therefore, individual recognition may be less important for workers than for foundresses. We find that (1) workers with unique faces receive amounts of aggression similar to those of workers with common faces, indicating that wasps do not benefit from advertising their individual identity with a unique appearance; (2) workers lack robust memories for individuals, as they cannot remember unique conspecifics after a 6-day separation; and (3) workers learn to distinguish between facial images more slowly than foundresses during training. The recognition differences between foundresses and workers are notable because Polistes lack discrete castes; foundresses and workers are morphologically similar, and workers can take over as queens. Overall, social benefits and receiver capacity for individual recognition are surprisingly plastic.

Implementation theory of distortion-invariant pattern recognition for optical and digital signal processing systems

NASA Astrophysics Data System (ADS)

Lhamon, Michael Earl

A pattern recognition system which uses complex correlation filter banks requires proportionally more computational effort than single-real valued filters. This introduces increased computation burden but also introduces a higher level of parallelism, that common computing platforms fail to identify. As a result, we consider algorithm mapping to both optical and digital processors. For digital implementation, we develop computationally efficient pattern recognition algorithms, referred to as, vector inner product operators that require less computational effort than traditional fast Fourier methods. These algorithms do not need correlation and they map readily onto parallel digital architectures, which imply new architectures for optical processors. These filters exploit circulant-symmetric matrix structures of the training set data representing a variety of distortions. By using the same mathematical basis as with the vector inner product operations, we are able to extend the capabilities of more traditional correlation filtering to what we refer to as "Super Images". These "Super Images" are used to morphologically transform a complicated input scene into a predetermined dot pattern. The orientation of the dot pattern is related to the rotational distortion of the object of interest. The optical implementation of "Super Images" yields feature reduction necessary for using other techniques, such as artificial neural networks. We propose a parallel digital signal processor architecture based on specific pattern recognition algorithms but general enough to be applicable to other similar problems. Such an architecture is classified as a data flow architecture. Instead of mapping an algorithm to an architecture, we propose mapping the DSP architecture to a class of pattern recognition algorithms. Today's optical processing systems have difficulties implementing full complex filter structures. Typically, optical systems (like the 4f correlators) are limited to phase-only implementation with lower detection performance than full complex electronic systems. Our study includes pseudo-random pixel encoding techniques for approximating full complex filtering. Optical filter bank implementation is possible and they have the advantage of time averaging the entire filter bank at real time rates. Time-averaged optical filtering is computational comparable to billions of digital operations-per-second. For this reason, we believe future trends in high speed pattern recognition will involve hybrid architectures of both optical and DSP elements.

Variability in the impairment of recognition memory in patients with frontal lobe lesions.

PubMed

Bastin, Christine; Van der Linden, Martial; Lekeu, Françoise; Andrés, Pilar; Salmon, Eric

2006-10-01

Fourteen patients with frontal lobe lesions and 14 normal subjects were tested on a recognition memory task that required discriminating between target words, new words that are synonyms of the targets and unrelated distractors. A deficit was found in 12 of the patients. Moreover, three different patterns of recognition impairment were identified: (I) poor memory for targets, (II) normal hits but increased false recognitions for both types of distractors, (III) normal hit rates, but increased false recognitions for synonyms only. Differences in terms of location of the damage and behavioral characteristics between these subgroups were examined. An encoding deficit was proposed to explain the performance of patients in subgroup I. The behavioral patterns of the patients in subgroups II and III could be interpreted as deficient post-retrieval verification processes and an inability to recollect item-specific information, respectively.

Effects of Cooperative Group Work Activities on Pre-School Children's Pattern Recognition Skills

ERIC Educational Resources Information Center

Tarim, Kamuran

2015-01-01

The aim of this research is twofold; to investigate the effects of cooperative group-based work activities on children's pattern recognition skills in pre-school and to examine the teachers' opinions about the implementation process. In line with this objective, for the study, 57 children (25 girls and 32 boys) were chosen from two private schools…

VLSI Microsystem for Rapid Bioinformatic Pattern Recognition

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Lue, Jaw-Chyng

2009-01-01

A system comprising very-large-scale integrated (VLSI) circuits is being developed as a means of bioinformatics-oriented analysis and recognition of patterns of fluorescence generated in a microarray in an advanced, highly miniaturized, portable genetic-expression-assay instrument. Such an instrument implements an on-chip combination of polymerase chain reactions and electrochemical transduction for amplification and detection of deoxyribonucleic acid (DNA).

Real-time object recognition in multidimensional images based on joined extended structural tensor and higher-order tensor decomposition methods

NASA Astrophysics Data System (ADS)

Cyganek, Boguslaw; Smolka, Bogdan

2015-02-01

In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.

Training Spiking Neural Models Using Artificial Bee Colony

PubMed Central

Vazquez, Roberto A.; Garro, Beatriz A.

2015-01-01

Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, several bioinspired algorithms have been proposed in the last years for solving a broad range of optimization problems, including those related to the field of artificial neural networks (ANNs). Artificial bee colony (ABC) is a novel algorithm based on the behavior of bees in the task of exploring their environment to find a food source. In this paper, we describe how the ABC algorithm can be used as a learning strategy to train a spiking neuron aiming to solve pattern recognition problems. Finally, the proposed approach is tested on several pattern recognition problems. It is important to remark that to realize the powerfulness of this type of model only one neuron will be used. In addition, we analyze how the performance of these models is improved using this kind of learning strategy. PMID:25709644

Multiclassifier information fusion methods for microarray pattern recognition

NASA Astrophysics Data System (ADS)

Braun, Jerome J.; Glina, Yan; Judson, Nicholas; Herzig-Marx, Rachel

2004-04-01

This paper addresses automatic recognition of microarray patterns, a capability that could have a major significance for medical diagnostics, enabling development of diagnostic tools for automatic discrimination of specific diseases. The paper presents multiclassifier information fusion methods for microarray pattern recognition. The input space partitioning approach based on fitness measures that constitute an a-priori gauging of classification efficacy for each subspace is investigated. Methods for generation of fitness measures, generation of input subspaces and their use in the multiclassifier fusion architecture are presented. In particular, two-level quantification of fitness that accounts for the quality of each subspace as well as the quality of individual neighborhoods within the subspace is described. Individual-subspace classifiers are Support Vector Machine based. The decision fusion stage fuses the information from mulitple SVMs along with the multi-level fitness information. Final decision fusion stage techniques, including weighted fusion as well as Dempster-Shafer theory based fusion are investigated. It should be noted that while the above methods are discussed in the context of microarray pattern recognition, they are applicable to a broader range of discrimination problems, in particular to problems involving a large number of information sources irreducible to a low-dimensional feature space.

Pattern Recognition Control Design

NASA Technical Reports Server (NTRS)

Gambone, Elisabeth A.

2018-01-01

Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.

Conditional random fields for pattern recognition applied to structured data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burr, Tom; Skurikhin, Alexei

In order to predict labels from an output domain, Y, pattern recognition is used to gather measurements from an input domain, X. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building) or “natural” (such as a tree). Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features betweenmore » parts of the model are often correlated. Thus, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. Our paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.« less

Recognition memory strength is predicted by pupillary responses at encoding while fixation patterns distinguish recollection from familiarity.

