Download or read book Force Myography Signal Based Hand Gesture Classification for the Implementation of Real Time Prosthetic Hand Control System written by Nguon Ha and published by . This book was released on 2017 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis aims to develop an interfacing mechanism for controlling prosthetic devices using Force Myography signal (FMG) and various hand gesture classifications. The FMG signals have been collected through three piezoelectric sensors banded around the forearm and Omega Data Acquisition (DAQ) System. The recorded data has been imported into Matlab, Simulink software for analysis and classification. The hand motion has been recorded through Virtual Motion Glove (VMG), and utilized in the system identification procedure to find out the dynamic relationship between the hand gesture and the corresponding FMG signals. Several classification and recognition models have been considered. Tree Decision Learning and Support Vector Machine (SVM) showed high accuracy results. Both of these estimated models generate above 82% of accuracy in terms of classification. The feasibility of the FMG signal for the implementation of a control system in the prosthetic hand is also tested. The result shows a high degree of accuracy in replicating the grasping gestures using threshold method. To limit and control, both the position and the amount of force applied at the fingertips of a prosthetic hand, a dynamic relationship has been established with the corresponding FMG signal through system identification method. These relationships will provide a useful foundation for the implementation and utilization of control system in an assistive device. In order to see the performance of FMG over electromyography (EMG), a comparative analysis has been performed by collecting EMG signals from the same groups of muscles. Unlike EMG, FMG signal is not affected by sweat, skin impedance, and doesn't need a reference signal.
Download or read book Pattern Recognition of Surface Electromyography Signals for Real time Control of Wrist Exoskeletons written by Zeeshan Omer Khokhar and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surface electromyography (sEMG) signals have been used in numerous studies for the classification of hand gestures and successfully implemented in the position control of different prosthetic hands. An estimation of the intended torque of the user could also provide sufficient information for an effective force control of hand prosthesis or an assistive device. This thesis presents the use of pattern recognition to estimate the torque applied by a human wrist and its real-time implementation to control an exoskeleton prototype that can function as an assistive device. Data from eight volunteers was gathered and Support Vector Machines (SVM) was used for classification. An average testing accuracy of 88% was achieved for nineteen classes. The classification and control algorithm implemented was executed in less than 125 ms. The results of this study showed that real-time classification of sEMG using SVM for controlling an exoskeleton is feasible.
Download or read book Robust Hand Gesture Recognition for Robotic Hand Control written by Ankit Chaudhary and published by Springer. This book was released on 2017-06-05 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on light invariant bare hand gesture recognition while there is no restriction on the types of gestures. Observations and results have confirmed that this research work can be used to remotely control a robotic hand using hand gestures. The system developed here is also able to recognize hand gestures in different lighting conditions. The pre-processing is performed by developing an image-cropping algorithm that ensures only the area of interest is included in the segmented image. The segmented image is compared with a predefined gesture set which must be installed in the recognition system. These images are stored and feature vectors are extracted from them. These feature vectors are subsequently presented using an orientation histogram, which provides a view of the edges in the form of frequency. Thereby, if the same gesture is shown twice in different lighting intensities, both repetitions will map to the same gesture in the stored data. The mapping of the segmented image's orientation histogram is firstly done using the Euclidian distance method. Secondly, the supervised neural network is trained for the same, producing better recognition results. An approach to controlling electro-mechanical robotic hands using dynamic hand gestures is also presented using a robot simulator. Such robotic hands have applications in commercial, military or emergency operations where human life cannot be risked. For such applications, an artificial robotic hand is required to perform real-time operations. This robotic hand should be able to move its fingers in the same manner as a human hand. For this purpose, hand geometry parameters are obtained using a webcam and also using KINECT. The parameter detection is direction invariant in both methods. Once the hand parameters are obtained, the fingers’ angle information is obtained by performing a geometrical analysis. An artificial neural network is also implemented to calculate the angles. These two methods can be used with only one hand, either right or left. A separate method that is applicable to both hands simultaneously is also developed and fingers angles are calculated. The contents of this book will be useful for researchers and professional engineers working on robotic arm/hand systems.
