Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter

PubMed Central

Kim, Seongwan; Ban, Yuseok; Lee, Sangyoun

2017-01-01

The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor’s stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity. PMID:28106716

Depth Camera-Based 3D Hand Gesture Controls with Immersive Tactile Feedback for Natural Mid-Air Gesture Interactions

PubMed Central

Kim, Kwangtaek; Kim, Joongrock; Choi, Jaesung; Kim, Junghyun; Lee, Sangyoun

2015-01-01

Vision-based hand gesture interactions are natural and intuitive when interacting with computers, since we naturally exploit gestures to communicate with other people. However, it is agreed that users suffer from discomfort and fatigue when using gesture-controlled interfaces, due to the lack of physical feedback. To solve the problem, we propose a novel complete solution of a hand gesture control system employing immersive tactile feedback to the user's hand. For this goal, we first developed a fast and accurate hand-tracking algorithm with a Kinect sensor using the proposed MLBP (modified local binary pattern) that can efficiently analyze 3D shapes in depth images. The superiority of our tracking method was verified in terms of tracking accuracy and speed by comparing with existing methods, Natural Interaction Technology for End-user (NITE), 3D Hand Tracker and CamShift. As the second step, a new tactile feedback technology with a piezoelectric actuator has been developed and integrated into the developed hand tracking algorithm, including the DTW (dynamic time warping) gesture recognition algorithm for a complete solution of an immersive gesture control system. The quantitative and qualitative evaluations of the integrated system were conducted with human subjects, and the results demonstrate that our gesture control with tactile feedback is a promising technology compared to a vision-based gesture control system that has typically no feedback for the user's gesture inputs. Our study provides researchers and designers with informative guidelines to develop more natural gesture control systems or immersive user interfaces with haptic feedback. PMID:25580901

Depth camera-based 3D hand gesture controls with immersive tactile feedback for natural mid-air gesture interactions.

PubMed

Kim, Kwangtaek; Kim, Joongrock; Choi, Jaesung; Kim, Junghyun; Lee, Sangyoun

2015-01-08

Vision-based hand gesture interactions are natural and intuitive when interacting with computers, since we naturally exploit gestures to communicate with other people. However, it is agreed that users suffer from discomfort and fatigue when using gesture-controlled interfaces, due to the lack of physical feedback. To solve the problem, we propose a novel complete solution of a hand gesture control system employing immersive tactile feedback to the user's hand. For this goal, we first developed a fast and accurate hand-tracking algorithm with a Kinect sensor using the proposed MLBP (modified local binary pattern) that can efficiently analyze 3D shapes in depth images. The superiority of our tracking method was verified in terms of tracking accuracy and speed by comparing with existing methods, Natural Interaction Technology for End-user (NITE), 3D Hand Tracker and CamShift. As the second step, a new tactile feedback technology with a piezoelectric actuator has been developed and integrated into the developed hand tracking algorithm, including the DTW (dynamic time warping) gesture recognition algorithm for a complete solution of an immersive gesture control system. The quantitative and qualitative evaluations of the integrated system were conducted with human subjects, and the results demonstrate that our gesture control with tactile feedback is a promising technology compared to a vision-based gesture control system that has typically no feedback for the user's gesture inputs. Our study provides researchers and designers with informative guidelines to develop more natural gesture control systems or immersive user interfaces with haptic feedback.

Kazakh Traditional Dance Gesture Recognition

NASA Astrophysics Data System (ADS)

Nussipbekov, A. K.; Amirgaliyev, E. N.; Hahn, Minsoo

2014-04-01

Full body gesture recognition is an important and interdisciplinary research field which is widely used in many application spheres including dance gesture recognition. The rapid growth of technology in recent years brought a lot of contribution in this domain. However it is still challenging task. In this paper we implement Kazakh traditional dance gesture recognition. We use Microsoft Kinect camera to obtain human skeleton and depth information. Then we apply tree-structured Bayesian network and Expectation Maximization algorithm with K-means clustering to calculate conditional linear Gaussians for classifying poses. And finally we use Hidden Markov Model to detect dance gestures. Our main contribution is that we extend Kinect skeleton by adding headwear as a new skeleton joint which is calculated from depth image. This novelty allows us to significantly improve the accuracy of head gesture recognition of a dancer which in turn plays considerable role in whole body gesture recognition. Experimental results show the efficiency of the proposed method and that its performance is comparable to the state-of-the-art system performances.

Appearance-based human gesture recognition using multimodal features for human computer interaction

NASA Astrophysics Data System (ADS)

Luo, Dan; Gao, Hua; Ekenel, Hazim Kemal; Ohya, Jun

2011-03-01

The use of gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and LDA is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.

Autonomous learning in gesture recognition by using lobe component analysis

NASA Astrophysics Data System (ADS)

Lu, Jian; Weng, Juyang

2007-02-01

Gesture recognition is a new human-machine interface method implemented by pattern recognition(PR).In order to assure robot safety when gesture is used in robot control, it is required to implement the interface reliably and accurately. Similar with other PR applications, 1) feature selection (or model establishment) and 2) training from samples, affect the performance of gesture recognition largely. For 1), a simple model with 6 feature points at shoulders, elbows, and hands, is established. The gestures to be recognized are restricted to still arm gestures, and the movement of arms is not considered. These restrictions are to reduce the misrecognition, but are not so unreasonable. For 2), a new biological network method, called lobe component analysis(LCA), is used in unsupervised learning. Lobe components, corresponding to high-concentrations in probability of the neuronal input, are orientation selective cells follow Hebbian rule and lateral inhibition. Due to the advantage of LCA method for balanced learning between global and local features, large amount of samples can be used in learning efficiently.

Study of recognizing multiple persons' complicated hand gestures from the video sequence acquired by a moving camera

NASA Astrophysics Data System (ADS)

Dan, Luo; Ohya, Jun

2010-02-01

Recognizing hand gestures from the video sequence acquired by a dynamic camera could be a useful interface between humans and mobile robots. We develop a state based approach to extract and recognize hand gestures from moving camera images. We improved Human-Following Local Coordinate (HFLC) System, a very simple and stable method for extracting hand motion trajectories, which is obtained from the located human face, body part and hand blob changing factor. Condensation algorithm and PCA-based algorithm was performed to recognize extracted hand trajectories. In last research, this Condensation Algorithm based method only applied for one person's hand gestures. In this paper, we propose a principal component analysis (PCA) based approach to improve the recognition accuracy. For further improvement, temporal changes in the observed hand area changing factor are utilized as new image features to be stored in the database after being analyzed by PCA. Every hand gesture trajectory in the database is classified into either one hand gesture categories, two hand gesture categories, or temporal changes in hand blob changes. We demonstrate the effectiveness of the proposed method by conducting experiments on 45 kinds of sign language based Japanese and American Sign Language gestures obtained from 5 people. Our experimental recognition results show better performance is obtained by PCA based approach than the Condensation algorithm based method.

Dactyl Alphabet Gesture Recognition in a Video Sequence Using Microsoft Kinect

NASA Astrophysics Data System (ADS)

Artyukhin, S. G.; Mestetskiy, L. M.

2015-05-01

This paper presents an efficient framework for solving the problem of static gesture recognition based on data obtained from the web cameras and depth sensor Kinect (RGB-D - data). Each gesture given by a pair of images: color image and depth map. The database store gestures by it features description, genereated by frame for each gesture of the alphabet. Recognition algorithm takes as input a video sequence (a sequence of frames) for marking, put in correspondence with each frame sequence gesture from the database, or decide that there is no suitable gesture in the database. First, classification of the frame of the video sequence is done separately without interframe information. Then, a sequence of successful marked frames in equal gesture is grouped into a single static gesture. We propose a method combined segmentation of frame by depth map and RGB-image. The primary segmentation is based on the depth map. It gives information about the position and allows to get hands rough border. Then, based on the color image border is specified and performed analysis of the shape of the hand. Method of continuous skeleton is used to generate features. We propose a method of skeleton terminal branches, which gives the opportunity to determine the position of the fingers and wrist. Classification features for gesture is description of the position of the fingers relative to the wrist. The experiments were carried out with the developed algorithm on the example of the American Sign Language. American Sign Language gesture has several components, including the shape of the hand, its orientation in space and the type of movement. The accuracy of the proposed method is evaluated on the base of collected gestures consisting of 2700 frames.

Gesture Recognition Based on the Probability Distribution of Arm Trajectories

NASA Astrophysics Data System (ADS)

Wan, Khairunizam; Sawada, Hideyuki

The use of human motions for the interaction between humans and computers is becoming an attractive alternative to verbal media, especially through the visual interpretation of the human body motion. In particular, hand gestures are used as non-verbal media for the humans to communicate with machines that pertain to the use of the human gestures to interact with them. This paper introduces a 3D motion measurement of the human upper body for the purpose of the gesture recognition, which is based on the probability distribution of arm trajectories. In this study, by examining the characteristics of the arm trajectories given by a signer, motion features are selected and classified by using a fuzzy technique. Experimental results show that the use of the features extracted from arm trajectories effectively works on the recognition of dynamic gestures of a human, and gives a good performance to classify various gesture patterns.

Human-Computer Interaction Based on Hand Gestures Using RGB-D Sensors

PubMed Central

Palacios, José Manuel; Sagüés, Carlos; Montijano, Eduardo; Llorente, Sergio

2013-01-01

In this paper we present a new method for hand gesture recognition based on an RGB-D sensor. The proposed approach takes advantage of depth information to cope with the most common problems of traditional video-based hand segmentation methods: cluttered backgrounds and occlusions. The algorithm also uses colour and semantic information to accurately identify any number of hands present in the image. Ten different static hand gestures are recognised, including all different combinations of spread fingers. Additionally, movements of an open hand are followed and 6 dynamic gestures are identified. The main advantage of our approach is the freedom of the user's hands to be at any position of the image without the need of wearing any specific clothing or additional devices. Besides, the whole method can be executed without any initial training or calibration. Experiments carried out with different users and in different environments prove the accuracy and robustness of the method which, additionally, can be run in real-time. PMID:24018953

Using arm and hand gestures to command robots during stealth operations

NASA Astrophysics Data System (ADS)

Stoica, Adrian; Assad, Chris; Wolf, Michael; You, Ki Sung; Pavone, Marco; Huntsberger, Terry; Iwashita, Yumi

2012-06-01

Command of support robots by the warfighter requires intuitive interfaces to quickly communicate high degree-offreedom (DOF) information while leaving the hands unencumbered. Stealth operations rule out voice commands and vision-based gesture interpretation techniques, as they often entail silent operations at night or in other low visibility conditions. Targeted at using bio-signal inputs to set navigation and manipulation goals for the robot (say, simply by pointing), we developed a system based on an electromyography (EMG) "BioSleeve", a high density sensor array for robust, practical signal collection from forearm muscles. The EMG sensor array data is fused with inertial measurement unit (IMU) data. This paper describes the BioSleeve system and presents initial results of decoding robot commands from the EMG and IMU data using a BioSleeve prototype with up to sixteen bipolar surface EMG sensors. The BioSleeve is demonstrated on the recognition of static hand positions (e.g. palm facing front, fingers upwards) and on dynamic gestures (e.g. hand wave). In preliminary experiments, over 90% correct recognition was achieved on five static and nine dynamic gestures. We use the BioSleeve to control a team of five LANdroid robots in individual and group/squad behaviors. We define a gesture composition mechanism that allows the specification of complex robot behaviors with only a small vocabulary of gestures/commands, and we illustrate it with a set of complex orders.

Using Arm and Hand Gestures to Command Robots during Stealth Operations

NASA Technical Reports Server (NTRS)

Stoica, Adrian; Assad, Chris; Wolf, Michael; You, Ki Sung; Pavone, Marco; Huntsberger, Terry; Iwashita, Yumi

2012-01-01

Command of support robots by the warfighter requires intuitive interfaces to quickly communicate high degree-of-freedom (DOF) information while leaving the hands unencumbered. Stealth operations rule out voice commands and vision-based gesture interpretation techniques, as they often entail silent operations at night or in other low visibility conditions. Targeted at using bio-signal inputs to set navigation and manipulation goals for the robot (say, simply by pointing), we developed a system based on an electromyography (EMG) "BioSleeve", a high density sensor array for robust, practical signal collection from forearm muscles. The EMG sensor array data is fused with inertial measurement unit (IMU) data. This paper describes the BioSleeve system and presents initial results of decoding robot commands from the EMG and IMU data using a BioSleeve prototype with up to sixteen bipolar surface EMG sensors. The BioSleeve is demonstrated on the recognition of static hand positions (e.g. palm facing front, fingers upwards) and on dynamic gestures (e.g. hand wave). In preliminary experiments, over 90% correct recognition was achieved on five static and nine dynamic gestures. We use the BioSleeve to control a team of five LANdroid robots in individual and group/squad behaviors. We define a gesture composition mechanism that allows the specification of complex robot behaviors with only a small vocabulary of gestures/commands, and we illustrate it with a set of complex orders.

Exploration of Force Myography and surface Electromyography in hand gesture classification.

PubMed

Jiang, Xianta; Merhi, Lukas-Karim; Xiao, Zhen Gang; Menon, Carlo

2017-03-01

Whereas pressure sensors increasingly have received attention as a non-invasive interface for hand gesture recognition, their performance has not been comprehensively evaluated. This work examined the performance of hand gesture classification using Force Myography (FMG) and surface Electromyography (sEMG) technologies by performing 3 sets of 48 hand gestures using a prototyped FMG band and an array of commercial sEMG sensors worn both on the wrist and forearm simultaneously. The results show that the FMG band achieved classification accuracies as good as the high quality, commercially available, sEMG system on both wrist and forearm positions; specifically, by only using 8 Force Sensitive Resisters (FSRs), the FMG band achieved accuracies of 91.2% and 83.5% in classifying the 48 hand gestures in cross-validation and cross-trial evaluations, which were higher than those of sEMG (84.6% and 79.1%). By using all 16 FSRs on the band, our device achieved high accuracies of 96.7% and 89.4% in cross-validation and cross-trial evaluations. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

A Versatile Embedded Platform for EMG Acquisition and Gesture Recognition.

PubMed

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

2015-10-01

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

Surgical gesture segmentation and recognition.

PubMed

Tao, Lingling; Zappella, Luca; Hager, Gregory D; Vidal, René

2013-01-01

Automatic surgical gesture segmentation and recognition can provide useful feedback for surgical training in robotic surgery. Most prior work in this field relies on the robot's kinematic data. Although recent work [1,2] shows that the robot's video data can be equally effective for surgical gesture recognition, the segmentation of the video into gestures is assumed to be known. In this paper, we propose a framework for joint segmentation and recognition of surgical gestures from kinematic and video data. Unlike prior work that relies on either frame-level kinematic cues, or segment-level kinematic or video cues, our approach exploits both cues by using a combined Markov/semi-Markov conditional random field (MsM-CRF) model. Our experiments show that the proposed model improves over a Markov or semi-Markov CRF when using video data alone, gives results that are comparable to state-of-the-art methods on kinematic data alone, and improves over state-of-the-art methods when combining kinematic and video data.

Dynamic gesture recognition using neural networks: a fundament for advanced interaction construction

NASA Astrophysics Data System (ADS)

Boehm, Klaus; Broll, Wolfgang; Sokolewicz, Michael A.

1994-04-01

Interaction in virtual reality environments is still a challenging task. Static hand posture recognition is currently the most common and widely used method for interaction using glove input devices. In order to improve the naturalness of interaction, and thereby decrease the user-interface learning time, there is a need to be able to recognize dynamic gestures. In this paper we describe our approach to overcoming the difficulties of dynamic gesture recognition (DGR) using neural networks. Backpropagation neural networks have already proven themselves to be appropriate and efficient for posture recognition. However, the extensive amount of data involved in DGR requires a different approach. Because of features such as topology preservation and automatic-learning, Kohonen Feature Maps are particularly suitable for the reduction of the high dimensional data space that is the result of a dynamic gesture, and are thus implemented for this task.

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

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.

New generation of human machine interfaces for controlling UAV through depth-based gesture recognition

NASA Astrophysics Data System (ADS)

Mantecón, Tomás.; del Blanco, Carlos Roberto; Jaureguizar, Fernando; García, Narciso

2014-06-01

New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

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

The content of the message influences the hand choice in co-speech gestures and in gesturing without speaking.

PubMed

Lausberg, Hedda; Kita, Sotaro

2003-07-01

The present study investigates the hand choice in iconic gestures that accompany speech. In 10 right-handed subjects gestures were elicited by verbal narration and by silent gestural demonstrations of animations with two moving objects. In both conditions, the left-hand was used as often as the right-hand to display iconic gestures. The choice of the right- or left-hands was determined by semantic aspects of the message. The influence of hemispheric language lateralization on the hand choice in co-speech gestures appeared to be minor. Instead, speaking seemed to induce a sequential organization of the iconic gestures.

Web-based interactive drone control using hand gesture

NASA Astrophysics Data System (ADS)

Zhao, Zhenfei; Luo, Hao; Song, Guang-Hua; Chen, Zhou; Lu, Zhe-Ming; Wu, Xiaofeng

2018-01-01

This paper develops a drone control prototype based on web technology with the aid of hand gesture. The uplink control command and downlink data (e.g., video) are transmitted by WiFi communication, and all the information exchange is realized on web. The control command is translated from various predetermined hand gestures. Specifically, the hardware of this friendly interactive control system is composed by a quadrotor drone, a computer vision-based hand gesture sensor, and a cost-effective computer. The software is simplified as a web-based user interface program. Aided by natural hand gestures, this system significantly reduces the complexity of traditional human-computer interaction, making remote drone operation more intuitive. Meanwhile, a web-based automatic control mode is provided in addition to the hand gesture control mode. For both operation modes, no extra application program is needed to be installed on the computer. Experimental results demonstrate the effectiveness and efficiency of the proposed system, including control accuracy, operation latency, etc. This system can be used in many applications such as controlling a drone in global positioning system denied environment or by handlers without professional drone control knowledge since it is easy to get started.

Web-based interactive drone control using hand gesture.

PubMed

Zhao, Zhenfei; Luo, Hao; Song, Guang-Hua; Chen, Zhou; Lu, Zhe-Ming; Wu, Xiaofeng

2018-01-01

This paper develops a drone control prototype based on web technology with the aid of hand gesture. The uplink control command and downlink data (e.g., video) are transmitted by WiFi communication, and all the information exchange is realized on web. The control command is translated from various predetermined hand gestures. Specifically, the hardware of this friendly interactive control system is composed by a quadrotor drone, a computer vision-based hand gesture sensor, and a cost-effective computer. The software is simplified as a web-based user interface program. Aided by natural hand gestures, this system significantly reduces the complexity of traditional human-computer interaction, making remote drone operation more intuitive. Meanwhile, a web-based automatic control mode is provided in addition to the hand gesture control mode. For both operation modes, no extra application program is needed to be installed on the computer. Experimental results demonstrate the effectiveness and efficiency of the proposed system, including control accuracy, operation latency, etc. This system can be used in many applications such as controlling a drone in global positioning system denied environment or by handlers without professional drone control knowledge since it is easy to get started.

The Effect of the Visual Context in the Recognition of Symbolic Gestures

PubMed Central

Villarreal, Mirta F.; Fridman, Esteban A.; Leiguarda, Ramón C.

2012-01-01

Background To investigate, by means of fMRI, the influence of the visual environment in the process of symbolic gesture recognition. Emblems are semiotic gestures that use movements or hand postures to symbolically encode and communicate meaning, independently of language. They often require contextual information to be correctly understood. Until now, observation of symbolic gestures was studied against a blank background where the meaning and intentionality of the gesture was not fulfilled. Methodology/Principal Findings Normal subjects were scanned while observing short videos of an individual performing symbolic gesture with or without the corresponding visual context and the context scenes without gestures. The comparison between gestures regardless of the context demonstrated increased activity in the inferior frontal gyrus, the superior parietal cortex and the temporoparietal junction in the right hemisphere and the precuneus and posterior cingulate bilaterally, while the comparison between context and gestures alone did not recruit any of these regions. Conclusions/Significance These areas seem to be crucial for the inference of intentions in symbolic gestures observed in their natural context and represent an interrelated network formed by components of the putative human neuron mirror system as well as the mentalizing system. PMID:22363406

Hand Leading and Hand Taking Gestures in Autism and Typically Developing Children

ERIC Educational Resources Information Center

Gómez, Juan-Carlos

2015-01-01

Children with autism use hand taking and hand leading gestures to interact with others. This is traditionally considered to be an example of atypical behaviour illustrating the lack of intersubjective understanding in autism. However the assumption that these gestures are atypical is based upon scarce empirical evidence. In this paper I present…

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition

PubMed Central

2017-01-01

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user’s location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively. PMID:28817094

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition.

PubMed

Choi, Hyo-Rim; Kim, TaeYong

2017-08-17

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user's location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively.

An interactive VR system based on full-body tracking and gesture recognition

NASA Astrophysics Data System (ADS)

Zeng, Xia; Sang, Xinzhu; Chen, Duo; Wang, Peng; Guo, Nan; Yan, Binbin; Wang, Kuiru

2016-10-01

Most current virtual reality (VR) interactions are realized with the hand-held input device which leads to a low degree of presence. There is other solutions using sensors like Leap Motion to recognize the gestures of users in order to interact in a more natural way, but the navigation in these systems is still a problem, because they fail to map the actual walking to virtual walking only with a partial body of the user represented in the synthetic environment. Therefore, we propose a system in which users can walk around in the virtual environment as a humanoid model, selecting menu items and manipulating with the virtual objects using natural hand gestures. With a Kinect depth camera, the system tracks the joints of the user, mapping them to a full virtual body which follows the move of the tracked user. The movements of the feet can be detected to determine whether the user is in walking state, so that the walking of model in the virtual world can be activated and stopped by means of animation control in Unity engine. This method frees the hands of users comparing to traditional navigation way using hand-held device. We use the point cloud data getting from Kinect depth camera to recognize the gestures of users, such as swiping, pressing and manipulating virtual objects. Combining the full body tracking and gestures recognition using Kinect, we achieve our interactive VR system in Unity engine with a high degree of presence.

Enhancement of gesture recognition for contactless interface using a personalized classifier in the operating room.

PubMed

Cho, Yongwon; Lee, Areum; Park, Jongha; Ko, Bemseok; Kim, Namkug

2018-07-01

Contactless operating room (OR) interfaces are important for computer-aided surgery, and have been developed to decrease the risk of contamination during surgical procedures. In this study, we used Leap Motion™, with a personalized automated classifier, to enhance the accuracy of gesture recognition for contactless interfaces. This software was trained and tested on a personal basis that means the training of gesture per a user. We used 30 features including finger and hand data, which were computed, selected, and fed into a multiclass support vector machine (SVM), and Naïve Bayes classifiers and to predict and train five types of gestures including hover, grab, click, one peak, and two peaks. Overall accuracy of the five gestures was 99.58% ± 0.06, and 98.74% ± 3.64 on a personal basis using SVM and Naïve Bayes classifiers, respectively. We compared gesture accuracy across the entire dataset and used SVM and Naïve Bayes classifiers to examine the strength of personal basis training. We developed and enhanced non-contact interfaces with gesture recognition to enhance OR control systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Interactive and Stereoscopic Hybrid 3D Viewer of Radar Data with Gesture Recognition

NASA Astrophysics Data System (ADS)

Goenetxea, Jon; Moreno, Aitor; Unzueta, Luis; Galdós, Andoni; Segura, Álvaro

This work presents an interactive and stereoscopic 3D viewer of weather information coming from a Doppler radar. The hybrid system shows a GIS model of the regional zone where the radar is located and the corresponding reconstructed 3D volume weather data. To enhance the immersiveness of the navigation, stereoscopic visualization has been added to the viewer, using a polarized glasses based system. The user can interact with the 3D virtual world using a Nintendo Wiimote for navigating through it and a Nintendo Wii Nunchuk for giving commands by means of hand gestures. We also present a dynamic gesture recognition procedure that measures the temporal advance of the performed gesture postures. Experimental results show how dynamic gestures are effectively recognized so that a more natural interaction and immersive navigation in the virtual world is achieved.

Multi-modal gesture recognition using integrated model of motion, audio and video

NASA Astrophysics Data System (ADS)

Goutsu, Yusuke; Kobayashi, Takaki; Obara, Junya; Kusajima, Ikuo; Takeichi, Kazunari; Takano, Wataru; Nakamura, Yoshihiko

2015-07-01

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

The neural basis of hand gesture comprehension: A meta-analysis of functional magnetic resonance imaging studies.

PubMed

Yang, Jie; Andric, Michael; Mathew, Mili M

2015-10-01

Gestures play an important role in face-to-face communication and have been increasingly studied via functional magnetic resonance imaging. Although a large amount of data has been provided to describe the neural substrates of gesture comprehension, these findings have never been quantitatively summarized and the conclusion is still unclear. This activation likelihood estimation meta-analysis investigated the brain networks underpinning gesture comprehension while considering the impact of gesture type (co-speech gestures vs. speech-independent gestures) and task demand (implicit vs. explicit) on the brain activation of gesture comprehension. The meta-analysis of 31 papers showed that as hand actions, gestures involve a perceptual-motor network important for action recognition. As meaningful symbols, gestures involve a semantic network for conceptual processing. Finally, during face-to-face interactions, gestures involve a network for social emotive processes. Our finding also indicated that gesture type and task demand influence the involvement of the brain networks during gesture comprehension. The results highlight the complexity of gesture comprehension, and suggest that future research is necessary to clarify the dynamic interactions among these networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Giving speech a hand: gesture modulates activity in auditory cortex during speech perception.

PubMed

Hubbard, Amy L; Wilson, Stephen M; Callan, Daniel E; Dapretto, Mirella

2009-03-01

Viewing hand gestures during face-to-face communication affects speech perception and comprehension. Despite the visible role played by gesture in social interactions, relatively little is known about how the brain integrates hand gestures with co-occurring speech. Here we used functional magnetic resonance imaging (fMRI) and an ecologically valid paradigm to investigate how beat gesture-a fundamental type of hand gesture that marks speech prosody-might impact speech perception at the neural level. Subjects underwent fMRI while listening to spontaneously-produced speech accompanied by beat gesture, nonsense hand movement, or a still body; as additional control conditions, subjects also viewed beat gesture, nonsense hand movement, or a still body all presented without speech. Validating behavioral evidence that gesture affects speech perception, bilateral nonprimary auditory cortex showed greater activity when speech was accompanied by beat gesture than when speech was presented alone. Further, the left superior temporal gyrus/sulcus showed stronger activity when speech was accompanied by beat gesture than when speech was accompanied by nonsense hand movement. Finally, the right planum temporale was identified as a putative multisensory integration site for beat gesture and speech (i.e., here activity in response to speech accompanied by beat gesture was greater than the summed responses to speech alone and beat gesture alone), indicating that this area may be pivotally involved in synthesizing the rhythmic aspects of both speech and gesture. Taken together, these findings suggest a common neural substrate for processing speech and gesture, likely reflecting their joint communicative role in social interactions.

Giving Speech a Hand: Gesture Modulates Activity in Auditory Cortex During Speech Perception

PubMed Central

Hubbard, Amy L.; Wilson, Stephen M.; Callan, Daniel E.; Dapretto, Mirella

2008-01-01

Viewing hand gestures during face-to-face communication affects speech perception and comprehension. Despite the visible role played by gesture in social interactions, relatively little is known about how the brain integrates hand gestures with co-occurring speech. Here we used functional magnetic resonance imaging (fMRI) and an ecologically valid paradigm to investigate how beat gesture – a fundamental type of hand gesture that marks speech prosody – might impact speech perception at the neural level. Subjects underwent fMRI while listening to spontaneously-produced speech accompanied by beat gesture, nonsense hand movement, or a still body; as additional control conditions, subjects also viewed beat gesture, nonsense hand movement, or a still body all presented without speech. Validating behavioral evidence that gesture affects speech perception, bilateral nonprimary auditory cortex showed greater activity when speech was accompanied by beat gesture than when speech was presented alone. Further, the left superior temporal gyrus/sulcus showed stronger activity when speech was accompanied by beat gesture than when speech was accompanied by nonsense hand movement. Finally, the right planum temporale was identified as a putative multisensory integration site for beat gesture and speech (i.e., here activity in response to speech accompanied by beat gesture was greater than the summed responses to speech alone and beat gesture alone), indicating that this area may be pivotally involved in synthesizing the rhythmic aspects of both speech and gesture. Taken together, these findings suggest a common neural substrate for processing speech and gesture, likely reflecting their joint communicative role in social interactions. PMID:18412134

Hand-gesture-based sterile interface for the operating room using contextual cues for the navigation of radiological images

PubMed Central

Jacob, Mithun George; Wachs, Juan Pablo; Packer, Rebecca A

2013-01-01

This paper presents a method to improve the navigation and manipulation of radiological images through a sterile hand gesture recognition interface based on attentional contextual cues. Computer vision algorithms were developed to extract intention and attention cues from the surgeon's behavior and combine them with sensory data from a commodity depth camera. The developed interface was tested in a usability experiment to assess the effectiveness of the new interface. An image navigation and manipulation task was performed, and the gesture recognition accuracy, false positives and task completion times were computed to evaluate system performance. Experimental results show that gesture interaction and surgeon behavior analysis can be used to accurately navigate, manipulate and access MRI images, and therefore this modality could replace the use of keyboard and mice-based interfaces. PMID:23250787

Hand-gesture-based sterile interface for the operating room using contextual cues for the navigation of radiological images.

PubMed

Jacob, Mithun George; Wachs, Juan Pablo; Packer, Rebecca A

2013-06-01

This paper presents a method to improve the navigation and manipulation of radiological images through a sterile hand gesture recognition interface based on attentional contextual cues. Computer vision algorithms were developed to extract intention and attention cues from the surgeon's behavior and combine them with sensory data from a commodity depth camera. The developed interface was tested in a usability experiment to assess the effectiveness of the new interface. An image navigation and manipulation task was performed, and the gesture recognition accuracy, false positives and task completion times were computed to evaluate system performance. Experimental results show that gesture interaction and surgeon behavior analysis can be used to accurately navigate, manipulate and access MRI images, and therefore this modality could replace the use of keyboard and mice-based interfaces.

Effects of hand gestures on auditory learning of second-language vowel length contrasts.

PubMed

Hirata, Yukari; Kelly, Spencer D; Huang, Jessica; Manansala, Michael

2014-12-01

Research has shown that hand gestures affect comprehension and production of speech at semantic, syntactic, and pragmatic levels for both native language and second language (L2). This study investigated a relatively less explored question: Do hand gestures influence auditory learning of an L2 at the segmental phonology level? To examine auditory learning of phonemic vowel length contrasts in Japanese, 88 native English-speaking participants took an auditory test before and after one of the following 4 types of training in which they (a) observed an instructor in a video speaking Japanese words while she made syllabic-rhythm hand gesture, (b) produced this gesture with the instructor, (c) observed the instructor speaking those words and her moraic-rhythm hand gesture, or (d) produced the moraic-rhythm gesture with the instructor. All of the training types yielded similar auditory improvement in identifying vowel length contrast. However, observing the syllabic-rhythm hand gesture yielded the most balanced improvement between word-initial and word-final vowels and between slow and fast speaking rates. The overall effect of hand gesture on learning of segmental phonology is limited. Implications for theories of hand gesture are discussed in terms of the role it plays at different linguistic levels.

A Natural Interaction Interface for UAVs Using Intuitive Gesture Recognition

NASA Technical Reports Server (NTRS)

Chandarana, Meghan; Trujillo, Anna; Shimada, Kenji; Allen, Danette

2016-01-01

The popularity of unmanned aerial vehicles (UAVs) is increasing as technological advancements boost their favorability for a broad range of applications. One application is science data collection. In fields like Earth and atmospheric science, researchers are seeking to use UAVs to augment their current portfolio of platforms and increase their accessibility to geographic areas of interest. By increasing the number of data collection platforms UAVs will significantly improve system robustness and allow for more sophisticated studies. Scientists would like be able to deploy an available fleet of UAVs to fly a desired flight path and collect sensor data without needing to understand the complex low-level controls required to describe and coordinate such a mission. A natural interaction interface for a Ground Control System (GCS) using gesture recognition is developed to allow non-expert users (e.g., scientists) to define a complex flight path for a UAV using intuitive hand gesture inputs from the constructed gesture library. The GCS calculates the combined trajectory on-line, verifies the trajectory with the user, and sends it to the UAV controller to be flown.

More than Just Hand Waving: Review of "Hearing Gestures--How Our Hands Help Us Think"

ERIC Educational Resources Information Center

Namy, Laura L.; Newcombe, Nora S.

2008-01-01

Susan Goldin-Meadow's "Hearing Gestures: How Our Hands Help Us to Think" synthesizes findings from various domains to demonstrate that gestures convey meaning and comprise a critical and fundamental form of communication. She also argues convincingly for the cognitive utility of gesture for the gesturer. Goldin-Meadow presents an airtight case…

SeleCon: Scalable IoT Device Selection and Control Using Hand Gestures.

PubMed

Alanwar, Amr; Alzantot, Moustafa; Ho, Bo-Jhang; Martin, Paul; Srivastava, Mani

2017-04-01

Although different interaction modalities have been proposed in the field of human-computer interface (HCI), only a few of these techniques could reach the end users because of scalability and usability issues. Given the popularity and the growing number of IoT devices, selecting one out of many devices becomes a hurdle in a typical smarthome environment. Therefore, an easy-to-learn, scalable, and non-intrusive interaction modality has to be explored. In this paper, we propose a pointing approach to interact with devices, as pointing is arguably a natural way for device selection. We introduce SeleCon for device selection and control which uses an ultra-wideband (UWB) equipped smartwatch. To interact with a device in our system, people can point to the device to select it then draw a hand gesture in the air to specify a control action. To this end, SeleCon employs inertial sensors for pointing gesture detection and a UWB transceiver for identifying the selected device from ranging measurements. Furthermore, SeleCon supports an alphabet of gestures that can be used for controlling the selected devices. We performed our experiment in a 9 m -by-10 m lab space with eight deployed devices. The results demonstrate that SeleCon can achieve 84.5% accuracy for device selection and 97% accuracy for hand gesture recognition. We also show that SeleCon is power efficient to sustain daily use by turning off the UWB transceiver, when a user's wrist is stationary.

MGRA: Motion Gesture Recognition via Accelerometer.

PubMed

Hong, Feng; You, Shujuan; Wei, Meiyu; Zhang, Yongtuo; Guo, Zhongwen

2016-04-13

Accelerometers have been widely embedded in most current mobile devices, enabling easy and intuitive operations. This paper proposes a Motion Gesture Recognition system (MGRA) based on accelerometer data only, which is entirely implemented on mobile devices and can provide users with real-time interactions. A robust and unique feature set is enumerated through the time domain, the frequency domain and singular value decomposition analysis using our motion gesture set containing 11,110 traces. The best feature vector for classification is selected, taking both static and mobile scenarios into consideration. MGRA exploits support vector machine as the classifier with the best feature vector. Evaluations confirm that MGRA can accommodate a broad set of gesture variations within each class, including execution time, amplitude and non-gestural movement. Extensive evaluations confirm that MGRA achieves higher accuracy under both static and mobile scenarios and costs less computation time and energy on an LG Nexus 5 than previous methods.

Research on gesture recognition of augmented reality maintenance guiding system based on improved SVM

NASA Astrophysics Data System (ADS)

Zhao, Shouwei; Zhang, Yong; Zhou, Bin; Ma, Dongxi

2014-09-01

Interaction is one of the key techniques of augmented reality (AR) maintenance guiding system. Because of the complexity of the maintenance guiding system's image background and the high dimensionality of gesture characteristics, the whole process of gesture recognition can be divided into three stages which are gesture segmentation, gesture characteristic feature modeling and trick recognition. In segmentation stage, for solving the misrecognition of skin-like region, a segmentation algorithm combing background mode and skin color to preclude some skin-like regions is adopted. In gesture characteristic feature modeling of image attributes stage, plenty of characteristic features are analyzed and acquired, such as structure characteristics, Hu invariant moments features and Fourier descriptor. In trick recognition stage, a classifier based on Support Vector Machine (SVM) is introduced into the augmented reality maintenance guiding process. SVM is a novel learning method based on statistical learning theory, processing academic foundation and excellent learning ability, having a lot of issues in machine learning area and special advantages in dealing with small samples, non-linear pattern recognition at high dimension. The gesture recognition of augmented reality maintenance guiding system is realized by SVM after the granulation of all the characteristic features. The experimental results of the simulation of number gesture recognition and its application in augmented reality maintenance guiding system show that the real-time performance and robustness of gesture recognition of AR maintenance guiding system can be greatly enhanced by improved SVM.

Gestural interaction in a virtual environment

NASA Astrophysics Data System (ADS)

Jacoby, Richard H.; Ferneau, Mark; Humphries, Jim

1994-04-01

This paper discusses the use of hand gestures (i.e., changing finger flexion) within a virtual environment (VE). Many systems now employ static hand postures (i.e., static finger flexion), often coupled with hand translations and rotations, as a method of interacting with a VE. However, few systems are currently using dynamically changing finger flexion for interacting with VEs. In our system, the user wears an electronically instrumented glove. We have developed a simple algorithm for recognizing gestures for use in two applications: automotive design and visualization of atmospheric data. In addition to recognizing the gestures, we also calculate the rate at which the gestures are made and the rate and direction of hand movement while making the gestures. We report on our experiences with the algorithm design and implementation, and the use of the gestures in our applications. We also talk about our background work in user calibration of the glove, as well as learned and innate posture recognition (postures recognized with and without training, respectively).

Training industrial robots with gesture recognition techniques

NASA Astrophysics Data System (ADS)

Piane, Jennifer; Raicu, Daniela; Furst, Jacob

2013-01-01

In this paper we propose to use gesture recognition approaches to track a human hand in 3D space and, without the use of special clothing or markers, be able to accurately generate code for training an industrial robot to perform the same motion. The proposed hand tracking component includes three methods: a color-thresholding model, naïve Bayes analysis and Support Vector Machine (SVM) to detect the human hand. Next, it performs stereo matching on the region where the hand was detected to find relative 3D coordinates. The list of coordinates returned is expectedly noisy due to the way the human hand can alter its apparent shape while moving, the inconsistencies in human motion and detection failures in the cluttered environment. Therefore, the system analyzes the list of coordinates to determine a path for the robot to move, by smoothing the data to reduce noise and looking for significant points used to determine the path the robot will ultimately take. The proposed system was applied to pairs of videos recording the motion of a human hand in a „real‟ environment to move the end-affector of a SCARA robot along the same path as the hand of the person in the video. The correctness of the robot motion was determined by observers indicating that motion of the robot appeared to match the motion of the video.

SeleCon: Scalable IoT Device Selection and Control Using Hand Gestures

PubMed Central

Alanwar, Amr; Alzantot, Moustafa; Ho, Bo-Jhang; Martin, Paul; Srivastava, Mani

2018-01-01

Although different interaction modalities have been proposed in the field of human-computer interface (HCI), only a few of these techniques could reach the end users because of scalability and usability issues. Given the popularity and the growing number of IoT devices, selecting one out of many devices becomes a hurdle in a typical smarthome environment. Therefore, an easy-to-learn, scalable, and non-intrusive interaction modality has to be explored. In this paper, we propose a pointing approach to interact with devices, as pointing is arguably a natural way for device selection. We introduce SeleCon for device selection and control which uses an ultra-wideband (UWB) equipped smartwatch. To interact with a device in our system, people can point to the device to select it then draw a hand gesture in the air to specify a control action. To this end, SeleCon employs inertial sensors for pointing gesture detection and a UWB transceiver for identifying the selected device from ranging measurements. Furthermore, SeleCon supports an alphabet of gestures that can be used for controlling the selected devices. We performed our experiment in a 9m-by-10m lab space with eight deployed devices. The results demonstrate that SeleCon can achieve 84.5% accuracy for device selection and 97% accuracy for hand gesture recognition. We also show that SeleCon is power efficient to sustain daily use by turning off the UWB transceiver, when a user’s wrist is stationary. PMID:29683151

Hand gestures support word learning in patients with hippocampal amnesia.

PubMed

Hilverman, Caitlin; Cook, Susan Wagner; Duff, Melissa C

2018-06-01

Co-speech hand gesture facilitates learning and memory, yet the cognitive and neural mechanisms supporting this remain unclear. One possibility is that motor information in gesture may engage procedural memory representations. Alternatively, iconic information from gesture may contribute to declarative memory representations mediated by the hippocampus. To investigate these alternatives, we examined gesture's effects on word learning in patients with hippocampal damage and declarative memory impairment, with intact procedural memory, and in healthy and in brain-damaged comparison groups. Participants learned novel label-object pairings while producing gesture, observing gesture, or observing without gesture. After a delay, recall and object identification were assessed. Unsurprisingly, amnesic patients were unable to recall the labels at test. However, they correctly identified objects at above chance levels, but only if they produced a gesture at encoding. Comparison groups performed well above chance at both recall and object identification regardless of gesture. These findings suggest that gesture production may support word learning by engaging nondeclarative (procedural) memory. © 2018 Wiley Periodicals, Inc.

Real time gesture based control: A prototype development

NASA Astrophysics Data System (ADS)

Bhargava, Deepshikha; Solanki, L.; Rai, Satish Kumar

2016-03-01

The computer industry is getting advanced. In a short span of years, industry is growing high with advanced techniques. Robots have been replacing humans, increasing the efficiency, accessibility and accuracy of the system and creating man-machine interaction. Robotic industry is developing many new trends. However, they still need to be controlled by humans itself. This paper presents an approach to control a motor like a robot with hand gestures not by old ways like buttons or physical devices. Controlling robots with hand gestures is very popular now-a-days. Currently, at this level, gesture features are applied for detecting and tracking the hand in real time. A principal component analysis algorithm is being used for identification of a hand gesture by using open CV image processing library. Contours, convex-hull, and convexity defects are the gesture features. PCA is a statistical approach used for reducing the number of variables in hand recognition. While extracting the most relevant information (feature) contained in the images (hand). After detecting and recognizing hand a servo motor is being controlled, which uses hand gesture as an input device (like mouse and keyboard), and reduces human efforts.

Power independent EMG based gesture recognition for robotics.

PubMed

Li, Ling; Looney, David; Park, Cheolsoo; Rehman, Naveed U; Mandic, Danilo P

2011-01-01

A novel method for detecting muscle contraction is presented. This method is further developed for identifying four different gestures to facilitate a hand gesture controlled robot system. It is achieved based on surface Electromyograph (EMG) measurements of groups of arm muscles. The cross-information is preserved through a simultaneous processing of EMG channels using a recent multivariate extension of Empirical Mode Decomposition (EMD). Next, phase synchrony measures are employed to make the system robust to different power levels due to electrode placements and impedances. The multiple pairwise muscle synchronies are used as features of a discrete gesture space comprising four gestures (flexion, extension, pronation, supination). Simulations on real-time robot control illustrate the enhanced accuracy and robustness of the proposed methodology.

An Interactive Astronaut-Robot System with Gesture Control

PubMed Central

Liu, Jinguo; Luo, Yifan; Ju, Zhaojie

2016-01-01

Human-robot interaction (HRI) plays an important role in future planetary exploration mission, where astronauts with extravehicular activities (EVA) have to communicate with robot assistants by speech-type or gesture-type user interfaces embedded in their space suits. This paper presents an interactive astronaut-robot system integrating a data-glove with a space suit for the astronaut to use hand gestures to control a snake-like robot. Support vector machine (SVM) is employed to recognize hand gestures and particle swarm optimization (PSO) algorithm is used to optimize the parameters of SVM to further improve its recognition accuracy. Various hand gestures from American Sign Language (ASL) have been selected and used to test and validate the performance of the proposed system. PMID:27190503

Give me a hand: Differential effects of gesture type in guiding young children's problem-solving.

PubMed

Vallotton, Claire; Fusaro, Maria; Hayden, Julia; Decker, Kalli; Gutowski, Elizabeth

2015-11-01

Adults' gestures support children's learning in problem-solving tasks, but gestures may be differentially useful to children of different ages, and different features of gestures may make them more or less useful to children. The current study investigated parents' use of gestures to support their young children (1.5 - 6 years) in a block puzzle task (N = 126 parent-child dyads), and identified patterns in parents' gesture use indicating different gestural strategies. Further, we examined the effect of child age on both the frequency and types of gestures parents used, and on their usefulness to support children's learning. Children attempted to solve the puzzle independently before and after receiving help from their parent; half of the parents were instructed to sit on their hands while they helped. Parents who could use their hands appear to use gestures in three strategies: orienting the child to the task, providing abstract information, and providing embodied information; further, they adapted their gesturing to their child's age and skill level. Younger children elicited more frequent and more proximal gestures from parents. Despite the greater use of gestures with younger children, it was the oldest group (4.5-6.0 years) who were most affected by parents' gestures. The oldest group was positively affected by the total frequency of parents' gestures, and in particular, parents' use of embodying gestures (indexes that touched their referents, representational demonstrations with object in hand, and physically guiding child's hands). Though parents rarely used the embodying strategy with older children, it was this strategy which most enhanced the problem-solving of children 4.5 - 6 years.