PubMed

Kafkas, Alexandros; Montaldi, Daniela

2011-10-01

Thirty-five healthy participants incidentally encoded a set of man-made and natural object pictures, while their pupil response and eye movements were recorded. At retrieval, studied and new stimuli were rated as novel, familiar (strong, moderate, or weak), or recollected. We found that both pupil response and fixation patterns at encoding predict later recognition memory strength. The extent of pupillary response accompanying incidental encoding was found to be predictive of subsequent memory. In addition, the number of fixations was also predictive of later recognition memory strength, suggesting that the accumulation of greater visual detail, even for single objects, is critical for the creation of a strong memory. Moreover, fixation patterns at encoding distinguished between recollection and familiarity at retrieval, with more dispersed fixations predicting familiarity and more clustered fixations predicting recollection. These data reveal close links between the autonomic control of pupil responses and eye movement patterns on the one hand and memory encoding on the other. Moreover, the data illustrate quantitative as well as qualitative differences in the incidental visual processing of stimuli, which are differentially predictive of the strength and the kind of memory experienced at recognition.

STATUS OF THE SYSTEM OF SIGNALING PATTERN RECOGNITION RECEPTORS OF MONOCYTES AND GRANULOCYTES IN COSMONAUTS' PERIPHERAL BLOOD BEFORE AND AFTER LONG-DURATION MISSIONS TO THE INTERNATIONAL SPACE STATION.

PubMed

Ponomarev, S A; Berendeeva, T A; Kalinin, S A; Muranova, A V

The system of signaling pattern recognition receptors was studied in 8 cosmonauts aged 35 to 56 years before and after (R+) long-duration missions to the International space station. Peripheral blood samples were analyzed for the content of monocytes and granulocytes that express the signaling pattern recognition Toll- like (TLR) receptors localized as on cell surface (TLR1, TLR2, TLR4, TLR5, TLR6), so inside cells (TLR3, TLR8, TLR9). In parallel, serum concentrations of TLR2 (HSP60) and TLR4 ligands (HSP70, HMGB1) were measured. The results of investigations showed growth of HSP60, HSP70 and HMGB1 concentrations on R+1. In the;majority of cosmonauts increases in endogenous ligands were followed by growth in the number of both monocytes and granulocytes that express TLR2 1 TLR4. This consistency gives ground to assume that changes in the system of signaling pattern recognition receptors can stem .from the predominantly endogenous ligands' response to the effects of long-duration space flight on human organism.

Conditional random fields for pattern recognition applied to structured data

DOE PAGES

Burr, Tom; Skurikhin, Alexei

2015-07-14

In order to predict labels from an output domain, Y, pattern recognition is used to gather measurements from an input domain, X. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building) or “natural” (such as a tree). Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features betweenmore » parts of the model are often correlated. Thus, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. Our paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.« less

Neonatal Recognition Processes and Attachment: The Masking Experiment.

ERIC Educational Resources Information Center

Cassel, Thomas Z. K.; Sander, Louis W.

This research project was designed to determine whether 1-week-old neonates would indicate biological recognition of their mothers. Biological recognition is defined as the particular configuration of sensory, kinesthetic, and motor cues and the temporal patterning of these cues which characterizes infants' exchange processes with their…

Elastic Face, An Anatomy-Based Biometrics Beyond Visible Cue

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsap, L V; Zhang, Y; Kundu, S J

2004-03-29

This paper describes a face recognition method that is designed based on the consideration of anatomical and biomechanical characteristics of facial tissues. Elastic strain pattern inferred from face expression can reveal an individual's biometric signature associated with the underlying anatomical structure, and thus has the potential for face recognition. A method based on the continuum mechanics in finite element formulation is employed to compute the strain pattern. Experiments show very promising results. The proposed method is quite different from other face recognition methods and both its advantages and limitations, as well as future research for improvement are discussed.

Context-aware mobile health monitoring: evaluation of different pattern recognition methods for classification of physical activity.

PubMed

Jatobá, Luciana C; Grossmann, Ulrich; Kunze, Chistophe; Ottenbacher, Jörg; Stork, Wilhelm

2008-01-01

There are various applications of physical activity monitoring for medical purposes, such as therapeutic rehabilitation, fitness enhancement or the use of physical activity as context information for evaluation of other vital data. Physical activity can be estimated using acceleration sensor-systems fixed on a person's body. By means of pattern recognition methods, it is possible to identify with certain accuracy which movement is being performed. This work presents a comparison of different methods for recognition of daily-life activities, which will serve as basis for the development of an online activity monitoring system.

A new approach for cancelable iris recognition

NASA Astrophysics Data System (ADS)

Yang, Kai; Sui, Yan; Zhou, Zhi; Du, Yingzi; Zou, Xukai

2010-04-01

The iris is a stable and reliable biometric for positive human identification. However, the traditional iris recognition scheme raises several privacy concerns. One's iris pattern is permanently bound with him and cannot be changed. Hence, once it is stolen, this biometric is lost forever as well as all the applications where this biometric is used. Thus, new methods are desirable to secure the original pattern and ensure its revocability and alternatives when compromised. In this paper, we propose a novel scheme which incorporates iris features, non-invertible transformation and data encryption to achieve "cancelability" and at the same time increases iris recognition accuracy.

Recognition of building group patterns in topographic maps based on graph partitioning and random forest

NASA Astrophysics Data System (ADS)

He, Xianjin; Zhang, Xinchang; Xin, Qinchuan

2018-02-01

Recognition of building group patterns (i.e., the arrangement and form exhibited by a collection of buildings at a given mapping scale) is important to the understanding and modeling of geographic space and is hence essential to a wide range of downstream applications such as map generalization. Most of the existing methods develop rigid rules based on the topographic relationships between building pairs to identify building group patterns and thus their applications are often limited. This study proposes a method to identify a variety of building group patterns that allow for map generalization. The method first identifies building group patterns from potential building clusters based on a machine-learning algorithm and further partitions the building clusters with no recognized patterns based on the graph partitioning method. The proposed method is applied to the datasets of three cities that are representative of the complex urban environment in Southern China. Assessment of the results based on the reference data suggests that the proposed method is able to recognize both regular (e.g., the collinear, curvilinear, and rectangular patterns) and irregular (e.g., the L-shaped, H-shaped, and high-density patterns) building group patterns well, given that the correctness values are consistently nearly 90% and the completeness values are all above 91% for three study areas. The proposed method shows promises in automated recognition of building group patterns that allows for map generalization.

Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

PubMed

Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

Neural network-based system for pattern recognition through a fiber optic bundle

NASA Astrophysics Data System (ADS)

Gamo-Aranda, Javier; Rodriguez-Horche, Paloma; Merchan-Palacios, Miguel; Rosales-Herrera, Pablo; Rodriguez, M.

2001-04-01

A neural network based system to identify images transmitted through a Coherent Fiber-optic Bundle (CFB) is presented. Patterns are generated in a computer, displayed on a Spatial Light Modulator, imaged onto the input face of the CFB, and recovered optically by a CCD sensor array for further processing. Input and output optical subsystems were designed and used to that end. The recognition step of the transmitted patterns is made by a powerful, widely-used, neural network simulator running on the control PC. A complete PC-based interface was developed to control the different tasks involved in the system. An optical analysis of the system capabilities was carried out prior to performing the recognition step. Several neural network topologies were tested, and the corresponding numerical results are also presented and discussed.

United States Homeland Security and National Biometric Identification

DTIC Science & Technology

2002-04-09

security number. Biometrics is the use of unique individual traits such as fingerprints, iris eye patterns, voice recognition, and facial recognition to...technology to control access onto their military bases using a Defense Manpower Management Command developed software application. FACIAL Facial recognition systems...installed facial recognition systems in conjunction with a series of 200 cameras to fight street crime and identify terrorists. The cameras, which are

The Wireless Ubiquitous Surveillance Testbed

DTIC Science & Technology

2003-03-01

c. Eye Patterns.............................................................................17 d. Facial Recognition ..................................................................19...27). ...........................................98 Table F.4. Facial Recognition Products. (After: Polemi, p. 25 and BiometriTech, 15 May 2002...it applies to homeland security. C. RESEARCH TASKS The main goals of this thesis are to: • Set up the biometric sensors and facial recognition surveillance

33 CFR 106.220 - Security training for all other OCS facility personnel.

Code of Federal Regulations, 2011 CFR

2011-07-01

... procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; and (e) Recognition of techniques used to circumvent security measures. (f) Familiarity with all relevant aspects of...