Download or read book Challenges and Applications for Hand Gesture Recognition written by Kane, Lalit and published by IGI Global. This book was released on 2022-03-25 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the rise of new applications in electronic appliances and pervasive devices, automated hand gesture recognition (HGR) has become an area of increasing interest. HGR developments have come a long way from the traditional sign language recognition (SLR) systems to depth and wearable sensor-based electronic devices. Where the former are more laboratory-oriented frameworks, the latter are comparatively realistic and practical systems. Based on various gestural traits, such as hand postures, gesture recognition takes different forms. Consequently, different interpretations can be associated with gestures in various application contexts. A considerable amount of research is still needed to introduce more practical gesture recognition systems and associated algorithms. Challenges and Applications for Hand Gesture Recognition highlights the state-of-the-art practices of HGR research and discusses key areas such as challenges, opportunities, and future directions. Covering a range of topics such as wearable sensors and hand kinematics, this critical reference source is ideal for researchers, academicians, scholars, industry professionals, engineers, instructors, and students.
Download or read book EMG Controlled Prosthetic Hand with Fuzzy Logic Classification Algorithm written by Beyda Taşar and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, researchers have conducted many studies on the design and control of prosthesis devices that take the place of a missing limb. Functional ability of prosthesis hands that mimic biological hand functions increases depending on the number of independent finger movements possible. From this perspective, in this study, six different finger movements were given to a prosthesis hand via bioelectrical signals, and the functionality of the prosthesis hand was increased. Bioelectrical signals were recorded by surface electromyography for four muscles with the help of surface electrodes. The recorded bioelectrical signals were subjected to a series of preprocessing and feature extraction processes. In order to create meaningful patterns of motion and an effective cognitive interaction network between the human and the prosthetic hand, fuzzy logic classification algorithms were developed. A five-fingered and 15-jointed prosthetic hand was designed via SolidWorks, and a prosthetic prototype was produced by a 3D printer. In addition, prosthetic hand simulator was designed in Matlab/SimMechanics. Pattern control of both the simulator and the prototype hand in real time was achieved. Position control of motors connected to each joint of the prosthetic hand was provided by a PID controller. Thus, an effective cognitive communication network established between the user, and the real-time pattern control of the prosthesis was provided by bioelectrical signals.
Download or read book Surface Electromyography written by Roberto Merletti and published by John Wiley & Sons. This book was released on 2016-05-02 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reflects on developments in noninvasive electromyography, and includes advances and applications in signal detection, processing and interpretation Addresses EMG imaging technology together with the issue of decomposition of surface EMG Includes advanced single and multi-channel techniques for information extraction from surface EMG signals Presents the analysis and information extraction of surface EMG at various scales, from motor units to the concept of muscle synergies.
Download or read book Advances in Digital Health and Medical Bioengineering written by Hariton-Nicolae Costin and published by Springer Nature. This book was released on with total page 849 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Real time Hand Gesture Detection and Recognition for Human Computer Interaction written by Nasser Hasan Abdel-Qader Dardas and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on bare hand gesture recognition by proposing a new architecture to solve the problem of real-time vision-based hand detection, tracking, and gesture recognition for interaction with an application via hand gestures. The first stage of our system allows detecting and tracking a bare hand in a cluttered background using face subtraction, skin detection and contour comparison. The second stage allows recognizing hand gestures using bag-of-features and multi-class Support Vector Machine (SVM) algorithms. Finally, a grammar has been developed to generate gesture commands for application control. Our hand gesture recognition system consists of two steps: offline training and online testing. In the training stage, after extracting the keypoints for every training image using the Scale Invariance Feature Transform (SIFT), a vector quantization technique will map keypoints from every training image into a unified dimensional histogram vector (bag-of-words) after K-means clustering. This histogram is treated as an input vector for a multi-class SVM to build the classifier. In the testing stage, for every frame captured from a webcam, the hand is detected using my algorithm. Then, the keypoints are extracted for every small image that contains the detected hand posture and fed into the cluster model to map them into a bag-of-words vector, which is fed into the multi-class SVM classifier to recognize the hand gesture. Another hand gesture recognition system was proposed using Principle Components Analysis (PCA). The most eigenvectors and weights of training images are determined. In the testing stage, the hand posture is detected for every frame using my algorithm. Then, the small image that contains the detected hand is projected onto the most eigenvectors of training images to form its test weights. Finally, the minimum Euclidean distance is determined among the test weights and the training weights of each training image to recognize the hand gesture. Two application of gesture-based interaction with a 3D gaming virtual environment were implemented. The exertion videogame makes use of a stationary bicycle as one of the main inputs for game playing. The user can control and direct left-right movement and shooting actions in the game by a set of hand gesture commands, while in the second game, the user can control and direct a helicopter over the city by a set of hand gesture commands.