Give me a hand: Differential effects of gesture type in guiding young children's problem-solving

PubMed Central

Vallotton, Claire; Fusaro, Maria; Hayden, Julia; Decker, Kalli; Gutowski, Elizabeth

2015-01-01

Adults’ gestures support children's learning in problem-solving tasks, but gestures may be differentially useful to children of different ages, and different features of gestures may make them more or less useful to children. The current study investigated parents’ use of gestures to support their young children (1.5 – 6 years) in a block puzzle task (N = 126 parent-child dyads), and identified patterns in parents’ gesture use indicating different gestural strategies. Further, we examined the effect of child age on both the frequency and types of gestures parents used, and on their usefulness to support children's learning. Children attempted to solve the puzzle independently before and after receiving help from their parent; half of the parents were instructed to sit on their hands while they helped. Parents who could use their hands appear to use gestures in three strategies: orienting the child to the task, providing abstract information, and providing embodied information; further, they adapted their gesturing to their child's age and skill level. Younger children elicited more frequent and more proximal gestures from parents. Despite the greater use of gestures with younger children, it was the oldest group (4.5-6.0 years) who were most affected by parents’ gestures. The oldest group was positively affected by the total frequency of parents’ gestures, and in particular, parents’ use of embodying gestures (indexes that touched their referents, representational demonstrations with object in hand, and physically guiding child's hands). Though parents rarely used the embodying strategy with older children, it was this strategy which most enhanced the problem-solving of children 4.5 – 6 years. PMID:26848192

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures

PubMed Central

Pi, Yiming

2017-01-01

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar. PMID:29267249

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

PubMed

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

Decoding static and dynamic arm and hand gestures from the JPL BioSleeve

NASA Astrophysics Data System (ADS)

Wolf, M. T.; Assad, C.; Stoica, A.; You, Kisung; Jethani, H.; Vernacchia, M. T.; Fromm, J.; Iwashita, Y.

This paper presents methods for inferring arm and hand gestures from forearm surface electromyography (EMG) sensors and an inertial measurement unit (IMU). These sensors, together with their electronics, are packaged in an easily donned device, termed the BioSleeve, worn on the forearm. The gestures decoded from BioSleeve signals can provide natural user interface commands to computers and robots, without encumbering the users hands and without problems that hinder camera-based systems. Potential aerospace applications for this technology include gesture-based crew-autonomy interfaces, high degree of freedom robot teleoperation, and astronauts' control of power-assisted gloves during extra-vehicular activity (EVA). We have developed techniques to interpret both static (stationary) and dynamic (time-varying) gestures from the BioSleeve signals, enabling a diverse and adaptable command library. For static gestures, we achieved over 96% accuracy on 17 gestures and nearly 100% accuracy on 11 gestures, based solely on EMG signals. Nine dynamic gestures were decoded with an accuracy of 99%. This combination of wearableEMGand IMU hardware and accurate algorithms for decoding both static and dynamic gestures thus shows promise for natural user interface applications.

A Kinect-Based Sign Language Hand Gesture Recognition System for Hearing- and Speech-Impaired: A Pilot Study of Pakistani Sign Language.

PubMed

Halim, Zahid; Abbas, Ghulam

2015-01-01

Sign language provides hearing and speech impaired individuals with an interface to communicate with other members of the society. Unfortunately, sign language is not understood by most of the common people. For this, a gadget based on image processing and pattern recognition can provide with a vital aid for detecting and translating sign language into a vocal language. This work presents a system for detecting and understanding the sign language gestures by a custom built software tool and later translating the gesture into a vocal language. For the purpose of recognizing a particular gesture, the system employs a Dynamic Time Warping (DTW) algorithm and an off-the-shelf software tool is employed for vocal language generation. Microsoft(®) Kinect is the primary tool used to capture video stream of a user. The proposed method is capable of successfully detecting gestures stored in the dictionary with an accuracy of 91%. The proposed system has the ability to define and add custom made gestures. Based on an experiment in which 10 individuals with impairments used the system to communicate with 5 people with no disability, 87% agreed that the system was useful.

Real-time face and gesture analysis for human-robot interaction

NASA Astrophysics Data System (ADS)

Wallhoff, Frank; Rehrl, Tobias; Mayer, Christoph; Radig, Bernd

2010-05-01

Human communication relies on a large number of different communication mechanisms like spoken language, facial expressions, or gestures. Facial expressions and gestures are one of the main nonverbal communication mechanisms and pass large amounts of information between human dialog partners. Therefore, to allow for intuitive human-machine interaction, a real-time capable processing and recognition of facial expressions, hand and head gestures are of great importance. We present a system that is tackling these challenges. The input features for the dynamic head gestures and facial expressions are obtained from a sophisticated three-dimensional model, which is fitted to the user in a real-time capable manner. Applying this model different kinds of information are extracted from the image data and afterwards handed over to a real-time capable data-transferring framework, the so-called Real-Time DataBase (RTDB). In addition to the head and facial-related features, also low-level image features regarding the human hand - optical flow, Hu-moments are stored into the RTDB for the evaluation process of hand gestures. In general, the input of a single camera is sufficient for the parallel evaluation of the different gestures and facial expressions. The real-time capable recognition of the dynamic hand and head gestures are performed via different Hidden Markov Models, which have proven to be a quick and real-time capable classification method. On the other hand, for the facial expressions classical decision trees or more sophisticated support vector machines are used for the classification process. These obtained results of the classification processes are again handed over to the RTDB, where other processes (like a Dialog Management Unit) can easily access them without any blocking effects. In addition, an adjustable amount of history can be stored by the RTDB buffer unit.

Using a social robot to teach gestural recognition and production in children with autism spectrum disorders.

PubMed

So, Wing-Chee; Wong, Miranda Kit-Yi; Lam, Carrie Ka-Yee; Lam, Wan-Yi; Chui, Anthony Tsz-Fung; Lee, Tsz-Lok; Ng, Hoi-Man; Chan, Chun-Hung; Fok, Daniel Chun-Wing

2017-07-04

While it has been argued that children with autism spectrum disorders are responsive to robot-like toys, very little research has examined the impact of robot-based intervention on gesture use. These children have delayed gestural development. We used a social robot in two phases to teach them to recognize and produce eight pantomime gestures that expressed feelings and needs. Compared to the children in the wait-list control group (N = 6), those in the intervention group (N = 7) were more likely to recognize gestures and to gesture accurately in trained and untrained scenarios. They also generalized the acquired recognition (but not production) skills to human-to-human interaction. The benefits and limitations of robot-based intervention for gestural learning were highlighted. Implications for Rehabilitation Compared to typically-developing children, children with autism spectrum disorders have delayed development of gesture comprehension and production. Robot-based intervention program was developed to teach children with autism spectrum disorders recognition (Phase I) and production (Phase II) of eight pantomime gestures that expressed feelings and needs. Children in the intervention group (but not in the wait-list control group) were able to recognize more gestures in both trained and untrained scenarios and generalize the acquired gestural recognition skills to human-to-human interaction. Similar findings were reported for gestural production except that there was no strong evidence showing children in the intervention group could produce gestures accurately in human-to-human interaction.

Gesture Recognition for Educational Games: Magic Touch Math

NASA Astrophysics Data System (ADS)

Kye, Neo Wen; Mustapha, Aida; Azah Samsudin, Noor

2017-08-01

Children nowadays are having problem learning and understanding basic mathematical operations because they are not interested in studying or learning mathematics. This project proposes an educational game called Magic Touch Math that focuses on basic mathematical operations targeted to children between the age of three to five years old using gesture recognition to interact with the game. Magic Touch Math was developed in accordance to the Game Development Life Cycle (GDLC) methodology. The prototype developed has helped children to learn basic mathematical operations via intuitive gestures. It is hoped that the application is able to get the children motivated and interested in mathematics.

Full-body gestures and movements recognition: user descriptive and unsupervised learning approaches in GDL classifier

NASA Astrophysics Data System (ADS)

Hachaj, Tomasz; Ogiela, Marek R.

2014-09-01

Gesture Description Language (GDL) is a classifier that enables syntactic description and real time recognition of full-body gestures and movements. Gestures are described in dedicated computer language named Gesture Description Language script (GDLs). In this paper we will introduce new GDLs formalisms that enable recognition of selected classes of movement trajectories. The second novelty is new unsupervised learning method with which it is possible to automatically generate GDLs descriptions. We have initially evaluated both proposed extensions of GDL and we have obtained very promising results. Both the novel methodology and evaluation results will be described in this paper.

Gesture recognition for smart home applications using portable radar sensors.

PubMed

Wan, Qian; Li, Yiran; Li, Changzhi; Pal, Ranadip

2014-01-01

In this article, we consider the design of a human gesture recognition system based on pattern recognition of signatures from a portable smart radar sensor. Powered by AAA batteries, the smart radar sensor operates in the 2.4 GHz industrial, scientific and medical (ISM) band. We analyzed the feature space using principle components and application-specific time and frequency domain features extracted from radar signals for two different sets of gestures. We illustrate that a nearest neighbor based classifier can achieve greater than 95% accuracy for multi class classification using 10 fold cross validation when features are extracted based on magnitude differences and Doppler shifts as compared to features extracted through orthogonal transformations. The reported results illustrate the potential of intelligent radars integrated with a pattern recognition system for high accuracy smart home and health monitoring purposes.

Speech-associated gestures, Broca’s area, and the human mirror system

PubMed Central

Skipper, Jeremy I.; Goldin-Meadow, Susan; Nusbaum, Howard C.; Small, Steven L

2009-01-01

Speech-associated gestures are hand and arm movements that not only convey semantic information to listeners but are themselves actions. Broca’s area has been assumed to play an important role both in semantic retrieval or selection (as part of a language comprehension system) and in action recognition (as part of a “mirror” or “observation–execution matching” system). We asked whether the role that Broca’s area plays in processing speech-associated gestures is consistent with the semantic retrieval/selection account (predicting relatively weak interactions between Broca’s area and other cortical areas because the meaningful information that speech-associated gestures convey reduces semantic ambiguity and thus reduces the need for semantic retrieval/selection) or the action recognition account (predicting strong interactions between Broca’s area and other cortical areas because speech-associated gestures are goal-direct actions that are “mirrored”). We compared the functional connectivity of Broca’s area with other cortical areas when participants listened to stories while watching meaningful speech-associated gestures, speech-irrelevant self-grooming hand movements, or no hand movements. A network analysis of neuroimaging data showed that interactions involving Broca’s area and other cortical areas were weakest when spoken language was accompanied by meaningful speech-associated gestures, and strongest when spoken language was accompanied by self-grooming hand movements or by no hand movements at all. Results are discussed with respect to the role that the human mirror system plays in processing speech-associated movements. PMID:17533001

Metaphor Explanation Attenuates the Right-Hand Preference for Depictive Co-Speech Gestures that Imitate Actions

ERIC Educational Resources Information Center

Kita, Sotaro; de Condappa, Olivier; Mohr, Christine

2007-01-01

Differential activation levels of the two hemispheres due to hemispheric specialization for various linguistic processes might determine hand choice for co-speech gestures. To test this hypothesis, we compared hand choices for gesturing in 20 healthy right-handed participants during explanation of metaphorical vs. non-metaphorical meanings, on the…

Coronary Heart Disease Preoperative Gesture Interactive Diagnostic System Based on Augmented Reality.

PubMed

Zou, Yi-Bo; Chen, Yi-Min; Gao, Ming-Ke; Liu, Quan; Jiang, Si-Yu; Lu, Jia-Hui; Huang, Chen; Li, Ze-Yu; Zhang, Dian-Hua

2017-08-01

Coronary heart disease preoperative diagnosis plays an important role in the treatment of vascular interventional surgery. Actually, most doctors are used to diagnosing the position of the vascular stenosis and then empirically estimating vascular stenosis by selective coronary angiography images instead of using mouse, keyboard and computer during preoperative diagnosis. The invasive diagnostic modality is short of intuitive and natural interaction and the results are not accurate enough. Aiming at above problems, the coronary heart disease preoperative gesture interactive diagnostic system based on Augmented Reality is proposed. The system uses Leap Motion Controller to capture hand gesture video sequences and extract the features which that are the position and orientation vector of the gesture motion trajectory and the change of the hand shape. The training planet is determined by K-means algorithm and then the effect of gesture training is improved by multi-features and multi-observation sequences for gesture training. The reusability of gesture is improved by establishing the state transition model. The algorithm efficiency is improved by gesture prejudgment which is used by threshold discriminating before recognition. The integrity of the trajectory is preserved and the gesture motion space is extended by employing space rotation transformation of gesture manipulation plane. Ultimately, the gesture recognition based on SRT-HMM is realized. The diagnosis and measurement of the vascular stenosis are intuitively and naturally realized by operating and measuring the coronary artery model with augmented reality and gesture interaction techniques. All of the gesture recognition experiments show the distinguish ability and generalization ability of the algorithm and gesture interaction experiments prove the availability and reliability of the system.

Motion-sensor fusion-based gesture recognition and its VLSI architecture design for mobile devices

NASA Astrophysics Data System (ADS)

Zhu, Wenping; Liu, Leibo; Yin, Shouyi; Hu, Siqi; Tang, Eugene Y.; Wei, Shaojun

2014-05-01

With the rapid proliferation of smartphones and tablets, various embedded sensors are incorporated into these platforms to enable multimodal human-computer interfaces. Gesture recognition, as an intuitive interaction approach, has been extensively explored in the mobile computing community. However, most gesture recognition implementations by now are all user-dependent and only rely on accelerometer. In order to achieve competitive accuracy, users are required to hold the devices in predefined manner during the operation. In this paper, a high-accuracy human gesture recognition system is proposed based on multiple motion sensor fusion. Furthermore, to reduce the energy overhead resulted from frequent sensor sampling and data processing, a high energy-efficient VLSI architecture implemented on a Xilinx Virtex-5 FPGA board is also proposed. Compared with the pure software implementation, approximately 45 times speed-up is achieved while operating at 20 MHz. The experiments show that the average accuracy for 10 gestures achieves 93.98% for user-independent case and 96.14% for user-dependent case when subjects hold the device randomly during completing the specified gestures. Although a few percent lower than the conventional best result, it still provides competitive accuracy acceptable for practical usage. Most importantly, the proposed system allows users to hold the device randomly during operating the predefined gestures, which substantially enhances the user experience.

Split-brain patients neglect left personal space during right-handed gestures.

PubMed

Lausberg, Hedda; Kita, Sotaro; Zaidel, Eran; Ptito, Alain

2003-01-01

Since some patients with right hemisphere damage or with spontaneous callosal disconnection neglect the left half of space, it has been suggested that the left cerebral hemisphere predominantly attends to the right half of space. However, clinical investigations of patients having undergone surgical callosal section have not shown neglect when the hemispheres are tested separately. These observations question the validity of theoretical models that propose a left hemispheric specialisation for attending to the right half of space. The present study aims to investigate neglect and the use of space by either hand in gestural demonstrations in three split-brain patients as compared to five patients with partial callosotomy and 11 healthy subjects. Subjects were asked to demonstrate with precise gestures and without speaking the content of animated scenes with two moving objects. The results show that in the absence of primary perceptual or representational neglect, split-brain patients neglect left personal space in right-handed gestural demonstrations. Since this neglect of left personal space cannot be explained by directional or spatial akinesia, it is suggested that it originates at the conceptual level, where the spatial coordinates for right-hand gestures are planned. The present findings are at odds with the position that the separate left hemisphere possesses adequate mechanisms for acting in both halves of space and neglect results from right hemisphere suppression of this potential. Rather, the results provide support for theoretical models that consider the left hemisphere as specialised for processing the right half of space during the execution of descriptive gestures.

Seeing Iconic Gestures While Encoding Events Facilitates Children's Memory of These Events.

PubMed

Aussems, Suzanne; Kita, Sotaro

2017-11-08

An experiment with 72 three-year-olds investigated whether encoding events while seeing iconic gestures boosts children's memory representation of these events. The events, shown in videos of actors moving in an unusual manner, were presented with either iconic gestures depicting how the actors performed these actions, interactive gestures, or no gesture. In a recognition memory task, children in the iconic gesture condition remembered actors and actions better than children in the control conditions. Iconic gestures were categorized based on how much of the actors was represented by the hands (feet, legs, or body). Only iconic hand-as-body gestures boosted actor memory. Thus, seeing iconic gestures while encoding events facilitates children's memory of those aspects of events that are schematically highlighted by gesture. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Gesture-Controlled Interfaces for Self-Service Machines

NASA Technical Reports Server (NTRS)

Cohen, Charles J.; Beach, Glenn

2006-01-01

Gesture-controlled interfaces are software- driven systems that facilitate device control by translating visual hand and body signals into commands. Such interfaces could be especially attractive for controlling self-service machines (SSMs) for example, public information kiosks, ticket dispensers, gasoline pumps, and automated teller machines (see figure). A gesture-controlled interface would include a vision subsystem comprising one or more charge-coupled-device video cameras (at least two would be needed to acquire three-dimensional images of gestures). The output of the vision system would be processed by a pure software gesture-recognition subsystem. Then a translator subsystem would convert a sequence of recognized gestures into commands for the SSM to be controlled; these could include, for example, a command to display requested information, change control settings, or actuate a ticket- or cash-dispensing mechanism. Depending on the design and operational requirements of the SSM to be controlled, the gesture-controlled interface could be designed to respond to specific static gestures, dynamic gestures, or both. Static and dynamic gestures can include stationary or moving hand signals, arm poses or motions, and/or whole-body postures or motions. Static gestures would be recognized on the basis of their shapes; dynamic gestures would be recognized on the basis of both their shapes and their motions. Because dynamic gestures include temporal as well as spatial content, this gesture- controlled interface can extract more information from dynamic than it can from static gestures.

Hands in space: gesture interaction with augmented-reality interfaces.

PubMed

Billinghurst, Mark; Piumsomboon, Tham; Huidong Bai

2014-01-01

Researchers at the Human Interface Technology Laboratory New Zealand (HIT Lab NZ) are investigating free-hand gestures for natural interaction with augmented-reality interfaces. They've applied the results to systems for desktop computers and mobile devices.

Development of a Wearable Controller for Gesture-Recognition-Based Applications Using Polyvinylidene Fluoride.

PubMed

Van Volkinburg, Kyle; Washington, Gregory

2017-08-01

This paper reports on a wearable gesture-based controller fabricated using the sensing capabilities of the flexible thin-film piezoelectric polymer polyvinylidene fluoride (PVDF) which is shown to repeatedly and accurately discern, in real time, between right and left hand gestures. The PVDF is affixed to a compression sleeve worn on the forearm to create a wearable device that is flexible, adaptable, and highly shape conforming. Forearm muscle movements, which drive hand motions, are detected by the PVDF which outputs its voltage signal to a developed microcontroller-based board and processed by an artificial neural network that was trained to recognize the generated voltage profile of right and left hand gestures. The PVDF has been spatially shaded (etched) in such a way as to increase sensitivity to expected deformations caused by the specific muscles employed in making the targeted right and left gestures. The device proves to be exceptionally accurate both when positioned as intended and when rotated and translated on the forearm.

A new method for recognizing hand configurations of Brazilian gesture language.

PubMed

Costa Filho, C F F; Dos Santos, B L; de Souza, R S; Dos Santos, J R; Costa, M G F

2016-08-01

This paper describes a new method for recognizing hand configurations of the Brazilian Gesture Language - LIBRAS - using depth maps obtained with a Kinect® camera. The proposed method comprised three phases: hand segmentation, feature extraction, and classification. The segmentation phase is independent from the background and depends only on pixel depth information. Using geometric operations and numerical normalization, the feature extraction process was done independent from rotation and translation. The features are extracted employing two techniques: (2D)2LDA and (2D)2PCA. The classification is made with a novelty classifier. A robust database was constructed for classifier evaluation, with 12,200 images of LIBRAS and 200 gestures of each hand configuration. The best accuracy obtained was 95.41%, which was greater than previous values obtained in the literature.

Hand movements with a phase structure and gestures that depict action stem from a left hemispheric system of conceptualization.

PubMed

Helmich, I; Lausberg, H

2014-10-01

The present study addresses the previously discussed controversy on the contribution of the right and left cerebral hemispheres to the production and conceptualization of spontaneous hand movements and gestures. Although it has been shown that each hemisphere contains the ability to produce hand movements, results of left hemispherically lateralized motor functions challenge the view of a contralateral hand movement production system. To examine hemispheric specialization in hand movement and gesture production, ten right-handed participants were tachistoscopically presented pictures of everyday life actions. The participants were asked to demonstrate with their hands, but without speaking what they had seen on the drawing. Two independent blind raters evaluated the videotaped hand movements and gestures employing the Neuropsychological Gesture Coding System. The results showed that the overall frequency of right- and left-hand movements is equal independent of stimulus lateralization. When hand movements were analyzed considering their Structure, the presentation of the action stimuli to the left hemisphere resulted in more hand movements with a phase structure than the presentation to the right hemisphere. Furthermore, the presentation to the left hemisphere resulted in more right and left-hand movements with a phase structure, whereas the presentation to the right hemisphere only increased contralateral left-hand movements with a phase structure as compared to hand movements without a phase structure. Gestures that depict action were primarily displayed in response to stimuli presented in the right visual field than in the left one. The present study shows that both hemispheres possess the faculty to produce hand movements in response to action stimuli. However, the left hemisphere dominates the production of hand movements with a phase structure and gestures that depict action. We therefore conclude that hand movements with a phase structure and gestures that

Human facial neural activities and gesture recognition for machine-interfacing applications.

PubMed

Hamedi, M; Salleh, Sh-Hussain; Tan, T S; Ismail, K; Ali, J; Dee-Uam, C; Pavaganun, C; Yupapin, P P

2011-01-01

The authors present a new method of recognizing different human facial gestures through their neural activities and muscle movements, which can be used in machine-interfacing applications. Human-machine interface (HMI) technology utilizes human neural activities as input controllers for the machine. Recently, much work has been done on the specific application of facial electromyography (EMG)-based HMI, which have used limited and fixed numbers of facial gestures. In this work, a multipurpose interface is suggested that can support 2-11 control commands that can be applied to various HMI systems. The significance of this work is finding the most accurate facial gestures for any application with a maximum of eleven control commands. Eleven facial gesture EMGs are recorded from ten volunteers. Detected EMGs are passed through a band-pass filter and root mean square features are extracted. Various combinations of gestures with a different number of gestures in each group are made from the existing facial gestures. Finally, all combinations are trained and classified by a Fuzzy c-means classifier. In conclusion, combinations with the highest recognition accuracy in each group are chosen. An average accuracy >90% of chosen combinations proved their ability to be used as command controllers.

Chair alarm for patient fall prevention based on gesture recognition and interactivity.

PubMed

Knight, Heather; Lee, Jae-Kyu; Ma, Hongshen

2008-01-01

The Gesture Recognition Interactive Technology (GRiT) Chair Alarm aims to prevent patient falls from chairs and wheelchairs by recognizing the gesture of a patient attempting to stand. Patient falls are one of the greatest causes of injury in hospitals. Current chair and bed exit alarm systems are inadequate because of insufficient notification, high false-alarm rate, and long trigger delays. The GRiT chair alarm uses an array of capacitive proximity sensors and pressure sensors to create a map of the patient's sitting position, which is then processed using gesture recognition algorithms to determine when a patient is attempting to stand and to alarm the care providers. This system also uses a range of voice and light feedback to encourage the patient to remain seated and/or to make use of the system's integrated nurse-call function. This system can be seamlessly integrated into existing hospital WiFi networks to send notifications and approximate patient location through existing nurse call systems.

Exploring the Relationship between Gestural Recognition and Imitation: Evidence of Dyspraxia in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Ham, Heidi Stieglitz; Bartolo, Angela; Corley, Martin; Rajendran, Gnanathusharan; Szabo, Aniko; Swanson, Sara

2011-01-01

In this study, the relationship between gesture recognition and imitation was explored. Nineteen individuals with Autism Spectrum Disorder (ASD) were compared to a control group of 23 typically developing children on their ability to imitate and recognize three gesture types (transitive, intransitive, and pantomimes). The ASD group performed more…

Hand gesture guided robot-assisted surgery based on a direct augmented reality interface.

PubMed

Wen, Rong; Tay, Wei-Liang; Nguyen, Binh P; Chng, Chin-Boon; Chui, Chee-Kong

2014-09-01

Radiofrequency (RF) ablation is a good alternative to hepatic resection for treatment of liver tumors. However, accurate needle insertion requires precise hand-eye coordination and is also affected by the difficulty of RF needle navigation. This paper proposes a cooperative surgical robot system, guided by hand gestures and supported by an augmented reality (AR)-based surgical field, for robot-assisted percutaneous treatment. It establishes a robot-assisted natural AR guidance mechanism that incorporates the advantages of the following three aspects: AR visual guidance information, surgeon's experiences and accuracy of robotic surgery. A projector-based AR environment is directly overlaid on a patient to display preoperative and intraoperative information, while a mobile surgical robot system implements specified RF needle insertion plans. Natural hand gestures are used as an intuitive and robust method to interact with both the AR system and surgical robot. The proposed system was evaluated on a mannequin model. Experimental results demonstrated that hand gesture guidance was able to effectively guide the surgical robot, and the robot-assisted implementation was found to improve the accuracy of needle insertion. This human-robot cooperative mechanism is a promising approach for precise transcutaneous ablation therapy. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Comprehension of iconic gestures by chimpanzees and human children.

PubMed

Bohn, Manuel; Call, Josep; Tomasello, Michael

2016-02-01

Iconic gestures-communicative acts using hand or body movements that resemble their referent-figure prominently in theories of language evolution and development. This study contrasted the abilities of chimpanzees (N=11) and 4-year-old human children (N=24) to comprehend novel iconic gestures. Participants learned to retrieve rewards from apparatuses in two distinct locations, each requiring a different action. In the test, a human adult informed the participant where to go by miming the action needed to obtain the reward. Children used the iconic gestures (more than arbitrary gestures) to locate the reward, whereas chimpanzees did not. Some children also used arbitrary gestures in the same way, but only after they had previously shown comprehension for iconic gestures. Over time, chimpanzees learned to associate iconic gestures with the appropriate location faster than arbitrary gestures, suggesting at least some recognition of the iconicity involved. These results demonstrate the importance of iconicity in referential communication. Copyright © 2015 Elsevier Inc. All rights reserved.

An Individual Finger Gesture Recognition System Based on Motion-Intent Analysis Using Mechanomyogram Signal

PubMed Central

Ding, Huijun; He, Qing; Zhou, Yongjin; Dan, Guo; Cui, Song

2017-01-01

Motion-intent-based finger gesture recognition systems are crucial for many applications such as prosthesis control, sign language recognition, wearable rehabilitation system, and human–computer interaction. In this article, a motion-intent-based finger gesture recognition system is designed to correctly identify the tapping of every finger for the first time. Two auto-event annotation algorithms are firstly applied and evaluated for detecting the finger tapping frame. Based on the truncated signals, the Wavelet packet transform (WPT) coefficients are calculated and compressed as the features, followed by a feature selection method that is able to improve the performance by optimizing the feature set. Finally, three popular classifiers including naive Bayes (NBC), K-nearest neighbor (KNN), and support vector machine (SVM) are applied and evaluated. The recognition accuracy can be achieved up to 94%. The design and the architecture of the system are presented with full system characterization results. PMID:29167655

What properties of talk are associated with the generation of spontaneous iconic hand gestures?

PubMed

Beattie, Geoffrey; Shovelton, Heather

2002-09-01

When people talk, they frequently make movements of their arms and hands, some of which appear connected with the content of the speech and are termed iconic gestures. Critical to our understanding of the relationship between speech and iconic gesture is an analysis of what properties of talk might give rise to these gestures. This paper focuses on two such properties, namely the familiarity and the imageability of the core propositional units that the gestures accompany. The study revealed that imageability had a significant effect overall on the probability of the core propositional unit being accompanied by a gesture, but that familiarity did not. Familiarity did, however, have a significant effect on the probability of a gesture in the case of high imageability units and in the case of units associated with frequent gesture use. Those iconic gestures accompanying core propositional units variously defined by the properties of imageability and familiarity were found to differ in their level of idiosyncrasy, the viewpoint from which they were generated and their overall communicative effect. This research thus uncovered a number of quite distinct relationships between gestures and speech in everyday talk, with important implications for future theories in this area.

Iconic hand gestures and the predictability of words in context in spontaneous speech.

PubMed

Beattie, G; Shovelton, H

2000-11-01

This study presents a series of empirical investigations to test a theory of speech production proposed by Butterworth and Hadar (1989; revised in Hadar & Butterworth, 1997) that iconic gestures have a functional role in lexical retrieval in spontaneous speech. Analysis 1 demonstrated that words which were totally unpredictable (as measured by the Shannon guessing technique) were more likely to occur after pauses than after fluent speech, in line with earlier findings. Analysis 2 demonstrated that iconic gestures were associated with words of lower transitional probability than words not associated with gesture, even when grammatical category was controlled. This therefore provided new supporting evidence for Butterworth and Hadar's claims that gestures' lexical affiliates are indeed unpredictable lexical items. However, Analysis 3 found that iconic gestures were not occasioned by lexical accessing difficulties because although gestures tended to occur with words of significantly lower transitional probability, these lower transitional probability words tended to be uttered quite fluently. Overall, therefore, this study provided little evidence for Butterworth and Hadar's theoretical claim that the main function of the iconic hand gestures that accompany spontaneous speech is to assist in the process of lexical access. Instead, such gestures are reconceptualized in terms of communicative function.

Exploring the role of hand gestures in learning novel phoneme contrasts and vocabulary in a second language

PubMed Central

Kelly, Spencer D.; Hirata, Yukari; Manansala, Michael; Huang, Jessica

2014-01-01

Co-speech hand gestures are a type of multimodal input that has received relatively little attention in the context of second language learning. The present study explored the role that observing and producing different types of gestures plays in learning novel speech sounds and word meanings in an L2. Naïve English-speakers were taught two components of Japanese—novel phonemic vowel length contrasts and vocabulary items comprised of those contrasts—in one of four different gesture conditions: Syllable Observe, Syllable Produce, Mora Observe, and Mora Produce. Half of the gestures conveyed intuitive information about syllable structure, and the other half, unintuitive information about Japanese mora structure. Within each Syllable and Mora condition, half of the participants only observed the gestures that accompanied speech during training, and the other half also produced the gestures that they observed along with the speech. The main finding was that participants across all four conditions had similar outcomes in two different types of auditory identification tasks and a vocabulary test. The results suggest that hand gestures may not be well suited for learning novel phonetic distinctions at the syllable level within a word, and thus, gesture-speech integration may break down at the lowest levels of language processing and learning. PMID:25071646

Gesture-Based Robot Control with Variable Autonomy from the JPL Biosleeve

NASA Technical Reports Server (NTRS)

Wolf, Michael T.; Assad, Christopher; Vernacchia, Matthew T.; Fromm, Joshua; Jethani, Henna L.

2013-01-01

This paper presents a new gesture-based human interface for natural robot control. Detailed activity of the user's hand and arm is acquired via a novel device, called the BioSleeve, which packages dry-contact surface electromyography (EMG) and an inertial measurement unit (IMU) into a sleeve worn on the forearm. The BioSleeve's accompanying algorithms can reliably decode as many as sixteen discrete hand gestures and estimate the continuous orientation of the forearm. These gestures and positions are mapped to robot commands that, to varying degrees, integrate with the robot's perception of its environment and its ability to complete tasks autonomously. This flexible approach enables, for example, supervisory point-to-goal commands, virtual joystick for guarded teleoperation, and high degree of freedom mimicked manipulation, all from a single device. The BioSleeve is meant for portable field use; unlike other gesture recognition systems, use of the BioSleeve for robot control is invariant to lighting conditions, occlusions, and the human-robot spatial relationship and does not encumber the user's hands. The BioSleeve control approach has been implemented on three robot types, and we present proof-of-principle demonstrations with mobile ground robots, manipulation robots, and prosthetic hands.

The use of open and machine vision technologies for development of gesture recognition intelligent systems

NASA Astrophysics Data System (ADS)

Cherkasov, Kirill V.; Gavrilova, Irina V.; Chernova, Elena V.; Dokolin, Andrey S.

2018-05-01

The article is devoted to reflection of separate aspects of intellectual system gesture recognition development. The peculiarity of the system is its intellectual block which completely based on open technologies: OpenCV library and Microsoft Cognitive Toolkit (CNTK) platform. The article presents the rationale for the choice of such set of tools, as well as the functional scheme of the system and the hierarchy of its modules. Experiments have shown that the system correctly recognizes about 85% of images received from sensors. The authors assume that the improvement of the algorithmic block of the system will increase the accuracy of gesture recognition up to 95%.

Detection of Hand-to-Mouth Gestures Using a RF Operated Proximity Sensor for Monitoring Cigarette Smoking.

PubMed

Lopez-Meyer, Paulo; Patil, Yogendra; Tiffany, Tiffany; Sazonov, Edward

2013-01-01

Common methods for monitoring of cigarette smoking, such as portable puff-topography instruments or self-report questionnaires, tend to be biased due to conscious or unconscious underreporting. Additionally, these methods may change the natural smoking behavior of individuals. Our long term objective is the development of a wearable non-invasive monitoring system (Personal Automatic Cigarette Tracker - PACT) to reliably monitor cigarette smoking behavior under free living conditions. PACT monitors smoking by observing characteristic breathing patterns of smoke inhalations that follow a cigarette-to-mouth hand gesture. As envisioned, PACT does not rely on self-report or require any conscious effort from the user. A major element of the PACT is a proximity sensor that detects typical cigarette-to-mouth gesture during cigarette smoking. This study describes the design and validation of a prototype RF proximity sensor that captures hand-to-mouth gestures with a high sensitivity (0.90), and a methodology that can reject up to 68% of artifacts gestures originating from activities other than cigarette smoking.

A word in the hand: action, gesture and mental representation in humans and non-human primates

PubMed Central

Cartmill, Erica A.; Beilock, Sian; Goldin-Meadow, Susan

2012-01-01

The movements we make with our hands both reflect our mental processes and help to shape them. Our actions and gestures can affect our mental representations of actions and objects. In this paper, we explore the relationship between action, gesture and thought in both humans and non-human primates and discuss its role in the evolution of language. Human gesture (specifically representational gesture) may provide a unique link between action and mental representation. It is kinaesthetically close to action and is, at the same time, symbolic. Non-human primates use gesture frequently to communicate, and do so flexibly. However, their gestures mainly resemble incomplete actions and lack the representational elements that characterize much of human gesture. Differences in the mirror neuron system provide a potential explanation for non-human primates' lack of representational gestures; the monkey mirror system does not respond to representational gestures, while the human system does. In humans, gesture grounds mental representation in action, but there is no evidence for this link in other primates. We argue that gesture played an important role in the transition to symbolic thought and language in human evolution, following a cognitive leap that allowed gesture to incorporate representational elements. PMID:22106432

Speech and gesture interfaces for squad-level human-robot teaming

NASA Astrophysics Data System (ADS)

Harris, Jonathan; Barber, Daniel

2014-06-01

As the military increasingly adopts semi-autonomous unmanned systems for military operations, utilizing redundant and intuitive interfaces for communication between Soldiers and robots is vital to mission success. Currently, Soldiers use a common lexicon to verbally and visually communicate maneuvers between teammates. In order for robots to be seamlessly integrated within mixed-initiative teams, they must be able to understand this lexicon. Recent innovations in gaming platforms have led to advancements in speech and gesture recognition technologies, but the reliability of these technologies for enabling communication in human robot teaming is unclear. The purpose for the present study is to investigate the performance of Commercial-Off-The-Shelf (COTS) speech and gesture recognition tools in classifying a Squad Level Vocabulary (SLV) for a spatial navigation reconnaissance and surveillance task. The SLV for this study was based on findings from a survey conducted with Soldiers at Fort Benning, GA. The items of the survey focused on the communication between the Soldier and the robot, specifically in regards to verbally instructing them to execute reconnaissance and surveillance tasks. Resulting commands, identified from the survey, were then converted to equivalent arm and hand gestures, leveraging existing visual signals (e.g. U.S. Army Field Manual for Visual Signaling). A study was then run to test the ability of commercially available automated speech recognition technologies and a gesture recognition glove to classify these commands in a simulated intelligence, surveillance, and reconnaissance task. This paper presents classification accuracy of these devices for both speech and gesture modalities independently.

Explore Efficient Local Features from RGB-D Data for One-Shot Learning Gesture Recognition.

PubMed

Wan, Jun; Guo, Guodong; Li, Stan Z

2016-08-01

Availability of handy RGB-D sensors has brought about a surge of gesture recognition research and applications. Among various approaches, one shot learning approach is advantageous because it requires minimum amount of data. Here, we provide a thorough review about one-shot learning gesture recognition from RGB-D data and propose a novel spatiotemporal feature extracted from RGB-D data, namely mixed features around sparse keypoints (MFSK). In the review, we analyze the challenges that we are facing, and point out some future research directions which may enlighten researchers in this field. The proposed MFSK feature is robust and invariant to scale, rotation and partial occlusions. To alleviate the insufficiency of one shot training samples, we augment the training samples by artificially synthesizing versions of various temporal scales, which is beneficial for coping with gestures performed at varying speed. We evaluate the proposed method on the Chalearn gesture dataset (CGD). The results show that our approach outperforms all currently published approaches on the challenging data of CGD, such as translated, scaled and occluded subsets. When applied to the RGB-D datasets that are not one-shot (e.g., the Cornell Activity Dataset-60 and MSR Daily Activity 3D dataset), the proposed feature also produces very promising results under leave-one-out cross validation or one-shot learning.

A Novel Phonology- and Radical-Coded Chinese Sign Language Recognition Framework Using Accelerometer and Surface Electromyography Sensors

PubMed Central

Cheng, Juan; Chen, Xun; Liu, Aiping; Peng, Hu

2015-01-01

Sign language recognition (SLR) is an important communication tool between the deaf and the external world. It is highly necessary to develop a worldwide continuous and large-vocabulary-scale SLR system for practical usage. In this paper, we propose a novel phonology- and radical-coded Chinese SLR framework to demonstrate the feasibility of continuous SLR using accelerometer (ACC) and surface electromyography (sEMG) sensors. The continuous Chinese characters, consisting of coded sign gestures, are first segmented into active segments using EMG signals by means of moving average algorithm. Then, features of each component are extracted from both ACC and sEMG signals of active segments (i.e., palm orientation represented by the mean and variance of ACC signals, hand movement represented by the fixed-point ACC sequence, and hand shape represented by both the mean absolute value (MAV) and autoregressive model coefficients (ARs)). Afterwards, palm orientation is first classified, distinguishing “Palm Downward” sign gestures from “Palm Inward” ones. Only the “Palm Inward” gestures are sent for further hand movement and hand shape recognition by dynamic time warping (DTW) algorithm and hidden Markov models (HMM) respectively. Finally, component recognition results are integrated to identify one certain coded gesture. Experimental results demonstrate that the proposed SLR framework with a vocabulary scale of 223 characters can achieve an averaged recognition accuracy of 96.01% ± 0.83% for coded gesture recognition tasks and 92.73% ± 1.47% for character recognition tasks. Besides, it demonstrats that sEMG signals are rather consistent for a given hand shape independent of hand movements. Hence, the number of training samples will not be significantly increased when the vocabulary scale increases, since not only the number of the completely new proposed coded gestures is constant and limited, but also the transition movement which connects successive signs

A Novel Phonology- and Radical-Coded Chinese Sign Language Recognition Framework Using Accelerometer and Surface Electromyography Sensors.

PubMed

Cheng, Juan; Chen, Xun; Liu, Aiping; Peng, Hu

2015-09-15

Sign language recognition (SLR) is an important communication tool between the deaf and the external world. It is highly necessary to develop a worldwide continuous and large-vocabulary-scale SLR system for practical usage. In this paper, we propose a novel phonology- and radical-coded Chinese SLR framework to demonstrate the feasibility of continuous SLR using accelerometer (ACC) and surface electromyography (sEMG) sensors. The continuous Chinese characters, consisting of coded sign gestures, are first segmented into active segments using EMG signals by means of moving average algorithm. Then, features of each component are extracted from both ACC and sEMG signals of active segments (i.e., palm orientation represented by the mean and variance of ACC signals, hand movement represented by the fixed-point ACC sequence, and hand shape represented by both the mean absolute value (MAV) and autoregressive model coefficients (ARs)). Afterwards, palm orientation is first classified, distinguishing "Palm Downward" sign gestures from "Palm Inward" ones. Only the "Palm Inward" gestures are sent for further hand movement and hand shape recognition by dynamic time warping (DTW) algorithm and hidden Markov models (HMM) respectively. Finally, component recognition results are integrated to identify one certain coded gesture. Experimental results demonstrate that the proposed SLR framework with a vocabulary scale of 223 characters can achieve an averaged recognition accuracy of 96.01% ± 0.83% for coded gesture recognition tasks and 92.73% ± 1.47% for character recognition tasks. Besides, it demonstrats that sEMG signals are rather consistent for a given hand shape independent of hand movements. Hence, the number of training samples will not be significantly increased when the vocabulary scale increases, since not only the number of the completely new proposed coded gestures is constant and limited, but also the transition movement which connects successive signs needs no

Support vector machine and mel frequency Cepstral coefficient based algorithm for hand gestures and bidirectional speech to text device

NASA Astrophysics Data System (ADS)

Balbin, Jessie R.; Padilla, Dionis A.; Fausto, Janette C.; Vergara, Ernesto M.; Garcia, Ramon G.; Delos Angeles, Bethsedea Joy S.; Dizon, Neil John A.; Mardo, Mark Kevin N.

2017-02-01

This research is about translating series of hand gesture to form a word and produce its equivalent sound on how it is read and said in Filipino accent using Support Vector Machine and Mel Frequency Cepstral Coefficient analysis. The concept is to detect Filipino speech input and translate the spoken words to their text form in Filipino. This study is trying to help the Filipino deaf community to impart their thoughts through the use of hand gestures and be able to communicate to people who do not know how to read hand gestures. This also helps literate deaf to simply read the spoken words relayed to them using the Filipino speech to text system.

Kinect-based sign language recognition of static and dynamic hand movements

NASA Astrophysics Data System (ADS)

Dalawis, Rando C.; Olayao, Kenneth Deniel R.; Ramos, Evan Geoffrey I.; Samonte, Mary Jane C.

2017-02-01

A different approach of sign language recognition of static and dynamic hand movements was developed in this study using normalized correlation algorithm. The goal of this research was to translate fingerspelling sign language into text using MATLAB and Microsoft Kinect. Digital input image captured by Kinect devices are matched from template samples stored in a database. This Human Computer Interaction (HCI) prototype was developed to help people with communication disability to express their thoughts with ease. Frame segmentation and feature extraction was used to give meaning to the captured images. Sequential and random testing was used to test both static and dynamic fingerspelling gestures. The researchers explained some factors they encountered causing some misclassification of signs.

Integration Head Mounted Display Device and Hand Motion Gesture Device for Virtual Reality Laboratory

NASA Astrophysics Data System (ADS)

Rengganis, Y. A.; Safrodin, M.; Sukaridhoto, S.

2018-01-01

Virtual Reality Laboratory (VR Lab) is an innovation for conventional learning media which show us whole learning process in laboratory. There are many tools and materials are needed by user for doing practical in it, so user could feel new learning atmosphere by using this innovation. Nowadays, technologies more sophisticated than before. So it would carry in education and it will be more effective, efficient. The Supported technologies are needed us for making VR Lab such as head mounted display device and hand motion gesture device. The integration among them will be used us for making this research. Head mounted display device for viewing 3D environment of virtual reality laboratory. Hand motion gesture device for catching user real hand and it will be visualized in virtual reality laboratory. Virtual Reality will show us, if using the newest technologies in learning process it could make more interesting and easy to understand.

Robust Real-Time and Rotation-Invariant American Sign Language Alphabet Recognition Using Range Camera

NASA Astrophysics Data System (ADS)

Lahamy, H.; Lichti, D.

2012-07-01

The automatic interpretation of human gestures can be used for a natural interaction with computers without the use of mechanical devices such as keyboards and mice. The recognition of hand postures have been studied for many years. However, most of the literature in this area has considered 2D images which cannot provide a full description of the hand gestures. In addition, a rotation-invariant identification remains an unsolved problem even with the use of 2D images. The objective of the current study is to design a rotation-invariant recognition process while using a 3D signature for classifying hand postures. An heuristic and voxelbased signature has been designed and implemented. The tracking of the hand motion is achieved with the Kalman filter. A unique training image per posture is used in the supervised classification. The designed recognition process and the tracking procedure have been successfully evaluated. This study has demonstrated the efficiency of the proposed rotation invariant 3D hand posture signature which leads to 98.24% recognition rate after testing 12723 samples of 12 gestures taken from the alphabet of the American Sign Language.

