Results 31 to 40 of about 3,364,312 (190)
Resolving the Limb Position Effect in Myoelectric Pattern Recognition
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2011 Reported studies on pattern recognition of electromyograms (EMG) for the control of prosthetic devices traditionally focus on classification accuracy of signals recorded in a laboratory. The difference between the constrained nature in which such data are often collected and the unpredictable nature of prosthetic use is an example of the semantic gap ...
Fougner, Anders Lyngvi +4 more
openaire +3 more sources
Reduce the User Burden of Multiuser Myoelectric Interface via Few-Shot Domain Adaptation
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 Due to physiological and anatomical variations across users, myoelectric interfaces trained by multiple users cannot be adapted to the unique hand movement patterns of the new user.
Bo Xue +5 more
doaj +1 more source
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022 Controlling several joints simultaneously is a common feature of natural arm movements. Robotic prostheses shall offer this possibility to their wearer.
Mathilde Legrand +7 more
doaj +1 more source
Improving the Robustness of Real-Time Myoelectric Pattern Recognition against Arm Position Changes in Transradial Amputees. [PDF]
Biomed Res Int, 2017 Previous studies have showed that arm position variations would significantly degrade the classification performance of myoelectric pattern-recognition-based prosthetic control, and the cascade classifier (CC) and multiposition classifier (MPC) have been
Geng Y, Samuel OW, Wei Y, Li G.
europepmc +2 more sources
Improved pattern recognition classification accuracy for surface myoelectric signals using spectral enhancement [PDF]
, 2015 In this paper, we demonstrate that Spectral Enhancement techniques can be configured to improve the classification accuracy of a pattern recognition-based myoelectric control system. This is based on the observation that, when the subject is at rest, the
Petropoulakis, Lykourgos +3 more
core +3 more sources
Frontiers in Neurorobotics, 2018 Surface Electromyography (EMG)-based pattern recognition methods have been investigated over the past years as a means of controlling upper limb prostheses.
Iris Kyranou +6 more
doaj +1 more source
Similarity Function for One-Shot Learning to Enhance the Flexibility of Myoelectric Interfaces
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 $\textit {Objective:}$ This study aims to develop a flexible myoelectric pattern recognition (MPR) method based on one-shot learning, which enables convenient switching across different usage scenarios, thereby reducing the re-training burden ...
Xiang Wang +5 more
doaj +1 more source
Crosspoint Switch Based EMG Frontend for Pattern Recognition Myoelectric Control [PDF]
, 2013 Control of myoelectric prosthesis can be achieved in two ways, direct control involving measuring the amplitude of the myoelectric signal or through pattern recognition (PR).
Rudhram Gajendran (7954574)
core +2 more sources
Development of a Parent Wireless Assistive Interface for Myoelectric Prosthetic Hands for Children
Frontiers in Neurorobotics, 2018 In this study, a one-degree-of-freedom myoelectric prosthesis system was proposed using a Parent Wireless Assistive Interface (PWAI) that allowed an external assistant (e. g., the parent of the user) to immediately adjust the parameters of the prosthetic
Yutaro Hiyoshi +12 more
doaj +1 more source
A Neuro-Fuzzy System for Characterization of Arm Movements
Sensors, 2013 The myoelectric signal reflects the electrical activity of skeletal muscles and contains information about the structure and function of the muscles which make different parts of the body move.
Alexandre Balbinot, Gabriela Favieiro
doaj +1 more source