Download or read book Robust and Reliable Hand Gesture Recognition for Myoelectric Control written by Yuzhou Lin and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 Robust Dynamic Hand Gesture Recognition System with Sparse Steric Haar like Feature written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Adaptive Frameworks for Robust Myoelectric Hand Gesture Prediction Using Machine Learning and Deep Learning written by Carl Robinson and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Robust Intent Recognition for the Control of Myoelectric Lower Limb Prostheses written by Howard John Hillstrom and published by . This book was released on 1989 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Novel Cost Measures for Robust Recognition of Dynamic Hand Gestures written by Ameya Kulkarni and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision aided automatic hand gesture recognition system plays a vital role in real world human computer interaction applications such as sign language recognition, game controls, virtual reality, intelligent home appliances and assistive robotics. In such systems, when input with a video sequence, the challenging task is to locate the gesturing hand (spatial segmentation) and determine when the gesture starts and ends (temporal segmentation). In this thesis, we use a framework which at its principal has a dynamic space time warping (DSTW) algorithm to simultaneously localize gesturing hand, to find an optimal alignment in time domain between query-model sequences and to compute a matching cost (a measure of how well the query sequence matches with the model sequence) for the query-model pair. Within the context of DSTW, the thesis proposes few novel cost measures to improve the performance of the framework for robust recognition of hand gesture with the help of translation and scale invariant feature vectors extracted at each frame of the input video. The performance of the system is evaluated in a real world scene with cluttered background and in presence of multiple moving skin colored distractors in the background.

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 Robust Real time Hand Tracking and Gesture Recognition Using Smart Snakes written by Tony Heap and published by . This book was released on 1995 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Real time Dynamic Hand Shape Gesture Controller written by Rajesh Radhakrishnan and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this thesis is to build a real time gesture recognition system which can spot and recognize specific gestures from continuous stream of input video. We address the recognition of single handed dynamic gestures. We have considered gestures which are sequences of distinct hand poses. Gestures are classified based on their hand poses and its nature of motion. The recognition strategy uses a combination of spatial hand shape recognition using chamfer distance measure and temporal characteristics through dynamic programming. The system is fairly robust to background clutter and uses skin color for tracking. Gestures are an important modality for human-machine communication, and robust gesture recognition can be an important component of intelligent homes and assistive environments in general. Challenging task in a robust recognition system is the amount of unique gesture classes that the system can recognize accurately. Our problem domain is two dimensional tracking and recognition with a single static camera. We also address the reliability of the system as we scale the size of gesture vocabulary. Our system is based on supervised learning, both detection and recognition uses the existing trained models. The hand tracking framework is based on non-parametric histogram bin based approach. A coarser histogram bin containing skin and non-skin models of size 32x32x32 was built. The histogram bins were generated by using samples of skin and non-skin images. The tracker framework effectively finds the moving skin locations as it integrates both the motion and skin detection. Hand shapes are another important modality of our gesture recognition system. Hand shapes can hold important information about the meaning of a gesture, or about the intent of an action. Recognizing hand shapes can be a very challenging task, because the same hand shape may look very different in different images, depending on the view point of the camera. We use chamfer matching of edge extracted hand regions to compute the minimum chamfer matching score. Dynamic Programming technique is used align the temporal sequences of gesture. In this paper, we propose a novel hand gesture recognition system where in user can specify his/her desired gestures vocabulary. The contributions made to the gesture recognition framework are, user-chosen gesture vocabulary (i.e) user is given an option to specify his/her desired gesture vocabulary, confusability analysis of gesture (i.e) During training, if user provides similar gesture pattern for two different gesture patterns the system automatically alerts the user to provide a different gesture pattern for a specific class, novel methodology to combine both hand shape and motion trajectory for recognition, hand tracker (using motion and skin color detection) aided hand shape recognition. The system runs in real time with frame rate of 15 frames per second in debug mode and 17 frames per second in release mode. The system was built in a normal hardware configuration with Microsoft Visual Studio, using OpenCV and C++. Experimental results establish the effectiveness of the system.