Arabic sign language recognition based on HOG descriptor

NASA Astrophysics Data System (ADS)

Ben Jmaa, Ahmed; Mahdi, Walid; Ben Jemaa, Yousra; Ben Hamadou, Abdelmajid

2017-02-01

We present in this paper a new approach for Arabic sign language (ArSL) alphabet recognition using hand gesture analysis. This analysis consists in extracting a histogram of oriented gradient (HOG) features from a hand image and then using them to generate an SVM Models. Which will be used to recognize the ArSL alphabet in real-time from hand gesture using a Microsoft Kinect camera. Our approach involves three steps: (i) Hand detection and localization using a Microsoft Kinect camera, (ii) hand segmentation and (iii) feature extraction using Arabic alphabet recognition. One each input image first obtained by using a depth sensor, we apply our method based on hand anatomy to segment hand and eliminate all the errors pixels. This approach is invariant to scale, to rotation and to translation of the hand. Some experimental results show the effectiveness of our new approach. Experiment revealed that the proposed ArSL system is able to recognize the ArSL with an accuracy of 90.12%.

Put your hands up! Gesturing improves preschoolers' executive function.

PubMed

Rhoads, Candace L; Miller, Patricia H; Jaeger, Gina O

2018-09-01

This study addressed the causal direction of a previously reported relation between preschoolers' gesturing and their executive functioning on the Dimensional Change Card Sort (DCCS) sorting-switch task. Gesturing the relevant dimension for sorting was induced in a Gesture group through instructions, imitation, and prompts. In contrast, the Control group was instructed to "think hard" when sorting. Preschoolers (N = 50) performed two DCCS tasks: (a) sort by size and then spatial orientation of two objects and (b) sort by shape and then proximity of the two objects. An examination of performance over trials permitted a fine-grained depiction of patterns of younger and older children in the Gesture and Control conditions. After the relevant dimension was switched, the Gesture group had more accurate sorts than the Control group, particularly among younger children on the second task. Moreover, the amount of gesturing predicted the number of correct sorts among younger children on the second task. The overall association between gesturing and sorting was not reflected at the level of individual trials, perhaps indicating covert gestural representation on some trials or the triggering of a relevant verbal representation by the gesturing. The delayed benefit of gesturing, until the second task, in the younger children may indicate a utilization deficiency. Results are discussed in terms of theories of gesturing and thought. The findings open up a new avenue of research and theorizing about the possible role of gesturing in emerging executive function. Copyright © 2018 Elsevier Inc. All rights reserved.

Speech-Associated Gestures, Broca's Area, and the Human Mirror System

ERIC Educational Resources Information Center

Skipper, Jeremy I.; Goldin-Meadow, Susan; Nusbaum, Howard C.; Small, Steven L.

2007-01-01

Speech-associated gestures are hand and arm movements that not only convey semantic information to listeners but are themselves actions. Broca's area has been assumed to play an important role both in semantic retrieval or selection (as part of a language comprehension system) and in action recognition (as part of a "mirror" or…

Hand Gesture and Mathematics Learning: Lessons From an Avatar.

PubMed

Cook, Susan Wagner; Friedman, Howard S; Duggan, Katherine A; Cui, Jian; Popescu, Voicu

2017-03-01

A beneficial effect of gesture on learning has been demonstrated in multiple domains, including mathematics, science, and foreign language vocabulary. However, because gesture is known to co-vary with other non-verbal behaviors, including eye gaze and prosody along with face, lip, and body movements, it is possible the beneficial effect of gesture is instead attributable to these other behaviors. We used a computer-generated animated pedagogical agent to control both verbal and non-verbal behavior. Children viewed lessons on mathematical equivalence in which an avatar either gestured or did not gesture, while eye gaze, head position, and lip movements remained identical across gesture conditions. Children who observed the gesturing avatar learned more, and they solved problems more quickly. Moreover, those children who learned were more likely to transfer and generalize their knowledge. These findings provide converging evidence that gesture facilitates math learning, and they reveal the potential for using technology to study non-verbal behavior in controlled experiments. Copyright © 2016 Cognitive Science Society, Inc.

Gesture-controlled interfaces for self-service machines and other applications

NASA Technical Reports Server (NTRS)

Cohen, Charles J. (Inventor); Jacobus, Charles J. (Inventor); Paul, George (Inventor); Beach, Glenn (Inventor); Foulk, Gene (Inventor); Obermark, Jay (Inventor); Cavell, Brook (Inventor)

2004-01-01

A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines.

The Role of Embodiment and Individual Empathy Levels in Gesture Comprehension.

PubMed

Jospe, Karine; Flöel, Agnes; Lavidor, Michal

2017-01-01

Research suggests that the action-observation network is involved in both emotional-embodiment (empathy) and action-embodiment (imitation) mechanisms. Here we tested whether empathy modulates action-embodiment, hypothesizing that restricting imitation abilities will impair performance in a hand gesture comprehension task. Moreover, we hypothesized that empathy levels will modulate the imitation restriction effect. One hundred twenty participants with a range of empathy scores performed gesture comprehension under restricted and unrestricted hand conditions. Empathetic participants performed better under the unrestricted compared to the restricted condition, and compared to the low empathy participants. Remarkably however, the latter showed the exactly opposite pattern and performed better under the restricted condition. This pattern was not found in a facial expression recognition task. The selective interaction of embodiment restriction and empathy suggests that empathy modulates the way people employ embodiment in gesture comprehension. We discuss the potential of embodiment-induced therapy to improve empathetic abilities in individuals with low empathy.

Gesture in the developing brain

PubMed Central

Dick, Anthony Steven; Goldin-Meadow, Susan; Solodkin, Ana; Small, Steven L.

2011-01-01

Speakers convey meaning not only through words, but also through gestures. Although children are exposed to co-speech gestures from birth, we do not know how the developing brain comes to connect meaning conveyed in gesture with speech. We used functional magnetic resonance imaging (fMRI) to address this question and scanned 8- to 11-year-old children and adults listening to stories accompanied by hand movements, either meaningful co-speech gestures or meaningless self-adaptors. When listening to stories accompanied by both types of hand movements, both children and adults recruited inferior frontal, inferior parietal, and posterior temporal brain regions known to be involved in processing language not accompanied by hand movements. There were, however, age-related differences in activity in posterior superior temporal sulcus (STSp), inferior frontal gyrus, pars triangularis (IFGTr), and posterior middle temporal gyrus (MTGp) regions previously implicated in processing gesture. Both children and adults showed sensitivity to the meaning of hand movements in IFGTr and MTGp, but in different ways. Finally, we found that hand movement meaning modulates interactions between STSp and other posterior temporal and inferior parietal regions for adults, but not for children. These results shed light on the developing neural substrate for understanding meaning contributed by co-speech gesture. PMID:22356173

Consolidation and transfer of learning after observing hand gesture.

PubMed

Cook, Susan Wagner; Duffy, Ryan G; Fenn, Kimberly M

2013-01-01

Children who observe gesture while learning mathematics perform better than children who do not, when tested immediately after training. How does observing gesture influence learning over time? Children (n = 184, ages = 7-10) were instructed with a videotaped lesson on mathematical equivalence and tested immediately after training and 24 hr later. The lesson either included speech and gesture or only speech. Children who saw gesture performed better overall and performance improved after 24 hr. Children who only heard speech did not improve after the delay. The gesture group also showed stronger transfer to different problem types. These findings suggest that gesture enhances learning of abstract concepts and affects how learning is consolidated over time. © 2013 The Authors. Child Development © 2013 Society for Research in Child Development, Inc.

When Actions Speak Too Much Louder than Words: Hand Gestures Disrupt Word Learning when Phonetic Demands Are High

ERIC Educational Resources Information Center

Kelly, Spencer D.; Lee, Angela L.

2012-01-01

It is now widely accepted that hand gestures help people understand and learn language. Here, we provide an exception to this general rule--when phonetic demands are high, gesture actually hurts. Native English-speaking adults were instructed on the meaning of novel Japanese word pairs that were for non-native speakers phonetically hard (/ite/ vs.…

Wearable Spiral Passive Electromagnetic Sensor (SPES) glove for sign language recognition of alphabet letters and numbers: a preliminary study

NASA Astrophysics Data System (ADS)

Iervolino, Onorio; Meo, Michele

2017-04-01

Sign language is a method of communication for deaf-mute people with articulated gestures and postures of hands and fingers to represent alphabet letters or complete words. Recognizing gestures is a difficult task, due to intrapersonal and interpersonal variations in performing them. This paper investigates the use of Spiral Passive Electromagnetic Sensor (SPES) as a motion recognition tool. An instrumented glove integrated with wearable multi-SPES sensors was developed to encode data and provide a unique response for each hand gesture. The device can be used for recognition of gestures; motion control and well-defined gesture sets such as sign languages. Each specific gesture was associated to a unique sensor response. The gloves encode data regarding the gesture directly in the frequency spectrum response of the SPES. The absence of chip or complex electronic circuit make the gloves light and comfortable to wear. Results showed encouraging data to use SPES in wearable applications.

Effect of Dialogue on Demonstrations: Direct Quotations, Facial Portrayals, Hand Gestures, and Figurative References

ERIC Educational Resources Information Center

Bavelas, Janet; Gerwing, Jennifer; Healing, Sara

2014-01-01

"Demonstrations" (e.g., direct quotations, conversational facial portrayals, conversational hand gestures, and figurative references) lack conventional meanings, relying instead on a resemblance to their referent. Two experiments tested our theory that demonstrations are a class of communicative acts that speakers are more likely to use…

iHand: an interactive bare-hand-based augmented reality interface on commercial mobile phones

NASA Astrophysics Data System (ADS)

Choi, Junyeong; Park, Jungsik; Park, Hanhoon; Park, Jong-Il

2013-02-01

The performance of mobile phones has rapidly improved, and they are emerging as a powerful platform. In many vision-based applications, human hands play a key role in natural interaction. However, relatively little attention has been paid to the interaction between human hands and the mobile phone. Thus, we propose a vision- and hand gesture-based interface in which the user holds a mobile phone in one hand but sees the other hand's palm through a built-in camera. The virtual contents are faithfully rendered on the user's palm through palm pose estimation, and reaction with hand and finger movements is achieved that is recognized by hand shape recognition. Since the proposed interface is based on hand gestures familiar to humans and does not require any additional sensors or markers, the user can freely interact with virtual contents anytime and anywhere without any training. We demonstrate that the proposed interface works at over 15 fps on a commercial mobile phone with a 1.2-GHz dual core processor and 1 GB RAM.

Gesture Analysis for Astronomy Presentation Software

NASA Astrophysics Data System (ADS)

Robinson, Marc A.

Astronomy presentation software in a planetarium setting provides a visually stimulating way to introduce varied scientific concepts, including computer science concepts, to a wide audience. However, the underlying computational complexity and opportunities for discussion are often overshadowed by the brilliance of the presentation itself. To bring this discussion back out into the open, a method needs to be developed to make the computer science applications more visible. This thesis introduces the GAAPS system, which endeavors to implement free-hand gesture-based control of astronomy presentation software, with the goal of providing that talking point to begin the discussion of computer science concepts in a planetarium setting. The GAAPS system incorporates gesture capture and analysis in a unique environment presenting unique challenges, and introduces a novel algorithm called a Bounding Box Tree to create and select features for this particular gesture data. This thesis also analyzes several different machine learning techniques to determine a well-suited technique for the classification of this particular data set, with an artificial neural network being chosen as the implemented algorithm. The results of this work will allow for the desired introduction of computer science discussion into the specific setting used, as well as provide for future work pertaining to gesture recognition with astronomy presentation software.

Gesture Based Control and EMG Decomposition

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

Self-organized Evaluation of Dynamic Hand Gestures for Sign Language Recognition

NASA Astrophysics Data System (ADS)

Buciu, Ioan; Pitas, Ioannis

Two main theories exist with respect to face encoding and representation in the human visual system (HVS). The first one refers to the dense (holistic) representation of the face, where faces have "holon"-like appearance. The second one claims that a more appropriate face representation is given by a sparse code, where only a small fraction of the neural cells corresponding to face encoding is activated. Theoretical and experimental evidence suggest that the HVS performs face analysis (encoding, storing, face recognition, facial expression recognition) in a structured and hierarchical way, where both representations have their own contribution and goal. According to neuropsychological experiments, it seems that encoding for face recognition, relies on holistic image representation, while a sparse image representation is used for facial expression analysis and classification. From the computer vision perspective, the techniques developed for automatic face and facial expression recognition fall into the same two representation types. Like in Neuroscience, the techniques which perform better for face recognition yield a holistic image representation, while those techniques suitable for facial expression recognition use a sparse or local image representation. The proposed mathematical models of image formation and encoding try to simulate the efficient storing, organization and coding of data in the human cortex. This is equivalent with embedding constraints in the model design regarding dimensionality reduction, redundant information minimization, mutual information minimization, non-negativity constraints, class information, etc. The presented techniques are applied as a feature extraction step followed by a classification method, which also heavily influences the recognition results.

Producing Gestures Facilitates Route Learning

PubMed Central

So, Wing Chee; Ching, Terence Han-Wei; Lim, Phoebe Elizabeth; Cheng, Xiaoqin; Ip, Kit Yee

2014-01-01

The present study investigates whether producing gestures would facilitate route learning in a navigation task and whether its facilitation effect is comparable to that of hand movements that leave physical visible traces. In two experiments, we focused on gestures produced without accompanying speech, i.e., co-thought gestures (e.g., an index finger traces the spatial sequence of a route in the air). Adult participants were asked to study routes shown in four diagrams, one at a time. Participants reproduced the routes (verbally in Experiment 1 and non-verbally in Experiment 2) without rehearsal or after rehearsal by mentally simulating the route, by drawing it, or by gesturing (either in the air or on paper). Participants who moved their hands (either in the form of gestures or drawing) recalled better than those who mentally simulated the routes and those who did not rehearse, suggesting that hand movements produced during rehearsal facilitate route learning. Interestingly, participants who gestured the routes in the air or on paper recalled better than those who drew them on paper in both experiments, suggesting that the facilitation effect of co-thought gesture holds for both verbal and nonverbal recall modalities. It is possibly because, co-thought gesture, as a kind of representational action, consolidates spatial sequence better than drawing and thus exerting more powerful influence on spatial representation. PMID:25426624

Gestures in an Intelligent User Interface

NASA Astrophysics Data System (ADS)

Fikkert, Wim; van der Vet, Paul; Nijholt, Anton

In this chapter we investigated which hand gestures are intuitive to control a large display multimedia interface from a user's perspective. Over the course of two sequential user evaluations, we defined a simple gesture set that allows users to fully control a large display multimedia interface, intuitively. First, we evaluated numerous gesture possibilities for a set of commands that can be issued to the interface. These gestures were selected from literature, science fiction movies, and a previous exploratory study. Second, we implemented a working prototype with which the users could interact with both hands and the preferred hand gestures with 2D and 3D visualizations of biochemical structures. We found that the gestures are influenced to significant extent by the fast paced developments in multimedia interfaces such as the Apple iPhone and the Nintendo Wii and to no lesser degree by decades of experience with the more traditional WIMP-based interfaces.

A gesture-controlled projection display for CT-guided interventions.

PubMed

Mewes, A; Saalfeld, P; Riabikin, O; Skalej, M; Hansen, C

2016-01-01

The interaction with interventional imaging systems within a sterile environment is a challenging task for physicians. Direct physician-machine interaction during an intervention is rather limited because of sterility and workspace restrictions. We present a gesture-controlled projection display that enables a direct and natural physician-machine interaction during computed tomography (CT)-based interventions. Therefore, a graphical user interface is projected on a radiation shield located in front of the physician. Hand gestures in front of this display are captured and classified using a leap motion controller. We propose a gesture set to control basic functions of intervention software such as gestures for 2D image exploration, 3D object manipulation and selection. Our methods were evaluated in a clinically oriented user study with 12 participants. The results of the performed user study confirm that the display and the underlying interaction concept are accepted by clinical users. The recognition of the gestures is robust, although there is potential for improvements. The gesture training times are less than 10 min, but vary heavily between the participants of the study. The developed gestures are connected logically to the intervention software and intuitive to use. The proposed gesture-controlled projection display counters current thinking, namely it gives the radiologist complete control of the intervention software. It opens new possibilities for direct physician-machine interaction during CT-based interventions and is well suited to become an integral part of future interventional suites.

Gesturing Gives Children New Ideas About Math

PubMed Central

Goldin-Meadow, Susan; Cook, Susan Wagner; Mitchell, Zachary A.

2009-01-01

How does gesturing help children learn? Gesturing might encourage children to extract meaning implicit in their hand movements. If so, children should be sensitive to the particular movements they produce and learn accordingly. Alternatively, all that may matter is that children move their hands. If so, they should learn regardless of which movements they produce. To investigate these alternatives, we manipulated gesturing during a math lesson. We found that children required to produce correct gestures learned more than children required to produce partially correct gestures, who learned more than children required to produce no gestures. This effect was mediated by whether children took information conveyed solely in their gestures and added it to their speech. The findings suggest that body movements are involved not only in processing old ideas, but also in creating new ones. We may be able to lay foundations for new knowledge simply by telling learners how to move their hands. PMID:19222810

Generating Control Commands From Gestures Sensed by EMG

NASA Technical Reports Server (NTRS)

Wheeler, Kevin R.; Jorgensen, Charles

2006-01-01

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

Speech-independent production of communicative gestures: evidence from patients with complete callosal disconnection.

PubMed

Lausberg, Hedda; Zaidel, Eran; Cruz, Robyn F; Ptito, Alain

2007-10-01

Recent neuropsychological, psycholinguistic, and evolutionary theories on language and gesture associate communicative gesture production exclusively with left hemisphere language production. An argument for this approach is the finding that right-handers with left hemisphere language dominance prefer the right hand for communicative gestures. However, several studies have reported distinct patterns of hand preferences for different gesture types, such as deictics, batons, or physiographs, and this calls for an alternative hypothesis. We investigated hand preference and gesture types in spontaneous gesticulation during three semi-standardized interviews of three right-handed patients and one left-handed patient with complete callosal disconnection, all with left hemisphere dominance for praxis. Three of them, with left hemisphere language dominance, exhibited a reliable left-hand preference for spontaneous communicative gestures despite their left hand agraphia and apraxia. The fourth patient, with presumed bihemispheric language representation, revealed a consistent right-hand preference for gestures. All four patients displayed batons, tosses, and shrugs more often with the left hand/shoulder, but exhibited a right hand preference for pantomime gestures. We conclude that the hand preference for certain gesture types cannot be predicted by hemispheric dominance for language or by handedness. We found distinct hand preferences for specific gesture types. This suggests a conceptual specificity of the left and right hand gestures. We propose that left hand gestures are related to specialized right hemisphere functions, such as prosody or emotion, and that they are generated independently of left hemisphere language production. Our findings challenge the traditional neuropsychological and psycholinguistic view on communicative gesture production.

The sound of one-hand clapping: handedness and perisylvian neural correlates of a communicative gesture in chimpanzees

PubMed Central

Meguerditchian, Adrien; Gardner, Molly J.; Schapiro, Steven J.; Hopkins, William D.

2012-01-01

Whether lateralization of communicative signalling in non-human primates might constitute prerequisites of hemispheric specialization for language is unclear. In the present study, we examined (i) hand preference for a communicative gesture (clapping in 94 captive chimpanzees from two research facilities) and (ii) the in vivo magnetic resonance imaging brain scans of 40 of these individuals. The preferred hand for clapping was defined as the one in the upper position when the two hands came together. Using computer manual tracing of regions of interest, we measured the neuroanatomical asymmetries for the homologues of key language areas, including the inferior frontal gyrus (IFG) and planum temporale (PT). When considering the entire sample, there was a predominance of right-handedness for clapping and the distribution of right- and left-handed individuals did not differ between the two facilities. The direction of hand preference (right- versus left-handed subjects) for clapping explained a significant portion of variability in asymmetries of the PT and IFG. The results are consistent with the view that gestural communication in the common ancestor may have been a precursor of language and its cerebral substrates in modern humans. PMID:22217719

Gestures make memories, but what kind? Patients with impaired procedural memory display disruptions in gesture production and comprehension

PubMed Central

Klooster, Nathaniel B.; Cook, Susan W.; Uc, Ergun Y.; Duff, Melissa C.

2015-01-01

Hand gesture, a ubiquitous feature of human interaction, facilitates communication. Gesture also facilitates new learning, benefiting speakers and listeners alike. Thus, gestures must impact cognition beyond simply supporting the expression of already-formed ideas. However, the cognitive and neural mechanisms supporting the effects of gesture on learning and memory are largely unknown. We hypothesized that gesture's ability to drive new learning is supported by procedural memory and that procedural memory deficits will disrupt gesture production and comprehension. We tested this proposal in patients with intact declarative memory, but impaired procedural memory as a consequence of Parkinson's disease (PD), and healthy comparison participants with intact declarative and procedural memory. In separate experiments, we manipulated the gestures participants saw and produced in a Tower of Hanoi (TOH) paradigm. In the first experiment, participants solved the task either on a physical board, requiring high arching movements to manipulate the discs from peg to peg, or on a computer, requiring only flat, sideways movements of the mouse. When explaining the task, healthy participants with intact procedural memory displayed evidence of their previous experience in their gestures, producing higher, more arching hand gestures after solving on a physical board, and smaller, flatter gestures after solving on a computer. In the second experiment, healthy participants who saw high arching hand gestures in an explanation prior to solving the task subsequently moved the mouse with significantly higher curvature than those who saw smaller, flatter gestures prior to solving the task. These patterns were absent in both gesture production and comprehension experiments in patients with procedural memory impairment. These findings suggest that the procedural memory system supports the ability of gesture to drive new learning. PMID:25628556

Device Control Using Gestures Sensed from EMG

NASA Technical Reports Server (NTRS)

Wheeler, Kevin R.

2003-01-01

In this paper we present neuro-electric interfaces for virtual device control. The examples presented rely upon sampling Electromyogram data from a participants forearm. This data is then fed into pattern recognition software that has been trained to distinguish gestures from a given gesture set. The pattern recognition software consists of hidden Markov models which are used to recognize the gestures as they are being performed in real-time. Two experiments were conducted to examine the feasibility of this interface technology. The first replicated a virtual joystick interface, and the second replicated a keyboard.

[A case with apraxia of tool use: selective inability to form a hand posture for a tool].

PubMed

Hayakawa, Yuko; Fujii, Toshikatsu; Yamadori, Atsushi; Meguro, Kenichi; Suzuki, Kyoko

2015-03-01

Impaired tool use is recognized as a symptom of ideational apraxia. While many studies have focused on difficulties in producing gestures as a whole, using tools involves several steps; these include forming hand postures appropriate for the use of certain tool, selecting objects or body parts to act on, and producing gestures. In previously reported cases, both producing and recognizing hand postures were impaired. Here we report the first case showing a selective impairment of forming hand postures appropriate for tools with preserved recognition of the required hand postures. A 24-year-old, right-handed man was admitted to hospital because of sensory impairment of the right side of the body, mild aphasia, and impaired tool use due to left parietal subcortical hemorrhage. His ability to make symbolic gestures, copy finger postures, and orient his hand to pass a slit was well preserved. Semantic knowledge for tools and hand postures was also intact. He could flawlessly select the correct hand postures in recognition tasks. He only demonstrated difficulties in forming a hand posture appropriate for a tool. Once he properly grasped a tool by trial and error, he could use it without hesitation. These observations suggest that each step of tool use should be thoroughly examined in patients with ideational apraxia.

Learning what children know about space from looking at their hands: The added value of gesture in spatial communication

PubMed Central

Sauter, Megan; Uttal, David H.; Alman, Amanda Schaal; Goldin-Meadow, Susan; Levine, Susan C.

2013-01-01

This article examines two issues: the role of gesture in the communication of spatial information and the relation between communication and mental representation. Children (8–10 years) and adults walked through a space to learn the locations of six hidden toy animals and then explained the space to another person. In Study 1, older children and adults typically gestured when describing the space and rarely provided spatial information in speech without also providing the information in gesture. However, few 8-year-olds communicated spatial information in speech or gesture. Studies 2 and 3 showed that 8-year-olds did understand the spatial arrangement of the animals and could communicate spatial information if prompted to use their hands. Taken together, these results indicate that gesture is important for conveying spatial relations at all ages and, as such, provides us with a more complete picture of what children do and do not know about communicating spatial relations. PMID:22209401

Iconic gestures prime related concepts: an ERP study.

PubMed

Wu, Ying Croon; Coulson, Seana

2007-02-01

To assess priming by iconic gestures, we recorded EEG (at 29 scalp sites) in two experiments while adults watched short, soundless videos of spontaneously produced, cospeech iconic gestures followed by related or unrelated probe words. In Experiment 1, participants classified the relatedness between gestures and words. In Experiment 2, they attended to stimuli, and performed an incidental recognition memory test on words presented during the EEG recording session. Event-related potentials (ERPs) time-locked to the onset of probe words were measured, along with response latencies and word recognition rates. Although word relatedness did not affect reaction times or recognition rates, contextually related probe words elicited less-negative ERPs than did unrelated ones between 300 and 500 msec after stimulus onset (N400) in both experiments. These findings demonstrate sensitivity to semantic relations between iconic gestures and words in brain activity engendered during word comprehension.

Gesture Recognition and Sensorimotor Learning-by-Doing of Motor Skills in Manual Professions: A Case Study in the Wheel-Throwing Art of Pottery

ERIC Educational Resources Information Center

Glushkova, Alina; Manitsaris, Sotiris

2018-01-01

This paper presents a methodological framework for the use of gesture recognition technologies in the learning/mastery of the gestural skills required in wheel-throwing pottery. In the case of self-instruction or training, learners face difficulties due to the absence of the teacher/expert and the consequent lack of guidance. Motion capture…

The Relationship between Visual Impairment and Gestures.

ERIC Educational Resources Information Center

Frame, Melissa J.

2000-01-01

A study found the gestural activity of 15 adolescents with visual impairments differed from that of 15 adolescents with sight. Subjects with visual impairments used more adapters (especially finger-to-hand gestures) and fewer conversational gestures. Differences in gestural activity by degree of visual impairment and grade in school were also…

Contrast of Hand Preferences between Communicative Gestures and Non-Communicative Actions in Baboons: Implications for the Origins of Hemispheric Specialization for Language

ERIC Educational Resources Information Center

Meguerditchian, Adrien; Vauclair, Jacques

2009-01-01

Gestural communication is a modality considered in the literature as a candidate for determining the ancestral prerequisites of the emergence of human language. As reported in captive chimpanzees and human children, a study in captive baboons revealed that a communicative gesture elicits stronger degree of right-hand bias than non-communicative…

A multifactorial investigation of captive gorillas' intraspecific gestural laterality.

PubMed

Prieur, Jacques; Pika, Simone; Barbu, Stéphanie; Blois-Heulin, Catherine

2017-12-05

Multifactorial investigations of intraspecific laterality of primates' gestural communication aim to shed light on factors that underlie the evolutionary origins of human handedness and language. This study assesses gorillas' intraspecific gestural laterality considering the effect of various factors related to gestural characteristics, interactional context and sociodemographic characteristics of signaller and recipient. Our question was: which factors influence gorillas' gestural laterality? We studied laterality in three captive groups of gorillas (N = 35) focusing on their most frequent gesture types (N = 16). We show that signallers used predominantly their hand ipsilateral to the recipient for tactile and visual gestures, whatever the emotional context, gesture duration, recipient's sex or the kin relationship between both interactants, and whether or not a communication tool was used. Signallers' contralateral hand was not preferentially used in any situation. Signallers' right-hand use was more pronounced in negative contexts, in short gestures, when signallers were females and its use increased with age. Our findings showed that gorillas' gestural laterality could be influenced by different types of social pressures thus supporting the theory of the evolution of laterality at the population level. Our study also evidenced that some particular gesture categories are better markers than others of the left-hemisphere language specialization.

Semantic relation vs. surprise: the differential effects of related and unrelated co-verbal gestures on neural encoding and subsequent recognition.

PubMed

Straube, Benjamin; Meyer, Lea; Green, Antonia; Kircher, Tilo

2014-06-03

Speech-associated gesturing leads to memory advantages for spoken sentences. However, unexpected or surprising events are also likely to be remembered. With this study we test the hypothesis that different neural mechanisms (semantic elaboration and surprise) lead to memory advantages for iconic and unrelated gestures. During fMRI-data acquisition participants were presented with video clips of an actor verbalising concrete sentences accompanied by iconic gestures (IG; e.g., circular gesture; sentence: "The man is sitting at the round table"), unrelated free gestures (FG; e.g., unrelated up down movements; same sentence) and no gestures (NG; same sentence). After scanning, recognition performance for the three conditions was tested. Videos were evaluated regarding semantic relation and surprise by a different group of participants. The semantic relationship between speech and gesture was rated higher for IG (IG>FG), whereas surprise was rated higher for FG (FG>IG). Activation of the hippocampus correlated with subsequent memory performance of both gesture conditions (IG+FG>NG). For the IG condition we found activation in the left temporal pole and middle cingulate cortex (MCC; IG>FG). In contrast, for the FG condition posterior thalamic structures (FG>IG) as well as anterior and posterior cingulate cortices were activated (FG>NG). Our behavioral and fMRI-data suggest different mechanisms for processing related and unrelated co-verbal gestures, both of them leading to enhanced memory performance. Whereas activation in MCC and left temporal pole for iconic co-verbal gestures may reflect semantic memory processes, memory enhancement for unrelated gestures relies on the surprise response, mediated by anterior/posterior cingulate cortex and thalamico-hippocampal structures. Copyright © 2014 Elsevier B.V. All rights reserved.

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech

PubMed Central

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances. PMID:26925010

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech.

PubMed

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances.

Hand Gesture and Mathematics Learning: Lessons from an Avatar

ERIC Educational Resources Information Center

Cook, Susan Wagner; Friedman, Howard S.; Duggan, Katherine A.; Cui, Jian; Popescu, Voicu

2017-01-01

A beneficial effect of gesture on learning has been demonstrated in multiple domains, including mathematics, science, and foreign language vocabulary. However, because gesture is known to co-vary with other non-verbal behaviors, including eye gaze and prosody along with face, lip, and body movements, it is possible the beneficial effect of gesture…

GESTURE'S ROLE IN CREATING AND LEARNING LANGUAGE.

PubMed

Goldin-Meadow, Susan

2010-09-22

Imagine a child who has never seen or heard language. Would such a child be able to invent a language? Despite what one might guess, the answer is "yes". This chapter describes children who are congenitally deaf and cannot learn the spoken language that surrounds them. In addition, the children have not been exposed to sign language, either by their hearing parents or their oral schools. Nevertheless, the children use their hands to communicate--they gesture--and those gestures take on many of the forms and functions of language (Goldin-Meadow 2003a). The properties of language that we find in these gestures are just those properties that do not need to be handed down from generation to generation, but can be reinvented by a child de novo. They are the resilient properties of language, properties that all children, deaf or hearing, come to language-learning ready to develop. In contrast to these deaf children who are inventing language with their hands, hearing children are learning language from a linguistic model. But they too produce gestures, as do all hearing speakers (Feyereisen and de Lannoy 1991; Goldin-Meadow 2003b; Kendon 1980; McNeill 1992). Indeed, young hearing children often use gesture to communicate before they use words. Interestingly, changes in a child's gestures not only predate but also predict changes in the child's early language, suggesting that gesture may be playing a role in the language-learning process. This chapter begins with a description of the gestures the deaf child produces without speech. These gestures assume the full burden of communication and take on a language-like form--they are language. This phenomenon stands in contrast to the gestures hearing speakers produce with speech. These gestures share the burden of communication with speech and do not take on a language-like form--they are part of language.

Computer-Assisted Culture Learning in an Online Augmented Reality Environment Based on Free-Hand Gesture Interaction

ERIC Educational Resources Information Center

Yang, Mau-Tsuen; Liao, Wan-Che

2014-01-01

The physical-virtual immersion and real-time interaction play an essential role in cultural and language learning. Augmented reality (AR) technology can be used to seamlessly merge virtual objects with real-world images to realize immersions. Additionally, computer vision (CV) technology can recognize free-hand gestures from live images to enable…

Different visual exploration of tool-related gestures in left hemisphere brain damaged patients is associated with poor gestural imitation.

PubMed

Vanbellingen, Tim; Schumacher, Rahel; Eggenberger, Noëmi; Hopfner, Simone; Cazzoli, Dario; Preisig, Basil C; Bertschi, Manuel; Nyffeler, Thomas; Gutbrod, Klemens; Bassetti, Claudio L; Bohlhalter, Stephan; Müri, René M

2015-05-01

According to the direct matching hypothesis, perceived movements automatically activate existing motor components through matching of the perceived gesture and its execution. The aim of the present study was to test the direct matching hypothesis by assessing whether visual exploration behavior correlate with deficits in gestural imitation in left hemisphere damaged (LHD) patients. Eighteen LHD patients and twenty healthy control subjects took part in the study. Gesture imitation performance was measured by the test for upper limb apraxia (TULIA). Visual exploration behavior was measured by an infrared eye-tracking system. Short videos including forty gestures (20 meaningless and 20 communicative gestures) were presented. Cumulative fixation duration was measured in different regions of interest (ROIs), namely the face, the gesturing hand, the body, and the surrounding environment. Compared to healthy subjects, patients fixated significantly less the ROIs comprising the face and the gesturing hand during the exploration of emblematic and tool-related gestures. Moreover, visual exploration of tool-related gestures significantly correlated with tool-related imitation as measured by TULIA in LHD patients. Patients and controls did not differ in the visual exploration of meaningless gestures, and no significant relationships were found between visual exploration behavior and the imitation of emblematic and meaningless gestures in TULIA. The present study thus suggests that altered visual exploration may lead to disturbed imitation of tool related gestures, however not of emblematic and meaningless gestures. Consequently, our findings partially support the direct matching hypothesis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Authentication based on gestures with smartphone in hand

NASA Astrophysics Data System (ADS)

Varga, Juraj; Švanda, Dominik; Varchola, Marek; Zajac, Pavol

2017-08-01

We propose a new method of authentication for smartphones and similar devices based on gestures made by user with the device itself. The main advantage of our method is that it combines subtle biometric properties of the gesture (something you are) with a secret information that can be freely chosen by the user (something you know). Our prototype implementation shows that the scheme is feasible in practice. Further development, testing and fine tuning of parameters is required for deployment in the real world.

Embodied Communication: Speakers' Gestures Affect Listeners' Actions

ERIC Educational Resources Information Center

Cook, Susan Wagner; Tanenhaus, Michael K.

2009-01-01

We explored how speakers and listeners use hand gestures as a source of perceptual-motor information during naturalistic communication. After solving the Tower of Hanoi task either with real objects or on a computer, speakers explained the task to listeners. Speakers' hand gestures, but not their speech, reflected properties of the particular…

Personal recognition using hand shape and texture.

PubMed

Kumar, Ajay; Zhang, David

2006-08-01

This paper proposes a new bimodal biometric system using feature-level fusion of hand shape and palm texture. The proposed combination is of significance since both the palmprint and hand-shape images are proposed to be extracted from the single hand image acquired from a digital camera. Several new hand-shape features that can be used to represent the hand shape and improve the performance are investigated. The new approach for palmprint recognition using discrete cosine transform coefficients, which can be directly obtained from the camera hardware, is demonstrated. None of the prior work on hand-shape or palmprint recognition has given any attention on the critical issue of feature selection. Our experimental results demonstrate that while majority of palmprint or hand-shape features are useful in predicting the subjects identity, only a small subset of these features are necessary in practice for building an accurate model for identification. The comparison and combination of proposed features is evaluated on the diverse classification schemes; naive Bayes (normal, estimated, multinomial), decision trees (C4.5, LMT), k-NN, SVM, and FFN. Although more work remains to be done, our results to date indicate that the combination of selected hand-shape and palmprint features constitutes a promising addition to the biometrics-based personal recognition systems.

Towards NIRS-based hand movement recognition.

PubMed

Paleari, Marco; Luciani, Riccardo; Ariano, Paolo

2017-07-01

This work reports on preliminary results about on hand movement recognition with Near InfraRed Spectroscopy (NIRS) and surface ElectroMyoGraphy (sEMG). Either basing on physical contact (touchscreens, data-gloves, etc.), vision techniques (Microsoft Kinect, Sony PlayStation Move, etc.), or other modalities, hand movement recognition is a pervasive function in today environment and it is at the base of many gaming, social, and medical applications. Albeit, in recent years, the use of muscle information extracted by sEMG has spread out from the medical applications to contaminate the consumer world, this technique still falls short when dealing with movements of the hand. We tested NIRS as a technique to get another point of view on the muscle phenomena and proved that, within a specific movements selection, NIRS can be used to recognize movements and return information regarding muscles at different depths. Furthermore, we propose here three different multimodal movement recognition approaches and compare their performances.

Real-Time Hand Posture Recognition Using a Range Camera

NASA Astrophysics Data System (ADS)

Lahamy, Herve

The basic goal of human computer interaction is to improve the interaction between users and computers by making computers more usable and receptive to the user's needs. Within this context, the use of hand postures in replacement of traditional devices such as keyboards, mice and joysticks is being explored by many researchers. The goal is to interpret human postures via mathematical algorithms. Hand posture recognition has gained popularity in recent years, and could become the future tool for humans to interact with computers or virtual environments. An exhaustive description of the frequently used methods available in literature for hand posture recognition is provided. It focuses on the different types of sensors and data used, the segmentation and tracking methods, the features used to represent the hand postures as well as the classifiers considered in the recognition process. Those methods are usually presented as highly robust with a recognition rate close to 100%. However, a couple of critical points necessary for a successful real-time hand posture recognition system require major improvement. Those points include the features used to represent the hand segment, the number of postures simultaneously recognizable, the invariance of the features with respect to rotation, translation and scale and also the behavior of the classifiers against non-perfect hand segments for example segments including part of the arm or missing part of the palm. A 3D time-of-flight camera named SR4000 has been chosen to develop a new methodology because of its capability to provide in real-time and at high frame rate 3D information on the scene imaged. This sensor has been described and evaluated for its capability for capturing in real-time a moving hand. A new recognition method that uses the 3D information provided by the range camera to recognize hand postures has been proposed. The different steps of this methodology including the segmentation, the tracking, the hand

Truth is at hand: How gesture adds information during investigative interviews

PubMed Central

Broaders, Sara C.; Goldin-Meadow, Susan

2010-01-01

The accuracy of information obtained in forensic interviews is critically important to credibility in our legal system. Research has shown that the way interviewers frame questions influences the accuracy of witnesses’ reports. A separate body of research has shown that speakers spontaneously gesture when they talk, and that these gestures can express information not found anywhere in the speaker’s talk. This study of children interviewed about an event that they witnessed joins these two literatures and demonstrates that (1) interviewers’ gestures serve as a source of information and, at times, misinformation that can lead witnesses to report incorrect details; (2) the gestures witnesses spontaneously produce during interviews convey substantive information that is often not conveyed anywhere in their speech, and thus would not appear in written transcripts of the proceedings. These findings underscore the need to attend to and document gestures produced in investigative interviews, particularly interviews conducted with children. PMID:20483837

Gesture, sign, and language: The coming of age of sign language and gesture studies.

PubMed

Goldin-Meadow, Susan; Brentari, Diane

2017-01-01

How does sign language compare with gesture, on the one hand, and spoken language on the other? Sign was once viewed as nothing more than a system of pictorial gestures without linguistic structure. More recently, researchers have argued that sign is no different from spoken language, with all of the same linguistic structures. The pendulum is currently swinging back toward the view that sign is gestural, or at least has gestural components. The goal of this review is to elucidate the relationships among sign language, gesture, and spoken language. We do so by taking a close look not only at how sign has been studied over the past 50 years, but also at how the spontaneous gestures that accompany speech have been studied. We conclude that signers gesture just as speakers do. Both produce imagistic gestures along with more categorical signs or words. Because at present it is difficult to tell where sign stops and gesture begins, we suggest that sign should not be compared with speech alone but should be compared with speech-plus-gesture. Although it might be easier (and, in some cases, preferable) to blur the distinction between sign and gesture, we argue that distinguishing between sign (or speech) and gesture is essential to predict certain types of learning and allows us to understand the conditions under which gesture takes on properties of sign, and speech takes on properties of gesture. We end by calling for new technology that may help us better calibrate the borders between sign and gesture.

The role of beat gesture and pitch accent in semantic processing: an ERP study.

PubMed

Wang, Lin; Chu, Mingyuan

2013-11-01

The present study investigated whether and how beat gesture (small baton-like hand movements used to emphasize information in speech) influences semantic processing as well as its interaction with pitch accent during speech comprehension. Event-related potentials were recorded as participants watched videos of a person gesturing and speaking simultaneously. The critical words in the spoken sentences were accompanied by a beat gesture, a control hand movement, or no hand movement, and were expressed either with or without pitch accent. We found that both beat gesture and control hand movement induced smaller negativities in the N400 time window than when no hand movement was presented. The reduced N400s indicate that both beat gesture and control movement facilitated the semantic integration of the critical word into the sentence context. In addition, the words accompanied by beat gesture elicited smaller negativities in the N400 time window than those accompanied by control hand movement over right posterior electrodes, suggesting that beat gesture has a unique role for enhancing semantic processing during speech comprehension. Finally, no interaction was observed between beat gesture and pitch accent, indicating that they affect semantic processing independently. © 2013 Elsevier Ltd. All rights reserved.

Wearable Sensors for eLearning of Manual Tasks: Using Forearm EMG in Hand Hygiene Training

PubMed Central

Kutafina, Ekaterina; Laukamp, David; Bettermann, Ralf; Schroeder, Ulrik; Jonas, Stephan M.

2016-01-01

In this paper, we propose a novel approach to eLearning that makes use of smart wearable sensors. Traditional eLearning supports the remote and mobile learning of mostly theoretical knowledge. Here we discuss the possibilities of eLearning to support the training of manual skills. We employ forearm armbands with inertial measurement units and surface electromyography sensors to detect and analyse the user’s hand motions and evaluate their performance. Hand hygiene is chosen as the example activity, as it is a highly standardized manual task that is often not properly executed. The World Health Organization guidelines on hand hygiene are taken as a model of the optimal hygiene procedure, due to their algorithmic structure. Gesture recognition procedures based on artificial neural networks and hidden Markov modeling were developed, achieving recognition rates of 98.30% (±1.26%) for individual gestures. Our approach is shown to be promising for further research and application in the mobile eLearning of manual skills. PMID:27527167

Wearable Sensors for eLearning of Manual Tasks: Using Forearm EMG in Hand Hygiene Training.

PubMed

Kutafina, Ekaterina; Laukamp, David; Bettermann, Ralf; Schroeder, Ulrik; Jonas, Stephan M

2016-08-03

In this paper, we propose a novel approach to eLearning that makes use of smart wearable sensors. Traditional eLearning supports the remote and mobile learning of mostly theoretical knowledge. Here we discuss the possibilities of eLearning to support the training of manual skills. We employ forearm armbands with inertial measurement units and surface electromyography sensors to detect and analyse the user's hand motions and evaluate their performance. Hand hygiene is chosen as the example activity, as it is a highly standardized manual task that is often not properly executed. The World Health Organization guidelines on hand hygiene are taken as a model of the optimal hygiene procedure, due to their algorithmic structure. Gesture recognition procedures based on artificial neural networks and hidden Markov modeling were developed, achieving recognition rates of 98 . 30 % ( ± 1 . 26 % ) for individual gestures. Our approach is shown to be promising for further research and application in the mobile eLearning of manual skills.

Gesture, sign and language: The coming of age of sign language and gesture studies

PubMed Central

Goldin-Meadow, Susan; Brentari, Diane

2016-01-01

How does sign language compare to gesture, on the one hand, and to spoken language on the other? At one time, sign was viewed as nothing more than a system of pictorial gestures with no linguistic structure. More recently, researchers have argued that sign is no different from spoken language with all of the same linguistic structures. The pendulum is currently swinging back toward the view that sign is gestural, or at least has gestural components. The goal of this review is to elucidate the relationships among sign language, gesture, and spoken language. We do so by taking a close look not only at how sign has been studied over the last 50 years, but also at how the spontaneous gestures that accompany speech have been studied. We come to the conclusion that signers gesture just as speakers do. Both produce imagistic gestures along with more categorical signs or words. Because, at the moment, it is difficult to tell where sign stops and where gesture begins, we suggest that sign should not be compared to speech alone, but should be compared to speech-plus-gesture. Although it might be easier (and, in some cases, preferable) to blur the distinction between sign and gesture, we argue that making a distinction between sign (or speech) and gesture is essential to predict certain types of learning, and allows us to understand the conditions under which gesture takes on properties of sign, and speech takes on properties of gesture. We end by calling for new technology that may help us better calibrate the borders between sign and gesture. PMID:26434499

Hands in the air: using ungrounded iconic gestures to teach children conservation of quantity.