33 CFR 106.220 - Security training for all other OCS facility personnel.

Code of Federal Regulations, 2010 CFR

2010-07-01

... procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who are likely to threaten security; and (e) Recognition of techniques used to circumvent security measures. (f) Familiarity with all relevant aspects of...

Asymmetries in Early Word Recognition: The Case of Stops and Fricatives

ERIC Educational Resources Information Center

Altvater-Mackensen, Nicole; van der Feest, Suzanne V. H.; Fikkert, Paula

2014-01-01

Toddlers' discrimination of native phonemic contrasts is generally unproblematic. Yet using those native contrasts in word learning and word recognition can be more challenging. In this article, we investigate perceptual versus phonological explanations for asymmetrical patterns found in early word recognition. We systematically investigated the…

Structure design for a Two-DoF myoelectric prosthetic hand to realize basic hand functions in ADLs.

PubMed

Hoshigawa, Suguru; Jiang, Yinlai; Kato, Ryu; Morishita, Soichiro; Nakamura, Tatsuhiro; Yabuki, Yoshiko; Yokoi, Hiroshi

2015-01-01

Prosthetic hands are desired by those who have lost a hand or both hands not only for decoration but also for the functions to help them with their activities of daily living (ADL). Prosthetic robotic hands that are developed to fully realize the function of a human hand are usually too expensive to be economically available, difficult to operate and maintain, or over heavy for longtime wearing. The aim of this study is therefore to develop a simplified prosthetic hand (sim-PH), which is to be controlled by myoelectric signals from the user, to realize the most important grasp motions in ADL by trading off the cost and performance. This paper reports the structure design of a two-DoF sim-PH with two motors to drive the CM joint of the thumb and the interlocked MP joints of the other four fingers. In order to optimize the structure, the model of the sim-PH was proposed based on which 7 sim-PHs with different structural parameters were manufactured and tested in a pick-and-place experiment. Correspondence analysis of the experimental results clarified the relationship between the hand functions and the shapes of fingers.

The application of neural networks to myoelectric signal analysis: a preliminary study.

PubMed

Kelly, M F; Parker, P A; Scott, R N

1990-03-01

Two neural network implementations are applied to myoelectric signal (MES) analysis tasks. The motivation behind this research is to explore more reliable methods of deriving control for multidegree of freedom arm prostheses. A discrete Hopfield network is used to calculate the time series parameters for a moving average MES model. It is demonstrated that the Hopfield network is capable of generating the same time series parameters as those produced by the conventional sequential least squares (SLS) algorithm. Furthermore, it can be extended to applications utilizing larger amounts of data, and possibly to higher order time series models, without significant degradation in computational efficiency. The second neural network implementation involves using a two-layer perceptron for classifying a single site MES based on two features, specifically the first time series parameter, and the signal power. Using these features, the perceptron is trained to distinguish between four separate arm functions. The two-dimensional decision boundaries used by the perceptron classifier are delineated. It is also demonstrated that the perceptron is able to rapidly compensate for variations when new data are incorporated into the training set. This adaptive quality suggests that perceptrons may provide a useful tool for future MES analysis.

The detection of intestinal spike activity on surface electroenterograms

NASA Astrophysics Data System (ADS)

Ye-Lin, Y.; Garcia-Casado, J.; Martinez-de-Juan, J. L.; Prats-Boluda, G.; Ponce, J. L.

2010-02-01

Myoelectrical recording could provide an alternative technique for assessing intestinal motility, which is a topic of great interest in gastroenterology since many gastrointestinal disorders are associated with intestinal dysmotility. The pacemaker activity (slow wave, SW) of the electroenterogram (EEnG) has been detected in abdominal surface recordings, although the activity related to bowel contractions (spike bursts, SB) has to date only been detected in experimental models with artificially favored electrical conductivity. The aim of the present work was to assess the possibility of detecting SB activity in abdominal surface recordings under physiological conditions. For this purpose, 11 recording sessions of simultaneous internal and external myolectrical signals were conducted on conscious dogs. Signal analysis was carried out in the spectral domain. The results show that in periods of intestinal contractile activity, high-frequency components of EEnG signals can be detected on the abdominal surface in addition to SW activity. The energy between 2 and 20 Hz of the surface myoelectrical recording presented good correlation with the internal intestinal motility index (0.64 ± 0.10 for channel 1 and 0.57 ± 0.11 for channel 2). This suggests that SB activity can also be detected in canine surface EEnG recording.

A dynamical model improves reconstruction of handwriting from multichannel electromyographic recordings

PubMed Central

Okorokova, Elizaveta; Lebedev, Mikhail; Linderman, Michael; Ossadtchi, Alex

2015-01-01

In recent years, several assistive devices have been proposed to reconstruct arm and hand movements from electromyographic (EMG) activity. Although simple to implement and potentially useful to augment many functions, such myoelectric devices still need improvement before they become practical. Here we considered the problem of reconstruction of handwriting from multichannel EMG activity. Previously, linear regression methods (e.g., the Wiener filter) have been utilized for this purpose with some success. To improve reconstruction accuracy, we implemented the Kalman filter, which allows to fuse two information sources: the physical characteristics of handwriting and the activity of the leading hand muscles, registered by the EMG. Applying the Kalman filter, we were able to convert eight channels of EMG activity recorded from the forearm and the hand muscles into smooth reconstructions of handwritten traces. The filter operates in a causal manner and acts as a true predictor utilizing the EMGs from the past only, which makes the approach suitable for real-time operations. Our algorithm is appropriate for clinical neuroprosthetic applications and computer peripherals. Moreover, it is applicable to a broader class of tasks where predictive myoelectric control is needed. PMID:26578856

Quantitative assessment of four men using above-elbow prosthetic control.

PubMed

Popat, R A; Krebs, D E; Mansfield, J; Russell, D; Clancy, E; Gill-Body, K M; Hogan, N

1993-07-01

We studied the relationship between kinematically unconstrained activities of daily living (ADL) tasks and a kinematically constrained task in above-elbow (AE) amputee subjects using myoelectrically controlled prostheses. Four men, 24 to 49 years old, with unilateral AE amputation wore a prosthesis interfaced to a programmable controller to emulate two different elbow control schemes, conventional velocity and a new "natural" controller. Subjects were timed during three ADL tasks--cutting meat, donning socks, and rolling dough--with both controllers. The prosthesis emulator was then connected to a crank device with a handle, and the subjects turned the crank from bottom to top positions in a vertical plane using each controller. Synergistic shoulder-elbow joint coordination required for crank turning was quantified as the maximum slope of the change in elbow torque versus the change in crank-angle. Performance between the two controllers differed significantly for the crank test but not for ADL tasks. One subject did not complete all crank turning tests. Positive canonical correlation of 0.77 was found between time and crank domain measures. We conclude that biomechanical assessments should be integrated with time-based clinical tests to comprehensively evaluate performance of AE amputee subjects with a myoelectric device.

Wireless radio channel for intramuscular electrode implants in the control of upper limb prostheses.