Download or read book The Promise of Assistive Technology to Enhance Activity and Work Participation written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-09-01 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: The U.S. Census Bureau has reported that 56.7 million Americans had some type of disability in 2010, which represents 18.7 percent of the civilian noninstitutionalized population included in the 2010 Survey of Income and Program Participation. The U.S. Social Security Administration (SSA) provides disability benefits through the Social Security Disability Insurance (SSDI) program and the Supplemental Security Income (SSI) program. As of December 2015, approximately 11 million individuals were SSDI beneficiaries, and about 8 million were SSI beneficiaries. SSA currently considers assistive devices in the nonmedical and medical areas of its program guidelines. During determinations of substantial gainful activity and income eligibility for SSI benefits, the reasonable cost of items, devices, or services applicants need to enable them to work with their impairment is subtracted from eligible earnings, even if those items or services are used for activities of daily living in addition to work. In addition, SSA considers assistive devices in its medical disability determination process and assessment of work capacity. The Promise of Assistive Technology to Enhance Activity and Work Participation provides an analysis of selected assistive products and technologies, including wheeled and seated mobility devices, upper-extremity prostheses, and products and technologies selected by the committee that pertain to hearing and to communication and speech in adults.

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 Targeted Muscle Reinnervation written by Todd A. Kuiken and published by Taylor & Francis. This book was released on 2013-07-23 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implement TMR with Your Patients and Improve Their Quality of LifeDeveloped by Dr. Todd A. Kuiken and Dr. Gregory A. Dumanian, targeted muscle reinnervation (TMR) is a new approach to accessing motor control signals from peripheral nerves after amputation and providing sensory feedback to prosthesis users. This practical approach has many advantage

Download or read book Powered Upper Limb Prostheses written by Ashok Muzumdar and published by Springer. This book was released on 2012-12-06 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Powered Upper Limb Prostheses deals with the concept, implementation and clinical application of utilizing inherent electrical signals within normally innervated residual muscles under voluntary control of an upper limb amputee. This amplifies these signals by battery-powered electrical means to make a terminal device, the prosthetic hand, move to perform intended function. The reader is introduced to various facets of upper limb amputations and their clinical management in both children and adults. The authors from Canada, USA and Great Britain are well known practicioners, academics and researchers in the field. The book has over 130 illustrations and contains an extensive bibliography.

Download or read book Journal of Rehabilitation Research and Development written by and published by . This book was released on 1989 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Artificial Intelligence written by Lu Fang and published by Springer Nature. This book was released on 2022-01-01 with total page 815 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 13069-13070 constitutes selected papers presented at the First CAAI International Conference on Artificial Intelligence, held in Hangzhou, China, in June 2021. Due to the COVID-19 pandemic the conference was partially held online. The 105 papers were thoroughly reviewed and selected from 307 qualified submissions. The papers are organized in topical sections on applications of AI; computer vision; data mining; explainability, understandability, and verifiability of AI; machine learning; natural language processing; robotics; and other AI related topics.

Download or read book Transactions on Computational Science XL written by Marina Gavrilova and published by Springer Nature. This book was released on 2023-08-20 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings, and solutions, and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods.This, the 40th issue of the Transactions on Computational Science, is a special issue, comprised of seven papers, and devoted to the developing and novel techniques for Trustworthy Technologies for Autonomous Human-Machine Systems. They include emerging and innovative applications of computer security-based applications, as well as theoretical contributions that are relevant to Trustworthy Technologies for Autonomous Human-Machine Systems.

Download or read book Intelligent Robotics and Applications written by Honghai Liu and published by Springer Nature. This book was released on 2022-08-03 with total page 808 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 4-volume set LNAI 13455 - 13458 constitutes the proceedings of the 15th International Conference on Intelligent Robotics and Applications, ICIRA 2022, which took place in Harbin China, during August 2022. The 284 papers included in these proceedings were carefully reviewed and selected from 442 submissions. They were organized in topical sections as follows: Robotics, Mechatronics, Applications, Robotic Machining, Medical Engineering, Soft and Hybrid Robots, Human-robot Collaboration, Machine Intelligence, and Human Robot Interaction.