PubMed

Ping, Raedy M; Goldin-Meadow, Susan

2008-09-01

Including gesture in instruction facilitates learning. Why? One possibility is that gesture points out objects in the immediate context and thus helps ground the words learners hear in the world they see. Previous work on gesture's role in instruction has used gestures that either point to or trace paths on objects, thus providing support for this hypothesis. The experiments described here investigated the possibility that gesture helps children learn even when it is not produced in relation to an object but is instead produced "in the air." Children were given instruction in Piagetian conservation problems with or without gesture and with or without concrete objects. The results indicate that children given instruction with speech and gesture learned more about conservation than children given instruction with speech alone, whether or not objects were present during instruction. Gesture in instruction can thus help learners learn even when those gestures do not direct attention to visible objects, suggesting that gesture can do more for learners than simply ground arbitrary, symbolic language in the physical, observable world.

Using the Hands to Represent Objects in Space: Gesture as a Substrate for Signed Language Acquisition.

PubMed

Janke, Vikki; Marshall, Chloë R

2017-01-01

An ongoing issue of interest in second language research concerns what transfers from a speaker's first language to their second. For learners of a sign language, gesture is a potential substrate for transfer. Our study provides a novel test of gestural production by eliciting silent gesture from novices in a controlled environment. We focus on spatial relationships, which in sign languages are represented in a very iconic way using the hands, and which one might therefore predict to be easy for adult learners to acquire. However, a previous study by Marshall and Morgan (2015) revealed that this was only partly the case: in a task that required them to express the relative locations of objects, hearing adult learners of British Sign Language (BSL) could represent objects' locations and orientations correctly, but had difficulty selecting the correct handshapes to represent the objects themselves. If hearing adults are indeed drawing upon their gestural resources when learning sign languages, then their difficulties may have stemmed from their having in manual gesture only a limited repertoire of handshapes to draw upon, or, alternatively, from having too broad a repertoire. If the first hypothesis is correct, the challenge for learners is to extend their handshape repertoire, but if the second is correct, the challenge is instead to narrow down to the handshapes appropriate for that particular sign language. 30 sign-naïve hearing adults were tested on Marshall and Morgan's task. All used some handshapes that were different from those used by native BSL signers and learners, and the set of handshapes used by the group as a whole was larger than that employed by native signers and learners. Our findings suggest that a key challenge when learning to express locative relations might be reducing from a very large set of gestural resources, rather than supplementing a restricted one, in order to converge on the conventionalized classifier system that forms part of the

Type of gesture, valence, and gaze modulate the influence of gestures on observer's behaviors

PubMed Central

De Stefani, Elisa; Innocenti, Alessandro; Secchi, Claudio; Papa, Veronica; Gentilucci, Maurizio

2013-01-01

The present kinematic study aimed at determining whether the observation of arm/hand gestures performed by conspecifics affected an action apparently unrelated to the gesture (i.e., reaching-grasping). In 3 experiments we examined the influence of different gestures on action kinematics. We also analyzed the effects of words corresponding in meaning to the gestures, on the same action. In Experiment 1, the type of gesture, valence and actor's gaze were the investigated variables Participants executed the action of reaching-grasping after discriminating whether the gestures produced by a conspecific were meaningful or not. The meaningful gestures were request or symbolic and their valence was positive or negative. They were presented by the conspecific either blindfolded or not. In control Experiment 2 we searched for effects of the sole gaze, and, in Experiment 3, the effects of the same characteristics of words corresponding in meaning to the gestures and visually presented by the conspecific. Type of gesture, valence, and gaze influenced the actual action kinematics; these effects were similar, but not the same as those induced by words. We proposed that the signal activated a response which made the actual action faster for negative valence of gesture, whereas for request signals and available gaze, the response interfered with the actual action more than symbolic signals and not available gaze. Finally, we proposed the existence of a common circuit involved in the comprehension of gestures and words and in the activation of consequent responses to them. PMID:24046742

The Different Benefits from Different Gestures in Understanding a Concept

ERIC Educational Resources Information Center

Kang, Seokmin; Hallman, Gregory L.; Son, Lisa K.; Black, John B.

2013-01-01

Explanations are typically accompanied by hand gestures. While research has shown that gestures can help learners understand a particular concept, different learning effects in different types of gesture have been less understood. To address the issues above, the current study focused on whether different types of gestures lead to different levels…

Gestural cue analysis in automated semantic miscommunication annotation

PubMed Central

Inoue, Masashi; Ogihara, Mitsunori; Hanada, Ryoko; Furuyama, Nobuhiro

2011-01-01

The automated annotation of conversational video by semantic miscommunication labels is a challenging topic. Although miscommunications are often obvious to the speakers as well as the observers, it is difficult for machines to detect them from the low-level features. We investigate the utility of gestural cues in this paper among various non-verbal features. Compared with gesture recognition tasks in human-computer interaction, this process is difficult due to the lack of understanding on which cues contribute to miscommunications and the implicitness of gestures. Nine simple gestural features are taken from gesture data, and both simple and complex classifiers are constructed using machine learning. The experimental results suggest that there is no single gestural feature that can predict or explain the occurrence of semantic miscommunication in our setting. PMID:23585724

Mexican sign language recognition using normalized moments and artificial neural networks

NASA Astrophysics Data System (ADS)

Solís-V., J.-Francisco; Toxqui-Quitl, Carina; Martínez-Martínez, David; H.-G., Margarita

2014-09-01

This work presents a framework designed for the Mexican Sign Language (MSL) recognition. A data set was recorded with 24 static signs from the MSL using 5 different versions, this MSL dataset was captured using a digital camera in incoherent light conditions. Digital Image Processing was used to segment hand gestures, a uniform background was selected to avoid using gloved hands or some special markers. Feature extraction was performed by calculating normalized geometric moments of gray scaled signs, then an Artificial Neural Network performs the recognition using a 10-fold cross validation tested in weka, the best result achieved 95.83% of recognition rate.

Gesture Imitation in Schizophrenia

PubMed Central

Matthews, Natasha; Gold, Brian J.; Sekuler, Robert; Park, Sohee

2013-01-01

Recent evidence suggests that individuals with schizophrenia (SZ) are impaired in their ability to imitate gestures and movements generated by others. This impairment in imitation may be linked to difficulties in generating and maintaining internal representations in working memory (WM). We used a novel quantitative technique to investigate the relationship between WM and imitation ability. SZ outpatients and demographically matched healthy control (HC) participants imitated hand gestures. In Experiment 1, participants imitated single gestures. In Experiment 2, they imitated sequences of 2 gestures, either while viewing the gesture online or after a short delay that forced the use of WM. In Experiment 1, imitation errors were increased in SZ compared with HC. Experiment 2 revealed a significant interaction between imitation ability and WM. SZ produced more errors and required more time to imitate when that imitation depended upon WM compared with HC. Moreover, impaired imitation from WM was significantly correlated with the severity of negative symptoms but not with positive symptoms. In sum, gesture imitation was impaired in schizophrenia, especially when the production of an imitation depended upon WM and when an imitation entailed multiple actions. Such a deficit may have downstream consequences for new skill learning. PMID:21765171

Patients with hippocampal amnesia successfully integrate gesture and speech.

PubMed

Hilverman, Caitlin; Clough, Sharice; Duff, Melissa C; Cook, Susan Wagner

2018-06-19

During conversation, people integrate information from co-speech hand gestures with information in spoken language. For example, after hearing the sentence, "A piece of the log flew up and hit Carl in the face" while viewing a gesture directed at the nose, people tend to later report that the log hit Carl in the nose (information only in gesture) rather than in the face (information in speech). The cognitive and neural mechanisms that support the integration of gesture with speech are unclear. One possibility is that the hippocampus - known for its role in relational memory and information integration - is necessary for integrating gesture and speech. To test this possibility, we examined how patients with hippocampal amnesia and healthy and brain-damaged comparison participants express information from gesture in a narrative retelling task. Participants watched videos of an experimenter telling narratives that included hand gestures that contained supplementary information. Participants were asked to retell the narratives and their spoken retellings were assessed for the presence of information from gesture. For features that had been accompanied by supplementary gesture, patients with amnesia retold fewer of these features overall and fewer retellings that matched the speech from the narrative. Yet their retellings included features that contained information that had been present uniquely in gesture in amounts that were not reliably different from comparison groups. Thus, a functioning hippocampus is not necessary for gesture-speech integration over short timescales. Providing unique information in gesture may enhance communication for individuals with declarative memory impairment, possibly via non-declarative memory mechanisms. Copyright © 2018. Published by Elsevier Ltd.

Hands in the Air: Using Ungrounded Iconic Gestures to Teach Children Conservation of Quantity

ERIC Educational Resources Information Center

Ping, Raedy M.; Goldin-Meadow, Susan

2008-01-01

Including gesture in instruction facilitates learning. Why? One possibility is that gesture points out objects in the immediate context and thus helps ground the words learners hear in the world they see. Previous work on gesture's role in instruction has used gestures that either point to or trace paths on objects, thus providing support for this…

Technological evaluation of gesture and speech interfaces for enabling dismounted soldier-robot dialogue

NASA Astrophysics Data System (ADS)

Kattoju, Ravi Kiran; Barber, Daniel J.; Abich, Julian; Harris, Jonathan

2016-05-01

With increasing necessity for intuitive Soldier-robot communication in military operations and advancements in interactive technologies, autonomous robots have transitioned from assistance tools to functional and operational teammates able to service an array of military operations. Despite improvements in gesture and speech recognition technologies, their effectiveness in supporting Soldier-robot communication is still uncertain. The purpose of the present study was to evaluate the performance of gesture and speech interface technologies to facilitate Soldier-robot communication during a spatial-navigation task with an autonomous robot. Gesture and speech semantically based spatial-navigation commands leveraged existing lexicons for visual and verbal communication from the U.S Army field manual for visual signaling and a previously established Squad Level Vocabulary (SLV). Speech commands were recorded by a Lapel microphone and Microsoft Kinect, and classified by commercial off-the-shelf automatic speech recognition (ASR) software. Visual signals were captured and classified using a custom wireless gesture glove and software. Participants in the experiment commanded a robot to complete a simulated ISR mission in a scaled down urban scenario by delivering a sequence of gesture and speech commands, both individually and simultaneously, to the robot. Performance and reliability of gesture and speech hardware interfaces and recognition tools were analyzed and reported. Analysis of experimental results demonstrated the employed gesture technology has significant potential for enabling bidirectional Soldier-robot team dialogue based on the high classification accuracy and minimal training required to perform gesture commands.

The revised NEUROGES-ELAN system: An objective and reliable interdisciplinary analysis tool for nonverbal behavior and gesture.

PubMed

Lausberg, Hedda; Sloetjes, Han

2016-09-01

As visual media spread to all domains of public and scientific life, nonverbal behavior is taking its place as an important form of communication alongside the written and spoken word. An objective and reliable method of analysis for hand movement behavior and gesture is therefore currently required in various scientific disciplines, including psychology, medicine, linguistics, anthropology, sociology, and computer science. However, no adequate common methodological standards have been developed thus far. Many behavioral gesture-coding systems lack objectivity and reliability, and automated methods that register specific movement parameters often fail to show validity with regard to psychological and social functions. To address these deficits, we have combined two methods, an elaborated behavioral coding system and an annotation tool for video and audio data. The NEUROGES-ELAN system is an effective and user-friendly research tool for the analysis of hand movement behavior, including gesture, self-touch, shifts, and actions. Since its first publication in 2009 in Behavior Research Methods, the tool has been used in interdisciplinary research projects to analyze a total of 467 individuals from different cultures, including subjects with mental disease and brain damage. Partly on the basis of new insights from these studies, the system has been revised methodologically and conceptually. The article presents the revised version of the system, including a detailed study of reliability. The improved reproducibility of the revised version makes NEUROGES-ELAN a suitable system for basic empirical research into the relation between hand movement behavior and gesture and cognitive, emotional, and interactive processes and for the development of automated movement behavior recognition methods.

GEsture: an online hand-drawing tool for gene expression pattern search.

PubMed

Wang, Chunyan; Xu, Yiqing; Wang, Xuelin; Zhang, Li; Wei, Suyun; Ye, Qiaolin; Zhu, Youxiang; Yin, Hengfu; Nainwal, Manoj; Tanon-Reyes, Luis; Cheng, Feng; Yin, Tongming; Ye, Ning

2018-01-01

Gene expression profiling data provide useful information for the investigation of biological function and process. However, identifying a specific expression pattern from extensive time series gene expression data is not an easy task. Clustering, a popular method, is often used to classify similar expression genes, however, genes with a 'desirable' or 'user-defined' pattern cannot be efficiently detected by clustering methods. To address these limitations, we developed an online tool called GEsture. Users can draw, or graph a curve using a mouse instead of inputting abstract parameters of clustering methods. GEsture explores genes showing similar, opposite and time-delay expression patterns with a gene expression curve as input from time series datasets. We presented three examples that illustrate the capacity of GEsture in gene hunting while following users' requirements. GEsture also provides visualization tools (such as expression pattern figure, heat map and correlation network) to display the searching results. The result outputs may provide useful information for researchers to understand the targets, function and biological processes of the involved genes.

[Assessment of gestures and their psychiatric relevance].

PubMed

Bulucz, Judit; Simon, Lajos

2008-01-01

Analyzing and investigating non-verbal behavior and gestures has been receiving much attention since the last century. Thanks to the pioneer work of Ekman and Friesen we have a number of descriptive-analytic, categorizing and semantic content related scales and scoring systems. Generation of gestures, the integrative system with speech and the inter-cultural differences are in the focus of interest. Furthermore, analysis of the gestural changes caused by lesions of distinct neurological areas point toward to formation of new diagnostic approaches. The more widespread application of computerized methods resulted in an increasing number of experiments which study gesture generation, reproduction in mechanical and virtual reality. Increasing efforts are directed towards the understanding of human and computerized recognition of human gestures. In this review we describe the results emphasizing the relations of those results with psychiatric and neuropsychiatric disorders, specifically schizophrenia and affective spectrum.

Spontaneous Gestures during Mental Rotation Tasks: Insights into the Microdevelopment of the Motor Strategy

ERIC Educational Resources Information Center

Chu, Mingyuan; Kita, Sotaro

2008-01-01

This study investigated the motor strategy involved in mental rotation tasks by examining 2 types of spontaneous gestures (hand-object interaction gestures, representing the agentive hand action on an object, vs. object-movement gestures, representing the movement of an object by itself) and different types of verbal descriptions of rotation.…

Exploring the Use of Discrete Gestures for Authentication

NASA Astrophysics Data System (ADS)

Chong, Ming Ki; Marsden, Gary

Research in user authentication has been a growing field in HCI. Previous studies have shown that peoples’ graphical memory can be used to increase password memorability. On the other hand, with the increasing number of devices with built-in motion sensors, kinesthetic memory (or muscle memory) can also be exploited for authentication. This paper presents a novel knowledge-based authentication scheme, called gesture password, which uses discrete gestures as password elements. The research presents a study of multiple password retention using PINs and gesture passwords. The study reports that although participants could use kinesthetic memory to remember gesture passwords, retention of PINs is far superior to retention of gesture passwords.

Ape gestures and language evolution

PubMed Central

Pollick, Amy S.; de Waal, Frans B. M.

2007-01-01

The natural communication of apes may hold clues about language origins, especially because apes frequently gesture with limbs and hands, a mode of communication thought to have been the starting point of human language evolution. The present study aimed to contrast brachiomanual gestures with orofacial movements and vocalizations in the natural communication of our closest primate relatives, bonobos (Pan paniscus) and chimpanzees (Pan troglodytes). We tested whether gesture is the more flexible form of communication by measuring the strength of association between signals and specific behavioral contexts, comparing groups of both the same and different ape species. Subjects were two captive bonobo groups, a total of 13 individuals, and two captive chimpanzee groups, a total of 34 individuals. The study distinguished 31 manual gestures and 18 facial/vocal signals. It was found that homologous facial/vocal displays were used very similarly by both ape species, yet the same did not apply to gestures. Both within and between species gesture usage varied enormously. Moreover, bonobos showed greater flexibility in this regard than chimpanzees and were also the only species in which multimodal communication (i.e., combinations of gestures and facial/vocal signals) added to behavioral impact on the recipient. PMID:17470779

Beating time: How ensemble musicians' cueing gestures communicate beat position and tempo.

PubMed

Bishop, Laura; Goebl, Werner

2018-01-01

Ensemble musicians typically exchange visual cues to coordinate piece entrances. "Cueing-in" gestures indicate when to begin playing and at what tempo. This study investigated how timing information is encoded in musicians' cueing-in gestures. Gesture acceleration patterns were expected to indicate beat position, while gesture periodicity, duration, and peak gesture velocity were expected to indicate tempo. Same-instrument ensembles (e.g., piano-piano) were expected to synchronize more successfully than mixed-instrument ensembles (e.g., piano-violin). Duos performed short passages as their head and (for violinists) bowing hand movements were tracked with accelerometers and Kinect sensors. Performers alternated between leader/follower roles; leaders heard a tempo via headphones and cued their partner in nonverbally. Violin duos synchronized more successfully than either piano duos or piano-violin duos, possibly because violinists were more experienced in ensemble playing than pianists. Peak acceleration indicated beat position in leaders' head-nodding gestures. Gesture duration and periodicity in leaders' head and bowing hand gestures indicated tempo. The results show that the spatio-temporal characteristics of cueing-in gestures guide beat perception, enabling synchronization with visual gestures that follow a range of spatial trajectories.

Co-Thought Gestures: Supporting Students to Successfully Navigate Map Tasks

ERIC Educational Resources Information Center

Logan, Tracy; Lowrie, Tom; Diezmann, Carmel M.

2014-01-01

This study considers the role and nature of co-thought gestures when students process map-based mathematics tasks. These gestures are typically spontaneously produced silent gestures which do not accompany speech and are represented by small movements of the hands or arms often directed toward an artefact. The study analysed 43 students (aged…

Combining heterogenous features for 3D hand-held object recognition

NASA Astrophysics Data System (ADS)

Lv, Xiong; Wang, Shuang; Li, Xiangyang; Jiang, Shuqiang

2014-10-01

Object recognition has wide applications in the area of human-machine interaction and multimedia retrieval. However, due to the problem of visual polysemous and concept polymorphism, it is still a great challenge to obtain reliable recognition result for the 2D images. Recently, with the emergence and easy availability of RGB-D equipment such as Kinect, this challenge could be relieved because the depth channel could bring more information. A very special and important case of object recognition is hand-held object recognition, as hand is a straight and natural way for both human-human interaction and human-machine interaction. In this paper, we study the problem of 3D object recognition by combining heterogenous features with different modalities and extraction techniques. For hand-craft feature, although it reserves the low-level information such as shape and color, it has shown weakness in representing hiconvolutionalgh-level semantic information compared with the automatic learned feature, especially deep feature. Deep feature has shown its great advantages in large scale dataset recognition but is not always robust to rotation or scale variance compared with hand-craft feature. In this paper, we propose a method to combine hand-craft point cloud features and deep learned features in RGB and depth channle. First, hand-held object segmentation is implemented by using depth cues and human skeleton information. Second, we combine the extracted hetegerogenous 3D features in different stages using linear concatenation and multiple kernel learning (MKL). Then a training model is used to recognize 3D handheld objects. Experimental results validate the effectiveness and gerneralization ability of the proposed method.

I See It in My Hands' Eye: Representational Gestures Reflect Conceptual Demands

ERIC Educational Resources Information Center

Hostetter, Autumn B.; Alibali, Martha W.; Kita, Sotaro

2007-01-01

The Information Packaging Hypothesis (Kita, 2000) holds that gestures play a role in conceptualising information for speaking. According to this view, speakers will gesture more when describing difficult-to-conceptualise information than when describing easy-to-conceptualise information. In the present study, 24 participants described ambiguous…

Give Me a Hand: Differential Effects of Gesture Type in Guiding Young Children's Problem-Solving

ERIC Educational Resources Information Center

Vallotton, Claire; Fusaro, Maria; Hayden, Julia; Decker, Kalli; Gutowski, Elizabeth

2015-01-01

Adults' gestures support children's learning in problem-solving tasks, but gestures may be differentially useful to children of different ages, and different features of gestures may make them more or less useful to children. The current study investigated parents' use of gestures to support their young children (1.5-6 years) in a block puzzle…

Nonverbal Social Communication and Gesture Control in Schizophrenia

PubMed Central

Walther, Sebastian; Stegmayer, Katharina; Sulzbacher, Jeanne; Vanbellingen, Tim; Müri, René; Strik, Werner; Bohlhalter, Stephan

2015-01-01

Schizophrenia patients are severely impaired in nonverbal communication, including social perception and gesture production. However, the impact of nonverbal social perception on gestural behavior remains unknown, as is the contribution of negative symptoms, working memory, and abnormal motor behavior. Thus, the study tested whether poor nonverbal social perception was related to impaired gesture performance, gestural knowledge, or motor abnormalities. Forty-six patients with schizophrenia (80%), schizophreniform (15%), or schizoaffective disorder (5%) and 44 healthy controls matched for age, gender, and education were included. Participants completed 4 tasks on nonverbal communication including nonverbal social perception, gesture performance, gesture recognition, and tool use. In addition, they underwent comprehensive clinical and motor assessments. Patients presented impaired nonverbal communication in all tasks compared with controls. Furthermore, in contrast to controls, performance in patients was highly correlated between tasks, not explained by supramodal cognitive deficits such as working memory. Schizophrenia patients with impaired gesture performance also demonstrated poor nonverbal social perception, gestural knowledge, and tool use. Importantly, motor/frontal abnormalities negatively mediated the strong association between nonverbal social perception and gesture performance. The factors negative symptoms and antipsychotic dosage were unrelated to the nonverbal tasks. The study confirmed a generalized nonverbal communication deficit in schizophrenia. Specifically, the findings suggested that nonverbal social perception in schizophrenia has a relevant impact on gestural impairment beyond the negative influence of motor/frontal abnormalities. PMID:25646526

Body schema and corporeal self-recognition in the alien hand syndrome.

PubMed

Olgiati, Elena; Maravita, Angelo; Spandri, Viviana; Casati, Roberta; Ferraro, Francesco; Tedesco, Lucia; Agostoni, Elio Clemente; Bolognini, Nadia

2017-07-01

The alien hand syndrome (AHS) is a rare neuropsychological disorder characterized by involuntary, yet purposeful, hand movements. Patients with the AHS typically complain about a loss of agency associated with a feeling of estrangement for actions performed by the affected limb. The present study explores the integrity of the body representation in AHS, focusing on 2 main processes: multisensory integration and visual self-recognition of body parts. Three patients affected by AHS following a right-hemisphere stroke, with clinical symptoms akin to the posterior variant of AHS, were tested and their performance was compared with that of 18 age-matched healthy controls. AHS patients and controls underwent 2 experimental tasks: a same-different visual matching task for body postures, which assessed the ability of using your own body schema for encoding others' body postural changes (Experiment 1), and an explicit self-hand recognition task, which assessed the ability to visually recognize your own hands (Experiment 2). As compared to controls, all AHS patients were unable to access a reliable multisensory representation of their alien hand and use it for decoding others' postural changes; however, they could rely on an efficient multisensory representation of their intact (ipsilesional) hand. Two AHS patients also presented with a specific impairment in the visual self-recognition of their alien hand, but normal recognition of their intact hand. This evidence suggests that the AHS following a right-hemisphere stroke may involve a disruption of the multisensory representation of the alien limb; instead, self-hand recognition mechanisms may be spared. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Hand biometric recognition based on fused hand geometry and vascular patterns.

PubMed

Park, GiTae; Kim, Soowon

2013-02-28

A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%.

Linking Gestures: Cross-Cultural Variation during Instructional Analogies

ERIC Educational Resources Information Center

Richland, Lindsey Engle

2015-01-01

Deictic linking gestures, hand and arm motions that physically embody links being communicated between two or more objects in the shared communicative environment, are explored in a cross-cultural sample of mathematics instruction. Linking gestures are specifically examined here when they occur in the context of communicative analogies designed to…

Hand Biometric Recognition Based on Fused Hand Geometry and Vascular Patterns

PubMed Central

Park, GiTae; Kim, Soowon

2013-01-01

A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%. PMID:23449119

Gesture-Controlled Interface for Contactless Control of Various Computer Programs with a Hooking-Based Keyboard and Mouse-Mapping Technique in the Operating Room

PubMed Central

Park, Ben Joonyeon; Jang, Taekjin; Choi, Jong Woo; Kim, Namkug

2016-01-01

We developed a contactless interface that exploits hand gestures to effectively control medical images in the operating room. We developed an in-house program called GestureHook that exploits message hooking techniques to convert gestures into specific functions. For quantitative evaluation of this program, we used gestures to control images of a dynamic biliary CT study and compared the results with those of a mouse (8.54 ± 1.77 s to 5.29 ± 1.00 s; p < 0.001) and measured the recognition rates of specific gestures and the success rates of tasks based on clinical scenarios. For clinical applications, this program was set up in the operating room to browse images for plastic surgery. A surgeon browsed images from three different programs: CT images from a PACS program, volume-rendered images from a 3D PACS program, and surgical planning photographs from a basic image viewing program. All programs could be seamlessly controlled by gestures and motions. This approach can control all operating room programs without source code modification and provide surgeons with a new way to safely browse through images and easily switch applications during surgical procedures. PMID:26981146

Gesture-Controlled Interface for Contactless Control of Various Computer Programs with a Hooking-Based Keyboard and Mouse-Mapping Technique in the Operating Room.

PubMed

Park, Ben Joonyeon; Jang, Taekjin; Choi, Jong Woo; Kim, Namkug

2016-01-01

We developed a contactless interface that exploits hand gestures to effectively control medical images in the operating room. We developed an in-house program called GestureHook that exploits message hooking techniques to convert gestures into specific functions. For quantitative evaluation of this program, we used gestures to control images of a dynamic biliary CT study and compared the results with those of a mouse (8.54 ± 1.77 s to 5.29 ± 1.00 s; p < 0.001) and measured the recognition rates of specific gestures and the success rates of tasks based on clinical scenarios. For clinical applications, this program was set up in the operating room to browse images for plastic surgery. A surgeon browsed images from three different programs: CT images from a PACS program, volume-rendered images from a 3D PACS program, and surgical planning photographs from a basic image viewing program. All programs could be seamlessly controlled by gestures and motions. This approach can control all operating room programs without source code modification and provide surgeons with a new way to safely browse through images and easily switch applications during surgical procedures.

Generation of co-speech gestures based on spatial imagery from the right-hemisphere: evidence from split-brain patients.

PubMed

Kita, Sotaro; Lausberg, Hedda

2008-02-01

It has been claimed that the linguistically dominant (left) hemisphere is obligatorily involved in production of spontaneous speech-accompanying gestures (Kimura, 1973a, 1973b; Lavergne and Kimura, 1987). We examined this claim for the gestures that are based on spatial imagery: iconic gestures with observer viewpoint (McNeill, 1992) and abstract deictic gestures (McNeill, et al. 1993). We observed gesture production in three patients with complete section of the corpus callosum in commissurotomy or callosotomy (two with left-hemisphere language, and one with bilaterally represented language) and nine healthy control participants. All three patients produced spatial-imagery gestures with the left-hand as well as with the right-hand. However, unlike healthy controls and the split-brain patient with bilaterally represented language, the two patients with left-hemispheric language dominance coordinated speech and spatial-imagery gestures more poorly in the left-hand than in the right-hand. It is concluded that the linguistically non-dominant (right) hemisphere alone can generate co-speech gestures based on spatial imagery, just as the left-hemisphere can.

Doing science by waving hands: Talk, symbiotic gesture, and interaction with digital content as resources in student inquiry

NASA Astrophysics Data System (ADS)

Gregorcic, Bor; Planinsic, Gorazd; Etkina, Eugenia

2017-12-01

In this paper, we investigate some of the ways in which students, when given the opportunity and an appropriate learning environment, spontaneously engage in collaborative inquiry. We studied small groups of high school students interacting around and with an interactive whiteboard equipped with Algodoo software, as they investigated orbital motion. Using multimodal discourse analysis, we found that in their discussions the students relied heavily on nonverbal meaning-making resources, most notably hand gestures and resources in the surrounding environment (items displayed on the interactive whiteboard). They juxtaposed talk with gestures and resources in the environment to communicate ideas that they initially were not able to express using words alone. By spontaneously recruiting and combining a diverse set of meaning-making resources, the students were able to express relatively fluently complex ideas on a novel physics topic, and to engage in practices that resemble a scientific approach to exploration of new phenomena.

The origins of non-human primates' manual gestures

PubMed Central

Liebal, Katja; Call, Josep

2012-01-01

The increasing body of research into human and non-human primates' gestural communication reflects the interest in a comparative approach to human communication, particularly possible scenarios of language evolution. One of the central challenges of this field of research is to identify appropriate criteria to differentiate a gesture from other non-communicative actions. After an introduction to the criteria currently used to define non-human primates' gestures and an overview of ongoing research, we discuss different pathways of how manual actions are transformed into manual gestures in both phylogeny and ontogeny. Currently, the relationship between actions and gestures is not only investigated on a behavioural, but also on a neural level. Here, we focus on recent evidence concerning the differential laterality of manual actions and gestures in apes in the framework of a functional asymmetry of the brain for both hand use and language. PMID:22106431

Multi-Touch Tabletop System Using Infrared Image Recognition for User Position Identification.

PubMed

Suto, Shota; Watanabe, Toshiya; Shibusawa, Susumu; Kamada, Masaru

2018-05-14

A tabletop system can facilitate multi-user collaboration in a variety of settings, including small meetings, group work, and education and training exercises. The ability to identify the users touching the table and their positions can promote collaborative work among participants, so methods have been studied that involve attaching sensors to the table, chairs, or to the users themselves. An effective method of recognizing user actions without placing a burden on the user would be some type of visual process, so the development of a method that processes multi-touch gestures by visual means is desired. This paper describes the development of a multi-touch tabletop system using infrared image recognition for user position identification and presents the results of touch-gesture recognition experiments and a system-usability evaluation. Using an inexpensive FTIR touch panel and infrared light, this system picks up the touch areas and the shadow area of the user's hand by an infrared camera to establish an association between the hand and table touch points and estimate the position of the user touching the table. The multi-touch gestures prepared for this system include an operation to change the direction of an object to face the user and a copy operation in which two users generate duplicates of an object. The system-usability evaluation revealed that prior learning was easy and that system operations could be easily performed.

The Different Benefits from Different Gestures in Understanding a Concept

NASA Astrophysics Data System (ADS)

Kang, Seokmin; Hallman, Gregory L.; Son, Lisa K.; Black, John B.

2013-12-01

Explanations are typically accompanied by hand gestures. While research has shown that gestures can help learners understand a particular concept, different learning effects in different types of gesture have been less understood. To address the issues above, the current study focused on whether different types of gestures lead to different levels of improvement in understanding. Two types of gestures were investigated, and thus, three instructional videos (two gesture videos plus a no gesture control) of the subject of mitosis—all identical except for the types of gesture used—were created. After watching one of the three videos, participants were tested on their level of understanding of mitosis. The results showed that (1) differences in comprehension were obtained across the three groups, and (2) representational (semantic) gestures led to a deeper level of comprehension than both beat gestures and the no gesture control. Finally, a language proficiency effect is discussed as a moderator that may affect understanding of a concept. Our findings suggest that a teacher is encouraged to use representational gestures even to adult learners, but more work is needed to prove the benefit of using gestures for adult learners in many subject areas.

From mouth to hand: gesture, speech, and the evolution of right-handedness.

PubMed

Corballis, Michael C

2003-04-01

The strong predominance of right-handedness appears to be a uniquely human characteristic, whereas the left-cerebral dominance for vocalization occurs in many species, including frogs, birds, and mammals. Right-handedness may have arisen because of an association between manual gestures and vocalization in the evolution of language. I argue that language evolved from manual gestures, gradually incorporating vocal elements. The transition may be traced through changes in the function of Broca's area. Its homologue in monkeys has nothing to do with vocal control, but contains the so-called "mirror neurons," the code for both the production of manual reaching movements and the perception of the same movements performed by others. This system is bilateral in monkeys, but predominantly left-hemispheric in humans, and in humans is involved with vocalization as well as manual actions. There is evidence that Broca's area is enlarged on the left side in Homo habilis, suggesting that a link between gesture and vocalization may go back at least two million years, although other evidence suggests that speech may not have become fully autonomous until Homo sapiens appeared some 170,000 years ago, or perhaps even later. The removal of manual gesture as a necessary component of language may explain the rapid advance of technology, allowing late migrations of Homo sapiens from Africa to replace all other hominids in other parts of the world, including the Neanderthals in Europe and Homo erectus in Asia. Nevertheless, the long association of vocalization with manual gesture left us a legacy of right-handedness.

Intelligent RF-Based Gesture Input Devices Implemented Using e-Textiles.

PubMed

Hughes, Dana; Profita, Halley; Radzihovsky, Sarah; Correll, Nikolaus

2017-01-24

We present an radio-frequency (RF)-based approach to gesture detection and recognition, using e-textile versions of common transmission lines used in microwave circuits. This approach allows for easy fabrication of input swatches that can detect a continuum of finger positions and similarly basic gestures, using a single measurement line. We demonstrate that the swatches can perform gesture detection when under thin layers of cloth or when weatherproofed, providing a high level of versatility not present with other types of approaches. Additionally, using small convolutional neural networks, low-level gestures can be identified with a high level of accuracy using a small, inexpensive microcontroller, allowing for an intelligent fabric that reports only gestures of interest, rather than a simple sensor requiring constant surveillance from an external computing device. The resulting e-textile smart composite has applications in controlling wearable devices by providing a simple, eyes-free mechanism to input simple gestures.

Dynamic Monitoring Reveals Motor Task Characteristics in Prehistoric Technical Gestures

PubMed Central

Pfleging, Johannes; Stücheli, Marius; Iovita, Radu; Buchli, Jonas

2015-01-01

Reconstructing ancient technical gestures associated with simple tool actions is crucial for understanding the co-evolution of the human forelimb and its associated control-related cognitive functions on the one hand, and of the human technological arsenal on the other hand. Although the topic of gesture is an old one in Paleolithic archaeology and in anthropology in general, very few studies have taken advantage of the new technologies from the science of kinematics in order to improve replicative experimental protocols. Recent work in paleoanthropology has shown the potential of monitored replicative experiments to reconstruct tool-use-related motions through the study of fossil bones, but so far comparatively little has been done to examine the dynamics of the tool itself. In this paper, we demonstrate that we can statistically differentiate gestures used in a simple scraping task through dynamic monitoring. Dynamics combines kinematics (position, orientation, and speed) with contact mechanical parameters (force and torque). Taken together, these parameters are important because they play a role in the formation of a visible archaeological signature, use-wear. We present our new affordable, yet precise methodology for measuring the dynamics of a simple hide-scraping task, carried out using a pull-to (PT) and a push-away (PA) gesture. A strain gage force sensor combined with a visual tag tracking system records force, torque, as well as position and orientation of hafted flint stone tools. The set-up allows switching between two tool configurations, one with distal and the other one with perpendicular hafting of the scrapers, to allow for ethnographically plausible reconstructions. The data show statistically significant differences between the two gestures: scraping away from the body (PA) generates higher shearing forces, but requires greater hand torque. Moreover, most benchmarks associated with the PA gesture are more highly variable than in the PT gesture

Training with Rhythmic Beat Gestures Benefits L2 Pronunciation in Discourse-Demanding Situations

ERIC Educational Resources Information Center

Gluhareva, Daria; Prieto, Pilar

2017-01-01

Recent research has shown that beat gestures (hand gestures that co-occur with speech in spontaneous discourse) are temporally integrated with prosodic prominence and that they help word memorization and discourse comprehension. However, little is known about the potential beneficial effects of beat gestures in second language (L2) pronunciation…

Hippocampal declarative memory supports gesture production: Evidence from amnesia

PubMed Central

Hilliard, Caitlin; Cook, Susan Wagner; Duff, Melissa C.

2016-01-01

Spontaneous co-speech hand gestures provide a visuospatial representation of what is being communicated in spoken language. Although it is clear that gestures emerge from representations in memory for what is being communicated (De Ruiter, 1998; Wesp, Hesse, Keutmann, & Wheaton, 2001), the mechanism supporting the relationship between gesture and memory is unknown. Current theories of gesture production posit that action – supported by motor areas of the brain – is key in determining whether gestures are produced. We propose that when and how gestures are produced is determined in part by hippocampally-mediated declarative memory. We examined the speech and gesture of healthy older adults and of memory-impaired patients with hippocampal amnesia during four discourse tasks that required accessing episodes and information from the remote past. Consistent with previous reports of impoverished spoken language in patients with hippocampal amnesia, we predicted that these patients, who have difficulty generating multifaceted declarative memory representations, may in turn have impoverished gesture production. We found that patients gestured less overall relative to healthy comparison participants, and that this was particularly evident in tasks that may rely more heavily on declarative memory. Thus, gestures do not just emerge from the motor representation activated for speaking, but are also sensitive to the representation available in hippocampal declarative memory, suggesting a direct link between memory and gesture production. PMID:27810497

Multi-Touch Tabletop System Using Infrared Image Recognition for User Position Identification

PubMed Central

Suto, Shota; Watanabe, Toshiya; Shibusawa, Susumu; Kamada, Masaru

2018-01-01

A tabletop system can facilitate multi-user collaboration in a variety of settings, including small meetings, group work, and education and training exercises. The ability to identify the users touching the table and their positions can promote collaborative work among participants, so methods have been studied that involve attaching sensors to the table, chairs, or to the users themselves. An effective method of recognizing user actions without placing a burden on the user would be some type of visual process, so the development of a method that processes multi-touch gestures by visual means is desired. This paper describes the development of a multi-touch tabletop system using infrared image recognition for user position identification and presents the results of touch-gesture recognition experiments and a system-usability evaluation. Using an inexpensive FTIR touch panel and infrared light, this system picks up the touch areas and the shadow area of the user’s hand by an infrared camera to establish an association between the hand and table touch points and estimate the position of the user touching the table. The multi-touch gestures prepared for this system include an operation to change the direction of an object to face the user and a copy operation in which two users generate duplicates of an object. The system-usability evaluation revealed that prior learning was easy and that system operations could be easily performed. PMID:29758006

Gesture's role in speaking, learning, and creating language.

PubMed

Goldin-Meadow, Susan; Alibali, Martha Wagner

2013-01-01

When speakers talk, they gesture. The goal of this review is to investigate the contribution that these gestures make to how we communicate and think. Gesture can play a role in communication and thought at many timespans. We explore, in turn, gesture's contribution to how language is produced and understood in the moment; its contribution to how we learn language and other cognitive skills; and its contribution to how language is created over generations, over childhood, and on the spot. We find that the gestures speakers produce when they talk are integral to communication and can be harnessed in a number of ways. (a) Gesture reflects speakers' thoughts, often their unspoken thoughts, and thus can serve as a window onto cognition. Encouraging speakers to gesture can thus provide another route for teachers, clinicians, interviewers, etc., to better understand their communication partners. (b) Gesture can change speakers' thoughts. Encouraging gesture thus has the potential to change how students, patients, witnesses, etc., think about a problem and, as a result, alter the course of learning, therapy, or an interchange. (c) Gesture provides building blocks that can be used to construct a language. By watching how children and adults who do not already have a language put those blocks together, we can observe the process of language creation. Our hands are with us at all times and thus provide researchers and learners with an ever-present tool for understanding how we talk and think.

Intelligent RF-Based Gesture Input Devices Implemented Using e-Textiles †

PubMed Central

Hughes, Dana; Profita, Halley; Radzihovsky, Sarah; Correll, Nikolaus

2017-01-01

We present an radio-frequency (RF)-based approach to gesture detection and recognition, using e-textile versions of common transmission lines used in microwave circuits. This approach allows for easy fabrication of input swatches that can detect a continuum of finger positions and similarly basic gestures, using a single measurement line. We demonstrate that the swatches can perform gesture detection when under thin layers of cloth or when weatherproofed, providing a high level of versatility not present with other types of approaches. Additionally, using small convolutional neural networks, low-level gestures can be identified with a high level of accuracy using a small, inexpensive microcontroller, allowing for an intelligent fabric that reports only gestures of interest, rather than a simple sensor requiring constant surveillance from an external computing device. The resulting e-textile smart composite has applications in controlling wearable devices by providing a simple, eyes-free mechanism to input simple gestures. PMID:28125010

Asymmetric Dynamic Attunement of Speech and Gestures in the Construction of Children's Understanding.

PubMed

De Jonge-Hoekstra, Lisette; Van der Steen, Steffie; Van Geert, Paul; Cox, Ralf F A

2016-01-01

As children learn they use their speech to express words and their hands to gesture. This study investigates the interplay between real-time gestures and speech as children construct cognitive understanding during a hands-on science task. 12 children (M = 6, F = 6) from Kindergarten (n = 5) and first grade (n = 7) participated in this study. Each verbal utterance and gesture during the task were coded, on a complexity scale derived from dynamic skill theory. To explore the interplay between speech and gestures, we applied a cross recurrence quantification analysis (CRQA) to the two coupled time series of the skill levels of verbalizations and gestures. The analysis focused on (1) the temporal relation between gestures and speech, (2) the relative strength and direction of the interaction between gestures and speech, (3) the relative strength and direction between gestures and speech for different levels of understanding, and (4) relations between CRQA measures and other child characteristics. The results show that older and younger children differ in the (temporal) asymmetry in the gestures-speech interaction. For younger children, the balance leans more toward gestures leading speech in time, while the balance leans more toward speech leading gestures for older children. Secondly, at the group level, speech attracts gestures in a more dynamically stable fashion than vice versa, and this asymmetry in gestures and speech extends to lower and higher understanding levels. Yet, for older children, the mutual coupling between gestures and speech is more dynamically stable regarding the higher understanding levels. Gestures and speech are more synchronized in time as children are older. A higher score on schools' language tests is related to speech attracting gestures more rigidly and more asymmetry between gestures and speech, only for the less difficult understanding levels. A higher score on math or past science tasks is related to less asymmetry between gestures and

Symbiotic symbolization by hand and mouth in sign language*

PubMed Central

Sandler, Wendy

2010-01-01

Current conceptions of human language include a gestural component in the communicative event. However, determining how the linguistic and gestural signals are distinguished, how each is structured, and how they interact still poses a challenge for the construction of a comprehensive model of language. This study attempts to advance our understanding of these issues with evidence from sign language. The study adopts McNeill’s criteria for distinguishing gestures from the linguistically organized signal, and provides a brief description of the linguistic organization of sign languages. Focusing on the subcategory of iconic gestures, the paper shows that signers create iconic gestures with the mouth, an articulator that acts symbiotically with the hands to complement the linguistic description of objects and events. A new distinction between the mimetic replica and the iconic symbol accounts for the nature and distribution of iconic mouth gestures and distinguishes them from mimetic uses of the mouth. Symbiotic symbolization by hand and mouth is a salient feature of human language, regardless of whether the primary linguistic modality is oral or manual. Speakers gesture with their hands, and signers gesture with their mouths. PMID:20445832

The Role of Gestures in a Teacher-Student-Discourse about Atoms

ERIC Educational Resources Information Center

Abels, Simone

2016-01-01

Recent educational research emphasises the importance of analysing talk and gestures to come to an understanding about students' conceptual learning. Gestures are perceived as complex hand movements being equivalent to other language modes. They can convey experienceable as well as abstract concepts. As well as technical language, gestures…

A Show of Hands: Relations between Young Children's Gesturing and Executive Function

ERIC Educational Resources Information Center

O'Neill, Gina; Miller, Patricia H.