PubMed

Stango, Antonietta; Yazdandoost, Kamya Yekeh; Farina, Dario

2015-01-01

In the last few years the use of implanted devices has been considered also in the field of myoelectric hand prostheses. Wireless implanted EMG (Electromyogram) sensors can improve the functioning of the prosthesis, providing information without the disadvantage of the wires, and the usability by amputees. The solutions proposed in the literature are based on proprietary communication protocols between the implanted devices and the prosthesis controller, using frequency bands that are already assigned to other purposes. This study proposes the use of a standard communication protocol (IEEE 802.15.6), specific for wireless body area networks (WBANs), which assign a specific bandwidth to implanted devices. The propagation losses from in-to-on body were investigated by numerical simulation with a 3D human model and an electromagnetic solver. The channel model resulting from the study represents the first step towards the development of myoelectric prosthetic hands which are driven by signals acquired by implanted sensors. However these results can provide important information to researchers for further developments, and manufacturers, which can decrease the production costs for hand prostheses having a common standard of communication with assigned frequencies of operation.

Trunk muscle activity during bridging exercises on and off a Swissball

PubMed Central

Lehman, Gregory J; Hoda, Wajid; Oliver, Steven

2005-01-01

Background A Swiss ball is often incorporated into trunk strengthening programs for injury rehabilitation and performance conditioning. It is often assumed that the use of a Swiss ball increases trunk muscle activity. The aim of this study was to determine whether the addition of a Swiss ball to trunk bridging exercises influences trunk muscle activity. Methods Surface electrodes recorded the myoelectric activity of trunk muscles during bridging exercises. Bridging exercises were performed on the floor as well as on a labile surface (Swiss ball). Results and Discussion During the prone bridge the addition of an exercise ball resulted in increased myoelectric activity in the rectus abdominis and external oblique. The internal oblique and erector spinae were not influenced. The addition of a swiss ball during supine bridging did not influence trunk muscle activity for any muscles studied. Conclusion The addition of a Swiss ball is capable of influencing trunk muscle activity in the rectus abdominis and external oblique musculature during prone bridge exercises. Modifying common bridging exercises can influence the amount of trunk muscle activity, suggesting that exercise routines can be designed to maximize or minimize trunk muscle exertion depending on the needs of the exercise population. PMID:16053529

Evaluation of Myoelectric Activity of Paraspinal Muscles in Adolescents with Idiopathic Scoliosis during Habitual Standing and Sitting.

PubMed

Kwok, Garcia; Yip, Joanne; Cheung, Mei-Chun; Yick, Kit-Lun

2015-01-01

There is a number of research work in the literature that have applied sEMG biofeedback as an instrument for muscle rehabilitation. Therefore, sEMG is a good tool for this research work and is used to record the myoelectric activity in the paraspinal muscles of those with AIS during habitual standing and sitting. After the sEMG evaluation, the root-mean-square (RMS) sEMG values of the paraspinal muscles in the habitual postures reflect the spinal curvature situation of the PUMC Type Ia and IIc subjects. Both groups have a stronger average RMS sEMG value on the convex side of the affected muscle regions. Correction to posture as instructed by the physiotherapist has helped the subjects to achieve a more balanced RMS sEMG ratio in the trapezius and latissimus dorsi regions; the erector spinae in the thoracic region and/or erector spinae in the lumbar region. It is, therefore, considered that with regular practice of the suggested positions, those with AIS can use motor learning to achieve a more balanced posture. Consequently, the findings can be used in less intrusive early orthotic intervention and provision of care to those with AIS.

Short- and Long-Term Learning of Feedforward Control of a Myoelectric Prosthesis with Sensory Feedback by Amputees.

PubMed

Strbac, Matija; Isakovic, Milica; Belic, Minja; Popovic, Igor; Simanic, Igor; Farina, Dario; Keller, Thierry; Dosen, Strahinja

2017-11-01

Human motor control relies on a combination of feedback and feedforward strategies. The aim of this study was to longitudinally investigate artificial somatosensory feedback and feedforward control in the context of grasping with myoelectric prosthesis. Nine amputee subjects performed routine grasping trials, with the aim to produce four levels of force during four blocks of 60 trials across five days. The electrotactile force feedback was provided in the second and third block using multipad electrode and spatial coding. The first baseline and last validation block (open-loop control) evaluated the effects of long- (across sessions) and short-term (within session) learning, respectively. The outcome measures were the absolute error between the generated and target force, and the number of force saturations. The results demonstrated that the electrotactile feedback improved the performance both within and across sessions. In the validation block, the performance did not significantly decrease and the quality of open-loop control (baseline) improved across days, converging to the performance characterizing closed-loop control. This paper provides important insights into the feedback and feedforward processes in prosthesis control, contributing to the better understanding of the role and design of feedback in prosthetic systems.

Linear and nonlinear regression techniques for simultaneous and proportional myoelectric control.

PubMed

Hahne, J M; Biessmann, F; Jiang, N; Rehbaum, H; Farina, D; Meinecke, F C; Muller, K-R; Parra, L C

2014-03-01

In recent years the number of active controllable joints in electrically powered hand-prostheses has increased significantly. However, the control strategies for these devices in current clinical use are inadequate as they require separate and sequential control of each degree-of-freedom (DoF). In this study we systematically compare linear and nonlinear regression techniques for an independent, simultaneous and proportional myoelectric control of wrist movements with two DoF. These techniques include linear regression, mixture of linear experts (ME), multilayer-perceptron, and kernel ridge regression (KRR). They are investigated offline with electro-myographic signals acquired from ten able-bodied subjects and one person with congenital upper limb deficiency. The control accuracy is reported as a function of the number of electrodes and the amount and diversity of training data providing guidance for the requirements in clinical practice. The results showed that KRR, a nonparametric statistical learning method, outperformed the other methods. However, simple transformations in the feature space could linearize the problem, so that linear models could achieve similar performance as KRR at much lower computational costs. Especially ME, a physiologically inspired extension of linear regression represents a promising candidate for the next generation of prosthetic devices.

Beneficial effects of naloxone in a patient with intestinal pseudoobstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schang, J.C.; Devroede, G.

1985-06-01

A 15-day course of Naloxone treatment was given to a patient with intestinal pseudoobstruction who had previously undergone subtotal colectomy with terminal ileostomy for invalidating constipation. The effects of the drug were assessed according to symptoms, by recording the myoelectric activity of the stomach, and by measuring gastric emptying of a radiolabeled solid-liquid meal and the intestinal transit time of radiopaque markers. All tests were performed 1) at baseline; 2) after 2 wk with Naloxone 1.6 mg subcutaneous per day; and 3) after 8 days of placebo. Results showed that before treatment gastric emptying of solids was delayed, emptying ofmore » liquids was normal, myoelectric activity of the stomach was normal, small intestinal transit time of radiopaque markers was considerably increased while ileal output was markedly decreased. After Naloxone, gastric emptying of solids was markedly accelerated, emptying of liquids remained normal, gastric electrical spiking activity increased, small intestinal transit time strikingly decreased, and ileal output increased. After placebo, a tendency to return to pretreatment values was observed. This observation suggests that Naloxone may be helpful in the treatment of some patients with intestinal pseudoobstruction.« less

Inconsistent emotion recognition deficits across stimulus modalities in Huntington׳s disease.