Download or read book Interfacing Humans and Machines for Rehabilitation and Assistive Devices written by Carlos A. Cifuentes and published by Frontiers Media SA. This book was released on 2022-01-24 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr Jan Veneman is employed by Hocoma AG. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
Download or read book Proceeding of the 3rd International Conference on Electronics Biomedical Engineering and Health Informatics written by Triwiyanto Triwiyanto and published by Springer Nature. This book was released on 2023-05-31 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents high-quality peer-reviewed papers from the International Conference on Electronics, Biomedical Engineering, and Health Informatics (ICEBEHI) 2022 held at Surabaya, Indonesia, virtually. The contents are broadly divided into three parts: (a) Electronics, (b) Biomedical Engineering, and (c) Health Informatics. The major focus is on emerging technologies and their applications in the domain of biomedical engineering. It includes papers based on original theoretical, practical, and experimental simulations, development, applications, measurements, and testing. Featuring the latest advances in the field of biomedical engineering applications, this book serves as a definitive reference resource for researchers, professors, and practitioners interested in exploring advanced techniques in the fields of electronics, biomedical engineering, and health informatics. The applications and solutions discussed here provide excellent reference material for future product development.
Download or read book Multi modal EMG based Hand Gesture Classification for the Control of a Robotic Prosthetic Hand written by Iris Kyranou and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Human Like Advances in Robotics Motion Actuation Sensing Cognition and Control written by Tadej Petric and published by Frontiers Media SA. This book was released on 2019-12-24 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Real time Pattern Recognition for Prosthetic Hand written by Mario Alejandro Benítez López and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Control of myoelectric prosthetic hands is still an open problem, currently, most commercial prostheses use direct, proportional or Finite State Machine control for this purpose. However, as mechanical design advances, more dexterous prostheses with more degrees of freedom (DOF) are created, then a more precise and intuitive control for the user is required. State of the art has focused in the use of pattern recognition as a control strategy with promising results. Studies have shown similar results to classic control strategies with the advantage of being more intuitive for the user. Many works have tried to find the algorithms that best follows the user?s intention. However, deployment of these algorithms for realtime classification in a prosthesis has not been widely explored. This project addresses this problem by deploying and testing in real-time an artificial neural network (ANN). The ANN was trained to classify three different motions: no grasp, precision grasp and power grasp in order to control a two DOF trans-radial prosthetic hand with electromyographic signals acquired from two channels. Static and dynamic tests were made to evaluate the ANN under those conditions, 95% and 81% accuracy scores were reached respectively. Our work shows the potential of pattern recognition algorithms to be deployed in microcontrollers that can fit inside myoelectric prostheses. On the other hand, a prototype of a prosthetic hand that is able to physically replicate the classified actions was developed.