2013-01-01

This study brought together 2 literatures--gesturing and executive function--in order to examine the possible role of gesture in children's executive function. Children (N = 41) aged 2½-6 years performed a sorting-shift executive function task (Dimensional Change Card Sort). Responses of interest included correct sorting, response latency,…

Inertial Sensor-Based Touch and Shake Metaphor for Expressive Control of 3D Virtual Avatars

PubMed Central

Patil, Shashidhar; Chintalapalli, Harinadha Reddy; Kim, Dubeom; Chai, Youngho

2015-01-01

In this paper, we present an inertial sensor-based touch and shake metaphor for expressive control of a 3D virtual avatar in a virtual environment. An intuitive six degrees-of-freedom wireless inertial motion sensor is used as a gesture and motion control input device with a sensor fusion algorithm. The algorithm enables user hand motions to be tracked in 3D space via magnetic, angular rate, and gravity sensors. A quaternion-based complementary filter is implemented to reduce noise and drift. An algorithm based on dynamic time-warping is developed for efficient recognition of dynamic hand gestures with real-time automatic hand gesture segmentation. Our approach enables the recognition of gestures and estimates gesture variations for continuous interaction. We demonstrate the gesture expressivity using an interactive flexible gesture mapping interface for authoring and controlling a 3D virtual avatar and its motion by tracking user dynamic hand gestures. This synthesizes stylistic variations in a 3D virtual avatar, producing motions that are not present in the motion database using hand gesture sequences from a single inertial motion sensor. PMID:26094629

Low-cost assistive device for hand gesture recognition using sEMG

NASA Astrophysics Data System (ADS)

Kainz, Ondrej; Cymbalák, Dávid; Kardoš, Slavomír.; Fecil'ak, Peter; Jakab, František

2016-07-01

In this paper a low-cost solution for surface EMG (sEMG) signal retrieval is presented. The principal goal is to enable reading the temporal parameters of muscles activity by a computer device, with its further processing. Paper integrates design and deployment of surface electrodes and amplifier following the prior researches. Bearing in mind the goal of creating low-cost solution, the Arduino micro-controller was utilized for analog-to-digital conversion and communication. The software part of the system employs support vector machine (SVM) to classify the EMG signal, as acquired from sensors. Accuracy of the proposed solution achieves over 90 percent for six hand movements. Proposed solution is to be tested as an assistive device for several cases, involving people with motor disabilities and amputees.

Thinking with Your Hands: Speech-Gesture Activity during an L2 Awareness-Raising Task

ERIC Educational Resources Information Center

van Compernolle, Remi A.; Williams, Lawrence

2011-01-01

This article reports on a study of second language (L2) French learners' self-generated use of gesture to think through and resolve a metalinguistic awareness-raising task during small-group work with an expert mediator. Although the use of gesture in L2 communication and pedagogy has recently received increasing attention, little research has…

Spoken language and arm gestures are controlled by the same motor control system.

PubMed

Gentilucci, Maurizio; Dalla Volta, Riccardo

2008-06-01

Arm movements can influence language comprehension much as semantics can influence arm movement planning. Arm movement itself can be used as a linguistic signal. We reviewed neurophysiological and behavioural evidence that manual gestures and vocal language share the same control system. Studies of primate premotor cortex and, in particular, of the so-called "mirror system", including humans, suggest the existence of a dual hand/mouth motor command system involved in ingestion activities. This may be the platform on which a combined manual and vocal communication system was constructed. In humans, speech is typically accompanied by manual gesture, speech production itself is influenced by executing or observing transitive hand actions, and manual actions play an important role in the development of speech, from the babbling stage onwards. Behavioural data also show reciprocal influence between word and symbolic gestures. Neuroimaging and repetitive transcranial magnetic stimulation (rTMS) data suggest that the system governing both speech and gesture is located in Broca's area. In general, the presented data support the hypothesis that the hand motor-control system is involved in higher order cognition.

Grasps Recognition and Evaluation of Stroke Patients for Supporting Rehabilitation Therapy

PubMed Central

Sale, Patrizio; Nijenhuis, Sharon; Prange, Gerdienke; Amirabdollahian, Farshid

2014-01-01

Stroke survivors often suffer impairments on their wrist and hand. Robot-mediated rehabilitation techniques have been proposed as a way to enhance conventional therapy, based on intensive repeated movements. Amongst the set of activities of daily living, grasping is one of the most recurrent. Our aim is to incorporate the detection of grasps in the machine-mediated rehabilitation framework so that they can be incorporated into interactive therapeutic games. In this study, we developed and tested a method based on support vector machines for recognizing various grasp postures wearing a passive exoskeleton for hand and wrist rehabilitation after stroke. The experiment was conducted with ten healthy subjects and eight stroke patients performing the grasping gestures. The method was tested in terms of accuracy and robustness with respect to intersubjects' variability and differences between different grasps. Our results show reliable recognition while also indicating that the recognition accuracy can be used to assess the patients' ability to consistently repeat the gestures. Additionally, a grasp quality measure was proposed to measure the capabilities of the stroke patients to perform grasp postures in a similar way than healthy people. These two measures can be potentially used as complementary measures to other upper limb motion tests. PMID:25258709

Gesture as a Resource for Intersubjectivity in Second-Language Learning Situations

ERIC Educational Resources Information Center

Belhiah, Hassan

2013-01-01

This study documents the role of hand gestures in achieving mutual understanding in second-language learning situations. The study tracks the way gesture is coordinated with talk in tutorials between two Korean students and their American teachers. The study adopts an interactional approach to the study of participants' talk and gestural…

Recognition of factitial hand injuries.

PubMed

Carlson, M J; Linscheid, R L; Lucas, A R

1977-01-01

Facitial injuries with various presentations occur with some frequency to the hand because it is a body part that is easily accessible. Methods used to produce wounds included insertion of porcupine quills, application of constrictive rubber bands, mascara injections and excoriation of healing wounds. It is important to recognize the factitial origin in order to avoid needless repetitive surgery and permanent hand disability. No specific pattern of psychopathology was found in our cases. The patients' attitude toward their lesions was one of bland unconcern and stoicism. The patients were resistant to psychiatric referral and persisted in seeking medical responsibility for cure. Successful management requires early suspicion and prompt recognition as well as establishment of non-accusatory relationship with the primary physician. Confrontation should be avoided if possible. Even if reinforced with collaborative evidence, such confrontation will have limited effect on the patient's subsequent behavior.

Geometry and Gesture-Based Features from Saccadic Eye-Movement as a Biometric in Radiology

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

Hammond, Tracy; Tourassi, Georgia; Yoon, Hong-Jun

In this study, we present a novel application of sketch gesture recognition on eye-movement for biometric identification and estimating task expertise. The study was performed for the task of mammographic screening with simultaneous viewing of four coordinated breast views as typically done in clinical practice. Eye-tracking data and diagnostic decisions collected for 100 mammographic cases (25 normal, 25 benign, 50 malignant) and 10 readers (three board certified radiologists and seven radiology residents), formed the corpus for this study. Sketch gesture recognition techniques were employed to extract geometric and gesture-based features from saccadic eye-movements. Our results show that saccadic eye-movement, characterizedmore » using sketch-based features, result in more accurate models for predicting individual identity and level of expertise than more traditional eye-tracking features.« less

Beat gestures help preschoolers recall and comprehend discourse information.

PubMed

Llanes-Coromina, Judith; Vilà-Giménez, Ingrid; Kushch, Olga; Borràs-Comes, Joan; Prieto, Pilar

2018-08-01

Although the positive effects of iconic gestures on word recall and comprehension by children have been clearly established, less is known about the benefits of beat gestures (rhythmic hand/arm movements produced together with prominent prosody). This study investigated (a) whether beat gestures combined with prosodic information help children recall contrastively focused words as well as information related to those words in a child-directed discourse (Experiment 1) and (b) whether the presence of beat gestures helps children comprehend a narrative discourse (Experiment 2). In Experiment 1, 51 4-year-olds were exposed to a total of three short stories with contrastive words presented in three conditions, namely with prominence in both speech and gesture, prominence in speech only, and nonprominent speech. Results of a recall task showed that (a) children remembered more words when exposed to prominence in both speech and gesture than in either of the other two conditions and that (b) children were more likely to remember information related to those words when the words were associated with beat gestures. In Experiment 2, 55 5- and 6-year-olds were presented with six narratives with target items either produced with prosodic prominence but no beat gestures or produced with both prosodic prominence and beat gestures. Results of a comprehension task demonstrated that stories told with beat gestures were comprehended better by children. Together, these results constitute evidence that beat gestures help preschoolers not only to recall discourse information but also to comprehend it. Copyright © 2018 Elsevier Inc. All rights reserved.

Human Classification Based on Gestural Motions by Using Components of PCA

NASA Astrophysics Data System (ADS)

Aziz, Azri A.; Wan, Khairunizam; Za'aba, S. K.; B, Shahriman A.; Adnan, Nazrul H.; H, Asyekin; R, Zuradzman M.

2013-12-01

Lately, a study of human capabilities with the aim to be integrated into machine is the famous topic to be discussed. Moreover, human are bless with special abilities that they can hear, see, sense, speak, think and understand each other. Giving such abilities to machine for improvement of human life is researcher's aim for better quality of life in the future. This research was concentrating on human gesture, specifically arm motions for differencing the individuality which lead to the development of the hand gesture database. We try to differentiate the human physical characteristic based on hand gesture represented by arm trajectories. Subjects are selected from different type of the body sizes, and then acquired data undergo resampling process. The results discuss the classification of human based on arm trajectories by using Principle Component Analysis (PCA).

A Coding System with Independent Annotations of Gesture Forms and Functions during Verbal Communication: Development of a Database of Speech and GEsture (DoSaGE)

PubMed Central

Kong, Anthony Pak-Hin; Law, Sam-Po; Kwan, Connie Ching-Yin; Lai, Christy; Lam, Vivian

2014-01-01

Gestures are commonly used together with spoken language in human communication. One major limitation of gesture investigations in the existing literature lies in the fact that the coding of forms and functions of gestures has not been clearly differentiated. This paper first described a recently developed Database of Speech and GEsture (DoSaGE) based on independent annotation of gesture forms and functions among 119 neurologically unimpaired right-handed native speakers of Cantonese (divided into three age and two education levels), and presented findings of an investigation examining how gesture use was related to age and linguistic performance. Consideration of these two factors, for which normative data are currently very limited or lacking in the literature, is relevant and necessary when one evaluates gesture employment among individuals with and without language impairment. Three speech tasks, including monologue of a personally important event, sequential description, and story-telling, were used for elicitation. The EUDICO Linguistic ANnotator (ELAN) software was used to independently annotate each participant’s linguistic information of the transcript, forms of gestures used, and the function for each gesture. About one-third of the subjects did not use any co-verbal gestures. While the majority of gestures were non-content-carrying, which functioned mainly for reinforcing speech intonation or controlling speech flow, the content-carrying ones were used to enhance speech content. Furthermore, individuals who are younger or linguistically more proficient tended to use fewer gestures, suggesting that normal speakers gesture differently as a function of age and linguistic performance. PMID:25667563

Gesture as Representational Action: A paper about function

PubMed Central

Novack, Miriam A.; Goldin-Meadow, Susan

2016-01-01

A great deal of attention has recently been paid to gesture and its effects on thinking and learning. It is well established that the hand movements that accompany speech are an integral part of communication, ubiquitous across cultures, and a unique feature of human behavior. In an attempt to understand this intriguing phenomenon, researchers have focused on pinpointing the mechanisms that underlie gesture production. One proposal—that gesture arises from simulated action (see Hostetter & Alibali, 2008)—has opened up discussions about action, gesture, and the relation between the two. However, there is another side to understanding a phenomenon, and that is to understand its function. A phenomenon’s function is its purpose rather than its precipitating cause—the why rather than the how. This paper sets forth a theoretical framework for exploring why gesture serves the functions that it does, and reviews where the current literature fits, and fails to fit, this proposal. Our framework proposes that whether or not gesture is simulated action in terms of its mechanism—it is clearly not reducible to action in terms of its function. Most notably, because gestures are abstracted representations and are not actions tied to particular events and objects, they can play a powerful role in thinking and learning beyond the particular, specifically, in supporting generalization and transfer of knowledge. PMID:27604493

From action to abstraction: Gesture as a mechanism of change

PubMed Central

Goldin-Meadow, Susan

2015-01-01

Piaget was a master at observing the routine behaviors children produce as they go from knowing less to knowing more about at a task, and making inferences not only about how the children understood the task at each point, but also about how they progressed from one point to the next. In this paper, I examine a routine behavior that Piaget overlooked—the spontaneous gestures speakers produce as they explain their solutions to a problem. These gestures are not mere hand waving. They reflect ideas that the speaker has about the problem, often ideas that are not found in that speaker’s talk. But gesture can do more than reflect ideas—it can also change them. In this sense, gesture behaves like any other action; both gesture and action on objects facilitate learning problems on which training was given. However, only gesture promotes transferring the knowledge gained to problems that require generalization. Gesture is, in fact, a special kind of action in that it represents the world rather than directly manipulating the world (gesture does not move objects around). The mechanisms by which gesture and action promote learning may therefore differ—gesture is able to highlight components of an action that promote abstract learning while leaving out details that could tie learning to a specific context. Because it is both an action and a representation, gesture can serve as a bridge between the two and thus be a powerful tool for learning abstract ideas. PMID:26692629

From action to abstraction: Gesture as a mechanism of change.

PubMed

Goldin-Meadow, Susan

2015-12-01

Piaget was a master at observing the routine behaviors children produce as they go from knowing less to knowing more about at a task, and making inferences not only about how the children understood the task at each point, but also about how they progressed from one point to the next. In this paper, I examine a routine behavior that Piaget overlooked-the spontaneous gestures speakers produce as they explain their solutions to a problem. These gestures are not mere hand waving. They reflect ideas that the speaker has about the problem, often ideas that are not found in that speaker's talk. But gesture can do more than reflect ideas-it can also change them. In this sense, gesture behaves like any other action; both gesture and action on objects facilitate learning problems on which training was given. However, only gesture promotes transferring the knowledge gained to problems that require generalization. Gesture is, in fact, a special kind of action in that it represents the world rather than directly manipulating the world (gesture does not move objects around). The mechanisms by which gesture and action promote learning may therefore differ-gesture is able to highlight components of an action that promote abstract learning while leaving out details that could tie learning to a specific context. Because it is both an action and a representation, gesture can serve as a bridge between the two and thus be a powerful tool for learning abstract ideas.

Early Gesture Provides a Helping Hand to Spoken Vocabulary Development for Children with Autism, Down Syndrome, and Typical Development

ERIC Educational Resources Information Center

Özçaliskan, Seyda; Adamson, Lauren B.; Dimitrova, Nevena; Baumann, Stephanie

2017-01-01

Typically developing (TD) children refer to objects uniquely in gesture (e.g., point at a cat) before they produce verbal labels for these objects ("cat"). The onset of such gestures predicts the onset of similar spoken words, showing a strong positive relation between early gestures and early words. We asked whether gesture plays the…

Mnemonic Effect of Iconic Gesture and Beat Gesture in Adults and Children: Is Meaning in Gesture Important for Memory Recall?

ERIC Educational Resources Information Center

So, Wing Chee; Chen-Hui, Colin Sim; Wei-Shan, Julie Low

2012-01-01

Abundant research has shown that encoding meaningful gesture, such as an iconic gesture, enhances memory. This paper asked whether gesture needs to carry meaning to improve memory recall by comparing the mnemonic effect of meaningful (i.e., iconic gestures) and nonmeaningful gestures (i.e., beat gestures). Beat gestures involve simple motoric…

Learning Semantics of Gestural Instructions for Human-Robot Collaboration

PubMed Central

Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

2018-01-01

Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions. PMID:29615888

Learning Semantics of Gestural Instructions for Human-Robot Collaboration.

PubMed

Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

2018-01-01

Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions.

An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control.

PubMed

Adewuyi, Adenike A; Hargrove, Levi J; Kuiken, Todd A

2016-04-01

Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for application to partial-hand prosthetic control.

An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control

PubMed Central

Adewuyi, Adenike A.; Hargrove, Levi J.; Kuiken, Todd A.

2015-01-01

Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for partial-hand applications. PMID:25955989

Face Recognition From One Example View.

DTIC Science & Technology

1995-09-01

Proceedings, International Workshop on Automatic Face- and Gesture-Recognition, pages 248{253, Zurich, 1995. [32] Yael Moses, Shimon Ullman, and Shimon...recognition. Journal of Cognitive Neuroscience, 3(1):71{86, 1991. [49] Shimon Ullman and Ronen Basri. Recognition by linear combinations of models

A Tale of Two Hands: Children's Early Gesture Use in Narrative Production Predicts Later Narrative Structure in Speech

ERIC Educational Resources Information Center

Demir, Özlem Ece; Levine, Susan C.; Goldin-Meadow, Susan

2015-01-01

Speakers of all ages spontaneously gesture as they talk. These gestures predict children's milestones in vocabulary and sentence structure. We ask whether gesture serves a similar role in the development of narrative skill. Children were asked to retell a story conveyed in a wordless cartoon at age five and then again at six, seven, and eight.…

A common functional neural network for overt production of speech and gesture.

PubMed

Marstaller, L; Burianová, H

2015-01-22

The perception of co-speech gestures, i.e., hand movements that co-occur with speech, has been investigated by several studies. The results show that the perception of co-speech gestures engages a core set of frontal, temporal, and parietal areas. However, no study has yet investigated the neural processes underlying the production of co-speech gestures. Specifically, it remains an open question whether Broca's area is central to the coordination of speech and gestures as has been suggested previously. The objective of this study was to use functional magnetic resonance imaging to (i) investigate the regional activations underlying overt production of speech, gestures, and co-speech gestures, and (ii) examine functional connectivity with Broca's area. We hypothesized that co-speech gesture production would activate frontal, temporal, and parietal regions that are similar to areas previously found during co-speech gesture perception and that both speech and gesture as well as co-speech gesture production would engage a neural network connected to Broca's area. Whole-brain analysis confirmed our hypothesis and showed that co-speech gesturing did engage brain areas that form part of networks known to subserve language and gesture. Functional connectivity analysis further revealed a functional network connected to Broca's area that is common to speech, gesture, and co-speech gesture production. This network consists of brain areas that play essential roles in motor control, suggesting that the coordination of speech and gesture is mediated by a shared motor control network. Our findings thus lend support to the idea that speech can influence co-speech gesture production on a motoric level. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

"Like the palm of my hands": Motor imagery enhances implicit and explicit visual recognition of one's own hands.

PubMed

Conson, Massimiliano; Volpicella, Francesco; De Bellis, Francesco; Orefice, Agnese; Trojano, Luigi

2017-10-01

A key point in motor imagery literature is that judging hands in palm view recruits sensory-motor information to a higher extent than judging hands in back view, due to the greater biomechanical complexity implied in rotating hands depicted from palm than from back. We took advantage from this solid evidence to test the nature of a phenomenon known as self-advantage, i.e. the advantage in implicitly recognizing self vs. others' hand images. The self-advantage has been actually found when implicitly but not explicitly judging self-hands, likely due to dissociation between implicit and explicit body representations. However, such a finding might be related to the extent to which motor imagery is recruited during implicit and explicit processing of hand images. We tested this hypothesis in two behavioural experiments. In Experiment 1, right-handed participants judged laterality of either self or others' hands, whereas in Experiment 2, an explicit recognition of one's own hands was required. Crucially, in both experiments participants were randomly presented with hand images viewed from back or from palm. The main result of both experiments was the self-advantage when participants judged hands from palm view. This novel finding demonstrate that increasing the "motor imagery load" during processing of self vs. others' hands can elicit a self-advantage in explicit recognition tasks as well. Future studies testing the possible dissociation between implicit and explicit visual body representations should take into account the modulatory effect of motor imagery load on self-hand processing. Copyright © 2017. Published by Elsevier B.V.

A Kinect based sign language recognition system using spatio-temporal features

NASA Astrophysics Data System (ADS)

Memiş, Abbas; Albayrak, Songül

2013-12-01

This paper presents a sign language recognition system that uses spatio-temporal features on RGB video images and depth maps for dynamic gestures of Turkish Sign Language. Proposed system uses motion differences and accumulation approach for temporal gesture analysis. Motion accumulation method, which is an effective method for temporal domain analysis of gestures, produces an accumulated motion image by combining differences of successive video frames. Then, 2D Discrete Cosine Transform (DCT) is applied to accumulated motion images and temporal domain features transformed into spatial domain. These processes are performed on both RGB images and depth maps separately. DCT coefficients that represent sign gestures are picked up via zigzag scanning and feature vectors are generated. In order to recognize sign gestures, K-Nearest Neighbor classifier with Manhattan distance is performed. Performance of the proposed sign language recognition system is evaluated on a sign database that contains 1002 isolated dynamic signs belongs to 111 words of Turkish Sign Language (TSL) in three different categories. Proposed sign language recognition system has promising success rates.

Interaction in planning movement direction for articulatory gestures and manual actions.

PubMed

Vainio, Lari; Tiainen, Mikko; Tiippana, Kaisa; Komeilipoor, Naeem; Vainio, Martti

2015-10-01

Some theories concerning speech mechanisms assume that overlapping representations are involved in programming certain articulatory gestures and hand actions. The present study investigated whether planning of movement direction for articulatory gestures and manual actions could interact. The participants were presented with written vowels (Experiment 1) or syllables (Experiment 2) that were associated with forward or backward movement of tongue (e.g., [i] vs. [ɑ] or [te] vs. [ke], respectively). They were required to pronounce the speech unit and simultaneously move the joystick forward or backward according to the color of the stimulus. Manual and vocal responses were performed relatively rapidly when the articulation and the hand action required movement into the same direction. The study suggests that planning horizontal tongue movements for articulation shares overlapping neural mechanisms with planning horizontal movement direction of hand actions.

Biomechanics-machine learning system for surgical gesture analysis and development of technologies for minimal access surgery.

PubMed

Cavallo, Filippo; Sinigaglia, Stefano; Megali, Giuseppe; Pietrabissa, Andrea; Dario, Paolo; Mosca, Franco; Cuschieri, Alfred

2014-10-01

The uptake of minimal access surgery (MAS) has by virtue of its clinical benefits become widespread across the surgical specialties. However, despite its advantages in reducing traumatic insult to the patient, it imposes significant ergonomic restriction on the operating surgeons who require training for the safe execution. Recent progress in manipulator technologies (robotic or mechanical) have certainly reduced the level of difficulty, however it requires information for a complete gesture analysis of surgical performance. This article reports on the development and evaluation of such a system capable of full biomechanical and machine learning. The system for gesture analysis comprises 5 principal modules, which permit synchronous acquisition of multimodal surgical gesture signals from different sources and settings. The acquired signals are used to perform a biomechanical analysis for investigation of kinematics, dynamics, and muscle parameters of surgical gestures and a machine learning model for segmentation and recognition of principal phases of surgical gesture. The biomechanical system is able to estimate the level of expertise of subjects and the ergonomics in using different instruments. The machine learning approach is able to ascertain the level of expertise of subjects and has the potential for automatic recognition of surgical gesture for surgeon-robot interactions. Preliminary tests have confirmed the efficacy of the system for surgical gesture analysis, providing an objective evaluation of progress during training of surgeons in their acquisition of proficiency in MAS approach and highlighting useful information for the design and evaluation of master-slave manipulator systems. © The Author(s) 2013.

Brief Training with Co-Speech Gesture Lends a Hand to Word Learning in a Foreign Language

ERIC Educational Resources Information Center

Kelly, Spencer D.; McDevitt, Tara; Esch, Megan

2009-01-01

Recent research in psychology and neuroscience has demonstrated that co-speech gestures are semantically integrated with speech during language comprehension and development. The present study explored whether gestures also play a role in language learning in adults. In Experiment 1, we exposed adults to a brief training session presenting novel…

Prosody in the hands of the speaker

PubMed Central

Guellaï, Bahia; Langus, Alan; Nespor, Marina

2014-01-01

In everyday life, speech is accompanied by gestures. In the present study, two experiments tested the possibility that spontaneous gestures accompanying speech carry prosodic information. Experiment 1 showed that gestures provide prosodic information, as adults are able to perceive the congruency between low-pass filtered—thus unintelligible—speech and the gestures of the speaker. Experiment 2 shows that in the case of ambiguous sentences (i.e., sentences with two alternative meanings depending on their prosody) mismatched prosody and gestures lead participants to choose more often the meaning signaled by gestures. Our results demonstrate that the prosody that characterizes speech is not a modality specific phenomenon: it is also perceived in the spontaneous gestures that accompany speech. We draw the conclusion that spontaneous gestures and speech form a single communication system where the suprasegmental aspects of spoken language are mapped to the motor-programs responsible for the production of both speech sounds and hand gestures. PMID:25071666

The impact of iconic gestures on foreign language word learning and its neural substrate.

PubMed

Macedonia, Manuela; Müller, Karsten; Friederici, Angela D

2011-06-01

Vocabulary acquisition represents a major challenge in foreign language learning. Research has demonstrated that gestures accompanying speech have an impact on memory for verbal information in the speakers' mother tongue and, as recently shown, also in foreign language learning. However, the neural basis of this effect remains unclear. In a within-subjects design, we compared learning of novel words coupled with iconic and meaningless gestures. Iconic gestures helped learners to significantly better retain the verbal material over time. After the training, participants' brain activity was registered by means of fMRI while performing a word recognition task. Brain activations to words learned with iconic and with meaningless gestures were contrasted. We found activity in the premotor cortices for words encoded with iconic gestures. In contrast, words encoded with meaningless gestures elicited a network associated with cognitive control. These findings suggest that memory performance for newly learned words is not driven by the motor component as such, but by the motor image that matches an underlying representation of the word's semantics. Copyright © 2010 Wiley-Liss, Inc.

Comprehension of Co-Speech Gestures in Aphasic Patients: An Eye Movement Study.

PubMed

Eggenberger, Noëmi; Preisig, Basil C; Schumacher, Rahel; Hopfner, Simone; Vanbellingen, Tim; Nyffeler, Thomas; Gutbrod, Klemens; Annoni, Jean-Marie; Bohlhalter, Stephan; Cazzoli, Dario; Müri, René M

2016-01-01

Co-speech gestures are omnipresent and a crucial element of human interaction by facilitating language comprehension. However, it is unclear whether gestures also support language comprehension in aphasic patients. Using visual exploration behavior analysis, the present study aimed to investigate the influence of congruence between speech and co-speech gestures on comprehension in terms of accuracy in a decision task. Twenty aphasic patients and 30 healthy controls watched videos in which speech was either combined with meaningless (baseline condition), congruent, or incongruent gestures. Comprehension was assessed with a decision task, while remote eye-tracking allowed analysis of visual exploration. In aphasic patients, the incongruent condition resulted in a significant decrease of accuracy, while the congruent condition led to a significant increase in accuracy compared to baseline accuracy. In the control group, the incongruent condition resulted in a decrease in accuracy, while the congruent condition did not significantly increase the accuracy. Visual exploration analysis showed that patients fixated significantly less on the face and tended to fixate more on the gesturing hands compared to controls. Co-speech gestures play an important role for aphasic patients as they modulate comprehension. Incongruent gestures evoke significant interference and deteriorate patients' comprehension. In contrast, congruent gestures enhance comprehension in aphasic patients, which might be valuable for clinical and therapeutic purposes.

Communication for coordination: gesture kinematics and conventionality affect synchronization success in piano duos.

PubMed

Bishop, Laura; Goebl, Werner

2017-07-21

Ensemble musicians often exchange visual cues in the form of body gestures (e.g., rhythmic head nods) to help coordinate piece entrances. These cues must communicate beats clearly, especially if the piece requires interperformer synchronization of the first chord. This study aimed to (1) replicate prior findings suggesting that points of peak acceleration in head gestures communicate beat position and (2) identify the kinematic features of head gestures that encourage successful synchronization. It was expected that increased precision of the alignment between leaders' head gestures and first note onsets, increased gesture smoothness, magnitude, and prototypicality, and increased leader ensemble/conducting experience would improve gesture synchronizability. Audio/MIDI and motion capture recordings were made of piano duos performing short musical passages under assigned leader/follower conditions. The leader of each trial listened to a particular tempo over headphones, then cued their partner in at the given tempo, without speaking. A subset of motion capture recordings were then presented as point-light videos with corresponding audio to a sample of musicians who tapped in synchrony with the beat. Musicians were found to align their first taps with the period of deceleration following acceleration peaks in leaders' head gestures, suggesting that acceleration patterns communicate beat position. Musicians' synchronization with leaders' first onsets improved as cueing gesture smoothness and magnitude increased and prototypicality decreased. Synchronization was also more successful with more experienced leaders' gestures. These results might be applied to interactive systems using gesture recognition or reproduction for music-making tasks (e.g., intelligent accompaniment systems).

Real-Time Control of an Exoskeleton Hand Robot with Myoelectric Pattern Recognition.

PubMed

Lu, Zhiyuan; Chen, Xiang; Zhang, Xu; Tong, Kay-Yu; Zhou, Ping

2017-08-01

Robot-assisted training provides an effective approach to neurological injury rehabilitation. To meet the challenge of hand rehabilitation after neurological injuries, this study presents an advanced myoelectric pattern recognition scheme for real-time intention-driven control of a hand exoskeleton. The developed scheme detects and recognizes user's intention of six different hand motions using four channels of surface electromyography (EMG) signals acquired from the forearm and hand muscles, and then drives the exoskeleton to assist the user accomplish the intended motion. The system was tested with eight neurologically intact subjects and two individuals with spinal cord injury (SCI). The overall control accuracy was [Formula: see text] for the neurologically intact subjects and [Formula: see text] for the SCI subjects. The total lag of the system was approximately 250[Formula: see text]ms including data acquisition, transmission and processing. One SCI subject also participated in training sessions in his second and third visits. Both the control accuracy and efficiency tended to improve. These results show great potential for applying the advanced myoelectric pattern recognition control of the wearable robotic hand system toward improving hand function after neurological injuries.

Gesture helps learners learn, but not merely by guiding their visual attention.

PubMed

Wakefield, Elizabeth; Novack, Miriam A; Congdon, Eliza L; Franconeri, Steven; Goldin-Meadow, Susan

2018-04-16

Teaching a new concept through gestures-hand movements that accompany speech-facilitates learning above-and-beyond instruction through speech alone (e.g., Singer & Goldin-Meadow, ). However, the mechanisms underlying this phenomenon are still under investigation. Here, we use eye tracking to explore one often proposed mechanism-gesture's ability to direct visual attention. Behaviorally, we replicate previous findings: Children perform significantly better on a posttest after learning through Speech+Gesture instruction than through Speech Alone instruction. Using eye tracking measures, we show that children who watch a math lesson with gesture do allocate their visual attention differently from children who watch a math lesson without gesture-they look more to the problem being explained, less to the instructor, and are more likely to synchronize their visual attention with information presented in the instructor's speech (i.e., follow along with speech) than children who watch the no-gesture lesson. The striking finding is that, even though these looking patterns positively predict learning outcomes, the patterns do not mediate the effects of training condition (Speech Alone vs. Speech+Gesture) on posttest success. We find instead a complex relation between gesture and visual attention in which gesture moderates the impact of visual looking patterns on learning-following along with speech predicts learning for children in the Speech+Gesture condition, but not for children in the Speech Alone condition. Gesture's beneficial effects on learning thus come not merely from its ability to guide visual attention, but also from its ability to synchronize with speech and affect what learners glean from that speech. © 2018 John Wiley & Sons Ltd.

Towards Gesture-Based Multi-User Interactions in Collaborative Virtual Environments

NASA Astrophysics Data System (ADS)

Pretto, N.; Poiesi, F.

2017-11-01

We present a virtual reality (VR) setup that enables multiple users to participate in collaborative virtual environments and interact via gestures. A collaborative VR session is established through a network of users that is composed of a server and a set of clients. The server manages the communication amongst clients and is created by one of the users. Each user's VR setup consists of a Head Mounted Display (HMD) for immersive visualisation, a hand tracking system to interact with virtual objects and a single-hand joypad to move in the virtual environment. We use Google Cardboard as a HMD for the VR experience and a Leap Motion for hand tracking, thus making our solution low cost. We evaluate our VR setup though a forensics use case, where real-world objects pertaining to a simulated crime scene are included in a VR environment, acquired using a smartphone-based 3D reconstruction pipeline. Users can interact using virtual gesture-based tools such as pointers and rulers.

Gestures, vocalizations, and memory in language origins.

PubMed

Aboitiz, Francisco

2012-01-01

THIS ARTICLE DISCUSSES THE POSSIBLE HOMOLOGIES BETWEEN THE HUMAN LANGUAGE NETWORKS AND COMPARABLE AUDITORY PROJECTION SYSTEMS IN THE MACAQUE BRAIN, IN AN ATTEMPT TO RECONCILE TWO EXISTING VIEWS ON LANGUAGE EVOLUTION: one that emphasizes hand control and gestures, and the other that emphasizes auditory-vocal mechanisms. The capacity for language is based on relatively well defined neural substrates whose rudiments have been traced in the non-human primate brain. At its core, this circuit constitutes an auditory-vocal sensorimotor circuit with two main components, a "ventral pathway" connecting anterior auditory regions with anterior ventrolateral prefrontal areas, and a "dorsal pathway" connecting auditory areas with parietal areas and with posterior ventrolateral prefrontal areas via the arcuate fasciculus and the superior longitudinal fasciculus. In humans, the dorsal circuit is especially important for phonological processing and phonological working memory, capacities that are critical for language acquisition and for complex syntax processing. In the macaque, the homolog of the dorsal circuit overlaps with an inferior parietal-premotor network for hand and gesture selection that is under voluntary control, while vocalizations are largely fixed and involuntary. The recruitment of the dorsal component for vocalization behavior in the human lineage, together with a direct cortical control of the subcortical vocalizing system, are proposed to represent a fundamental innovation in human evolution, generating an inflection point that permitted the explosion of vocal language and human communication. In this context, vocal communication and gesturing have a common history in primate communication.

Gesture Interaction Browser-Based 3D Molecular Viewer.

PubMed

Virag, Ioan; Stoicu-Tivadar, Lăcrămioara; Crişan-Vida, Mihaela

2016-01-01

The paper presents an open source system that allows the user to interact with a 3D molecular viewer using associated hand gestures for rotating, scaling and panning the rendered model. The novelty of this approach is that the entire application is browser-based and doesn't require installation of third party plug-ins or additional software components in order to visualize the supported chemical file formats. This kind of solution is suitable for instruction of users in less IT oriented environments, like medicine or chemistry. For rendering various molecular geometries our team used GLmol (a molecular viewer written in JavaScript). The interaction with the 3D models is made with Leap Motion controller that allows real-time tracking of the user's hand gestures. The first results confirmed that the resulting application leads to a better way of understanding various types of translational bioinformatics related problems in both biomedical research and education.

Comprehension of Co-Speech Gestures in Aphasic Patients: An Eye Movement Study

PubMed Central

Eggenberger, Noëmi; Preisig, Basil C.; Schumacher, Rahel; Hopfner, Simone; Vanbellingen, Tim; Nyffeler, Thomas; Gutbrod, Klemens; Annoni, Jean-Marie; Bohlhalter, Stephan; Cazzoli, Dario; Müri, René M.

2016-01-01

Background Co-speech gestures are omnipresent and a crucial element of human interaction by facilitating language comprehension. However, it is unclear whether gestures also support language comprehension in aphasic patients. Using visual exploration behavior analysis, the present study aimed to investigate the influence of congruence between speech and co-speech gestures on comprehension in terms of accuracy in a decision task. Method Twenty aphasic patients and 30 healthy controls watched videos in which speech was either combined with meaningless (baseline condition), congruent, or incongruent gestures. Comprehension was assessed with a decision task, while remote eye-tracking allowed analysis of visual exploration. Results In aphasic patients, the incongruent condition resulted in a significant decrease of accuracy, while the congruent condition led to a significant increase in accuracy compared to baseline accuracy. In the control group, the incongruent condition resulted in a decrease in accuracy, while the congruent condition did not significantly increase the accuracy. Visual exploration analysis showed that patients fixated significantly less on the face and tended to fixate more on the gesturing hands compared to controls. Conclusion Co-speech gestures play an important role for aphasic patients as they modulate comprehension. Incongruent gestures evoke significant interference and deteriorate patients’ comprehension. In contrast, congruent gestures enhance comprehension in aphasic patients, which might be valuable for clinical and therapeutic purposes. PMID:26735917

Gestural communication in young gorillas (Gorilla gorilla): gestural repertoire, learning, and use.

PubMed

Pika, Simone; Liebal, Katja; Tomasello, Michael

2003-07-01

In the present study we investigated the gestural communication of gorillas (Gorilla gorilla). The subjects were 13 gorillas (1-6 years old) living in two different groups in captivity. Our goal was to compile the gestural repertoire of subadult gorillas, with a special focus on processes of social cognition, including attention to individual and developmental variability, group variability, and flexibility of use. Thirty-three different gestures (six auditory, 11 tactile, and 16 visual gestures) were recorded. We found idiosyncratic gestures, individual differences, and similar degrees of concordance between and within groups, as well as some group-specific gestures. These results provide evidence that ontogenetic ritualization is the main learning process involved, but some form of social learning may also be responsible for the acquisition of special gestures. The present study establishes that gorillas have a multifaceted gestural repertoire, characterized by a great deal of flexibility with accommodations to various communicative circumstances, including the attentional state of the recipient. The possibility of assigning Seyfarth and Cheney's [1997] model for nonhuman primate vocal development to the development of nonhuman primate gestural communication is discussed. Copyright 2003 Wiley-Liss, Inc.

Enrichment Effects of Gestures and Pictures on Abstract Words in a Second Language.

PubMed

Repetto, Claudia; Pedroli, Elisa; Macedonia, Manuela

2017-01-01

Laboratory research has demonstrated that multisensory enrichment promotes verbal learning in a foreign language (L2). Enrichment can be done in various ways, e.g., by adding a picture that illustrates the L2 word's meaning or by the learner performing a gesture to the word (enactment). Most studies have tested enrichment on concrete but not on abstract words. Unlike concrete words, the representation of abstract words is deprived of sensory-motor features. This has been addressed as one of the reasons why abstract words are difficult to remember. Here, we ask whether a brief enrichment training by means of pictures and by self-performed gestures also enhances the memorability of abstract words in L2. Further, we explore which of these two enrichment strategies is more effective. Twenty young adults learned 30 novel abstract words in L2 according to three encoding conditions: (1) reading, (2) reading and pairing the novel word to a picture, and (3) reading and enacting the word by means of a gesture. We measured memory performance in free and cued recall tests, as well as in a visual recognition task. Words encoded with gestures were better remembered in the free recall in the native language (L1). When recognizing the novel words, participants made less errors for words encoded with gestures compared to words encoded with pictures. The reaction times in the recognition task did not differ across conditions. The present findings support, even if only partially, the idea that enactment promotes learning of abstract words and that it is superior to enrichment by means of pictures even after short training.

Enrichment Effects of Gestures and Pictures on Abstract Words in a Second Language

PubMed Central

Repetto, Claudia; Pedroli, Elisa; Macedonia, Manuela

2017-01-01

Laboratory research has demonstrated that multisensory enrichment promotes verbal learning in a foreign language (L2). Enrichment can be done in various ways, e.g., by adding a picture that illustrates the L2 word’s meaning or by the learner performing a gesture to the word (enactment). Most studies have tested enrichment on concrete but not on abstract words. Unlike concrete words, the representation of abstract words is deprived of sensory-motor features. This has been addressed as one of the reasons why abstract words are difficult to remember. Here, we ask whether a brief enrichment training by means of pictures and by self-performed gestures also enhances the memorability of abstract words in L2. Further, we explore which of these two enrichment strategies is more effective. Twenty young adults learned 30 novel abstract words in L2 according to three encoding conditions: (1) reading, (2) reading and pairing the novel word to a picture, and (3) reading and enacting the word by means of a gesture. We measured memory performance in free and cued recall tests, as well as in a visual recognition task. Words encoded with gestures were better remembered in the free recall in the native language (L1). When recognizing the novel words, participants made less errors for words encoded with gestures compared to words encoded with pictures. The reaction times in the recognition task did not differ across conditions. The present findings support, even if only partially, the idea that enactment promotes learning of abstract words and that it is superior to enrichment by means of pictures even after short training. PMID:29326617

Grids and Gestures: A Comics Making Exercise

ERIC Educational Resources Information Center

Sousanis, Nick

2015-01-01

Grids and Gestures is an exercise intended to offer participants insight into a comics maker's decision-making process for composing the entire page through the hands-on activity of making an abstract comic. It requires no prior drawing experience and serves to help reexamine what it means to draw. In addition to a description of how to proceed…

Self-Recognition in Autistic Children.

ERIC Educational Resources Information Center

Dawson, Geraldine; McKissick, Fawn Celeste

1984-01-01

Fifteen autistic children (four to six years old) were assessed for visual self-recognition ability, as well as for object permanence and gestural imitation. It was found that 13 of 15 autistic children showed evidence of self-recognition. Consistent relationships were suggested between self-cognition and object permanence but not between…

Development of Pointing Gestures in Children With Typical and Delayed Language Acquisition.

PubMed

Lüke, Carina; Ritterfeld, Ute; Grimminger, Angela; Liszkowski, Ulf; Rohlfing, Katharina J

2017-11-09

This longitudinal study compared the development of hand and index-finger pointing in children with typical language development (TD) and children with language delay (LD). First, we examined whether the number and the form of pointing gestures during the second year of life are potential indicators of later LD. Second, we analyzed the influence of caregivers' gestural and verbal input on children's communicative development. Thirty children with TD and 10 children with LD were observed together with their primary caregivers in a seminatural setting in 5 sessions between the ages of 12 and 21 months. Language skills were assessed at 24 months. Compared with children with TD, children with LD used fewer index-finger points at 12 and 14 months but more pointing gestures in total at 21 months. There were no significant differences in verbal or gestural input between caregivers of children with or without LD. Using more index-finger points at the beginning of the second year of life is associated with TD, whereas using more pointing gestures at the end of the second year of life is associated with delayed acquisition. Neither the verbal nor gestural input of caregivers accounted for differences in children's skills.

Repetitive transcranial magnetic stimulation of Broca's area affects verbal responses to gesture observation.

PubMed

Gentilucci, Maurizio; Bernardis, Paolo; Crisi, Girolamo; Dalla Volta, Riccardo

2006-07-01

The aim of the present study was to determine whether Broca's area is involved in translating some aspects of arm gesture representations into mouth articulation gestures. In Experiment 1, we applied low-frequency repetitive transcranial magnetic stimulation over Broca's area and over the symmetrical loci of the right hemisphere of participants responding verbally to communicative spoken words, to gestures, or to the simultaneous presentation of the two signals. We performed also sham stimulation over the left stimulation loci. In Experiment 2, we performed the same stimulations as in Experiment 1 to participants responding with words congruent and incongruent with gestures. After sham stimulation voicing parameters were enhanced when responding to communicative spoken words or to gestures as compared to a control condition of word reading. This effect increased when participants responded to the simultaneous presentation of both communicative signals. In contrast, voicing was interfered when the verbal responses were incongruent with gestures. The left stimulation neither induced enhancement on voicing parameters of words congruent with gestures nor interference on words incongruent with gestures. We interpreted the enhancement of the verbal response to gesturing in terms of intention to interact directly. Consequently, we proposed that Broca's area is involved in the process of translating into speech aspects concerning the social intention coded by the gesture. Moreover, we discussed the results in terms of evolution to support the theory [Corballis, M. C. (2002). From hand to mouth: The origins of language. Princeton, NJ: Princeton University Press] proposing spoken language as evolved from an ancient communication system using arm gestures.

Rising tones and rustling noises: Metaphors in gestural depictions of sounds

PubMed Central

Scurto, Hugo; Françoise, Jules; Bevilacqua, Frédéric; Houix, Olivier; Susini, Patrick

2017-01-01

Communicating an auditory experience with words is a difficult task and, in consequence, people often rely on imitative non-verbal vocalizations and gestures. This work explored the combination of such vocalizations and gestures to communicate auditory sensations and representations elicited by non-vocal everyday sounds. Whereas our previous studies have analyzed vocal imitations, the present research focused on gestural depictions of sounds. To this end, two studies investigated the combination of gestures and non-verbal vocalizations. A first, observational study examined a set of vocal and gestural imitations of recordings of sounds representative of a typical everyday environment (ecological sounds) with manual annotations. A second, experimental study used non-ecological sounds whose parameters had been specifically designed to elicit the behaviors highlighted in the observational study, and used quantitative measures and inferential statistics. The results showed that these depicting gestures are based on systematic analogies between a referent sound, as interpreted by a receiver, and the visual aspects of the gestures: auditory-visual metaphors. The results also suggested a different role for vocalizations and gestures. Whereas the vocalizations reproduce all features of the referent sounds as faithfully as vocally possible, the gestures focus on one salient feature with metaphors based on auditory-visual correspondences. Both studies highlighted two metaphors consistently shared across participants: the spatial metaphor of pitch (mapping different pitches to different positions on the vertical dimension), and the rustling metaphor of random fluctuations (rapidly shaking of hands and fingers). We interpret these metaphors as the result of two kinds of representations elicited by sounds: auditory sensations (pitch and loudness) mapped to spatial position, and causal representations of the sound sources (e.g. rain drops, rustling leaves) pantomimed and

Adaptive Local Spatiotemporal Features from RGB-D Data for One-Shot Learning Gesture Recognition.