PubMed

Rees, Elin M; Farmer, Ruth; Cole, James H; Henley, Susie M D; Sprengelmeyer, Reiner; Frost, Chris; Scahill, Rachael I; Hobbs, Nicola Z; Tabrizi, Sarah J

2014-11-01

Recognition of negative emotions is impaired in Huntington׳s Disease (HD). It is unclear whether these emotion-specific problems are driven by dissociable cognitive deficits, emotion complexity, test cue difficulty, or visuoperceptual impairments. This study set out to further characterise emotion recognition in HD by comparing patterns of deficits across stimulus modalities; notably including for the first time in HD, the more ecologically and clinically relevant modality of film clips portraying dynamic facial expressions. Fifteen early HD and 17 control participants were tested on emotion recognition from static facial photographs, non-verbal vocal expressions and one second dynamic film clips, all depicting different emotions. Statistically significant evidence of impairment of anger, disgust and fear recognition was seen in HD participants compared with healthy controls across multiple stimulus modalities. The extent of the impairment, as measured by the difference in the number of errors made between HD participants and controls, differed according to the combination of emotion and modality (p=0.013, interaction test). The largest between-group difference was seen in the recognition of anger from film clips. Consistent with previous reports, anger, disgust and fear were the most poorly recognised emotions by the HD group. This impairment did not appear to be due to task demands or expression complexity as the pattern of between-group differences did not correspond to the pattern of errors made by either group; implicating emotion-specific cognitive processing pathology. There was however evidence that the extent of emotion recognition deficits significantly differed between stimulus modalities. The implications in terms of designing future tests of emotion recognition and care giving are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

Development of Pattern Recognition Techniques for the Evaluation of Toxicant Impacts to Multispecies Systems

DTIC Science & Technology

1993-06-18

the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and clustering methods...rule rather than the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and...experiments using two microcosm protocols. We use nonmetric clustering, a multivariate pattern recognition technique developed by Matthews and Heame (1991

Pattern recognition for Space Applications Center director's discretionary fund

NASA Technical Reports Server (NTRS)

Singley, M. E.

1984-01-01

Results and conclusions are presented on the application of recent developments in pattern recognition to spacecraft star mapping systems. Sensor data for two representative starfields are processed by an adaptive shape-seeking version of the Fc-V algorithm with good results. Cluster validity measures are evaluated, but not found especially useful to this application. Recommendations are given two system configurations worthy of additional study,

Method of synthesized phase objects for pattern recognition with rotation invariance

NASA Astrophysics Data System (ADS)

Ostroukh, Alexander P.; Butok, Alexander M.; Shvets, Rostislav A.; Yezhov, Pavel V.; Kim, Jin-Tae; Kuzmenko, Alexander V.

2015-11-01

We present a development of the method of synthesized phase objects (SPO-method) [1] for the rotation-invariant pattern recognition. For the standard method of recognition and the SPO-method, the comparison of the parameters of correlation signals for a number of amplitude objects is executed at the realization of a rotation in an optical-digital correlator with the joint Fourier transformation. It is shown that not only the invariance relative to a rotation at a realization of the joint correlation for synthesized phase objects (SP-objects) but also the main advantage of the method of SP-objects over the reference one such as the unified δ-like recognition signal with the largest possible signal-to-noise ratio independent of the type of an object are attained.

Effects of emotional and perceptual-motor stress on a voice recognition system's accuracy: An applied investigation

NASA Astrophysics Data System (ADS)

Poock, G. K.; Martin, B. J.

1984-02-01

This was an applied investigation examining the ability of a speech recognition system to recognize speakers' inputs when the speakers were under different stress levels. Subjects were asked to speak to a voice recognition system under three conditions: (1) normal office environment, (2) emotional stress, and (3) perceptual-motor stress. Results indicate a definite relationship between voice recognition system performance and the type of low stress reference patterns used to achieve recognition.

A comparison of lumbopelvic motion patterns and erector spinae behavior between asymptomatic subjects and patients with recurrent low back pain during pain-free periods.

PubMed

Sánchez-Zuriaga, Daniel; López-Pascual, Juan; Garrido-Jaén, David; García-Mas, Maria Amparo

2015-02-01

The purpose of this study was to determine the patterns of lumbopelvic motion and erector spinae (ES) activity during trunk flexion-extension movements and to compare these patterns between patients with recurrent low back pain (LBP) in their pain-free periods and matched asymptomatic subjects. Thirty subjects participated (15 patients with disc herniation and recurrent LBP in their pain-free periods and 15 asymptomatic control subjects). A 3-dimensional videophotogrammetric system and surface electromyography (EMG) were used to record the angular displacements of the lumbar spine and hip in the sagittal plane and the EMG activity of the ES during standardized trunk flexion-extension cycles. Variables were maximum ranges of spine and hip flexion; percentages of maximum lumbar and hip flexion at the start and end of ES relaxation; average percentages of EMG activity during flexion, relaxation, and extension; and flexion-extension ratio of myoelectrical activity. Recurrent LBP patients during their pain-free period showed significantly greater ES activation both in flexion and extension, with a higher flexion-extension ratio than controls. Maximum ranges of lumbar and hip flexion showed no differences between controls and patients, although patients spent less time with their lumbar spine maximally flexed. This study showed that reduced maximum ranges of motion and absence of ES flexion-relaxation phenomenon were not useful to identify LBP patients in the absence of acute pain. However, these patients showed subtle alterations of their lumbopelvic motion and ES activity patterns, which may have important clinical implications. Copyright © 2015 National University of Health Sciences. Published by Elsevier Inc. All rights reserved.

Brain angiogenesis inhibitor 1 (BAI1) is a pattern recognition receptor that mediates macrophage binding and engulfment of Gram-negative bacteria

PubMed Central

Das, Soumita; Owen, Katherine A.; Ly, Kim T.; Park, Daeho; Black, Steven G.; Wilson, Jeffrey M.; Sifri, Costi D.; Ravichandran, Kodi S.; Ernst, Peter B.; Casanova, James E.

2011-01-01

Bacterial recognition by host cells is essential for initiation of infection and the host response. Bacteria interact with host cells via multiple pattern recognition receptors that recognize microbial products or pathogen-associated molecular patterns. In response to this interaction, host cell signaling cascades are activated that lead to inflammatory responses and/or phagocytic clearance of attached bacteria. Brain angiogenesis inhibitor 1 (BAI1) is a receptor that recognizes apoptotic cells through its conserved type I thrombospondin repeats and triggers their engulfment through an ELMO1/Dock/Rac1 signaling module. Because thrombospondin repeats in other proteins have been shown to bind bacterial surface components, we hypothesized that BAI1 may also mediate the recognition and clearance of pathogenic bacteria. We found that preincubation of bacteria with recombinant soluble BAI1 ectodomain or knockdown of endogenous BAI1 in primary macrophages significantly reduced binding and internalization of the Gram-negative pathogen Salmonella typhimurium. Conversely, overexpression of BAI1 enhanced attachment and engulfment of Salmonella in macrophages and in heterologous nonphagocytic cells. Bacterial uptake is triggered by the BAI1-mediated activation of Rac through an ELMO/Dock-dependent mechanism, and inhibition of the BAI1/ELMO1 interaction prevents both Rac activation and bacterial uptake. Moreover, inhibition of ELMO1 or Rac function significantly impairs the proinflammatory response to infection. Finally, we show that BAI1 interacts with a variety of Gram-negative, but not Gram-positive, bacteria through recognition of their surface lipopolysaccharide. Together these findings identify BAI1 as a pattern recognition receptor that mediates nonopsonic phagocytosis of Gram-negative bacteria by macrophages and directly affects the host response to infection. PMID:21245295

Do subitizing deficits in developmental dyscalculia involve pattern recognition weakness?

