Results 101 to 110 of about 3,364,312 (190)

Recent advances in graph-based pattern recognition with applications in document analysis

, 2011
Emeriti, Faculty of ScienceInstitute of Computer ScienceInstitute of Computer Science, Pattern Recognition Group ...
Bunke, Horst, Riesen, Kaspar
core   +1 more source

ADAPTIVE PATTERN RECOGNITION TO ENSURE CLINICAL VIABILITY OVER TIME

, 2008
Pattern Recognition is a useful tool for deciphering movement intent from myoelectric signals. In order to be clinically viable over time, recognition paradigms must be capable of adapting with the user. Most existing paradigms are static, although two
Kuiken, Todd A., Lock, Blair A., Sensinger, Jonathan W.   +2 more
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A Comparison of Surface and Internally Measured Myoelectric Signals for use in Prosthetic Control

, 2005
The surface myoelectric signal (MES) has proven to be an effective control input for powered prostheses. Pattern recognition based controllers use multi-channel surface MES as inputs to discriminate between the desired classes of limb activation.
Englehart, K., Hargrove, L., Leckey, R., Hudgins, B.   +3 more
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Examining the adverse effects of limb position on pattern recognition based myoelectric control

, 2010
Pattern recognition of myoelectric signals for the control of prosthetic devices has been widely reported and debated. A large portion of the literature focuses on offline classification accuracy of pre-recorded signals.
A Fougner, Scheme, Erik, A D C Chan, Fougner, Anders Lyngvi, Stavdahl, Øyvind, Chan, Adrian D. C., Ø Stavdahl, K Englehart, Englehart, Kevin, E Scheme   +9 more
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A memory-friendly class-incremental learning method for hand gesture recognition using HD-sEMG

Medicine in Novel Technology and Devices
Hand gesture recognition (HGR) plays a vital role in human-computer interaction. The integration of high-density surface electromyography (HD-sEMG) and deep neural networks (DNNs) has significantly improved the robustness and accuracy of HGR systems ...
Yu Bai, Le Wu, Shengcai Duan, Xun Chen
doaj   +1 more source

User Intention Estimation for an Elbow Exoskeleton using Surface Myoelectric Pattern Recognition

Current Directions in Biomedical Engineering
This paper presents a neural network for detecting arm movement intentions in an elbow exoskeleton for stroke rehabilitation. The system uses electromyography signals (biceps and triceps), an elbow encoder, and an accelerometer. Data from 23 participants
Weymann Sylvia, Pretty Chris, Pott Peter P.   +2 more
doaj   +1 more source

A Review on Commercially Available Anthropomorphic Myoelectric Prosthetic Hands, Pattern-Recognition-Based Microcontrollers and sEMG Sensors used for Prosthetic Control

, 2019
It has been reported that over 3 million individuals live with upper limb amputation worldwide. Losing a hand drastically reduces the individual's quality of life.
Calado, Alexandre, Soares, Filomena, Matos, Demétrio   +2 more
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Prosthesis-Guided Training For Practical Use Of Pattern Recognition Control Of Prostheses

, 2011
The potential for pattern recognition to improve powered prosthesis control has been discussed for many years. One remaining barrier to at-home use of these techniques is that practical methods of user prompting during system training are lacking.
Hargrove, Levi J., Lock, Blair A., Simon, Ann M., Stubblefield, Kathy   +3 more
core  

Computer-oriented approaches to pattern recognition /

, 1972
Computer-oriented approaches to pattern recognition.Includes bibliographical references and index.Front Cover; Computer-Oriented Approaches to Pattern Recognition; Copyright Page; Contents; Preface; CHAPTER I.
Meisel, William S.
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Electromyogram Signal Enhancement and Upper-Limb Myoelectric Pattern Recognition.

, 2019
Att förlora en extremitet orsakar svårigheter i vår vardag. För att återfå förmågan till ett självständigt liv har artificiella händer och ben utvecklats. Handproteser kan kontrolleras av användaren genom aktiviteten hos återstående muskler ovanför amputationen.
openaire   +2 more sources