PubMed

Lin, Jia; Ruan, Xiaogang; Yu, Naigong; Yang, Yee-Hong

2016-12-17

Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF) using fused RGB-D data is proposed. First, motion regions of interest (MRoIs) are adaptively extracted using grayscale and depth velocity variance information to greatly reduce the impact of noise. Then, corners are used as keypoints if their depth, and velocities of grayscale and of depth meet several adaptive local constraints in each MRoI. With further filtering of noise, an accurate and sufficient number of keypoints is obtained within the desired moving body parts (MBPs). Finally, four kinds of multiple descriptors are calculated and combined in extended gradient and motion spaces to represent the appearance and motion features of gestures. The experimental results on the ChaLearn gesture, CAD-60 and MSRDailyActivity3D datasets demonstrate that the proposed feature achieves higher performance compared with published state-of-the-art approaches under the one-shot learning setting and comparable accuracy under the leave-one-out cross validation.

Priming Gestures with Sounds

PubMed Central

Lemaitre, Guillaume; Heller, Laurie M.; Navolio, Nicole; Zúñiga-Peñaranda, Nicolas

2015-01-01

We report a series of experiments about a little-studied type of compatibility effect between a stimulus and a response: the priming of manual gestures via sounds associated with these gestures. The goal was to investigate the plasticity of the gesture-sound associations mediating this type of priming. Five experiments used a primed choice-reaction task. Participants were cued by a stimulus to perform response gestures that produced response sounds; those sounds were also used as primes before the response cues. We compared arbitrary associations between gestures and sounds (key lifts and pure tones) created during the experiment (i.e. no pre-existing knowledge) with ecological associations corresponding to the structure of the world (tapping gestures and sounds, scraping gestures and sounds) learned through the entire life of the participant (thus existing prior to the experiment). Two results were found. First, the priming effect exists for ecological as well as arbitrary associations between gestures and sounds. Second, the priming effect is greatly reduced for ecologically existing associations and is eliminated for arbitrary associations when the response gesture stops producing the associated sounds. These results provide evidence that auditory-motor priming is mainly created by rapid learning of the association between sounds and the gestures that produce them. Auditory-motor priming is therefore mediated by short-term associations between gestures and sounds that can be readily reconfigured regardless of prior knowledge. PMID:26544884

Gesturing during mental problem solving reduces eye movements, especially for individuals with lower visual working memory capacity.

PubMed

Pouw, Wim T J L; Mavilidi, Myrto-Foteini; van Gog, Tamara; Paas, Fred

2016-08-01

Non-communicative hand gestures have been found to benefit problem-solving performance. These gestures seem to compensate for limited internal cognitive capacities, such as visual working memory capacity. Yet, it is not clear how gestures might perform this cognitive function. One hypothesis is that gesturing is a means to spatially index mental simulations, thereby reducing the need for visually projecting the mental simulation onto the visual presentation of the task. If that hypothesis is correct, less eye movements should be made when participants gesture during problem solving than when they do not gesture. We therefore used mobile eye tracking to investigate the effect of co-thought gesturing and visual working memory capacity on eye movements during mental solving of the Tower of Hanoi problem. Results revealed that gesturing indeed reduced the number of eye movements (lower saccade counts), especially for participants with a relatively lower visual working memory capacity. Subsequent problem-solving performance was not affected by having (not) gestured during the mental solving phase. The current findings suggest that our understanding of gestures in problem solving could be improved by taking into account eye movements during gesturing.

Universal brain systems for recognizing word shapes and handwriting gestures during reading

PubMed Central

Nakamura, Kimihiro; Kuo, Wen-Jui; Pegado, Felipe; Cohen, Laurent; Tzeng, Ovid J. L.; Dehaene, Stanislas

2012-01-01

Do the neural circuits for reading vary across culture? Reading of visually complex writing systems such as Chinese has been proposed to rely on areas outside the classical left-hemisphere network for alphabetic reading. Here, however, we show that, once potential confounds in cross-cultural comparisons are controlled for by presenting handwritten stimuli to both Chinese and French readers, the underlying network for visual word recognition may be more universal than previously suspected. Using functional magnetic resonance imaging in a semantic task with words written in cursive font, we demonstrate that two universal circuits, a shape recognition system (reading by eye) and a gesture recognition system (reading by hand), are similarly activated and show identical patterns of activation and repetition priming in the two language groups. These activations cover most of the brain regions previously associated with culture-specific tuning. Our results point to an extended reading network that invariably comprises the occipitotemporal visual word-form system, which is sensitive to well-formed static letter strings, and a distinct left premotor region, Exner’s area, which is sensitive to the forward or backward direction with which cursive letters are dynamically presented. These findings suggest that cultural effects in reading merely modulate a fixed set of invariant macroscopic brain circuits, depending on surface features of orthographies. PMID:23184998

Shared processing of planning articulatory gestures and grasping.

PubMed

Vainio, L; Tiainen, M; Tiippana, K; Vainio, M

2014-07-01

It has been proposed that articulatory gestures are shaped by tight integration in planning mouth and hand acts. This hypothesis is supported by recent behavioral evidence showing that response selection between the precision and power grip is systematically influenced by simultaneous articulation of a syllable. For example, precision grip responses are performed relatively fast when the syllable articulation employs the tongue tip (e.g., [te]), whereas power grip responses are performed relatively fast when the syllable articulation employs the tongue body (e.g., [ke]). However, this correspondence effect, and other similar effects that demonstrate the interplay between grasping and articulatory gestures, has been found when the grasping is performed during overt articulation. The present study demonstrates that merely reading the syllables silently (Experiment 1) or hearing them (Experiment 2) results in a similar correspondence effect. The results suggest that the correspondence effect is based on integration in planning articulatory gestures and grasping rather than requiring an overt articulation of the syllables. We propose that this effect reflects partially overlapped planning of goal shapes of the two distal effectors: a vocal tract shape for articulation and a hand shape for grasping. In addition, the paper shows a pitch-grip correspondence effect in which the precision grip is associated with a high-pitched vocalization of the auditory stimuli and the power grip is associated with a low-pitched vocalization. The underlying mechanisms of this phenomenon are discussed in relation to the articulation-grip correspondence.

On the origins of human handedness and language: a comparative review of hand preferences for bimanual coordinated actions and gestural communication in nonhuman primates.

PubMed

Meguerditchian, Adrien; Vauclair, Jacques; Hopkins, William D

2013-09-01

Within the evolutionary framework about the origin of human handedness and hemispheric specialization for language, the question of expression of population-level manual biases in nonhuman primates and their potential continuities with humans remains controversial. Nevertheless, there is a growing body of evidence showing consistent population-level handedness particularly for complex manual behaviors in both monkeys and apes. In the present article, within a large comparative approach among primates, we will review our contribution to the field and the handedness literature related to two particular sophisticated manual behaviors regarding their potential and specific implications for the origins of hemispheric specialization in humans: bimanual coordinated actions and gestural communication. Whereas bimanual coordinated actions seem to elicit predominance of left-handedness in arboreal primates and of right-handedness in terrestrial primates, all handedness studies that have investigated gestural communication in several primate species have reported stronger degree of population-level right-handedness compared to noncommunicative actions. Communicative gestures and bimanual actions seem to affect differently manual asymmetries in both human and nonhuman primates and to be related to different lateralized brain substrates. We will discuss (1) how the data of hand preferences for bimanual coordinated actions highlight the role of ecological factors in the evolution of handedness and provide additional support the postural origin theory of handedness proposed by MacNeilage [MacNeilage [2007]. Present status of the postural origins theory. In W. D. Hopkins (Ed.), The evolution of hemispheric specialization in primates (pp. 59-91). London: Elsevier/Academic Press] and (2) the hypothesis that the emergence of gestural communication might have affected lateralization in our ancestor and may constitute the precursors of the hemispheric specialization for language. �

Glove-talk II - a neural-network interface which maps gestures to parallel formant speech synthesizer controls.

PubMed

Fels, S S; Hinton, G E

1997-01-01

Glove-Talk II is a system which translates hand gestures to speech through an adaptive interface. Hand gestures are mapped continuously to ten control parameters of a parallel formant speech synthesizer. The mapping allows the hand to act as an artificial vocal tract that produces speech in real time. This gives an unlimited vocabulary in addition to direct control of fundamental frequency and volume. Currently, the best version of Glove-Talk II uses several input devices, a parallel formant speech synthesizer, and three neural networks. The gesture-to-speech task is divided into vowel and consonant production by using a gating network to weight the outputs of a vowel and a consonant neural network. The gating network and the consonant network are trained with examples from the user. The vowel network implements a fixed user-defined relationship between hand position and vowel sound and does not require any training examples from the user. Volume, fundamental frequency, and stop consonants are produced with a fixed mapping from the input devices. With Glove-Talk II, the subject can speak slowly but with far more natural sounding pitch variations than a text-to-speech synthesizer.

A natural approach to convey numerical digits using hand activity recognition based on hand shape features

NASA Astrophysics Data System (ADS)

Chidananda, H.; Reddy, T. Hanumantha

2017-06-01

This paper presents a natural representation of numerical digit(s) using hand activity analysis based on number of fingers out stretched for each numerical digit in sequence extracted from a video. The analysis is based on determining a set of six features from a hand image. The most important features used from each frame in a video are the first fingertip from top, palm-line, palm-center, valley points between the fingers exists above the palm-line. Using this work user can convey any number of numerical digits using right or left or both the hands naturally in a video. Each numerical digit ranges from 0 to9. Hands (right/left/both) used to convey digits can be recognized accurately using the valley points and with this recognition whether the user is a right / left handed person in practice can be analyzed. In this work, first the hand(s) and face parts are detected by using YCbCr color space and face part is removed by using ellipse based method. Then, the hand(s) are analyzed to recognize the activity that represents a series of numerical digits in a video. This work uses pixel continuity algorithm using 2D coordinate geometry system and does not use regular use of calculus, contours, convex hull and datasets.

Person and gesture tracking with smart stereo cameras

NASA Astrophysics Data System (ADS)

Gordon, Gaile; Chen, Xiangrong; Buck, Ron

2008-02-01

Physical security increasingly involves sophisticated, real-time visual tracking of a person's location inside a given environment, often in conjunction with biometrics and other security-related technologies. However, demanding real-world conditions like crowded rooms, changes in lighting and physical obstructions have proved incredibly challenging for 2D computer vision technology. In contrast, 3D imaging technology is not affected by constant changes in lighting and apparent color, and thus allows tracking accuracy to be maintained in dynamically lit environments. In addition, person tracking with a 3D stereo camera can provide the location and movement of each individual very precisely, even in a very crowded environment. 3D vision only requires that the subject be partially visible to a single stereo camera to be correctly tracked; multiple cameras are used to extend the system's operational footprint, and to contend with heavy occlusion. A successful person tracking system, must not only perform visual analysis robustly, but also be small, cheap and consume relatively little power. The TYZX Embedded 3D Vision systems are perfectly suited to provide the low power, small footprint, and low cost points required by these types of volume applications. Several security-focused organizations, including the U.S Government, have deployed TYZX 3D stereo vision systems in security applications. 3D image data is also advantageous in the related application area of gesture tracking. Visual (uninstrumented) tracking of natural hand gestures and movement provides new opportunities for interactive control including: video gaming, location based entertainment, and interactive displays. 2D images have been used to extract the location of hands within a plane, but 3D hand location enables a much broader range of interactive applications. In this paper, we provide some background on the TYZX smart stereo cameras platform, describe the person tracking and gesture tracking systems

Using our hands to change our minds

PubMed Central

Goldin-Meadow, Susan

2015-01-01

Jean Piaget was a master at observing the routine behaviors children produce as they go from knowing less to knowing more about at a task, and making inferences not only about how children understand the task at each point, but also about how they progress from one point to the next. This paper examines a routine behavior that Piaget overlooked–the spontaneous gestures speakers produce as they explain their solutions to a problem. These gestures are not mere hand waving. They reflect ideas that the speaker has about the problem, often ideas that are not found in that speaker's talk. Gesture can do more than reflect ideas–it can also change them. Observing the gestures that others produce can change a learner's ideas, as can producing one's own gestures. In this sense, gesture behaves like any other action. But gesture differs from many other actions in that it also promotes generalization of new ideas. Gesture represents the world rather than directly manipulating the world (gesture does not move objects around) and is thus a special kind of action. As a result, the mechanisms by which gesture and action promote learning may differ. Because it is both an action and a representation, gesture can serve as a bridge between the two and thus be a powerful tool for learning abstract ideas. PMID:27906502

Gesture Facilitates Children's Creative Thinking.

PubMed

Kirk, Elizabeth; Lewis, Carine

2017-02-01

Gestures help people think and can help problem solvers generate new ideas. We conducted two experiments exploring the self-oriented function of gesture in a novel domain: creative thinking. In Experiment 1, we explored the relationship between children's spontaneous gesture production and their ability to generate novel uses for everyday items (alternative-uses task). There was a significant correlation between children's creative fluency and their gesture production, and the majority of children's gestures depicted an action on the target object. Restricting children from gesturing did not significantly reduce their fluency, however. In Experiment 2, we encouraged children to gesture, and this significantly boosted their generation of creative ideas. These findings demonstrate that gestures serve an important self-oriented function and can assist creative thinking.

The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping.

PubMed

Bahlmann, Claus; Burkhardt, Hans

2004-03-01

In this paper, we give a comprehensive description of our writer-independent online handwriting recognition system frog on hand. The focus of this work concerns the presentation of the classification/training approach, which we call cluster generative statistical dynamic time warping (CSDTW). CSDTW is a general, scalable, HMM-based method for variable-sized, sequential data that holistically combines cluster analysis and statistical sequence modeling. It can handle general classification problems that rely on this sequential type of data, e.g., speech recognition, genome processing, robotics, etc. Contrary to previous attempts, clustering and statistical sequence modeling are embedded in a single feature space and use a closely related distance measure. We show character recognition experiments of frog on hand using CSDTW on the UNIPEN online handwriting database. The recognition accuracy is significantly higher than reported results of other handwriting recognition systems. Finally, we describe the real-time implementation of frog on hand on a Linux Compaq iPAQ embedded device.

Adaptive Local Spatiotemporal Features from RGB-D Data for One-Shot Learning Gesture Recognition

PubMed Central

Lin, Jia; Ruan, Xiaogang; Yu, Naigong; Yang, Yee-Hong

2016-01-01

Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF) using fused RGB-D data is proposed. First, motion regions of interest (MRoIs) are adaptively extracted using grayscale and depth velocity variance information to greatly reduce the impact of noise. Then, corners are used as keypoints if their depth, and velocities of grayscale and of depth meet several adaptive local constraints in each MRoI. With further filtering of noise, an accurate and sufficient number of keypoints is obtained within the desired moving body parts (MBPs). Finally, four kinds of multiple descriptors are calculated and combined in extended gradient and motion spaces to represent the appearance and motion features of gestures. The experimental results on the ChaLearn gesture, CAD-60 and MSRDailyActivity3D datasets demonstrate that the proposed feature achieves higher performance compared with published state-of-the-art approaches under the one-shot learning setting and comparable accuracy under the leave-one-out cross validation. PMID:27999337

Grounded Blends and Mathematical Gesture Spaces: Developing Mathematical Understandings via Gestures

ERIC Educational Resources Information Center

Yoon, Caroline; Thomas, Michael O. J.; Dreyfus, Tommy

2011-01-01

This paper examines how a person's gesture space can become endowed with mathematical meaning associated with mathematical spaces and how the resulting mathematical gesture space can be used to communicate and interpret mathematical features of gestures. We use the theory of grounded blends to analyse a case study of two teachers who used gestures…

Impact of body posture on laterality judgement and explicit recognition tasks performed on self and others' hands.

PubMed

Conson, Massimiliano; Errico, Domenico; Mazzarella, Elisabetta; De Bellis, Francesco; Grossi, Dario; Trojano, Luigi

2015-04-01

Judgments on laterality of hand stimuli are faster and more accurate when dealing with one's own than others' hand, i.e. the self-advantage. This advantage seems to be related to activation of a sensorimotor mechanism while implicitly processing one's own hands, but not during explicit one's own hand recognition. Here, we specifically tested the influence of proprioceptive information on the self-hand advantage by manipulating participants' body posture during self and others' hand processing. In Experiment 1, right-handed healthy participants judged laterality of either self or others' hands, whereas in Experiment 2, an explicit recognition of one's own hands was required. In both experiments, the participants performed the task while holding their left or right arm flexed with their hand in direct contact with their chest ("flexed self-touch posture") or with their hand placed on a wooden smooth surface in correspondence with their chest ("flexed proprioceptive-only posture"). In an "extended control posture", both arms were extended and in contact with thighs. In Experiment 1 (hand laterality judgment), we confirmed the self-advantage and demonstrated that it was enhanced when the subjects judged left-hand stimuli at 270° orientation while keeping their left arm in the flexed proprioceptive-only posture. In Experiment 2 (explicit self-hand recognition), instead, we found an advantage for others' hand ("self-disadvantage") independently from posture manipulation. Thus, position-related proprioceptive information from left non-dominant arm can enhance sensorimotor one's own body representation selectively favouring implicit self-hands processing.

What Iconic Gesture Fragments Reveal about Gesture-Speech Integration: When Synchrony Is Lost, Memory Can Help

ERIC Educational Resources Information Center

Obermeier, Christian; Holle, Henning; Gunter, Thomas C.

2011-01-01

The present series of experiments explores several issues related to gesture-speech integration and synchrony during sentence processing. To be able to more precisely manipulate gesture-speech synchrony, we used gesture fragments instead of complete gestures, thereby avoiding the usual long temporal overlap of gestures with their coexpressive…

Impaired imitation of gestures in mild dementia: comparison of dementia with Lewy bodies, Alzheimer's disease and vascular dementia.

PubMed

Nagahama, Yasuhiro; Okina, Tomoko; Suzuki, Norio

2015-11-01

To examine whether imitation of gestures provided useful information to diagnose early dementia in elderly patients. Imitation of finger and hand gestures was evaluated in patients with mild dementia; 74 patients had dementia with Lewy bodies (DLB), 100 with Alzheimer's disease (AD) and 52 with subcortical vascular dementia (SVaD). Significantly, more patients with DLB (32.4%) compared with patients with AD (5%) or SVaD (11.5%) had an impaired ability to imitate finger gestures bilaterally. Also, significantly, more patients with DLB (36.5%) compared with patients with AD (5%) or SVaD (15.4%) had lower mean scores of both hands. In contrast, impairment of the imitation of bimanual gestures was comparable among the three patient groups (DLB 50%, AD 42%, SVaD 42.3%). Our study revealed that imitation of bimanual gestures was impaired non-specifically in about half of the patients with mild dementia, whereas imitation of finger gestures was significantly more impaired in patients with early DLB than in those with AD or SVaD. Although the sensitivity was not high, the imitation tasks may provide additional information for diagnosis of mild dementia, especially for DLB. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Glove-TalkII--a neural-network interface which maps gestures to parallel formant speech synthesizer controls.

PubMed

Fels, S S; Hinton, G E

1998-01-01

Glove-TalkII is a system which translates hand gestures to speech through an adaptive interface. Hand gestures are mapped continuously to ten control parameters of a parallel formant speech synthesizer. The mapping allows the hand to act as an artificial vocal tract that produces speech in real time. This gives an unlimited vocabulary in addition to direct control of fundamental frequency and volume. Currently, the best version of Glove-TalkII uses several input devices (including a Cyberglove, a ContactGlove, a three-space tracker, and a foot pedal), a parallel formant speech synthesizer, and three neural networks. The gesture-to-speech task is divided into vowel and consonant production by using a gating network to weight the outputs of a vowel and a consonant neural network. The gating network and the consonant network are trained with examples from the user. The vowel network implements a fixed user-defined relationship between hand position and vowel sound and does not require any training examples from the user. Volume, fundamental frequency, and stop consonants are produced with a fixed mapping from the input devices. One subject has trained to speak intelligibly with Glove-TalkII. He speaks slowly but with far more natural sounding pitch variations than a text-to-speech synthesizer.

RehabGesture: An Alternative Tool for Measuring Human Movement.

PubMed

Brandão, Alexandre F; Dias, Diego R C; Castellano, Gabriela; Parizotto, Nivaldo A; Trevelin, Luis Carlos

2016-07-01

Systems for range of motion (ROM) measurement such as OptoTrak, Motion Capture, Motion Analysis, Vicon, and Visual 3D are so expensive that they become impracticable in public health systems and even in private rehabilitation clinics. Telerehabilitation is a branch within telemedicine intended to offer ways to increase motor and/or cognitive stimuli, aimed at faster and more effective recovery of given disabilities, and to measure kinematic data such as the improvement in ROM. In the development of the RehabGesture tool, we used the gesture recognition sensor Kinect(®) (Microsoft, Redmond, WA) and the concepts of Natural User Interface and Open Natural Interaction. RehabGesture can measure and record the ROM during rehabilitation sessions while the user interacts with the virtual reality environment. The software allows the measurement of the ROM (in the coronal plane) from 0° extension to 145° flexion of the elbow joint, as well as from 0° adduction to 180° abduction of the glenohumeral (shoulder) joint, leaving the standing position. The proposed tool has application in the fields of training and physical evaluation of professional and amateur athletes in clubs and gyms and may have application in rehabilitation and physiotherapy clinics for patients with compromised motor abilities. RehabGesture represents a low-cost solution to measure the movement of the upper limbs, as well as to stimulate the process of teaching and learning in disciplines related to the study of human movement, such as kinesiology.

Language, Gesture, and Space.

ERIC Educational Resources Information Center

Emmorey, Karen, Ed.; Reilly, Judy S., Ed.

A collection of papers addresses a variety of issues regarding the nature and structure of sign language, gesture, and gesture systems. Articles include: "Theoretical Issues Relating Language, Gesture, and Space: An Overview" (Karen Emmorey, Judy S. Reilly); "Real, Surrogate, and Token Space: Grammatical Consequences in ASL American…

Neural integration of speech and gesture in schizophrenia: evidence for differential processing of metaphoric gestures.

PubMed

Straube, Benjamin; Green, Antonia; Sass, Katharina; Kirner-Veselinovic, André; Kircher, Tilo

2013-07-01

Gestures are an important component of interpersonal communication. Especially, complex multimodal communication is assumed to be disrupted in patients with schizophrenia. In healthy subjects, differential neural integration processes for gestures in the context of concrete [iconic (IC) gestures] and abstract sentence contents [metaphoric (MP) gestures] had been demonstrated. With this study we wanted to investigate neural integration processes for both gesture types in patients with schizophrenia. During functional magnetic resonance imaging-data acquisition, 16 patients with schizophrenia (P) and a healthy control group (C) were shown videos of an actor performing IC and MP gestures and associated sentences. An isolated gesture (G) and isolated sentence condition (S) were included to separate unimodal from bimodal effects at the neural level. During IC conditions (IC > G ∩ IC > S) we found increased activity in the left posterior middle temporal gyrus (pMTG) in both groups. Whereas in the control group the left pMTG and the inferior frontal gyrus (IFG) were activated for the MP conditions (MP > G ∩ MP > S), no significant activation was found for the identical contrast in patients. The interaction of group (P/C) and gesture condition (MP/IC) revealed activation in the bilateral hippocampus, the left middle/superior temporal and IFG. Activation of the pMTG for the IC condition in both groups indicates intact neural integration of IC gestures in schizophrenia. However, failure to activate the left pMTG and IFG for MP co-verbal gestures suggests a disturbed integration of gestures embedded in an abstract sentence context. This study provides new insight into the neural integration of co-verbal gestures in patients with schizophrenia. Copyright © 2012 Wiley Periodicals, Inc.

Hand motion modeling for psychology analysis in job interview using optical flow-history motion image: OF-HMI

NASA Astrophysics Data System (ADS)

Khalifa, Intissar; Ejbali, Ridha; Zaied, Mourad

2018-04-01

To survive the competition, companies always think about having the best employees. The selection is depended on the answers to the questions of the interviewer and the behavior of the candidate during the interview session. The study of this behavior is always based on a psychological analysis of the movements accompanying the answers and discussions. Few techniques are proposed until today to analyze automatically candidate's non verbal behavior. This paper is a part of a work psychology recognition system; it concentrates in spontaneous hand gesture which is very significant in interviews according to psychologists. We propose motion history representation of hand based on an hybrid approach that merges optical flow and history motion images. The optical flow technique is used firstly to detect hand motions in each frame of a video sequence. Secondly, we use the history motion images (HMI) to accumulate the output of the optical flow in order to have finally a good representation of the hand`s local movement in a global temporal template.

Using our hands to change our minds.

PubMed

Goldin-Meadow, Susan

2017-01-01

Jean Piaget was a master at observing the routine behaviors children produce as they go from knowing less to knowing more about at a task, and making inferences not only about how children understand the task at each point, but also about how they progress from one point to the next. This article examines a routine behavior that Piaget overlooked-the spontaneous gestures speakers produce as they explain their solutions to a problem. These gestures are not mere hand waving. They reflect ideas that the speaker has about the problem, often ideas that are not found in that speaker's talk. Gesture can do more than reflect ideas-it can also change them. Observing the gestures that others produce can change a learner's ideas, as can producing one's own gestures. In this sense, gesture behaves like any other action. But gesture differs from many other actions in that it also promotes generalization of new ideas. Gesture represents the world rather than directly manipulating the world (gesture does not move objects around) and is thus a special kind of action. As a result, the mechanisms by which gesture and action promote learning may differ. Because it is both an action and a representation, gesture can serve as a bridge between the two and thus be a powerful tool for learning abstract ideas. WIREs Cogn Sci 2017, 8:e1368. doi: 10.1002/wcs.1368 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

Recognition of surgical skills using hidden Markov models

NASA Astrophysics Data System (ADS)

Speidel, Stefanie; Zentek, Tom; Sudra, Gunther; Gehrig, Tobias; Müller-Stich, Beat Peter; Gutt, Carsten; Dillmann, Rüdiger

2009-02-01

Minimally invasive surgery is a highly complex medical discipline and can be regarded as a major breakthrough in surgical technique. A minimally invasive intervention requires enhanced motor skills to deal with difficulties like the complex hand-eye coordination and restricted mobility. To alleviate these constraints we propose to enhance the surgeon's capabilities by providing a context-aware assistance using augmented reality techniques. To recognize and analyze the current situation for context-aware assistance, we need intraoperative sensor data and a model of the intervention. Characteristics of a situation are the performed activity, the used instruments, the surgical objects and the anatomical structures. Important information about the surgical activity can be acquired by recognizing the surgical gesture performed. Surgical gestures in minimally invasive surgery like cutting, knot-tying or suturing are here referred to as surgical skills. We use the motion data from the endoscopic instruments to classify and analyze the performed skill and even use it for skill evaluation in a training scenario. The system uses Hidden Markov Models (HMM) to model and recognize a specific surgical skill like knot-tying or suturing with an average recognition rate of 92%.

A Supramodal Neural Network for Speech and Gesture Semantics: An fMRI Study

PubMed Central

Weis, Susanne; Kircher, Tilo

2012-01-01

In a natural setting, speech is often accompanied by gestures. As language, speech-accompanying iconic gestures to some extent convey semantic information. However, if comprehension of the information contained in both the auditory and visual modality depends on same or different brain-networks is quite unknown. In this fMRI study, we aimed at identifying the cortical areas engaged in supramodal processing of semantic information. BOLD changes were recorded in 18 healthy right-handed male subjects watching video clips showing an actor who either performed speech (S, acoustic) or gestures (G, visual) in more (+) or less (−) meaningful varieties. In the experimental conditions familiar speech or isolated iconic gestures were presented; during the visual control condition the volunteers watched meaningless gestures (G−), while during the acoustic control condition a foreign language was presented (S−). The conjunction of the visual and acoustic semantic processing revealed activations extending from the left inferior frontal gyrus to the precentral gyrus, and included bilateral posterior temporal regions. We conclude that proclaiming this frontotemporal network the brain's core language system is to take too narrow a view. Our results rather indicate that these regions constitute a supramodal semantic processing network. PMID:23226488

Make Gestures to Learn: Reproducing Gestures Improves the Learning of Anatomical Knowledge More than Just Seeing Gestures

PubMed Central

Cherdieu, Mélaine; Palombi, Olivier; Gerber, Silvain; Troccaz, Jocelyne; Rochet-Capellan, Amélie

2017-01-01

Manual gestures can facilitate problem solving but also language or conceptual learning. Both seeing and making the gestures during learning seem to be beneficial. However, the stronger activation of the motor system in the second case should provide supplementary cues to consolidate and re-enact the mental traces created during learning. We tested this hypothesis in the context of anatomy learning by naïve adult participants. Anatomy is a challenging topic to learn and is of specific interest for research on embodied learning, as the learning content can be directly linked to learners' body. Two groups of participants were asked to look at a video lecture on the forearm anatomy. The video included a model making gestures related to the content of the lecture. Both groups see the gestures but only one also imitate the model. Tests of knowledge were run just after learning and few days later. The results revealed that imitating gestures improves the recall of structures names and their localization on a diagram. This effect was however significant only in long-term assessments. This suggests that: (1) the integration of motor actions and knowledge may require sleep; (2) a specific activation of the motor system during learning may improve the consolidation and/or the retrieval of memories. PMID:29062287

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.

From action to abstraction: Using the hands to learn math

PubMed Central

Novack, Miriam A.; Congdon, Eliza L.; Hemani-Lopez, Naureen; Goldin-Meadow, Susan

2014-01-01

Previous research has shown that children benefit from gesturing during math instruction. Here we ask whether gesturing promotes learning because it is itself a physical action, or because it uses physical action to represent abstract ideas. To address this question, we taught third-grade children a strategy for solving mathematical equivalence problems that was instantiated in one of three ways: (1) in the physical action children performed on objects, (2) in a concrete gesture miming that action, or (3) in an abstract gesture. All three types of hand movements helped children learn how to solve the problems on which they were trained. However, only gesture led to success on problems that required generalizing the knowledge gained. The results provide the first evidence that gesture promotes transfer of knowledge better than action, and suggest that the beneficial effects gesture has on learning may reside in the features that differentiate it from action. PMID:24503873

The magic glove: a gesture-based remote controller for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Luo, Chaomin; Chen, Yue; Krishnan, Mohan; Paulik, Mark

2012-01-01

This paper describes the design of a gesture-based Human Robot Interface (HRI) for an autonomous mobile robot entered in the 2010 Intelligent Ground Vehicle Competition (IGVC). While the robot is meant to operate autonomously in the various Challenges of the competition, an HRI is useful in moving the robot to the starting position and after run termination. In this paper, a user-friendly gesture-based embedded system called the Magic Glove is developed for remote control of a robot. The system consists of a microcontroller and sensors that is worn by the operator as a glove and is capable of recognizing hand signals. These are then transmitted through wireless communication to the robot. The design of the Magic Glove included contributions on two fronts: hardware configuration and algorithm development. A triple axis accelerometer used to detect hand orientation passes the information to a microcontroller, which interprets the corresponding vehicle control command. A Bluetooth device interfaced to the microcontroller then transmits the information to the vehicle, which acts accordingly. The user-friendly Magic Glove was successfully demonstrated first in a Player/Stage simulation environment. The gesture-based functionality was then also successfully verified on an actual robot and demonstrated to judges at the 2010 IGVC.

Complementary Hand Responses Occur in Both Peri- and Extrapersonal Space.

PubMed

Faber, Tim W; van Elk, Michiel; Jonas, Kai J

2016-01-01

Human beings have a strong tendency to imitate. Evidence from motor priming paradigms suggests that people automatically tend to imitate observed actions such as hand gestures by performing mirror-congruent movements (e.g., lifting one's right finger upon observing a left finger movement; from a mirror perspective). Many observed actions however, do not require mirror-congruent responses but afford complementary (fitting) responses instead (e.g., handing over a cup; shaking hands). Crucially, whereas mirror-congruent responses don't require physical interaction with another person, complementary actions often do. Given that most experiments studying motor priming have used stimuli devoid of contextual information, this space or interaction-dependency of complementary responses has not yet been assessed. To address this issue, we let participants perform a task in which they had to mirror or complement a hand gesture (fist or open hand) performed by an actor depicted either within or outside of reach. In three studies, we observed faster reaction times and less response errors for complementary relative to mirrored hand movements in response to open hand gestures (i.e., 'hand-shaking') irrespective of the perceived interpersonal distance of the actor. This complementary effect could not be accounted for by a low-level spatial cueing effect. These results demonstrate that humans have a strong and automatic tendency to respond by performing complementary actions. In addition, our findings underline the limitations of manipulations of space in modulating effects of motor priming and the perception of affordances.

Iconic gestures prime words: comparison of priming effects when gestures are presented alone and when they are accompanying speech

PubMed Central

So, Wing-Chee; Yi-Feng, Alvan Low; Yap, De-Fu; Kheng, Eugene; Yap, Ju-Min Melvin

2013-01-01

Previous studies have shown that iconic gestures presented in an isolated manner prime visually presented semantically related words. Since gestures and speech are almost always produced together, this study examined whether iconic gestures accompanying speech would prime words and compared the priming effect of iconic gestures with speech to that of iconic gestures presented alone. Adult participants (N = 180) were randomly assigned to one of three conditions in a lexical decision task: Gestures-Only (the primes were iconic gestures presented alone); Speech-Only (the primes were auditory tokens conveying the same meaning as the iconic gestures); Gestures-Accompanying-Speech (the primes were the simultaneous coupling of iconic gestures and their corresponding auditory tokens). Our findings revealed significant priming effects in all three conditions. However, the priming effect in the Gestures-Accompanying-Speech condition was comparable to that in the Speech-Only condition and was significantly weaker than that in the Gestures-Only condition, suggesting that the facilitatory effect of iconic gestures accompanying speech may be constrained by the level of language processing required in the lexical decision task where linguistic processing of words forms is more dominant than semantic processing. Hence, the priming effect afforded by the co-speech iconic gestures was weakened. PMID:24155738

Control of a powered prosthetic device via a pinch gesture interface

NASA Astrophysics Data System (ADS)

Yetkin, Oguz; Wallace, Kristi; Sanford, Joseph D.; Popa, Dan O.

2015-06-01

A novel system is presented to control a powered prosthetic device using a gesture tracking system worn on a user's sound hand in order to detect different grasp patterns. Experiments are presented with two different gesture tracking systems: one comprised of Conductive Thimbles worn on each finger (Conductive Thimble system), and another comprised of a glove which leaves the fingers free (Conductive Glove system). Timing tests were performed on the selection and execution of two grasp patterns using the Conductive Thimble system and the iPhone app provided by the manufacturer. A modified Box and Blocks test was performed using Conductive Glove system and the iPhone app provided by Touch Bionics. The best prosthetic device performance is reported with the developed Conductive Glove system in this test. Results show that these low encumbrance gesture-based wearable systems for selecting grasp patterns may provide a viable alternative to EMG and other prosthetic control modalities, especially for new prosthetic users who are not trained in using EMG signals.

What iconic gesture fragments reveal about gesture-speech integration: when synchrony is lost, memory can help.

PubMed

Obermeier, Christian; Holle, Henning; Gunter, Thomas C

2011-07-01

The present series of experiments explores several issues related to gesture-speech integration and synchrony during sentence processing. To be able to more precisely manipulate gesture-speech synchrony, we used gesture fragments instead of complete gestures, thereby avoiding the usual long temporal overlap of gestures with their coexpressive speech. In a pretest, the minimal duration of an iconic gesture fragment needed to disambiguate a homonym (i.e., disambiguation point) was therefore identified. In three subsequent ERP experiments, we then investigated whether the gesture information available at the disambiguation point has immediate as well as delayed consequences on the processing of a temporarily ambiguous spoken sentence, and whether these gesture-speech integration processes are susceptible to temporal synchrony. Experiment 1, which used asynchronous stimuli as well as an explicit task, showed clear N400 effects at the homonym as well as at the target word presented further downstream, suggesting that asynchrony does not prevent integration under explicit task conditions. No such effects were found when asynchronous stimuli were presented using a more shallow task (Experiment 2). Finally, when gesture fragment and homonym were synchronous, similar results as in Experiment 1 were found, even under shallow task conditions (Experiment 3). We conclude that when iconic gesture fragments and speech are in synchrony, their interaction is more or less automatic. When they are not, more controlled, active memory processes are necessary to be able to combine the gesture fragment and speech context in such a way that the homonym is disambiguated correctly.

Relationship between Manual Preferences for Object Manipulation and Pointing Gestures in Infants and Toddlers

ERIC Educational Resources Information Center

Vauclair, Jacques; Imbault, Juliette

2009-01-01

The aim of this study was to measure the pattern of hand preferences for pointing gestures as a function of object-manipulation handedness in 123 infants and toddlers (10-40 months). The results showed that not only right-handers but also left-handers and ambidextrous participants tended to use their right hand for pointing. There was a…

Recognition of face identity and emotion in expressive specific language impairment.

PubMed

Merkenschlager, A; Amorosa, H; Kiefl, H; Martinius, J

2012-01-01

To study face and emotion recognition in children with mostly expressive specific language impairment (SLI-E). A test movie to study perception and recognition of faces and mimic-gestural expression was applied to 24 children diagnosed as suffering from SLI-E and an age-matched control group of normally developing children. Compared to a normal control group, the SLI-E children scored significantly worse in both the face and expression recognition tasks with a preponderant effect on emotion recognition. The performance of the SLI-E group could not be explained by reduced attention during the test session. We conclude that SLI-E is associated with a deficiency in decoding non-verbal emotional facial and gestural information, which might lead to profound and persistent problems in social interaction and development. Copyright © 2012 S. Karger AG, Basel.

Vision-based posture recognition using an ensemble classifier and a vote filter

NASA Astrophysics Data System (ADS)

Ji, Peng; Wu, Changcheng; Xu, Xiaonong; Song, Aiguo; Li, Huijun

2016-10-01

Posture recognition is a very important Human-Robot Interaction (HRI) way. To segment effective posture from an image, we propose an improved region grow algorithm which combining with the Single Gauss Color Model. The experiment shows that the improved region grow algorithm can get the complete and accurate posture than traditional Single Gauss Model and region grow algorithm, and it can eliminate the similar region from the background at the same time. In the posture recognition part, and in order to improve the recognition rate, we propose a CNN ensemble classifier, and in order to reduce the misjudgments during a continuous gesture control, a vote filter is proposed and applied to the sequence of recognition results. Comparing with CNN classifier, the CNN ensemble classifier we proposed can yield a 96.27% recognition rate, which is better than that of CNN classifier, and the proposed vote filter can improve the recognition result and reduce the misjudgments during the consecutive gesture switch.

Hand Motion Classification Using a Multi-Channel Surface Electromyography Sensor

PubMed Central

Tang, Xueyan; Liu, Yunhui; Lv, Congyi; Sun, Dong

2012-01-01

The human hand has multiple degrees of freedom (DOF) for achieving high-dexterity motions. Identifying and replicating human hand motions are necessary to perform precise and delicate operations in many applications, such as haptic applications. Surface electromyography (sEMG) sensors are a low-cost method for identifying hand motions, in addition to the conventional methods that use data gloves and vision detection. The identification of multiple hand motions is challenging because the error rate typically increases significantly with the addition of more hand motions. Thus, the current study proposes two new methods for feature extraction to solve the problem above. The first method is the extraction of the energy ratio features in the time-domain, which are robust and invariant to motion forces and speeds for the same gesture. The second method is the extraction of the concordance correlation features that describe the relationship between every two channels of the multi-channel sEMG sensor system. The concordance correlation features of a multi-channel sEMG sensor system were shown to provide a vast amount of useful information for identification. Furthermore, a new cascaded-structure classifier is also proposed, in which 11 types of hand gestures can be identified accurately using the newly defined features. Experimental results show that the success rate for the identification of the 11 gestures is significantly high. PMID:22438703

Hand motion classification using a multi-channel surface electromyography sensor.

PubMed

Tang, Xueyan; Liu, Yunhui; Lv, Congyi; Sun, Dong

2012-01-01

The human hand has multiple degrees of freedom (DOF) for achieving high-dexterity motions. Identifying and replicating human hand motions are necessary to perform precise and delicate operations in many applications, such as haptic applications. Surface electromyography (sEMG) sensors are a low-cost method for identifying hand motions, in addition to the conventional methods that use data gloves and vision detection. The identification of multiple hand motions is challenging because the error rate typically increases significantly with the addition of more hand motions. Thus, the current study proposes two new methods for feature extraction to solve the problem above. The first method is the extraction of the energy ratio features in the time-domain, which are robust and invariant to motion forces and speeds for the same gesture. The second method is the extraction of the concordance correlation features that describe the relationship between every two channels of the multi-channel sEMG sensor system. The concordance correlation features of a multi-channel sEMG sensor system were shown to provide a vast amount of useful information for identification. Furthermore, a new cascaded-structure classifier is also proposed, in which 11 types of hand gestures can be identified accurately using the newly defined features. Experimental results show that the success rate for the identification of the 11 gestures is significantly high.

What makes a movement a gesture?

PubMed

Novack, Miriam A; Wakefield, Elizabeth M; Goldin-Meadow, Susan

2016-01-01

Theories of how adults interpret the actions of others have focused on the goals and intentions of actors engaged in object-directed actions. Recent research has challenged this assumption, and shown that movements are often interpreted as being for their own sake (Schachner & Carey, 2013). Here we postulate a third interpretation of movement-movement that represents action, but does not literally act on objects in the world. These movements are gestures. In this paper, we describe a framework for predicting when movements are likely to be seen as representations. In Study 1, adults described one of three scenes: (1) an actor moving objects, (2) an actor moving her hands in the presence of objects (but not touching them) or (3) an actor moving her hands in the absence of objects. Participants systematically described the movements as depicting an object-directed action when the actor moved objects, and favored describing the movements as depicting movement for its own sake when the actor produced the same movements in the absence of objects. However, participants favored describing the movements as representations when the actor produced the movements near, but not on, the objects. Study 2 explored two additional features-the form of an actor's hands and the presence of speech-like sounds-to test the effect of context on observers' classification of movement as representational. When movements are seen as representations, they have the power to influence communication, learning, and cognition in ways that movement for its own sake does not. By incorporating representational gesture into our framework for movement analysis, we take an important step towards developing a more cohesive understanding of action-interpretation. Copyright © 2015 Elsevier B.V. All rights reserved.

Hearing and seeing meaning in speech and gesture: insights from brain and behaviour

PubMed Central

Özyürek, Aslı

2014-01-01

As we speak, we use not only the arbitrary form–meaning mappings of the speech channel but also motivated form–meaning correspondences, i.e. iconic gestures that accompany speech (e.g. inverted V-shaped hand wiggling across gesture space to demonstrate walking). This article reviews what we know about processing of semantic information from speech and iconic gestures in spoken languages during comprehension of such composite utterances. Several studies have shown that comprehension of iconic gestures involves brain activations known to be involved in semantic processing of speech: i.e. modulation of the electrophysiological recording component N400, which is sensitive to the ease of semantic integration of a word to previous context, and recruitment of the left-lateralized frontal–posterior temporal network (left inferior frontal gyrus (IFG), medial temporal gyrus (MTG) and superior temporal gyrus/sulcus (STG/S)). Furthermore, we integrate the information coming from both channels recruiting brain areas such as left IFG, posterior superior temporal sulcus (STS)/MTG and even motor cortex. Finally, this integration is flexible: the temporal synchrony between the iconic gesture and the speech segment, as well as the perceived communicative intent of the speaker, modulate the integration process. Whether these findings are special to gestures or are shared with actions or other visual accompaniments to speech (e.g. lips) or other visual symbols such as pictures are discussed, as well as the implications for a multimodal view of language. PMID:25092664

Semantic Processing of Mathematical Gestures

ERIC Educational Resources Information Center

Lim, Vanessa K.; Wilson, Anna J.; Hamm, Jeff P.; Phillips, Nicola; Iwabuchi, Sarina J.; Corballis, Michael C.; Arzarello, Ferdinando; Thomas, Michael O. J.

2009-01-01

Objective: To examine whether or not university mathematics students semantically process gestures depicting mathematical functions (mathematical gestures) similarly to the way they process action gestures and sentences. Semantic processing was indexed by the N400 effect. Results: The N400 effect elicited by words primed with mathematical gestures…

Dissociating Neural Correlates of Meaningful Emblems from Meaningless Gestures in Deaf Signers and Hearing Non-Signers

PubMed Central

Husain, Fatima T.; Patkin, Debra J.; Kim, Jieun; Braun, Allen R.; Horwitz, Barry

2012-01-01

Emblems are meaningful, culturally-specific hand gestures that are analogous to words. In this fMRI study, we contrasted the processing of emblematic gestures with meaningless gestures by pre-lingually Deaf and hearing participants. Deaf participants, who used American Sign Language, activated bilateral auditory processing and associative areas in the temporal cortex to a greater extent than the hearing participants while processing both types of gestures relative to rest. The hearing non-signers activated a diverse set of regions, including those implicated in the mirror neuron system, such as premotor cortex (BA 6) and inferior parietal lobule (BA 40) for the same contrast. Further, when contrasting the processing of meaningful to meaningless gestures (both relative to rest), the Deaf participants, but not the hearing, showed greater response in the left angular and supramarginal gyri, regions that play important roles in linguistic processing. These results suggest that whereas the signers interpreted emblems to be comparable to words, the non-signers treated emblems as similar to pictorial descriptions of the world and engaged the mirror neuron system. PMID:22968047

Developing a 3D Gestural Interface for Anesthesia-Related Human-Computer Interaction Tasks Using Both Experts and Novices.