PubMed

Ashkenazi, Sarit; Mark-Zigdon, Nitza; Henik, Avishai

2013-01-01

The abilities of children diagnosed with developmental dyscalculia (DD) were examined in two types of object enumeration: subitizing, and small estimation (5-9 dots). Subitizing is usually defined as a fast and accurate assessment of a number of small dots (range 1 to 4 dots), and estimation is an imprecise process to assess a large number of items (range 5 dots or more). Based on reaction time (RT) and accuracy analysis, our results indicated a deficit in the subitizing and small estimation range among DD participants in relation to controls. There are indications that subitizing is based on pattern recognition, thus presenting dots in a canonical shape in the estimation range should result in a subitizing-like pattern. In line with this theory, our control group presented a subitizing-like pattern in the small estimation range for canonically arranged dots, whereas the DD participants presented a deficit in the estimation of canonically arranged dots. The present finding indicates that pattern recognition difficulties may play a significant role in both subitizing and subitizing deficits among those with DD. © 2012 Blackwell Publishing Ltd.

Beyond sensory images: Object-based representation in the human ventral pathway

PubMed Central

Pietrini, Pietro; Furey, Maura L.; Ricciardi, Emiliano; Gobbini, M. Ida; Wu, W.-H. Carolyn; Cohen, Leonardo; Guazzelli, Mario; Haxby, James V.

2004-01-01

We investigated whether the topographically organized, category-related patterns of neural response in the ventral visual pathway are a representation of sensory images or a more abstract representation of object form that is not dependent on sensory modality. We used functional MRI to measure patterns of response evoked during visual and tactile recognition of faces and manmade objects in sighted subjects and during tactile recognition in blind subjects. Results showed that visual and tactile recognition evoked category-related patterns of response in a ventral extrastriate visual area in the inferior temporal gyrus that were correlated across modality for manmade objects. Blind subjects also demonstrated category-related patterns of response in this “visual” area, and in more ventral cortical regions in the fusiform gyrus, indicating that these patterns are not due to visual imagery and, furthermore, that visual experience is not necessary for category-related representations to develop in these cortices. These results demonstrate that the representation of objects in the ventral visual pathway is not simply a representation of visual images but, rather, is a representation of more abstract features of object form. PMID:15064396

Pattern recognition and feature extraction with an optical Hough transform

NASA Astrophysics Data System (ADS)

Fernández, Ariel

2016-09-01

Pattern recognition and localization along with feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for the recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital- only methods. Starting from the integral representation of the GHT, it is possible to device an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a rotating pupil mask for orientation variation, implemented on a high-contrast spatial light modulator (SLM). Real-time (as limited by the frame rate of the device used to capture the GHT) can also be achieved, allowing for the processing of video sequences. Besides, by thresholding of the GHT (with the aid of another SLM) and inverse transforming (which is optically achieved in the incoherent system under appropriate focusing setting), the previously detected features of interest can be extracted.

Reading recognition of pointer meter based on pattern recognition and dynamic three-points on a line

NASA Astrophysics Data System (ADS)

Zhang, Yongqiang; Ding, Mingli; Fu, Wuyifang; Li, Yongqiang

2017-03-01

Pointer meters are frequently applied to industrial production for they are directly readable. They should be calibrated regularly to ensure the precision of the readings. Currently the method of manual calibration is most frequently adopted to accomplish the verification of the pointer meter, and professional skills and subjective judgment may lead to big measurement errors and poor reliability and low efficiency, etc. In the past decades, with the development of computer technology, the skills of machine vision and digital image processing have been applied to recognize the reading of the dial instrument. In terms of the existing recognition methods, all the parameters of dial instruments are supposed to be the same, which is not the case in practice. In this work, recognition of pointer meter reading is regarded as an issue of pattern recognition. We obtain the features of a small area around the detected point, make those features as a pattern, divide those certified images based on Gradient Pyramid Algorithm, train a classifier with the support vector machine (SVM) and complete the pattern matching of the divided mages. Then we get the reading of the pointer meter precisely under the theory of dynamic three points make a line (DTPML), which eliminates the error caused by tiny differences of the panels. Eventually, the result of the experiment proves that the proposed method in this work is superior to state-of-the-art works.

Pattern recognition monitoring of PEM fuel cell

DOEpatents

Meltser, M.A.

1999-08-31

The CO-concentration in the H{sub 2} feed stream to a PEM fuel cell stack is monitored by measuring current and voltage behavior patterns from an auxiliary cell attached to the end of the stack. The auxiliary cell is connected to the same oxygen and hydrogen feed manifolds that supply the stack, and discharges through a constant load. Pattern recognition software compares the current and voltage patterns from the auxiliary cell to current and voltage signature determined from a reference cell similar to the auxiliary cell and operated under controlled conditions over a wide range of CO-concentrations in the H{sub 2} fuel stream. 4 figs.

Pattern recognition monitoring of PEM fuel cell

DOEpatents

Meltser, Mark Alexander

1999-01-01

The CO-concentration in the H.sub.2 feed stream to a PEM fuel cell stack is monitored by measuring current and voltage behavior patterns from an auxiliary cell attached to the end of the stack. The auxiliary cell is connected to the same oxygen and hydrogen feed manifolds that supply the stack, and discharges through a constant load. Pattern recognition software compares the current and voltage patterns from the auxiliary cell to current and voltage signature determined from a reference cell similar to the auxiliary cell and operated under controlled conditions over a wide range of CO-concentrations in the H.sub.2 fuel stream.

Symbol Recognition Using a Concept Lattice of Graphical Patterns

NASA Astrophysics Data System (ADS)

Rusiñol, Marçal; Bertet, Karell; Ogier, Jean-Marc; Lladós, Josep

In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest.

Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection

PubMed Central

Gottschlich, Carsten

2016-01-01

We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by comparing pairs of two DCT coefficients. These patterns are summarized into one or more histograms per image. Each histogram comprises the relative frequencies of pattern occurrences. Multiple histograms are concatenated and the resulting feature vector is used for image classification. We name this novel type of descriptor convolution comparison pattern (CCP). Experimental results show the usefulness of the proposed CCP descriptor for fingerprint liveness detection. CCP outperforms other local image descriptors such as LBP, LPQ and WLD on the LivDet 2013 benchmark. The CCP descriptor is a general type of local image descriptor which we expect to prove useful in areas beyond fingerprint liveness detection such as biological and medical image processing, texture recognition, face recognition and iris recognition, liveness detection for face and iris images, and machine vision for surface inspection and material classification. PMID:26844544

An RLP23-SOBIR1-BAK1 complex mediates NLP-triggered immunity.

PubMed

Albert, Isabell; Böhm, Hannah; Albert, Markus; Feiler, Christina E; Imkampe, Julia; Wallmeroth, Niklas; Brancato, Caterina; Raaymakers, Tom M; Oome, Stan; Zhang, Heqiao; Krol, Elzbieta; Grefen, Christopher; Gust, Andrea A; Chai, Jijie; Hedrich, Rainer; Van den Ackerveken, Guido; Nürnberger, Thorsten

2015-10-05

Plants and animals employ innate immune systems to cope with microbial infection. Pattern-triggered immunity relies on the recognition of microbe-derived patterns by pattern recognition receptors (PRRs). Necrosis and ethylene-inducing peptide 1-like proteins (NLPs) constitute plant immunogenic patterns that are unique, as these proteins are produced by multiple prokaryotic (bacterial) and eukaryotic (fungal, oomycete) species. Here we show that the leucine-rich repeat receptor protein (LRR-RP) RLP23 binds in vivo to a conserved 20-amino-acid fragment found in most NLPs (nlp20), thereby mediating immune activation in Arabidopsis thaliana. RLP23 forms a constitutive, ligand-independent complex with the LRR receptor kinase (LRR-RK) SOBIR1 (Suppressor of Brassinosteroid insensitive 1 (BRI1)-associated kinase (BAK1)-interacting receptor kinase 1), and recruits a second LRR-RK, BAK1, into a tripartite complex upon ligand binding. Stable, ectopic expression of RLP23 in potato (Solanum tuberosum) confers nlp20 pattern recognition and enhanced immunity to destructive oomycete and fungal plant pathogens, such as Phytophthora infestans and Sclerotinia sclerotiorum. PRRs that recognize widespread microbial patterns might be particularly suited for engineering immunity in crop plants.