Download or read book Novel Methods for Robust Real time Hand Gesture Interfaces written by Nathaniel Sean Rossol and published by . This book was released on 2015 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-time control of visual display systems via mid-air hand gestures offers many advantages over traditional interaction modalities. In medicine, for example, it allows a practitioner to adjust display values, e.g. contrast or zoom, on a medical visualization interface without the need to re-sterilize the interface. However, there are many practical challenges that make such interfaces non-robust including poor tracking due to frequent occlusion of fingers, interference from hand-held objects, and complex interfaces that are difficult for users to learn to use efficiently. In this work, various techniques are explored for improving the robustness of computer interfaces that use hand gestures. This work is focused predominately on real-time markerless Computer Vision (CV) based tracking methods with an emphasis on systems with high sampling rates. First, we explore a novel approach to increase hand pose estimation accuracy from multiple sensors at high sampling rates in real-time. This approach is achieved through an intelligent analysis of pose estimations from multiple sensors in a way that is highly scalable because raw image data is not transmitted between devices. Experimental results demonstrate that our proposed technique significantly improves the pose estimation accuracy while still maintaining the ability to capture individual hand poses at over 120 frames per second. Next, we explore techniques for improving pose estimation for the purposes of gesture recognition in situations where only a single sensor is used at high sampling rates without image data. In this situation, we demonstrate an approach where a combination of kinematic constraints and computed heuristics are used to estimate occluded keypoints to produce a partial pose estimation of a user's hand which is then used with our gestures recognition system to control a display. The results of our user study demonstrate that the proposed algorithm significantly improves the gesture recognition rate of the setup. We then explore gesture interface designs for situations where the user may (or may not) have a large portion of their hand occluded by a hand-held tool while gesturing. We address this challenge by developing a novel interface that uses a single set of gestures designed to be equally effective for fingers and hand-held tools without the need for any markers. The effectiveness of our approach is validated through a user study on a group of people given the task of adjusting parameters on a medical image display. Finally, we examine improving the efficiency of training for our interfaces by automatically assessing key user performance metrics (such as dexterity and confidence), and adapting the interface accordingly to reduce user frustration. We achieve this through a framework that uses Bayesian networks to estimate values for abstract hidden variables in our user model, based on analysis of data recorded from the user during operation of our system.
Download or read book Event Based Neuromorphic Systems written by Shih-Chii Liu and published by John Wiley & Sons. This book was released on 2015-02-16 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuromorphic electronic engineering takes its inspiration from the functioning of nervous systems to build more power efficient electronic sensors and processors. Event-based neuromorphic systems are inspired by the brain's efficient data-driven communication design, which is key to its quick responses and remarkable capabilities. This cross-disciplinary text establishes how circuit building blocks are combined in architectures to construct complete systems. These include vision and auditory sensors as well as neuronal processing and learning circuits that implement models of nervous systems. Techniques for building multi-chip scalable systems are considered throughout the book, including methods for dealing with transistor mismatch, extensive discussions of communication and interfacing, and making systems that operate in the real world. The book also provides historical context that helps relate the architectures and circuits to each other and that guides readers to the extensive literature. Chapters are written by founding experts and have been extensively edited for overall coherence. This pioneering text is an indispensable resource for practicing neuromorphic electronic engineers, advanced electrical engineering and computer science students and researchers interested in neuromorphic systems. Key features: Summarises the latest design approaches, applications, and future challenges in the field of neuromorphic engineering. Presents examples of practical applications of neuromorphic design principles. Covers address-event communication, retinas, cochleas, locomotion, learning theory, neurons, synapses, floating gate circuits, hardware and software infrastructure, algorithms, and future challenges.
Download or read book Real time Static Hand Gesture Recognition Using a Novel Automatic Bubble Standardization Process to Prepare Monochromatic Thermal Hand Images for Gesture Classification written by James Michael Ballow and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Control of Prosthetic Hands written by Kianoush Nazarpour and published by . This book was released on 2020 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book brings together research from laboratories across the world, offering a global perspective on advances in prosthetic hand control. State-of-the-art control of prosthetics in laboratories and clinical spaces are presented and challenges discussed, and effects of user training on control of prosthetics are also highlighted.