PubMed

Jurewicz, Katherina A; Neyens, David M; Catchpole, Ken; Reeves, Scott T

2018-06-01

The purpose of this research was to compare gesture-function mappings for experts and novices using a 3D, vision-based, gestural input system when exposed to the same context of anesthesia tasks in the operating room (OR). 3D, vision-based, gestural input systems can serve as a natural way to interact with computers and are potentially useful in sterile environments (e.g., ORs) to limit the spread of bacteria. Anesthesia providers' hands have been linked to bacterial transfer in the OR, but a gestural input system for anesthetic tasks has not been investigated. A repeated-measures study was conducted with two cohorts: anesthesia providers (i.e., experts) ( N = 16) and students (i.e., novices) ( N = 30). Participants chose gestures for 10 anesthetic functions across three blocks to determine intuitive gesture-function mappings. Reaction time was collected as a complementary measure for understanding the mappings. The two gesture-function mapping sets showed some similarities and differences. The gesture mappings of the anesthesia providers showed a relationship to physical components in the anesthesia environment that were not seen in the students' gestures. The students also exhibited evidence related to longer reaction times compared to the anesthesia providers. Domain expertise is influential when creating gesture-function mappings. However, both experts and novices should be able to use a gesture system intuitively, so development methods need to be refined for considering the needs of different user groups. The development of a touchless interface for perioperative anesthesia may reduce bacterial contamination and eventually offer a reduced risk of infection to patients.

Do Parents Model Gestures Differently When Children's Gestures Differ?

ERIC Educational Resources Information Center

Özçaliskan, Seyda; Adamson, Lauren B.; Dimitrova, Nevena; Baumann, Stephanie

2018-01-01

Children with autism spectrum disorder (ASD) or with Down syndrome (DS) show diagnosis-specific differences from typically developing (TD) children in gesture production. We asked whether these differences reflect the differences in parental gesture input. Our systematic observations of 23 children with ASD and 23 with DS (M[subscript…

Thirty years of great ape gestures.

PubMed

Tomasello, Michael; Call, Josep

2018-02-21

We and our colleagues have been doing studies of great ape gestural communication for more than 30 years. Here we attempt to spell out what we have learned. Some aspects of the process have been reliably established by multiple researchers, for example, its intentional structure and its sensitivity to the attentional state of the recipient. Other aspects are more controversial. We argue here that it is a mistake to assimilate great ape gestures to the species-typical displays of other mammals by claiming that they are fixed action patterns, as there are many differences, including the use of attention-getters. It is also a mistake, we argue, to assimilate great ape gestures to human gestures by claiming that they are used referentially and declaratively in a human-like manner, as apes' "pointing" gesture has many limitations and they do not gesture iconically. Great ape gestures constitute a unique form of primate communication with their own unique qualities.

The ontogenetic ritualization of bonobo gestures.

PubMed

Halina, Marta; Rossano, Federico; Tomasello, Michael

2013-07-01

Great apes communicate with gestures in flexible ways. Based on several lines of evidence, Tomasello and colleagues have posited that many of these gestures are learned via ontogenetic ritualization-a process of mutual anticipation in which particular social behaviors come to function as intentional communicative signals. Recently, Byrne and colleagues have argued that all great ape gestures are basically innate. In the current study, for the first time, we attempted to observe the process of ontogenetic ritualization as it unfolds over time. We focused on one communicative function between bonobo mothers and infants: initiation of "carries" for joint travel. We observed 1,173 carries in ten mother-infant dyads. These were initiated by nine different gesture types, with mothers and infants using many different gestures in ways that reflected their different roles in the carry interaction. There was also a fair amount of variability among the different dyads, including one idiosyncratic gesture used by one infant. This gestural variation could not be attributed to sampling effects alone. These findings suggest that ontogenetic ritualization plays an important role in the origin of at least some great ape gestures.

Optical gesture sensing and depth mapping technologies for head-mounted displays: an overview

NASA Astrophysics Data System (ADS)

Kress, Bernard; Lee, Johnny

2013-05-01

Head Mounted Displays (HMDs), and especially see-through HMDs have gained renewed interest in recent time, and for the first time outside the traditional military and defense realm, due to several high profile consumer electronics companies presenting their products to hit market. Consumer electronics HMDs have quite different requirements and constrains as their military counterparts. Voice comments are the de-facto interface for such devices, but when the voice recognition does not work (not connection to the cloud for example), trackpad and gesture sensing technologies have to be used to communicate information to the device. We review in this paper the various technologies developed today integrating optical gesture sensing in a small footprint, as well as the various related 3d depth mapping sensors.

Co-speech hand movements during narrations: What is the impact of right vs. left hemisphere brain damage?

PubMed

Hogrefe, Katharina; Rein, Robert; Skomroch, Harald; Lausberg, Hedda

2016-12-01

Persons with brain damage show deviant patterns of co-speech hand movement behaviour in comparison to healthy speakers. It has been claimed by several authors that gesture and speech rely on a single production mechanism that depends on the same neurological substrate while others claim that both modalities are closely related but separate production channels. Thus, findings so far are contradictory and there is a lack of studies that systematically analyse the full range of hand movements that accompany speech in the condition of brain damage. In the present study, we aimed to fill this gap by comparing hand movement behaviour in persons with unilateral brain damage to the left and the right hemisphere and a matched control group of healthy persons. For hand movement coding, we applied Module I of NEUROGES, an objective and reliable analysis system that enables to analyse the full repertoire of hand movements independent of speech, which makes it specifically suited for the examination of persons with aphasia. The main results of our study show a decreased use of communicative conceptual gestures in persons with damage to the right hemisphere and an increased use of these gestures in persons with left brain damage and aphasia. These results not only suggest that the production of gesture and speech do not rely on the same neurological substrate but also underline the important role of right hemisphere functioning for gesture production. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gesture therapy: a vision-based system for upper extremity stroke rehabilitation.

PubMed

Sucar, L; Luis, Roger; Leder, Ron; Hernandez, Jorge; Sanchez, Israel

2010-01-01

Stroke is the main cause of motor and cognitive disabilities requiring therapy in the world. Therefor it is important to develop rehabilitation technology that allows individuals who had suffered a stroke to practice intensive movement training without the expense of an always-present therapist. We have developed a low-cost vision-based system that allows stroke survivors to practice arm movement exercises at home or at the clinic, with periodic interactions with a therapist. The system integrates a virtual environment for facilitating repetitive movement training, with computer vision algorithms that track the hand of a patient, using an inexpensive camera and a personal computer. This system, called Gesture Therapy, includes a gripper with a pressure sensor to include hand and finger rehabilitation; and it tracks the head of the patient to detect and avoid trunk compensation. It has been evaluated in a controlled clinical trial at the National Institute for Neurology and Neurosurgery in Mexico City, comparing it with conventional occupational therapy. In this paper we describe the latest version of the Gesture Therapy System and summarize the results of the clinical trail.

Body language: The interplay between positional behavior and gestural signaling in the genus Pan and its implications for language evolution.

PubMed

Smith, Lindsey W; Delgado, Roberto A

2015-08-01

The gestural repertoires of bonobos and chimpanzees are well documented, but the relationship between gestural signaling and positional behavior (i.e., body postures and locomotion) has yet to be explored. Given that one theory for language evolution attributes the emergence of increased gestural communication to habitual bipedality, this relationship is important to investigate. In this study, we examined the interplay between gestures, body postures, and locomotion in four captive groups of bonobos and chimpanzees using ad libitum and focal video data. We recorded 43 distinct manual (involving upper limbs and/or hands) and bodily (involving postures, locomotion, head, lower limbs, or feet) gestures. In both species, actors used manual and bodily gestures significantly more when recipients were attentive to them, suggesting these movements are intentionally communicative. Adults of both species spent less than 1.0% of their observation time in bipedal postures or locomotion, yet 14.0% of all bonobo gestures and 14.7% of all chimpanzee gestures were produced when subjects were engaged in bipedal postures or locomotion. Among both bonobo groups and one chimpanzee group, these were mainly manual gestures produced by infants and juvenile females. Among the other chimpanzee group, however, these were mainly bodily gestures produced by adult males in which bipedal posture and locomotion were incorporated into communicative displays. Overall, our findings reveal that bipedality did not prompt an increase in manual gesturing in these study groups. Rather, body postures and locomotion are intimately tied to many gestures and certain modes of locomotion can be used as gestures themselves. © 2015 Wiley Periodicals, Inc.

Gesture in the Developing Brain

ERIC Educational Resources Information Center

Dick, Anthony Steven; Goldin-Meadow, Susan; Solodkin, Ana; Small, Steven L.

2012-01-01

Speakers convey meaning not only through words, but also through gestures. Although children are exposed to co-speech gestures from birth, we do not know how the developing brain comes to connect meaning conveyed in gesture with speech. We used functional magnetic resonance imaging (fMRI) to address this question and scanned 8- to 11-year-old…

Effects of lips and hands on auditory learning of second-language speech sounds.

PubMed

Hirata, Yukari; Kelly, Spencer D

2010-04-01

Previous research has found that auditory training helps native English speakers to perceive phonemic vowel length contrasts in Japanese, but their performance did not reach native levels after training. Given that multimodal information, such as lip movement and hand gesture, influences many aspects of native language processing, the authors examined whether multimodal input helps to improve native English speakers' ability to perceive Japanese vowel length contrasts. Sixty native English speakers participated in 1 of 4 types of training: (a) audio-only; (b) audio-mouth; (c) audio-hands; and (d) audio-mouth-hands. Before and after training, participants were given phoneme perception tests that measured their ability to identify short and long vowels in Japanese (e.g., /kato/ vs. /kato/). Although all 4 groups improved from pre- to posttest (replicating previous research), the participants in the audio-mouth condition improved more than those in the audio-only condition, whereas the 2 conditions involving hand gestures did not. Seeing lip movements during training significantly helps learners to perceive difficult second-language phonemic contrasts, but seeing hand gestures does not. The authors discuss possible benefits and limitations of using multimodal information in second-language phoneme learning.

Using the Hand to Choreograph Instruction: On the Functional Role of Gesture in Definition Talk

ERIC Educational Resources Information Center

Belhiah, Hassan

2013-01-01

This article examines the coordination of speech and gesture in teachers' definition talk, that is, vocabulary explanations addressed to language learners. By analyzing one ESL teacher's spoken definitions, the study demonstrates in the details of the unfolding talk how a teacher crafts and choreographs his definitions moment by moment, while…

Hearing and seeing meaning in speech and gesture: insights from brain and behaviour.

PubMed

Özyürek, Aslı

2014-09-19

As we speak, we use not only the arbitrary form-meaning mappings of the speech channel but also motivated form-meaning correspondences, i.e. iconic gestures that accompany speech (e.g. inverted V-shaped hand wiggling across gesture space to demonstrate walking). This article reviews what we know about processing of semantic information from speech and iconic gestures in spoken languages during comprehension of such composite utterances. Several studies have shown that comprehension of iconic gestures involves brain activations known to be involved in semantic processing of speech: i.e. modulation of the electrophysiological recording component N400, which is sensitive to the ease of semantic integration of a word to previous context, and recruitment of the left-lateralized frontal-posterior temporal network (left inferior frontal gyrus (IFG), medial temporal gyrus (MTG) and superior temporal gyrus/sulcus (STG/S)). Furthermore, we integrate the information coming from both channels recruiting brain areas such as left IFG, posterior superior temporal sulcus (STS)/MTG and even motor cortex. Finally, this integration is flexible: the temporal synchrony between the iconic gesture and the speech segment, as well as the perceived communicative intent of the speaker, modulate the integration process. Whether these findings are special to gestures or are shared with actions or other visual accompaniments to speech (e.g. lips) or other visual symbols such as pictures are discussed, as well as the implications for a multimodal view of language. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Gesturing more diminishes recall of abstract words when gesture is allowed and concrete words when it is taboo.

PubMed

Matthews-Saugstad, Krista M; Raymakers, Erik P; Kelty-Stephen, Damian G

2017-07-01

Gesture during speech can promote or diminish recall for conversation content. We explored effects of cognitive load on this relationship, manipulating it at two scales: individual-word abstractness and social constraints to prohibit gestures. Prohibited gestures can diminish recall but more so for abstract-word recall. Insofar as movement planning adds to cognitive load, movement amplitude may moderate gesture effects on memory, with greater permitted- and prohibited-gesture movements reducing abstract-word recall and concrete-word recall, respectively. We tested these effects in a dyadic game in which 39 adult participants described words to confederates without naming the word or five related words. Results supported our expectations and indicated that memory effects of gesturing depend on social, cognitive, and motoric aspects of discourse.

Learning from gesture: How early does it happen?

PubMed

Novack, Miriam A; Goldin-Meadow, Susan; Woodward, Amanda L

2015-09-01

Iconic gesture is a rich source of information for conveying ideas to learners. However, in order to learn from iconic gesture, a learner must be able to interpret its iconic form-a nontrivial task for young children. Our study explores how young children interpret iconic gesture and whether they can use it to infer a previously unknown action. In Study 1, 2- and 3-year-old children were shown iconic gestures that illustrated how to operate a novel toy to achieve a target action. Children in both age groups successfully figured out the target action more often after seeing an iconic gesture demonstration than after seeing no demonstration. However, the 2-year-olds (but not the 3-year-olds) figured out fewer target actions after seeing an iconic gesture demonstration than after seeing a demonstration of an incomplete-action and, in this sense, were not yet experts at interpreting gesture. Nevertheless, both age groups seemed to understand that gesture could convey information that can be used to guide their own actions, and that gesture is thus not movement for its own sake. That is, the children in both groups produced the action displayed in gesture on the object itself, rather than producing the action in the air (in other words, they rarely imitated the experimenter's gesture as it was performed). Study 2 compared 2-year-olds' performance following iconic vs. point gesture demonstrations. Iconic gestures led children to discover more target actions than point gestures, suggesting that iconic gesture does more than just focus a learner's attention, it conveys substantive information about how to solve the problem, information that is accessible to children as young as 2. The ability to learn from iconic gesture is thus in place by toddlerhood and, although still fragile, allows children to process gesture, not as meaningless movement, but as an intentional communicative representation. Copyright © 2015 Elsevier B.V. All rights reserved.

Learning from gesture: How early does it happen?

PubMed Central

Novack, Miriam A.; Goldin-Meadow, Susan; Woodward, Amanda L.

2015-01-01

Iconic gesture is a rich source of information for conveying ideas to learners. However, in order to learn from iconic gesture, a learner must be able to interpret its iconic form--a nontrivial task for young children. Our study explores how young children interpret iconic gesture and whether they can use it to infer a previously unknown action. In Study 1, 2- and 3-year-old children were shown iconic gestures that illustrated how to operate a novel toy to achieve a target action. Children in both age groups successfully figured out the target action more often after seeing an iconic gesture demonstration than after seeing no demonstration. However, the 2-year-olds (but not the 3-year-olds) figured out fewer target actions after seeing an iconic gesture demonstration than after seeing a demonstration of an incomplete-action and, in this sense, were not yet experts at interpreting gesture. Nevertheless, both age groups seemed to understand that gesture could convey information that can be used to guide their own actions, and that gesture is thus not movement for its own sake. That is, the children in both groups produced the action displayed in gesture on the object itself, rather than producing the action in the air (in other words, they rarely imitated the experimenter’s gesture as it was performed). Study 2 compared 2-year-olds’ performance following iconic vs. point gesture demonstrations. Iconic gestures led children to discover more target actions than point gestures, suggesting that iconic gesture does more than just focus a learner’s attention--,it conveys substantive information about how to solve the problem, information that is accessible to children as young as 2. The ability to learn from iconic gesture is thus in place by toddlerhood and, although still fragile, allows children to process gesture, not as meaningless movement, but as an intentional communicative representation. PMID:26036925

Gesture's Role in Facilitating Language Development

ERIC Educational Resources Information Center

LeBarton, Eve Angela Sauer

2010-01-01

Previous investigators have found significant relations between children's early spontaneous gesture and their subsequent vocabulary development: the more gesture children produce early, the larger their later vocabularies. The questions we address here are (1) whether we can increase children's gesturing through experimental manipulation and, if…

Gestures and Insight in Advanced Mathematical Thinking

ERIC Educational Resources Information Center

Yoon, Caroline; Thomas, Michael O. J.; Dreyfus, Tommy

2011-01-01

What role do gestures play in advanced mathematical thinking? We argue that the role of gestures goes beyond merely communicating thought and supporting understanding--in some cases, gestures can help generate new mathematical insights. Gestures feature prominently in a case study of two participants working on a sequence of calculus activities.…

When does a system become phonological? Handshape production in gesturers, signers, and homesigners

PubMed Central

Coppola, Marie; Mazzoni, Laura; Goldin-Meadow, Susan

2013-01-01

Sign languages display remarkable crosslinguistic consistencies in the use of handshapes. In particular, handshapes used in classifier predicates display a consistent pattern in finger complexity: classifier handshapes representing objects display more finger complexity than those representing how objects are handled. Here we explore the conditions under which this morphophonological phenomenon arises. In Study 1, we ask whether hearing individuals in Italy and the United States, asked to communicate using only their hands, show the same pattern of finger complexity found in the classifier handshapes of two sign languages: Italian Sign Language (LIS) and American Sign Language (ASL). We find that they do not: gesturers display more finger complexity in handling handshapes than in object handshapes. The morphophonological pattern found in conventional sign languages is therefore not a codified version of the pattern invented by hearing individuals on the spot. In Study 2, we ask whether continued use of gesture as a primary communication system results in a pattern that is more similar to the morphophonological pattern found in conventional sign languages or to the pattern found in gesturers. Homesigners have not acquired a signed or spoken language and instead use a self-generated gesture system to communicate with their hearing family members and friends. We find that homesigners pattern more like signers than like gesturers: their finger complexity in object handshapes is higher than that of gesturers (indeed as high as signers); and their finger complexity in handling handshapes is lower than that of gesturers (but not quite as low as signers). Generally, our findings indicate two markers of the phonologization of handshape in sign languages: increasing finger complexity in object handshapes, and decreasing finger complexity in handling handshapes. These first indicators of phonology appear to be present in individuals developing a gesture system without benefit

Development of Pointing Gestures in Children with Typical and Delayed Language Acquisition

ERIC Educational Resources Information Center

Lüke, Carina; Ritterfeld, Ute; Grimminger, Angela; Liszkowski, Ulf; Rohlfing, Katharina J.

2017-01-01

Purpose: This longitudinal study compared the development of hand and index-finger pointing in children with typical language development (TD) and children with language delay (LD). First, we examined whether the number and the form of pointing gestures during the second year of life are potential indicators of later LD. Second, we analyzed the…

Gesture Supports Spatial Thinking in STEM

ERIC Educational Resources Information Center

Stieff, Mike; Lira, Matthew E.; Scopelitis, Stephanie A.

2016-01-01

The present article describes two studies that examine the impact of teaching students to use gesture to support spatial thinking in the Science, Technology, Engineering, and Mathematics (STEM) discipline of chemistry. In Study 1 we compared the effectiveness of instruction that involved either watching gesture, reproducing gesture, or reading…

Viewpoint Integration for Hand-Based Recognition of Social Interactions from a First-Person View.

PubMed

Bambach, Sven; Crandall, David J; Yu, Chen

2015-11-01

Wearable devices are becoming part of everyday life, from first-person cameras (GoPro, Google Glass), to smart watches (Apple Watch), to activity trackers (FitBit). These devices are often equipped with advanced sensors that gather data about the wearer and the environment. These sensors enable new ways of recognizing and analyzing the wearer's everyday personal activities, which could be used for intelligent human-computer interfaces and other applications. We explore one possible application by investigating how egocentric video data collected from head-mounted cameras can be used to recognize social activities between two interacting partners (e.g. playing chess or cards). In particular, we demonstrate that just the positions and poses of hands within the first-person view are highly informative for activity recognition, and present a computer vision approach that detects hands to automatically estimate activities. While hand pose detection is imperfect, we show that combining evidence across first-person views from the two social partners significantly improves activity recognition accuracy. This result highlights how integrating weak but complimentary sources of evidence from social partners engaged in the same task can help to recognize the nature of their interaction.

Viewpoint Integration for Hand-Based Recognition of Social Interactions from a First-Person View

PubMed Central

Bambach, Sven; Crandall, David J.; Yu, Chen

2016-01-01

Wearable devices are becoming part of everyday life, from first-person cameras (GoPro, Google Glass), to smart watches (Apple Watch), to activity trackers (FitBit). These devices are often equipped with advanced sensors that gather data about the wearer and the environment. These sensors enable new ways of recognizing and analyzing the wearer’s everyday personal activities, which could be used for intelligent human-computer interfaces and other applications. We explore one possible application by investigating how egocentric video data collected from head-mounted cameras can be used to recognize social activities between two interacting partners (e.g. playing chess or cards). In particular, we demonstrate that just the positions and poses of hands within the first-person view are highly informative for activity recognition, and present a computer vision approach that detects hands to automatically estimate activities. While hand pose detection is imperfect, we show that combining evidence across first-person views from the two social partners significantly improves activity recognition accuracy. This result highlights how integrating weak but complimentary sources of evidence from social partners engaged in the same task can help to recognize the nature of their interaction. PMID:28966999

Hearing and seeing meaning in noise: Alpha, beta, and gamma oscillations predict gestural enhancement of degraded speech comprehension.

PubMed

Drijvers, Linda; Özyürek, Asli; Jensen, Ole

2018-05-01

During face-to-face communication, listeners integrate speech with gestures. The semantic information conveyed by iconic gestures (e.g., a drinking gesture) can aid speech comprehension in adverse listening conditions. In this magnetoencephalography (MEG) study, we investigated the spatiotemporal neural oscillatory activity associated with gestural enhancement of degraded speech comprehension. Participants watched videos of an actress uttering clear or degraded speech, accompanied by a gesture or not and completed a cued-recall task after watching every video. When gestures semantically disambiguated degraded speech comprehension, an alpha and beta power suppression and a gamma power increase revealed engagement and active processing in the hand-area of the motor cortex, the extended language network (LIFG/pSTS/STG/MTG), medial temporal lobe, and occipital regions. These observed low- and high-frequency oscillatory modulations in these areas support general unification, integration and lexical access processes during online language comprehension, and simulation of and increased visual attention to manual gestures over time. All individual oscillatory power modulations associated with gestural enhancement of degraded speech comprehension predicted a listener's correct disambiguation of the degraded verb after watching the videos. Our results thus go beyond the previously proposed role of oscillatory dynamics in unimodal degraded speech comprehension and provide first evidence for the role of low- and high-frequency oscillations in predicting the integration of auditory and visual information at a semantic level. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Delayed Stimulus-Specific Improvements in Discourse Following Anomia Treatment Using an Intentional Gesture

ERIC Educational Resources Information Center

Altmann, Lori J. P.; Hazamy, Audrey A.; Carvajal, Pamela J.; Benjamin, Michelle; Rosenbek, John C.; Crosson, Bruce

2014-01-01

Purpose: In this study, the authors assessed how the addition of intentional left-hand gestures to an intensive treatment for anomia affects 2 types of discourse: picture description and responses to open-ended questions. Method: Fourteen people with aphasia completed treatment for anomia comprising 30 treatment sessions over 3 weeks. Seven…

Gesture-Based Controls for Robots: Overview and Implications for Use by Soldiers

DTIC Science & Technology

2016-07-01

to go somewhere but you did not say where”), (Kennedy et al. 2007; Perzanowski et al 2000a, 2000b). Many efforts are currently focused on developing...start/end of a gesture. They reported a 98% accuracy using a modified handwriting recognition statistical algorithm. The same algorithm was tested...to the device (light switch, music player) and saying “lights on” or “volume up” (Wilson and Shafer 2003). The Nintendo Wii remote controller has

Type of iconicity influences children's comprehension of gesture.

PubMed

Hodges, Leslie E; Özçalışkan, Şeyda; Williamson, Rebecca

2018-02-01

Children produce iconic gestures conveying action information earlier than the ones conveying attribute information (Özçalışkan, Gentner, & Goldin-Meadow, 2014). In this study, we ask whether children's comprehension of iconic gestures follows a similar pattern, also with earlier comprehension of iconic gestures conveying action. Children, ages 2-4years, were presented with 12 minimally-informative speech+iconic gesture combinations, conveying either an action (e.g., open palm flapping as if bird flying) or an attribute (e.g., fingers spread as if bird's wings) associated with a referent. They were asked to choose the correct match for each gesture in a forced-choice task. Our results showed that children could identify the referent of an iconic gesture conveying characteristic action earlier (age 2) than the referent of an iconic gesture conveying characteristic attribute (age 3). Overall, our study identifies ages 2-3 as important in the development of comprehension of iconic co-speech gestures, and indicates that the comprehension of iconic gestures with action meanings is easier than, and may even precede, the comprehension of iconic gestures with attribute meanings. Copyright © 2017 Elsevier Inc. All rights reserved.

Spontaneous gestures influence strategy choices in problem solving.

PubMed

Alibali, Martha W; Spencer, Robert C; Knox, Lucy; Kita, Sotaro

2011-09-01

Do gestures merely reflect problem-solving processes, or do they play a functional role in problem solving? We hypothesized that gestures highlight and structure perceptual-motor information, and thereby make such information more likely to be used in problem solving. Participants in two experiments solved problems requiring the prediction of gear movement, either with gesture allowed or with gesture prohibited. Such problems can be correctly solved using either a perceptual-motor strategy (simulation of gear movements) or an abstract strategy (the parity strategy). Participants in the gesture-allowed condition were more likely to use perceptual-motor strategies than were participants in the gesture-prohibited condition. Gesture promoted use of perceptual-motor strategies both for participants who talked aloud while solving the problems (Experiment 1) and for participants who solved the problems silently (Experiment 2). Thus, spontaneous gestures influence strategy choices in problem solving.

The influence of the visual modality on language structure and conventionalization: insights from sign language and gesture.

PubMed

Perniss, Pamela; Özyürek, Asli; Morgan, Gary

2015-01-01

For humans, the ability to communicate and use language is instantiated not only in the vocal modality but also in the visual modality. The main examples of this are sign languages and (co-speech) gestures. Sign languages, the natural languages of Deaf communities, use systematic and conventionalized movements of the hands, face, and body for linguistic expression. Co-speech gestures, though non-linguistic, are produced in tight semantic and temporal integration with speech and constitute an integral part of language together with speech. The articles in this issue explore and document how gestures and sign languages are similar or different and how communicative expression in the visual modality can change from being gestural to grammatical in nature through processes of conventionalization. As such, this issue contributes to our understanding of how the visual modality shapes language and the emergence of linguistic structure in newly developing systems. Studying the relationship between signs and gestures provides a new window onto the human ability to recruit multiple levels of representation (e.g., categorical, gradient, iconic, abstract) in the service of using or creating conventionalized communicative systems. Copyright © 2015 Cognitive Science Society, Inc.

Gestures for Picture Archiving and Communication Systems (PACS) operation in the operating room: Is there any standard?

PubMed

Madapana, Naveen; Gonzalez, Glebys; Rodgers, Richard; Zhang, Lingsong; Wachs, Juan P

2018-01-01

Gestural interfaces allow accessing and manipulating Electronic Medical Records (EMR) in hospitals while keeping a complete sterile environment. Particularly, in the Operating Room (OR), these interfaces enable surgeons to browse Picture Archiving and Communication System (PACS) without the need of delegating functions to the surgical staff. Existing gesture based medical interfaces rely on a suboptimal and an arbitrary small set of gestures that are mapped to a few commands available in PACS software. The objective of this work is to discuss a method to determine the most suitable set of gestures based on surgeon's acceptability. To achieve this goal, the paper introduces two key innovations: (a) a novel methodology to incorporate gestures' semantic properties into the agreement analysis, and (b) a new agreement metric to determine the most suitable gesture set for a PACS. Three neurosurgical diagnostic tasks were conducted by nine neurosurgeons. The set of commands and gesture lexicons were determined using a Wizard of Oz paradigm. The gestures were decomposed into a set of 55 semantic properties based on the motion trajectory, orientation and pose of the surgeons' hands and their ground truth values were manually annotated. Finally, a new agreement metric was developed, using the known Jaccard similarity to measure consensus between users over a gesture set. A set of 34 PACS commands were found to be a sufficient number of actions for PACS manipulation. In addition, it was found that there is a level of agreement of 0.29 among the surgeons over the gestures found. Two statistical tests including paired t-test and Mann Whitney Wilcoxon test were conducted between the proposed metric and the traditional agreement metric. It was found that the agreement values computed using the former metric are significantly higher (p < 0.001) for both tests. This study reveals that the level of agreement among surgeons over the best gestures for PACS operation is higher than the

24 DOF EMG controlled hybrid actuated prosthetic hand.

PubMed

Atasoy, A; Kaya, E; Toptas, E; Kuchimov, S; Kaplanoglu, E; Ozkan, M

2016-08-01

A complete mechanical design concept of an electromyogram (EMG) controlled hybrid prosthetic hand, with 24 degree of freedom (DOF) anthropomorphic structure is presented. Brushless DC motors along with Shape Memory Alloy (SMA) actuators are used to achieve dexterous functionality. An 8 channel EMG is used for detecting 7 basic hand gestures for control purposes. The prosthetic hand will be integrated with the Neural Network (NNE) based controller in the next phase of the study.

Evaluating the utility of two gestural discomfort evaluation methods

PubMed Central

Son, Minseok; Jung, Jaemoon; Park, Woojin

2017-01-01

Evaluating physical discomfort of designed gestures is important for creating safe and usable gesture-based interaction systems; yet, gestural discomfort evaluation has not been extensively studied in HCI, and few evaluation methods seem currently available whose utility has been experimentally confirmed. To address this, this study empirically demonstrated the utility of the subjective rating method after a small number of gesture repetitions (a maximum of four repetitions) in evaluating designed gestures in terms of physical discomfort resulting from prolonged, repetitive gesture use. The subjective rating method has been widely used in previous gesture studies but without empirical evidence on its utility. This study also proposed a gesture discomfort evaluation method based on an existing ergonomics posture evaluation tool (Rapid Upper Limb Assessment) and demonstrated its utility in evaluating designed gestures in terms of physical discomfort resulting from prolonged, repetitive gesture use. Rapid Upper Limb Assessment is an ergonomics postural analysis tool that quantifies the work-related musculoskeletal disorders risks for manual tasks, and has been hypothesized to be capable of correctly determining discomfort resulting from prolonged, repetitive gesture use. The two methods were evaluated through comparisons against a baseline method involving discomfort rating after actual prolonged, repetitive gesture use. Correlation analyses indicated that both methods were in good agreement with the baseline. The methods proposed in this study seem useful for predicting discomfort resulting from prolonged, repetitive gesture use, and are expected to help interaction designers create safe and usable gesture-based interaction systems. PMID:28423016

Upper-limb prosthetic control using wearable multichannel mechanomyography.

PubMed

Wilson, Samuel; Vaidyanathan, Ravi

2017-07-01

In this paper we introduce a robust multi-channel wearable sensor system for capturing user intent to control robotic hands. The interface is based on a fusion of inertial measurement and mechanomyography (MMG), which measures the vibrations of muscle fibres during motion. MMG is immune to issues such as sweat, skin impedance, and the need for a reference signal that is common to electromyography (EMG). The main contributions of this work are: 1) the hardware design of a fused inertial and MMG measurement system that can be worn on the arm, 2) a unified algorithm for detection, segmentation, and classification of muscle movement corresponding to hand gestures, and 3) experiments demonstrating the real-time control of a commercial prosthetic hand (Bebionic Version 2). Results show recognition of seven gestures, achieving an offline classification accuracy of 83.5% performed on five healthy subjects and one transradial amputee. The gesture recognition was then tested in real time on subsets of two and five gestures, with an average accuracy of 93.3% and 62.2% respectively. To our knowledge this is the first applied MMG based control system for practical prosthetic control.

Gesturing about Number Sense

ERIC Educational Resources Information Center

Lee, Joanne; Kotsopoulos, Donna; Tumber, Anupreet; Makosz, Samantha

2015-01-01

Gestures such as finger counting, pointing, and touching have been found to facilitate mathematical development in preschool and school-aged children. However, little is known about the types of mathematically related gestures used by parent-toddler dyads to facilitate early mathematics learning during the first 3 years of life. A total of 24…

Wavelet decomposition based principal component analysis for face recognition using MATLAB

NASA Astrophysics Data System (ADS)

Sharma, Mahesh Kumar; Sharma, Shashikant; Leeprechanon, Nopbhorn; Ranjan, Aashish

2016-03-01

For the realization of face recognition systems in the static as well as in the real time frame, algorithms such as principal component analysis, independent component analysis, linear discriminate analysis, neural networks and genetic algorithms are used for decades. This paper discusses an approach which is a wavelet decomposition based principal component analysis for face recognition. Principal component analysis is chosen over other algorithms due to its relative simplicity, efficiency, and robustness features. The term face recognition stands for identifying a person from his facial gestures and having resemblance with factor analysis in some sense, i.e. extraction of the principal component of an image. Principal component analysis is subjected to some drawbacks, mainly the poor discriminatory power and the large computational load in finding eigenvectors, in particular. These drawbacks can be greatly reduced by combining both wavelet transform decomposition for feature extraction and principal component analysis for pattern representation and classification together, by analyzing the facial gestures into space and time domain, where, frequency and time are used interchangeably. From the experimental results, it is envisaged that this face recognition method has made a significant percentage improvement in recognition rate as well as having a better computational efficiency.

Co-verbal gestures among speakers with aphasia: Influence of aphasia severity, linguistic and semantic skills, and hemiplegia on gesture employment in oral discourse

PubMed Central

Kong, Anthony Pak-Hin; Law, Sam-Po; Wat, Watson Ka-Chun; Lai, Christy

2015-01-01

The use of co-verbal gestures is common in human communication and has been reported to assist word retrieval and to facilitate verbal interactions. This study systematically investigated the impact of aphasia severity, integrity of semantic processing, and hemiplegia on the use of co-verbal gestures, with reference to gesture forms and functions, by 131 normal speakers, 48 individuals with aphasia and their controls. All participants were native Cantonese speakers. It was found that the severity of aphasia and verbal-semantic impairment was associated with significantly more co-verbal gestures. However, there was no relationship between right-sided hemiplegia and gesture employment. Moreover, significantly more gestures were employed by the speakers with aphasia, but about 10% of them did not gesture. Among those who used gestures, content-carrying gestures, including iconic, metaphoric, deictic gestures, and emblems, served the function of enhancing language content and providing information additional to the language content. As for the non-content carrying gestures, beats were used primarily for reinforcing speech prosody or guiding speech flow, while non-identifiable gestures were associated with assisting lexical retrieval or with no specific functions. The above findings would enhance our understanding of the use of various forms of co-verbal gestures in aphasic discourse production and their functions. Speech-language pathologists may also refer to the current annotation system and the results to guide clinical evaluation and remediation of gestures in aphasia. PMID:26186256

Fusion of Haptic and Gesture Sensors for Rehabilitation of Bimanual Coordination and Dexterous Manipulation.

PubMed

Yu, Ningbo; Xu, Chang; Li, Huanshuai; Wang, Kui; Wang, Liancheng; Liu, Jingtai

2016-03-18

Disabilities after neural injury, such as stroke, bring tremendous burden to patients, families and society. Besides the conventional constrained-induced training with a paretic arm, bilateral rehabilitation training involves both the ipsilateral and contralateral sides of the neural injury, fitting well with the fact that both arms are needed in common activities of daily living (ADLs), and can promote good functional recovery. In this work, the fusion of a gesture sensor and a haptic sensor with force feedback capabilities has enabled a bilateral rehabilitation training therapy. The Leap Motion gesture sensor detects the motion of the healthy hand, and the omega.7 device can detect and assist the paretic hand, according to the designed cooperative task paradigm, as much as needed, with active force feedback to accomplish the manipulation task. A virtual scenario has been built up, and the motion and force data facilitate instantaneous visual and audio feedback, as well as further analysis of the functional capabilities of the patient. This task-oriented bimanual training paradigm recruits the sensory, motor and cognitive aspects of the patient into one loop, encourages the active involvement of the patients into rehabilitation training, strengthens the cooperation of both the healthy and impaired hands, challenges the dexterous manipulation capability of the paretic hand, suits easy of use at home or centralized institutions and, thus, promises effective potentials for rehabilitation training.

Fusion of Haptic and Gesture Sensors for Rehabilitation of Bimanual Coordination and Dexterous Manipulation

PubMed Central

Yu, Ningbo; Xu, Chang; Li, Huanshuai; Wang, Kui; Wang, Liancheng; Liu, Jingtai

2016-01-01

Disabilities after neural injury, such as stroke, bring tremendous burden to patients, families and society. Besides the conventional constrained-induced training with a paretic arm, bilateral rehabilitation training involves both the ipsilateral and contralateral sides of the neural injury, fitting well with the fact that both arms are needed in common activities of daily living (ADLs), and can promote good functional recovery. In this work, the fusion of a gesture sensor and a haptic sensor with force feedback capabilities has enabled a bilateral rehabilitation training therapy. The Leap Motion gesture sensor detects the motion of the healthy hand, and the omega.7 device can detect and assist the paretic hand, according to the designed cooperative task paradigm, as much as needed, with active force feedback to accomplish the manipulation task. A virtual scenario has been built up, and the motion and force data facilitate instantaneous visual and audio feedback, as well as further analysis of the functional capabilities of the patient. This task-oriented bimanual training paradigm recruits the sensory, motor and cognitive aspects of the patient into one loop, encourages the active involvement of the patients into rehabilitation training, strengthens the cooperation of both the healthy and impaired hands, challenges the dexterous manipulation capability of the paretic hand, suits easy of use at home or centralized institutions and, thus, promises effective potentials for rehabilitation training. PMID:26999149

Young Children Create Iconic Gestures to Inform Others

ERIC Educational Resources Information Center

Behne, Tanya; Carpenter, Malinda; Tomasello, Michael

2014-01-01

Much is known about young children's use of deictic gestures such as pointing. Much less is known about their use of other types of communicative gestures, especially iconic or symbolic gestures. In particular, it is unknown whether children can create iconic gestures on the spot to inform others. Study 1 provided 27-month-olds with the…

Online gesture spotting from visual hull data.

PubMed

Peng, Bo; Qian, Gang

2011-06-01

This paper presents a robust framework for online full-body gesture spotting from visual hull data. Using view-invariant pose features as observations, hidden Markov models (HMMs) are trained for gesture spotting from continuous movement data streams. Two major contributions of this paper are 1) view-invariant pose feature extraction from visual hulls, and 2) a systematic approach to automatically detecting and modeling specific nongesture movement patterns and using their HMMs for outlier rejection in gesture spotting. The experimental results have shown the view-invariance property of the proposed pose features for both training poses and new poses unseen in training, as well as the efficacy of using specific nongesture models for outlier rejection. Using the IXMAS gesture data set, the proposed framework has been extensively tested and the gesture spotting results are superior to those reported on the same data set obtained using existing state-of-the-art gesture spotting methods.

Gesture analysis for physics education researchers

NASA Astrophysics Data System (ADS)

Scherr, Rachel E.

2008-06-01

Systematic observations of student gestures can not only fill in gaps in students’ verbal expressions, but can also offer valuable information about student ideas, including their source, their novelty to the speaker, and their construction in real time. This paper provides a review of the research in gesture analysis that is most relevant to physics education researchers and illustrates gesture analysis for the purpose of better understanding student thinking about physics.

A Cross-cultural Study of the Communication of Emotion by Facial and Gestural Cues

ERIC Educational Resources Information Center

Graham, Jean Ann; And Others

1975-01-01

Discusses a study dealing with English, Northern Italian and Southern Italian encoders role-playing specific emotions and degrees of two dimensions of emotion, and presents evidence suggesting that for neither the English nor the Italians, do hand gestures and other bodily cues function as a major communication channel for emotion. Available from:…

Releasing the Constraints on Aphasia Therapy: The Positive Impact of Gesture and Multimodality Treatments

ERIC Educational Resources Information Center

Rose, Miranda L.

2013-01-01

Purpose: There is a 40-year history of interest in the use of arm and hand gestures in treatments that target the reduction of aphasic linguistic impairment and compensatory methods of communication (Rose, 2006). Arguments for constraining aphasia treatment to the verbal modality have arisen from proponents of constraint-induced aphasia therapy…

An integrated analysis of speech and gestural characteristics in conversational child-computer interactions

NASA Astrophysics Data System (ADS)

Yildirim, Serdar; Montanari, Simona; Andersen, Elaine; Narayanan, Shrikanth S.

2003-10-01

Understanding the fine details of children's speech and gestural characteristics helps, among other things, in creating natural computer interfaces. We analyze the acoustic, lexical/non-lexical and spoken/gestural discourse characteristics of young children's speech using audio-video data gathered using a Wizard of Oz technique from 4 to 6 year old children engaged in resolving a series of age-appropriate cognitive challenges. Fundamental and formant frequencies exhibited greater variations between subjects consistent with previous results on read speech [Lee et al., J. Acoust. Soc. Am. 105, 1455-1468 (1999)]. Also, our analysis showed that, in a given bandwidth, phonemic information contained in the speech of young child is significantly less than that of older ones and adults. To enable an integrated analysis, a multi-track annotation board was constructed using the ANVIL tool kit [M. Kipp, Eurospeech 1367-1370 (2001)]. Along with speech transcriptions and acoustic analysis, non-lexical and discourse characteristics, and child's gesture (facial expressions, body movements, hand/head movements) were annotated in a synchronized multilayer system. Initial results showed that younger children rely more on gestures to emphasize their verbal assertions. Younger children use non-lexical speech (e.g., um, huh) associated with frustration and pondering/reflecting more frequently than older ones. Younger children also repair more with humans than with computer.

Control and Guidance of Low-Cost Robots via Gesture Perception for Monitoring Activities in the Home

PubMed Central

Sempere, Angel D.; Serna-Leon, Arturo; Gil, Pablo; Puente, Santiago; Torres, Fernando

2015-01-01

This paper describes the development of a low-cost mini-robot that is controlled by visual gestures. The prototype allows a person with disabilities to perform visual inspections indoors and in domestic spaces. Such a device could be used as the operator's eyes obviating the need for him to move about. The robot is equipped with a motorised webcam that is also controlled by visual gestures. This camera is used to monitor tasks in the home using the mini-robot while the operator remains quiet and motionless. The prototype was evaluated through several experiments testing the ability to use the mini-robot’s kinematics and communication systems to make it follow certain paths. The mini-robot can be programmed with specific orders and can be tele-operated by means of 3D hand gestures to enable the operator to perform movements and monitor tasks from a distance. PMID:26690448

Enhancement of naming in nonfluent aphasia through gesture.

PubMed

Hanlon, R E; Brown, J W; Gerstman, L J

1990-02-01

In a number of studies that have examined the gestural disturbance in aphasia and the utility of gestural interventions in aphasia therapy, a variable degree of facilitation of verbalization during gestural activity has been reported. The present study examined the effect of different unilateral gestural movements on simultaneous oral-verbal expression, specifically naming to confrontation. It was hypothesized that activation of the phylogenetically older proximal motor system of the hemiplegic right arm in the execution of a communicative but nonrepresentational pointing gesture would have a facilitatory effect on naming ability. Twenty-four aphasic patients, representing five aphasic subtypes, including Broca's, Transcortical Motor, Anomic, Global, and Wernicke's aphasics were assessed under three gesture/naming conditions. The findings indicated that gestures produced through activation of the proximal (shoulder) musculature of the right paralytic limb differentially facilitated naming performance in the nonfluent subgroup, but not in the Wernicke's aphasics. These findings may be explained on the view that functional activation of the archaic proximal motor system of the hemiplegic limb, in the execution of a communicative gesture, permits access to preliminary stages in the formative process of the anterior action microgeny, which ultimately emerges in vocal articulation.

Gesture production and comprehension in children with specific language impairment.

PubMed

Botting, Nicola; Riches, Nicholas; Gaynor, Marguerite; Morgan, Gary

2010-03-01

Children with specific language impairment (SLI) have difficulties with spoken language. However, some recent research suggests that these impairments reflect underlying cognitive limitations. Studying gesture may inform us clinically and theoretically about the nature of the association between language and cognition. A total of 20 children with SLI and 19 typically developing (TD) peers were assessed on a novel measure of gesture production. Children were also assessed for sentence comprehension errors in a speech-gesture integration task. Children with SLI performed equally to peers on gesture production but performed less well when comprehending integrated speech and gesture. Error patterns revealed a significant group interaction: children with SLI made more gesture-based errors, whilst TD children made semantically based ones. Children with SLI accessed and produced lexically encoded gestures despite having impaired spoken vocabulary and this group also showed stronger associations between gesture and language than TD children. When SLI comprehension breaks down, gesture may be relied on over speech, whilst TD children have a preference for spoken cues. The findings suggest that for children with SLI, gesture scaffolds are still more related to language development than for TD peers who have out-grown earlier reliance on gestures. Future clinical implications may include standardized assessment of symbolic gesture and classroom based gesture support for clinical groups.