Model driven mobile care for patients with type 1 diabetes.

PubMed

Skrøvseth, Stein Olav; Arsand, Eirik; Godtliebsen, Fred; Joakimsen, Ragnar M

2012-01-01

We gathered a data set from 30 patients with type 1 diabetes by giving the patients a mobile phone application, where they recorded blood glucose measurements, insulin injections, meals, and physical activity. Using these data as a learning data set, we describe a new approach of building a mobile feedback system for these patients based on periodicities, pattern recognition, and scale-space trends. Most patients have important patterns for periodicities and trends, though better resolution of input variables is needed to provide useful feedback using pattern recognition.

Hierarchical singleton-type recurrent neural fuzzy networks for noisy speech recognition.

PubMed

Juang, Chia-Feng; Chiou, Chyi-Tian; Lai, Chun-Lung

2007-05-01

This paper proposes noisy speech recognition using hierarchical singleton-type recurrent neural fuzzy networks (HSRNFNs). The proposed HSRNFN is a hierarchical connection of two singleton-type recurrent neural fuzzy networks (SRNFNs), where one is used for noise filtering and the other for recognition. The SRNFN is constructed by recurrent fuzzy if-then rules with fuzzy singletons in the consequences, and their recurrent properties make them suitable for processing speech patterns with temporal characteristics. In n words recognition, n SRNFNs are created for modeling n words, where each SRNFN receives the current frame feature and predicts the next one of its modeling word. The prediction error of each SRNFN is used as recognition criterion. In filtering, one SRNFN is created, and each SRNFN recognizer is connected to the same SRNFN filter, which filters noisy speech patterns in the feature domain before feeding them to the SRNFN recognizer. Experiments with Mandarin word recognition under different types of noise are performed. Other recognizers, including multilayer perceptron (MLP), time-delay neural networks (TDNNs), and hidden Markov models (HMMs), are also tested and compared. These experiments and comparisons demonstrate good results with HSRNFN for noisy speech recognition tasks.

The effect of inversion on face recognition in adults with autism spectrum disorder.

PubMed

Hedley, Darren; Brewer, Neil; Young, Robyn

2015-05-01

Face identity recognition has widely been shown to be impaired in individuals with autism spectrum disorders (ASD). In this study we examined the influence of inversion on face recognition in 26 adults with ASD and 33 age and IQ matched controls. Participants completed a recognition test comprising upright and inverted faces. Participants with ASD performed worse than controls on the recognition task but did not show an advantage for inverted face recognition. Both groups directed more visual attention to the eye than the mouth region and gaze patterns were not found to be associated with recognition performance. These results provide evidence of a normal effect of inversion on face recognition in adults with ASD.

Mapping of the human upper arm muscle activity with an electrode matrix.

PubMed

Côté, J; Mathieu, P A

2000-06-01

Surface electrode matrices allow measurement of muscle activity while avoiding certain hazardous risks and inconvenience associated with invasive techniques. Major challenges of such equipment involve optimizing spatial resolution, and designing simple acquisition systems able to record simultaneously many potentials over large anatomical areas. We present a surface electromyography acquisition system comprising of 3 x 8 Ag-AgCl electrodes mounted onto an elastic band, which can be adjusted to fit an entire human upper limb segment. Using this equipment, we acquired a simultaneous representation of muscular activity from a segment of the upper limb surface of 6 healthy subjects during isometric contractions at various intensities. We found that the location of regions of highest activity depended on elbow torque direction but also varied among subjects. Signals obtained with such equipment can be used to solve the inverse problem and help optimize the electrode configuration in volume conduction studies. The efficacy of decision algorithms of multi-functional myoelectric prostheses can be tested with the global muscle activity patterns gathered. The electrode cuff could also be used in the investigation of fatigue and injury mechanisms during occupational activities.

Recognition without Awareness: Encoding and Retrieval Factors

ERIC Educational Resources Information Center

Craik, Fergus I. M.; Rose, Nathan S.; Gopie, Nigel

2015-01-01

The article reports 4 experiments that explore the notion of recognition without awareness using words as the material. Previous work by Voss and associates has shown that complex visual patterns were correctly selected as targets in a 2-alternative forced-choice (2-AFC) recognition test although participants reported that they were guessing. The…

Determination of polychlorinated biphenyl levels in the serum of residents and in the homogenates of seafood from the New Bedford, Massachusetts Area: A comparison of exposure sources through pattern recognition techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burse, V.W.; Groce, D.F.; Caudill, S.P.

1994-01-01

Gas chromatographic patterns of polychlorinated biophenyls (PCBs) found in the serum of New Bedford, MA residents with high serum PCBs were compared to patterns found in lobsters and bluefish taken from local waters, and goats fed selected technical Aroclors (e.g., Aroclors 1016, 1242, 1254, or 1260) using Jaccard measures of similarity and Principal Component Analysis. Pattern in humans were silimar to patterns in lobsters and both were more similar to those in the goat fed Aroclor 1254 as demonstrated by both pattern recognition techniques. However, patterns observed in humans, lobsters and bluefish all exhibited some presence of PCBs more characteristicmore » of Aroclors 1016 and/or 1242 or 1260.« less

Parallel and orthogonal stimulus in ultradiluted neural networks

NASA Astrophysics Data System (ADS)

Sobral, G. A., Jr.; Vieira, V. M.; Lyra, M. L.; da Silva, C. R.

2006-10-01

Extending a model due to Derrida, Gardner, and Zippelius, we have studied the recognition ability of an extreme and asymmetrically diluted version of the Hopfield model for associative memory by including the effect of a stimulus in the dynamics of the system. We obtain exact results for the dynamic evolution of the average network superposition. The stimulus field was considered as proportional to the overlapping of the state of the system with a particular stimulated pattern. Two situations were analyzed, namely, the external stimulus acting on the initialization pattern (parallel stimulus) and the external stimulus acting on a pattern orthogonal to the initialization one (orthogonal stimulus). In both cases, we obtained the complete phase diagram in the parameter space composed of the stimulus field, thermal noise, and network capacity. Our results show that the system improves its recognition ability for parallel stimulus. For orthogonal stimulus two recognition phases emerge with the system locking at the initialization or stimulated pattern. We confront our analytical results with numerical simulations for the noiseless case T=0 .

Multi-texture local ternary pattern for face recognition

NASA Astrophysics Data System (ADS)

Essa, Almabrok; Asari, Vijayan

2017-05-01

In imagery and pattern analysis domain a variety of descriptors have been proposed and employed for different computer vision applications like face detection and recognition. Many of them are affected under different conditions during the image acquisition process such as variations in illumination and presence of noise, because they totally rely on the image intensity values to encode the image information. To overcome these problems, a novel technique named Multi-Texture Local Ternary Pattern (MTLTP) is proposed in this paper. MTLTP combines the edges and corners based on the local ternary pattern strategy to extract the local texture features of the input image. Then returns a spatial histogram feature vector which is the descriptor for each image that we use to recognize a human being. Experimental results using a k-nearest neighbors classifier (k-NN) on two publicly available datasets justify our algorithm for efficient face recognition in the presence of extreme variations of illumination/lighting environments and slight variation of pose conditions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sobral, G. A. Jr.; Vieira, V. M.; Lyra, M. L.