Gestonurse: a robotic surgical nurse for handling surgical instruments in the operating room.

PubMed

Jacob, Mithun; Li, Yu-Ting; Akingba, George; Wachs, Juan P

2012-03-01

While surgeon-scrub nurse collaboration provides a fast, straightforward and inexpensive method of delivering surgical instruments to the surgeon, it often results in "mistakes" (e.g. missing information, ambiguity of instructions and delays). It has been shown that these errors can have a negative impact on the outcome of the surgery. These errors could potentially be reduced or eliminated by introducing robotics into the operating room. Gesture control is a natural and fundamentally sound alternative that allows interaction without disturbing the normal flow of surgery. This paper describes the development of a robotic scrub nurse Gestonurse to support surgeons by passing surgical instruments during surgery as required. The robot responds to recognized hand signals detected through sophisticated computer vision and pattern recognition techniques. Experimental results show that 95% of the gestures were recognized correctly. The gesture recognition algorithm presented is robust to changes in scale and rotation of the hand gestures. The system was compared to human task performance and was found to be only 0.83 s slower on average.

Age, gesture span, and dissociations among component subsystems of working memory.

PubMed

Dolman, R; Roy, E A; Dimeck, P T; Hall, C R

2000-01-01

Working memory was examined in old and young adults using a series of span tasks, including the forward versions of the visual-spatial and digit span tasks from the Wechsler Memory Scale-Revised, and comparable hand gesture and visual design span tasks. The observation that the young participants performed significantly better on all the tasks except digit span suggested that aging has an impact on some component subsystems of working memory but not others. Analyses of intercorrelations in span performance supports the dissociation among three component subsystems, one for auditory verbal information (the articulatory loop), one for visual-spatial information (visual-spatial scratch-pad), and one for hand/body postural configuration.

Perceived Conventionality in Co-speech Gestures Involves the Fronto-Temporal Language Network.

PubMed

Wolf, Dhana; Rekittke, Linn-Marlen; Mittelberg, Irene; Klasen, Martin; Mathiak, Klaus

2017-01-01

Face-to-face communication is multimodal; it encompasses spoken words, facial expressions, gaze, and co-speech gestures. In contrast to linguistic symbols (e.g., spoken words or signs in sign language) relying on mostly explicit conventions, gestures vary in their degree of conventionality. Bodily signs may have a general accepted or conventionalized meaning (e.g., a head shake) or less so (e.g., self-grooming). We hypothesized that subjective perception of conventionality in co-speech gestures relies on the classical language network, i.e., the left hemispheric inferior frontal gyrus (IFG, Broca's area) and the posterior superior temporal gyrus (pSTG, Wernicke's area) and studied 36 subjects watching video-recorded story retellings during a behavioral and an functional magnetic resonance imaging (fMRI) experiment. It is well documented that neural correlates of such naturalistic videos emerge as intersubject covariance (ISC) in fMRI even without involving a stimulus (model-free analysis). The subjects attended either to perceived conventionality or to a control condition (any hand movements or gesture-speech relations). Such tasks modulate ISC in contributing neural structures and thus we studied ISC changes to task demands in language networks. Indeed, the conventionality task significantly increased covariance of the button press time series and neuronal synchronization in the left IFG over the comparison with other tasks. In the left IFG, synchronous activity was observed during the conventionality task only. In contrast, the left pSTG exhibited correlated activation patterns during all conditions with an increase in the conventionality task at the trend level only. Conceivably, the left IFG can be considered a core region for the processing of perceived conventionality in co-speech gestures similar to spoken language. In general, the interpretation of conventionalized signs may rely on neural mechanisms that engage during language comprehension.

Perceived Conventionality in Co-speech Gestures Involves the Fronto-Temporal Language Network

PubMed Central

Wolf, Dhana; Rekittke, Linn-Marlen; Mittelberg, Irene; Klasen, Martin; Mathiak, Klaus

2017-01-01

Face-to-face communication is multimodal; it encompasses spoken words, facial expressions, gaze, and co-speech gestures. In contrast to linguistic symbols (e.g., spoken words or signs in sign language) relying on mostly explicit conventions, gestures vary in their degree of conventionality. Bodily signs may have a general accepted or conventionalized meaning (e.g., a head shake) or less so (e.g., self-grooming). We hypothesized that subjective perception of conventionality in co-speech gestures relies on the classical language network, i.e., the left hemispheric inferior frontal gyrus (IFG, Broca's area) and the posterior superior temporal gyrus (pSTG, Wernicke's area) and studied 36 subjects watching video-recorded story retellings during a behavioral and an functional magnetic resonance imaging (fMRI) experiment. It is well documented that neural correlates of such naturalistic videos emerge as intersubject covariance (ISC) in fMRI even without involving a stimulus (model-free analysis). The subjects attended either to perceived conventionality or to a control condition (any hand movements or gesture-speech relations). Such tasks modulate ISC in contributing neural structures and thus we studied ISC changes to task demands in language networks. Indeed, the conventionality task significantly increased covariance of the button press time series and neuronal synchronization in the left IFG over the comparison with other tasks. In the left IFG, synchronous activity was observed during the conventionality task only. In contrast, the left pSTG exhibited correlated activation patterns during all conditions with an increase in the conventionality task at the trend level only. Conceivably, the left IFG can be considered a core region for the processing of perceived conventionality in co-speech gestures similar to spoken language. In general, the interpretation of conventionalized signs may rely on neural mechanisms that engage during language comprehension. PMID:29249945

Comprehensibility and neural substrate of communicative gestures in severe aphasia.

PubMed

Hogrefe, Katharina; Ziegler, Wolfram; Weidinger, Nicole; Goldenberg, Georg

2017-08-01

Communicative gestures can compensate incomprehensibility of oral speech in severe aphasia, but the brain damage that causes aphasia may also have an impact on the production of gestures. We compared the comprehensibility of gestural communication of persons with severe aphasia and non-aphasic persons and used voxel based lesion symptom mapping (VLSM) to determine lesion sites that are responsible for poor gestural expression in aphasia. On group level, persons with aphasia conveyed more information via gestures than controls indicating a compensatory use of gestures in persons with severe aphasia. However, individual analysis showed a broad range of gestural comprehensibility. VLSM suggested that poor gestural expression was associated with lesions in anterior temporal and inferior frontal regions. We hypothesize that likely functional correlates of these localizations are selection of and flexible changes between communication channels as well as between different types of gestures and between features of actions and objects that are expressed by gestures. Copyright © 2017 Elsevier Inc. All rights reserved.

Action’s influence on thought: The case of gesture

PubMed Central

Goldin-Meadow, Susan; Beilock, Sian

2010-01-01

Recent research shows that our actions can influence how we think. A separate body of research shows that the gestures we produce when we speak can also influence how we think. Here we bring these two literatures together to explore whether gesture has an impact on thinking by virtue of its ability to reflect real-world actions. We first argue that gestures contain detailed perceptual-motor information about the actions they represent, information often not found in the speech that accompanies the gestures. We then show that the action features in gesture do not just reflect the gesturer’s thinking—they can feed back and alter that thinking. Gesture actively brings action into a speaker’s mental representations, and those mental representations then affect behavior—at times more powerfully than the actions on which the gestures are based. Gesture thus has the potential to serve as a unique bridge between action and abstract thought. PMID:21572548

Adult Gesture in Collaborative Mathematics Reasoning in Different Ages

NASA Astrophysics Data System (ADS)

Noto, M. S.; Harisman, Y.; Harun, L.; Amam, A.; Maarif, S.

2017-09-01

This article describes the case study on postgraduate students by using descriptive method. A problem is designed to facilitate the reasoning in the topic of Chi-Square test. The problem was given to two male students with different ages to investigate the gesture pattern and it will be related to their reasoning process. The indicators in reasoning problem can obtain the conclusion of analogy and generalization, and arrange the conjectures. This study refers to some questions—whether unique gesture is for every individual or to identify the pattern of the gesture used by the students with different ages. Reasoning problem was employed to collect the data. Two students were asked to collaborate to reason the problem. The discussion process recorded in using video tape to observe the gestures. The video recorded are explained clearly in this writing. Prosodic cues such as time, conversation text, gesture that appears, might help in understanding the gesture. The purpose of this study is to investigate whether different ages influences the maturity in collaboration observed from gesture perspective. The finding of this study shows that age is not a primary factor that influences the gesture in that reasoning process. In this case, adult gesture or gesture performed by order student does not show that he achieves, maintains, and focuses on the problem earlier on. Adult gesture also does not strengthen and expand the meaning if the student’s words or the language used in reasoning is not familiar for younger student. Adult gesture also does not affect cognitive uncertainty in mathematics reasoning. The future research is suggested to take more samples to find the consistency from that statement.

"I use it when I see it": The role of development and experience in Deaf and hearing children's understanding of iconic gesture.

PubMed

Magid, Rachel W; Pyers, Jennie E

2017-05-01

Iconicity is prevalent in gesture and in sign languages, yet the degree to which children recognize and leverage iconicity for early language learning is unclear. In Experiment 1 of the current study, we presented sign-naïve 3-, 4- and 5-year-olds (n=87) with iconic shape gestures and no additional scaffolding to ask whether children can spontaneously map iconic gestures to their referents. Four- and five-year-olds, but not three-year-olds, recognized the referents of iconic shape gestures above chance. Experiment 2 asked whether preschoolers (n=93) show an advantage in fast-mapping iconic gestures compared to arbitrary ones. We found that iconicity played a significant role in supporting 4- and 5-year-olds' ability to learn new gestures presented in an explicit pedagogical context, and a lesser role in 3-year-olds' learning. Using similar tasks in Experiment 3, we found that Deaf preschoolers (n=41) exposed to American Sign Language showed a similar pattern of recognition and learning but starting at an earlier age, suggesting that learning a language with rich iconicity may lead to earlier use of iconicity. These results suggest that sensitivity to iconicity is shaped by experience, and while not fundamental to the earliest stages of language development, is a useful tool once children unlock these form-meaning relationships. Copyright © 2017 Elsevier B.V. All rights reserved.

Gesturing by Speakers with Aphasia: How Does It Compare?

ERIC Educational Resources Information Center

Mol, Lisette; Krahmer, Emiel; van de Sandt-Koenderman, Mieke

2013-01-01

Purpose: To study the independence of gesture and verbal language production. The authors assessed whether gesture can be semantically compensatory in cases of verbal language impairment and whether speakers with aphasia and control participants use similar depiction techniques in gesture. Method: The informativeness of gesture was assessed in 3…

Recognition of iconicity doesn't come for free.

PubMed

Namy, Laura L

2008-11-01

Iconicity--resemblance between a symbol and its referent--has long been presumed to facilitate symbolic insight and symbol use in infancy. These two experiments test children's ability to recognize iconic gestures at ages 14 through 26 months. The results indicate a clear ability to recognize how a gesture resembles its referent by 26 months, but little evidence of recognition of iconicity at the onset of symbolic development. These findings imply that iconicity is not available as an aid at the onset of symbolic development but rather that the ability to apprehend the relation between a symbol and its referent develops over the course of the second year.

Gestural Communication and Mating Tactics in Wild Chimpanzees

PubMed Central

Roberts, Anna Ilona; Roberts, Sam George Bradley

2015-01-01

The extent to which primates can flexibly adjust the production of gestural communication according to the presence and visual attention of the audience provides key insights into the social cognition underpinning gestural communication, such as an understanding of third party relationships. Gestures given in a mating context provide an ideal area for examining this flexibility, as frequently the interests of a male signaller, a female recipient and a rival male bystander conflict. Dominant chimpanzee males seek to monopolize matings, but subordinate males may use gestural communication flexibly to achieve matings despite their low rank. Here we show that the production of mating gestures in wild male East African chimpanzees (Pan troglodytes schweunfurthii) was influenced by a conflict of interest with females, which in turn was influenced by the presence and visual attention of rival males. When the conflict of interest was low (the rival male was present and looking away), chimpanzees used visual/ tactile gestures over auditory gestures. However, when the conflict of interest was high (the rival male was absent, or was present and looking at the signaller) chimpanzees used auditory gestures over visual/ tactile gestures. Further, the production of mating gestures was more common when the number of oestrous and non-oestrus females in the party increased, when the female was visually perceptive and when there was no wind. Females played an active role in mating behaviour, approaching for copulations more often when the number of oestrus females in the party increased and when the rival male was absent, or was present and looking away. Examining how social and ecological factors affect mating tactics in primates may thus contribute to understanding the previously unexplained reproductive success of subordinate male chimpanzees. PMID:26536467

Natural user interface as a supplement of the holographic Raman tweezers

NASA Astrophysics Data System (ADS)

Tomori, Zoltan; Kanka, Jan; Kesa, Peter; Jakl, Petr; Sery, Mojmir; Bernatova, Silvie; Antalik, Marian; Zemánek, Pavel

2014-09-01

Holographic Raman tweezers (HRT) manipulates with microobjects by controlling the positions of multiple optical traps via the mouse or joystick. Several attempts have appeared recently to exploit touch tablets, 2D cameras or Kinect game console instead. We proposed a multimodal "Natural User Interface" (NUI) approach integrating hands tracking, gestures recognition, eye tracking and speech recognition. For this purpose we exploited "Leap Motion" and "MyGaze" low-cost sensors and a simple speech recognition program "Tazti". We developed own NUI software which processes signals from the sensors and sends the control commands to HRT which subsequently controls the positions of trapping beams, micropositioning stage and the acquisition system of Raman spectra. System allows various modes of operation proper for specific tasks. Virtual tools (called "pin" and "tweezers") serving for the manipulation with particles are displayed on the transparent "overlay" window above the live camera image. Eye tracker identifies the position of the observed particle and uses it for the autofocus. Laser trap manipulation navigated by the dominant hand can be combined with the gestures recognition of the secondary hand. Speech commands recognition is useful if both hands are busy. Proposed methods make manual control of HRT more efficient and they are also a good platform for its future semi-automated and fully automated work.

Talk to the Virtual Hands: Self-Animated Avatars Improve Communication in Head-Mounted Display Virtual Environments

PubMed Central

Dodds, Trevor J.; Mohler, Betty J.; Bülthoff, Heinrich H.

2011-01-01

Background When we talk to one another face-to-face, body gestures accompany our speech. Motion tracking technology enables us to include body gestures in avatar-mediated communication, by mapping one's movements onto one's own 3D avatar in real time, so the avatar is self-animated. We conducted two experiments to investigate (a) whether head-mounted display virtual reality is useful for researching the influence of body gestures in communication; and (b) whether body gestures are used to help in communicating the meaning of a word. Participants worked in pairs and played a communication game, where one person had to describe the meanings of words to the other. Principal Findings In experiment 1, participants used significantly more hand gestures and successfully described significantly more words when nonverbal communication was available to both participants (i.e. both describing and guessing avatars were self-animated, compared with both avatars in a static neutral pose). Participants ‘passed’ (gave up describing) significantly more words when they were talking to a static avatar (no nonverbal feedback available). In experiment 2, participants' performance was significantly worse when they were talking to an avatar with a prerecorded listening animation, compared with an avatar animated by their partners' real movements. In both experiments participants used significantly more hand gestures when they played the game in the real world. Conclusions Taken together, the studies show how (a) virtual reality can be used to systematically study the influence of body gestures; (b) it is important that nonverbal communication is bidirectional (real nonverbal feedback in addition to nonverbal communication from the describing participant); and (c) there are differences in the amount of body gestures that participants use with and without the head-mounted display, and we discuss possible explanations for this and ideas for future investigation. PMID:22022442

Talk to the virtual hands: self-animated avatars improve communication in head-mounted display virtual environments.

PubMed

Dodds, Trevor J; Mohler, Betty J; Bülthoff, Heinrich H

2011-01-01

When we talk to one another face-to-face, body gestures accompany our speech. Motion tracking technology enables us to include body gestures in avatar-mediated communication, by mapping one's movements onto one's own 3D avatar in real time, so the avatar is self-animated. We conducted two experiments to investigate (a) whether head-mounted display virtual reality is useful for researching the influence of body gestures in communication; and (b) whether body gestures are used to help in communicating the meaning of a word. Participants worked in pairs and played a communication game, where one person had to describe the meanings of words to the other. In experiment 1, participants used significantly more hand gestures and successfully described significantly more words when nonverbal communication was available to both participants (i.e. both describing and guessing avatars were self-animated, compared with both avatars in a static neutral pose). Participants 'passed' (gave up describing) significantly more words when they were talking to a static avatar (no nonverbal feedback available). In experiment 2, participants' performance was significantly worse when they were talking to an avatar with a prerecorded listening animation, compared with an avatar animated by their partners' real movements. In both experiments participants used significantly more hand gestures when they played the game in the real world. Taken together, the studies show how (a) virtual reality can be used to systematically study the influence of body gestures; (b) it is important that nonverbal communication is bidirectional (real nonverbal feedback in addition to nonverbal communication from the describing participant); and (c) there are differences in the amount of body gestures that participants use with and without the head-mounted display, and we discuss possible explanations for this and ideas for future investigation.

Increased pain intensity is associated with greater verbal communication difficulty and increased production of speech and co-speech gestures.

PubMed

Rowbotham, Samantha; Wardy, April J; Lloyd, Donna M; Wearden, Alison; Holler, Judith

2014-01-01

Effective pain communication is essential if adequate treatment and support are to be provided. Pain communication is often multimodal, with sufferers utilising speech, nonverbal behaviours (such as facial expressions), and co-speech gestures (bodily movements, primarily of the hands and arms that accompany speech and can convey semantic information) to communicate their experience. Research suggests that the production of nonverbal pain behaviours is positively associated with pain intensity, but it is not known whether this is also the case for speech and co-speech gestures. The present study explored whether increased pain intensity is associated with greater speech and gesture production during face-to-face communication about acute, experimental pain. Participants (N = 26) were exposed to experimentally elicited pressure pain to the fingernail bed at high and low intensities and took part in video-recorded semi-structured interviews. Despite rating more intense pain as more difficult to communicate (t(25)  = 2.21, p =  .037), participants produced significantly longer verbal pain descriptions and more co-speech gestures in the high intensity pain condition (Words: t(25)  = 3.57, p  = .001; Gestures: t(25)  = 3.66, p =  .001). This suggests that spoken and gestural communication about pain is enhanced when pain is more intense. Thus, in addition to conveying detailed semantic information about pain, speech and co-speech gestures may provide a cue to pain intensity, with implications for the treatment and support received by pain sufferers. Future work should consider whether these findings are applicable within the context of clinical interactions about pain.

Gesturing with an injured brain: How gesture helps children with early brain injury learn linguistic constructions

PubMed Central

Özçalışkan, Şeyda; Levine, Susan C.; Goldin-Meadow, Susan

2013-01-01

Children with pre/perinatal unilateral brain lesions (PL) show remarkable plasticity for language development. Is this plasticity characterized by the same developmental trajectory that characterizes typically developing (TD) children, with gesture leading the way into speech? We explored this question, comparing 11 children with PL—matched to 30 TD children on expressive vocabulary—in the second year of life. Children with PL showed similarities to TD children for simple but not complex sentence types. Children with PL produced simple sentences across gesture and speech several months before producing them entirely in speech, exhibiting parallel delays in both gesture+speech and speech-alone. However, unlike TD children, children with PL produced complex sentence types first in speech-alone. Overall, the gesture-speech system appears to be a robust feature of language-learning for simple—but not complex—sentence constructions, acting as a harbinger of change in language development even when that language is developing in an injured brain. PMID:23217292

Exploring the Relation Between Memory, Gestural Communication, and the Emergence of Language in Infancy: A Longitudinal Study

PubMed Central

Heimann, Mikael; Strid, Karin; Smith, Lars; Tjus, Tomas; Ulvund, Stein Erik; Meltzoff, Andrew N.

2006-01-01

The relationship between recall memory, visual recognition memory, social communication, and the emergence of language skills was measured in a longitudinal study. Thirty typically developing Swedish children were tested at 6, 9 and 14 months. The result showed that, in combination, visual recognition memory at 6 months, deferred imitation at 9 months and turn-taking skills at 14 months could explain 41% of the variance in the infants’ production of communicative gestures as measured by a Swedish variant of the MacArthur Communicative Development Inventories (CDI). In this statistical model, deferred imitation stood out as the strongest predictor. PMID:16886041

Specialization of the left supramarginal gyrus for hand-independent praxis representation is not related to hand dominance.

PubMed

Króliczak, Gregory; Piper, Brian J; Frey, Scott H

2016-12-01

Data from focal brain injury and functional neuroimaging studies implicate a distributed network of parieto-fronto-temporal areas in the human left cerebral hemisphere as playing distinct roles in the representation of meaningful actions (praxis). Because these data come primarily from right-handed individuals, the relationship between left cerebral specialization for praxis representation and hand dominance remains unclear. We used functional magnetic resonance imaging (fMRI) to evaluate the hypothesis that strongly left-handed (right hemisphere motor dominant) adults also exhibit this left cerebral specialization. Participants planned familiar actions for subsequent performance with the left or right hand in response to transitive (e.g., "pounding") or intransitive (e.g. "waving") action words. In linguistic control trials, cues denoted non-physical actions (e.g., "believing"). Action planning was associated with significant, exclusively left-lateralized and extensive increases of activity in the supramarginal gyrus (SMg), and more focal modulations in the left caudal middle temporal gyrus (cMTg). This activity was hand- and gesture-independent, i.e., unaffected by the hand involved in subsequent action performance, and the type of gesture (i.e., transitive or intransitive). Compared directly with right-handers, left-handers exhibited greater involvement of the right angular gyrus (ANg) and dorsal premotor cortex (dPMC), which is indicative of a less asymmetric functional architecture for praxis representation. We therefore conclude that the organization of mechanisms involved in planning familiar actions is influenced by one's motor dominance. However, independent of hand dominance, the left SMg and cMTg are specialized for ideomotor transformations-the integration of conceptual knowledge and motor representations into meaningful actions. These findings support the view that higher-order praxis representation and lower-level motor dominance rely on dissociable

Specialization of the left supramarginal gyrus for hand-independent praxis representation is not related to hand dominance

PubMed Central

Króliczak, Gregory; Piper, Brian J.; Frey, Scott H.

2016-01-01

Data from focal brain injury and functional neuroimaging studies implicate a distributed network of parieto-fronto-temporal areas in the human left cerebral hemisphere as playing distinct roles in the representation of meaningful actions (praxis). Because these data come primarily from right-handed individuals, the relationship between left cerebral specialization for praxis representation and hand dominance remains unclear. We used functional magnetic resonance imaging (fMRI) to evaluate the hypothesis that strongly left-handed (right hemisphere motor dominant) adults also exhibit this left cerebral specialization. Participants planned familiar actions for subsequent performance with the left or right hand in response to transitive (e.g., “pounding”) or intransitive (e.g. “waving”) action words. In linguistic control trials, cues denoted non-physical actions (e.g., “believing”). Action planning was associated with significant, exclusively left-lateralized and extensive increases of activity in the supramarginal gyrus (SMg), and more focal modulations in the left caudal middle temporal gyrus (cMTg). This activity was hand- and gesture-independent, i.e., unaffected by the hand involved in subsequent action performance, and the type of gesture (i.e., transitive or intransitive). Compared directly with right-handers, left-handers exhibited greater involvement of the right angular gyrus (ANg) and dorsal premotor cortex (dPMC), which is indicative of a less asymmetric functional architecture for praxis representation. We therefore conclude that the organization of mechanisms involved in planning familiar actions is influenced by one’s motor dominance. However, independent of hand dominance, the left SMg and cMTg are specialized for ideomotor transformations—the integration of conceptual knowledge and motor representations into meaningful actions. These findings support the view that higher-order praxis representation and lower-level motor dominance rely

Data-driven approach to human motion modeling with Lua and gesture description language

NASA Astrophysics Data System (ADS)

Hachaj, Tomasz; Koptyra, Katarzyna; Ogiela, Marek R.

2017-03-01

The aim of this paper is to present the novel proposition of the human motion modelling and recognition approach that enables real time MoCap signal evaluation. By motions (actions) recognition we mean classification. The role of this approach is to propose the syntactic description procedure that can be easily understood, learnt and used in various motion modelling and recognition tasks in all MoCap systems no matter if they are vision or wearable sensor based. To do so we have prepared extension of Gesture Description Language (GDL) methodology that enables movements description and real-time recognition so that it can use not only positional coordinates of body joints but virtually any type of discreetly measured output MoCap signals like accelerometer, magnetometer or gyroscope. We have also prepared and evaluated the cross-platform implementation of this approach using Lua scripting language and JAVA technology. This implementation is called Data Driven GDL (DD-GDL). In tested scenarios the average execution speed is above 100 frames per second which is an acquisition time of many popular MoCap solutions.

Vocal Generalization Depends on Gesture Identity and Sequence

PubMed Central

Sober, Samuel J.

2014-01-01

Generalization, the brain's ability to transfer motor learning from one context to another, occurs in a wide range of complex behaviors. However, the rules of generalization in vocal behavior are poorly understood, and it is unknown how vocal learning generalizes across an animal's entire repertoire of natural vocalizations and sequences. Here, we asked whether generalization occurs in a nonhuman vocal learner and quantified its properties. We hypothesized that adaptive error correction of a vocal gesture produced in one sequence would generalize to the same gesture produced in other sequences. To test our hypothesis, we manipulated the fundamental frequency (pitch) of auditory feedback in Bengalese finches (Lonchura striata var. domestica) to create sensory errors during vocal gestures (song syllables) produced in particular sequences. As hypothesized, error-corrective learning on pitch-shifted vocal gestures generalized to the same gestures produced in other sequential contexts. Surprisingly, generalization magnitude depended strongly on sequential distance from the pitch-shifted syllables, with greater adaptation for gestures produced near to the pitch-shifted syllable. A further unexpected result was that nonshifted syllables changed their pitch in the direction opposite from the shifted syllables. This apparently antiadaptive pattern of generalization could not be explained by correlations between generalization and the acoustic similarity to the pitch-shifted syllable. These findings therefore suggest that generalization depends on the type of vocal gesture and its sequential context relative to other gestures and may reflect an advantageous strategy for vocal learning and maintenance. PMID:24741046

Effects of Isometric Hand-Grip Muscle Contraction on Young Adults' Free Recall and Recognition Memory

ERIC Educational Resources Information Center

Tomporowski, Phillip D.; Albrecht, Chelesa; Pendleton, Daniel M.

2017-01-01

Purpose: The purpose of this study was to determine if physical arousal produced by isometric hand-dynamometer contraction performed during word-list learning affects young adults' free recall or recognition memory. Method: Twenty-four young adults (12 female; M[subscript age] = 22 years) were presented with 4 20-item word lists. Moderate arousal…

GestuRe and ACtion Exemplar (GRACE) video database: stimuli for research on manners of human locomotion and iconic gestures.

PubMed

Aussems, Suzanne; Kwok, Natasha; Kita, Sotaro

2018-06-01

Human locomotion is a fundamental class of events, and manners of locomotion (e.g., how the limbs are used to achieve a change of location) are commonly encoded in language and gesture. To our knowledge, there is no openly accessible database containing normed human locomotion stimuli. Therefore, we introduce the GestuRe and ACtion Exemplar (GRACE) video database, which contains 676 videos of actors performing novel manners of human locomotion (i.e., moving from one location to another in an unusual manner) and videos of a female actor producing iconic gestures that represent these actions. The usefulness of the database was demonstrated across four norming experiments. First, our database contains clear matches and mismatches between iconic gesture videos and action videos. Second, the male actors and female actors whose action videos matched the gestures in the best possible way, perform the same actions in very similar manners and different actions in highly distinct manners. Third, all the actions in the database are distinct from each other. Fourth, adult native English speakers were unable to describe the 26 different actions concisely, indicating that the actions are unusual. This normed stimuli set is useful for experimental psychologists working in the language, gesture, visual perception, categorization, memory, and other related domains.

Coding gestural behavior with the NEUROGES--ELAN system.

PubMed

Lausberg, Hedda; Sloetjes, Han

2009-08-01

We present a coding system combined with an annotation tool for the analysis of gestural behavior. The NEUROGES coding system consists of three modules that progress from gesture kinetics to gesture function. Grounded on empirical neuropsychological and psychological studies, the theoretical assumption behind NEUROGES is that its main kinetic and functional movement categories are differentially associated with specific cognitive, emotional, and interactive functions. ELAN is a free, multimodal annotation tool for digital audio and video media. It supports multileveled transcription and complies with such standards as XML and Unicode. ELAN allows gesture categories to be stored with associated vocabularies that are reusable by means of template files. The combination of the NEUROGES coding system and the annotation tool ELAN creates an effective tool for empirical research on gestural behavior.

Gesture analysis of students' majoring mathematics education in micro teaching process

NASA Astrophysics Data System (ADS)

Maldini, Agnesya; Usodo, Budi; Subanti, Sri

2017-08-01

In the process of learning, especially math learning, process of interaction between teachers and students is certainly a noteworthy thing. In these interactions appear gestures or other body spontaneously. Gesture is an important source of information, because it supports oral communication and reduce the ambiguity of understanding the concept/meaning of the material and improve posture. This research which is particularly suitable for an exploratory research design to provide an initial illustration of the phenomenon. The goal of the research in this article is to describe the gesture of S1 and S2 students of mathematics education at the micro teaching process. To analyze gesture subjects, researchers used McNeil clarification. The result is two subjects using 238 gesture in the process of micro teaching as a means of conveying ideas and concepts in mathematics learning. During the process of micro teaching, subjects using the four types of gesture that is iconic gestures, deictic gesture, regulator gesturesand adapter gesture as a means to facilitate the delivery of the intent of the material being taught and communication to the listener. Variance gesture that appear on the subject due to the subject using a different gesture patterns to communicate mathematical ideas of their own so that the intensity of gesture that appeared too different.

Multimodal interfaces with voice and gesture input

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

Milota, A.D.; Blattner, M.M.

1995-07-20

The modalities of speech and gesture have different strengths and weaknesses, but combined they create synergy where each modality corrects the weaknesses of the other. We believe that a multimodal system such a one interwining speech and gesture must start from a different foundation than ones which are based solely on pen input. In order to provide a basis for the design of a speech and gesture system, we have examined the research in other disciplines such as anthropology and linguistics. The result of this investigation was a taxonomy that gave us material for the incorporation of gestures whose meaningsmore » are largely transparent to the users. This study describes the taxonomy and gives examples of applications to pen input systems.« less

With Some Help from Others' Hands: Iconic Gesture Helps Semantic Learning in Children with Specific Language Impairment

ERIC Educational Resources Information Center

Vogt, Susanne S.; Kauschke, Christina

2017-01-01

Purpose: Semantic learning under 2 co-speech gesture conditions was investigated in children with specific language impairment (SLI) and typically developing (TD) children. Learning was analyzed between conditions. Method: Twenty children with SLI (aged 4 years), 20 TD children matched for age, and 20 TD children matched for language scores were…

Development of the bedridden person support system using hand gesture.

PubMed

Ichimura, Kouhei; Magatani, Kazushige

2015-08-01

The purpose of this study is to support the bedridden and physically handicapped person who live independently. In this study, we developed Electric appliances control system that can be used on the bed. The subject can control Electric appliances using hand motion. Infrared sensors of a Kinect are used for the hand motion detection. Our developed system was tested with some normal subjects and results of the experiment were evaluated. In this experiment, all subjects laid on the bed and tried to control our system. As results, most of subjects were able to control our developed system perfectly. However, motion tracking of some subject's hand was reset forcibly. It was difficult for these subjects to make the system recognize his opened hand. From these results, we think if this problem will be improved our support system will be useful for the bedridden and physically handicapped persons.

Referring to Actions and Objects in Co-Speech Gesture Production

ERIC Educational Resources Information Center

Keily, Holly

2017-01-01

A number of theories exist to explain why people gesture when speaking, when they produce gesture, and the origin of their gestures. This dissertation focuses on four individual variables that can influence gesture: (i) familiarity, (ii) imageability, (iii) codability, and (iv) motor experience. Four experiments were designed to determine how each…

Novel calcium recognition constructions in proteins: Calcium blade and EF-hand zone

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

Denesyuk, Alexander I., E-mail: adenesyu@abo.fi; Institute for Biological Instrumentation of the Russian Academy of Sciences, Pushchino 142290; Permyakov, Sergei E.

Metal ions can regulate various cell processes being first, second or third messengers, and some of them, especially transition metal ions, take part in catalysis in many enzymes. As an intracellular ion, Ca{sup 2+} is involved in many cellular functions from fertilization and contraction, cell differentiation and proliferation, to apoptosis and cancer. Here, we have identified and described two novel calcium recognition environments in proteins: the calcium blade zone and the EF-hand zone, common to 12 and 8 different protein families, respectively. Each of the two environments contains three distinct structural elements: (a) the well-known characteristic Dx[DN]xDG motif; (b) anmore » adjacent structurally identical segment, which binds metal ion in the same way between the calcium blade zone and the EF-hand zone; and (c) the following structurally variable segment, which distinguishes the calcium blade zone from the EF-hand zone. Both zones have sequence insertions between the last residue of the zone and calcium-binding residues in positions V or VI. The long insertion often connects the active and the calcium-binding sites in proteins. Using the structurally identical segments as an anchor, we were able to construct the classical calmodulin type EF-hand calcium-binding site out of two different calcium-binding motifs from two unrelated proteins.« less

An observational study of implicit motor imagery using laterality recognition of the hand after stroke.

PubMed

Amesz, Sarah; Tessari, Alessia; Ottoboni, Giovanni; Marsden, Jon

2016-01-01

To explore the relationship between laterality recognition after stroke and impairments in attention, 3D object rotation and functional ability. Observational cross-sectional study. Acute care teaching hospital. Thirty-two acute and sub-acute people with stroke and 36 healthy, age-matched controls. Laterality recognition, attention and mental rotation of objects. Within the stroke group, the relationship between laterality recognition and functional ability, neglect, hemianopia and dyspraxia were further explored. People with stroke were significantly less accurate (69% vs 80%) and showed delayed reaction times (3.0 vs 1.9 seconds) when determining the laterality of a pictured hand. Deficits either in accuracy or reaction times were seen in 53% of people with stroke. The accuracy of laterality recognition was associated with reduced functional ability (R(2) = 0.21), less accurate mental rotation of objects (R(2) = 0.20) and dyspraxia (p = 0.03). Implicit motor imagery is affected in a significant number of patients after stroke with these deficits related to lesions to the motor networks as well as other deficits seen after stroke. This research provides new insights into how laterality recognition is related to a number of other deficits after stroke, including the mental rotation of 3D objects, attention and dyspraxia. Further research is required to determine if treatment programmes can improve deficits in laterality recognition and impact functional outcomes after stroke.

From gesture to sign language: conventionalization of classifier constructions by adult hearing learners of British Sign Language.

PubMed

Marshall, Chloë R; Morgan, Gary

2015-01-01

There has long been interest in why languages are shaped the way they are, and in the relationship between sign language and gesture. In sign languages, entity classifiers are handshapes that encode how objects move, how they are located relative to one another, and how multiple objects of the same type are distributed in space. Previous studies have shown that hearing adults who are asked to use only manual gestures to describe how objects move in space will use gestures that bear some similarities to classifiers. We investigated how accurately hearing adults, who had been learning British Sign Language (BSL) for 1-3 years, produce and comprehend classifiers in (static) locative and distributive constructions. In a production task, learners of BSL knew that they could use their hands to represent objects, but they had difficulty choosing the same, conventionalized, handshapes as native signers. They were, however, highly accurate at encoding location and orientation information. Learners therefore show the same pattern found in sign-naïve gesturers. In contrast, handshape, orientation, and location were comprehended with equal (high) accuracy, and testing a group of sign-naïve adults showed that they too were able to understand classifiers with higher than chance accuracy. We conclude that adult learners of BSL bring their visuo-spatial knowledge and gestural abilities to the tasks of understanding and producing constructions that contain entity classifiers. We speculate that investigating the time course of adult sign language acquisition might shed light on how gesture became (and, indeed, becomes) conventionalized during the genesis of sign languages. Copyright © 2014 Cognitive Science Society, Inc.

Perception of co-speech gestures in aphasic patients: a visual exploration study during the observation of dyadic conversations.

PubMed

Preisig, Basil C; Eggenberger, Noëmi; Zito, Giuseppe; Vanbellingen, Tim; Schumacher, Rahel; Hopfner, Simone; Nyffeler, Thomas; Gutbrod, Klemens; Annoni, Jean-Marie; Bohlhalter, Stephan; Müri, René M

2015-03-01

Co-speech gestures are part of nonverbal communication during conversations. They either support the verbal message or provide the interlocutor with additional information. Furthermore, they prompt as nonverbal cues the cooperative process of turn taking. In the present study, we investigated the influence of co-speech gestures on the perception of dyadic dialogue in aphasic patients. In particular, we analysed the impact of co-speech gestures on gaze direction (towards speaker or listener) and fixation of body parts. We hypothesized that aphasic patients, who are restricted in verbal comprehension, adapt their visual exploration strategies. Sixteen aphasic patients and 23 healthy control subjects participated in the study. Visual exploration behaviour was measured by means of a contact-free infrared eye-tracker while subjects were watching videos depicting spontaneous dialogues between two individuals. Cumulative fixation duration and mean fixation duration were calculated for the factors co-speech gesture (present and absent), gaze direction (to the speaker or to the listener), and region of interest (ROI), including hands, face, and body. Both aphasic patients and healthy controls mainly fixated the speaker's face. We found a significant co-speech gesture × ROI interaction, indicating that the presence of a co-speech gesture encouraged subjects to look at the speaker. Further, there was a significant gaze direction × ROI × group interaction revealing that aphasic patients showed reduced cumulative fixation duration on the speaker's face compared to healthy controls. Co-speech gestures guide the observer's attention towards the speaker, the source of semantic input. It is discussed whether an underlying semantic processing deficit or a deficit to integrate audio-visual information may cause aphasic patients to explore less the speaker's face. Copyright © 2014 Elsevier Ltd. All rights reserved.

Individual differences in mental rotation: what does gesture tell us?

PubMed

Göksun, Tilbe; Goldin-Meadow, Susan; Newcombe, Nora; Shipley, Thomas

2013-05-01

Gestures are common when people convey spatial information, for example, when they give directions or describe motion in space. Here, we examine the gestures speakers produce when they explain how they solved mental rotation problems (Shepard and Meltzer in Science 171:701-703, 1971). We asked whether speakers gesture differently while describing their problems as a function of their spatial abilities. We found that low-spatial individuals (as assessed by a standard paper-and-pencil measure) gestured more to explain their solutions than high-spatial individuals. While this finding may seem surprising, finer-grained analyses showed that low-spatial participants used gestures more often than high-spatial participants to convey "static only" information but less often than high-spatial participants to convey dynamic information. Furthermore, the groups differed in the types of gestures used to convey static information: high-spatial individuals were more likely than low-spatial individuals to use gestures that captured the internal structure of the block forms. Our gesture findings thus suggest that encoding block structure may be as important as rotating the blocks in mental spatial transformation.

Gestures: Silent Scaffolding within Small Groups

ERIC Educational Resources Information Center

Carter, Glenda; Wiebe, Eric N.; Reid-Griffin, Angela

2006-01-01

This paper describes how gestures are used to enhance scaffolding that occurs in small group settings. Sixth and eighth grade students participated in an elective science course focused on earth science concepts with a substantial spatial visualization component. Gestures that students used in small group discussions were analyzed and four…

The impact of impaired semantic knowledge on spontaneous iconic gesture production

PubMed Central

Cocks, Naomi; Dipper, Lucy; Pritchard, Madeleine; Morgan, Gary

2013-01-01

Background Previous research has found that people with aphasia produce more spontaneous iconic gesture than control participants, especially during word-finding difficulties. There is some evidence that impaired semantic knowledge impacts on the diversity of gestural handshapes, as well as the frequency of gesture production. However, no previous research has explored how impaired semantic knowledge impacts on the frequency and type of iconic gestures produced during fluent speech compared with those produced during word-finding difficulties. Aims To explore the impact of impaired semantic knowledge on the frequency and type of iconic gestures produced during fluent speech and those produced during word-finding difficulties. Methods & Procedures A group of 29 participants with aphasia and 29 control participants were video recorded describing a cartoon they had just watched. All iconic gestures were tagged and coded as either “manner,” “path only,” “shape outline” or “other”. These gestures were then separated into either those occurring during fluent speech or those occurring during a word-finding difficulty. The relationships between semantic knowledge and gesture frequency and form were then investigated in the two different conditions. Outcomes & Results As expected, the participants with aphasia produced a higher frequency of iconic gestures than the control participants, but when the iconic gestures produced during word-finding difficulties were removed from the analysis, the frequency of iconic gesture was not significantly different between the groups. While there was not a significant relationship between the frequency of iconic gestures produced during fluent speech and semantic knowledge, there was a significant positive correlation between semantic knowledge and the proportion of word-finding difficulties that contained gesture. There was also a significant positive correlation between the speakers' semantic knowledge and the proportion

Young children make their gestural communication systems more language-like: segmentation and linearization of semantic elements in motion events.

PubMed

Clay, Zanna; Pople, Sally; Hood, Bruce; Kita, Sotaro

2014-08-01

Research on Nicaraguan Sign Language, created by deaf children, has suggested that young children use gestures to segment the semantic elements of events and linearize them in ways similar to those used in signed and spoken languages. However, it is unclear whether this is due to children's learning processes or to a more general effect of iterative learning. We investigated whether typically developing children, without iterative learning, segment and linearize information. Gestures produced in the absence of speech to express a motion event were examined in 4-year-olds, 12-year-olds, and adults (all native English speakers). We compared the proportions of gestural expressions that segmented semantic elements into linear sequences and that encoded them simultaneously. Compared with adolescents and adults, children reshaped the holistic stimuli by segmenting and recombining their semantic features into linearized sequences. A control task on recognition memory ruled out the possibility that this was due to different event perception or memory. Young children spontaneously bring fundamental properties of language into their communication system. © The Author(s) 2014.

[Verbal and gestural communication in interpersonal interaction with Alzheimer's disease patients].

PubMed

Schiaratura, Loris Tamara; Di Pastena, Angela; Askevis-Leherpeux, Françoise; Clément, Sylvain

2015-03-01

Communication can be defined as a verbal and non verbal exchange of thoughts and emotions. While verbal communication deficit in Alzheimer's disease is well documented, very little is known about gestural communication, especially in interpersonal situations. This study examines the production of gestures and its relations with verbal aspects of communication. Three patients suffering from moderately severe Alzheimer's disease were compared to three healthy adults. Each one were given a series of pictures and asked to explain which one she preferred and why. The interpersonal interaction was video recorded. Analyses concerned verbal production (quantity and quality) and gestures. Gestures were either non representational (i.e., gestures of small amplitude punctuating speech or accentuating some parts of utterance) or representational (i.e., referring to the object of the speech). Representational gestures were coded as iconic (depicting of concrete aspects), metaphoric (depicting of abstract meaning) or deictic (pointing toward an object). In comparison with healthy participants, patients revealed a decrease in quantity and quality of speech. Nevertheless, their production of gestures was always present. This pattern is in line with the conception that gestures and speech depend on different communicational systems and look inconsistent with the assumption of a parallel dissolution of gesture and speech. Moreover, analyzing the articulation between verbal and gestural dimensions suggests that representational gestures may compensate for speech deficits. It underlines the importance for the role of gestures in maintaining interpersonal communication.

Verbal working memory predicts co-speech gesture: evidence from individual differences.

PubMed

Gillespie, Maureen; James, Ariel N; Federmeier, Kara D; Watson, Duane G

2014-08-01

Gesture facilitates language production, but there is debate surrounding its exact role. It has been argued that gestures lighten the load on verbal working memory (VWM; Goldin-Meadow, Nusbaum, Kelly, & Wagner, 2001), but gestures have also been argued to aid in lexical retrieval (Krauss, 1998). In the current study, 50 speakers completed an individual differences battery that included measures of VWM and lexical retrieval. To elicit gesture, each speaker described short cartoon clips immediately after viewing. Measures of lexical retrieval did not predict spontaneous gesture rates, but lower VWM was associated with higher gesture rates, suggesting that gestures can facilitate language production by supporting VWM when resources are taxed. These data also suggest that individual variability in the propensity to gesture is partly linked to cognitive capacities. Copyright © 2014 Elsevier B.V. All rights reserved.