Extending a model due to Derrida, Gardner, and Zippelius, we have studied the recognition ability of an extreme and asymmetrically diluted version of the Hopfield model for associative memory by including the effect of a stimulus in the dynamics of the system. We obtain exact results for the dynamic evolution of the average network superposition. The stimulus field was considered as proportional to the overlapping of the state of the system with a particular stimulated pattern. Two situations were analyzed, namely, the external stimulus acting on the initialization pattern (parallel stimulus) and the external stimulus acting on a pattern orthogonalmore » to the initialization one (orthogonal stimulus). In both cases, we obtained the complete phase diagram in the parameter space composed of the stimulus field, thermal noise, and network capacity. Our results show that the system improves its recognition ability for parallel stimulus. For orthogonal stimulus two recognition phases emerge with the system locking at the initialization or stimulated pattern. We confront our analytical results with numerical simulations for the noiseless case T=0.« less

Artificial Immune System for Recognizing Patterns

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance

2005-01-01

A method of recognizing or classifying patterns is based on an artificial immune system (AIS), which includes an algorithm and a computational model of nonlinear dynamics inspired by the behavior of a biological immune system. The method has been proposed as the theoretical basis of the computational portion of a star-tracking system aboard a spacecraft. In that system, a newly acquired star image would be treated as an antigen that would be matched by an appropriate antibody (an entry in a star catalog). The method would enable rapid convergence, would afford robustness in the face of noise in the star sensors, would enable recognition of star images acquired in any sensor or spacecraft orientation, and would not make an excessive demand on the computational resources of a typical spacecraft. Going beyond the star-tracking application, the AIS-based pattern-recognition method is potentially applicable to pattern- recognition and -classification processes for diverse purposes -- for example, reconnaissance, detecting intruders, and mining data.

Collocation and Pattern Recognition Effects on System Failure Remediation

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Press, Hayes N.

2007-01-01

Previous research found that operators prefer to have status, alerts, and controls located on the same screen. Unfortunately, that research was done with displays that were not designed specifically for collocation. In this experiment, twelve subjects evaluated two displays specifically designed for collocating system information against a baseline that consisted of dial status displays, a separate alert area, and a controls panel. These displays differed in the amount of collocation, pattern matching, and parameter movement compared to display size. During the data runs, subjects kept a randomly moving target centered on a display using a left-handed joystick and they scanned system displays to find a problem in order to correct it using the provided checklist. Results indicate that large parameter movement aided detection and then pattern recognition is needed for diagnosis but the collocated displays centralized all the information subjects needed, which reduced workload. Therefore, the collocated display with large parameter movement may be an acceptable display after familiarization because of the possible pattern recognition developed with training and its use.

Problems Associated with Statistical Pattern Recognition of Acoustic Emission Signals in a Compact Tension Fatigue Specimen

NASA Technical Reports Server (NTRS)

Hinton, Yolanda L.

1999-01-01

Acoustic emission (AE) data were acquired during fatigue testing of an aluminum 2024-T4 compact tension specimen using a commercially available AE system. AE signals from crack extension were identified and separated from noise spikes, signals that reflected from the specimen edges, and signals that saturated the instrumentation. A commercially available software package was used to train a statistical pattern recognition system to classify the signals. The software trained a network to recognize signals with a 91-percent accuracy when compared with the researcher's interpretation of the data. Reasons for the discrepancies are examined and it is postulated that additional preprocessing of the AE data to focus on the extensional wave mode and eliminate other effects before training the pattern recognition system will result in increased accuracy.

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors

PubMed Central

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-01-01

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

PubMed

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-07-07

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

33 CFR 104.225 - Security training for all other vessel personnel.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (MARSEC) Levels, including emergency procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who...

33 CFR 104.225 - Security training for all other vessel personnel.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (MARSEC) Levels, including emergency procedures and contingency plans; (c) Recognition and detection of dangerous substances and devices; (d) Recognition of characteristics and behavioral patterns of persons who...

Effects of age and hearing loss on recognition of unaccented and accented multisyllabic words.

PubMed

Gordon-Salant, Sandra; Yeni-Komshian, Grace H; Fitzgibbons, Peter J; Cohen, Julie I

2015-02-01

The effects of age and hearing loss on recognition of unaccented and accented words of varying syllable length were investigated. It was hypothesized that with increments in length of syllables, there would be atypical alterations in syllable stress in accented compared to native English, and that these altered stress patterns would be sensitive to auditory temporal processing deficits with aging. Sets of one-, two-, three-, and four-syllable words with the same initial syllable were recorded by one native English and two Spanish-accented talkers. Lists of these words were presented in isolation and in sentence contexts to younger and older normal-hearing listeners and to older hearing-impaired listeners. Hearing loss effects were apparent for unaccented and accented monosyllabic words, whereas age effects were observed for recognition of accented multisyllabic words, consistent with the notion that altered syllable stress patterns with accent are sensitive for revealing effects of age. Older listeners also exhibited lower recognition scores for moderately accented words in sentence contexts than in isolation, suggesting that the added demands on working memory for words in sentence contexts impact recognition of accented speech. The general pattern of results suggests that hearing loss, age, and cognitive factors limit the ability to recognize Spanish-accented speech.

Effects of age and hearing loss on recognition of unaccented and accented multisyllabic words

PubMed Central

Gordon-Salant, Sandra; Yeni-Komshian, Grace H.; Fitzgibbons, Peter J.; Cohen, Julie I.

2015-01-01

The effects of age and hearing loss on recognition of unaccented and accented words of varying syllable length were investigated. It was hypothesized that with increments in length of syllables, there would be atypical alterations in syllable stress in accented compared to native English, and that these altered stress patterns would be sensitive to auditory temporal processing deficits with aging. Sets of one-, two-, three-, and four-syllable words with the same initial syllable were recorded by one native English and two Spanish-accented talkers. Lists of these words were presented in isolation and in sentence contexts to younger and older normal-hearing listeners and to older hearing-impaired listeners. Hearing loss effects were apparent for unaccented and accented monosyllabic words, whereas age effects were observed for recognition of accented multisyllabic words, consistent with the notion that altered syllable stress patterns with accent are sensitive for revealing effects of age. Older listeners also exhibited lower recognition scores for moderately accented words in sentence contexts than in isolation, suggesting that the added demands on working memory for words in sentence contexts impact recognition of accented speech. The general pattern of results suggests that hearing loss, age, and cognitive factors limit the ability to recognize Spanish-accented speech. PMID:25698021

Ultrafast learning in a hard-limited neural network pattern recognizer

NASA Astrophysics Data System (ADS)

Hu, Chia-Lun J.

1996-03-01

As we published in the last five years, the supervised learning in a hard-limited perceptron system can be accomplished in a noniterative manner if the input-output mapping to be learned satisfies a certain positive-linear-independency (or PLI) condition. When this condition is satisfied (for most practical pattern recognition applications, this condition should be satisfied,) the connection matrix required to meet this mapping can be obtained noniteratively in one step. Generally, there exist infinitively many solutions for the connection matrix when the PLI condition is satisfied. We can then select an optimum solution such that the recognition of any untrained patterns will become optimally robust in the recognition mode. The learning speed is very fast and close to real-time because the learning process is noniterative and one-step. This paper reports the theoretical analysis and the design of a practical charter recognition system for recognizing hand-written alphabets. The experimental result is recorded in real-time on an unedited video tape for demonstration purposes. It is seen from this real-time movie that the recognition of the untrained hand-written alphabets is invariant to size, location, orientation, and writing sequence, even the training is done with standard size, standard orientation, central location and standard writing sequence.

Pattern recognition for passive polarimetric data using nonparametric classifiers

NASA Astrophysics Data System (ADS)

Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.

2005-08-01

Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.