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IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 With the increasing availability of more advanced prostheses individuals with a transradial amputation can now be fit with single to multi-degree of freedom hands. Reliable and accurate control of these multi-grip hands still remains challenging. This is
Ann M. Simon +7 more
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Shoulder Motion Intention Detection through Myoelectric Pattern Recognition [PDF]
, 2021 In this letter, a motion intention detection (MID) problem from surface electromyographic (sEMG) signals, involving upper limbs, was faced through a pattern recognition approach. Linear discriminant analysis (LDA) and multinomial logistic regression (MLR)
Mengarelli A. +9 more
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A Training Strategy for Learning Pattern Recognition Control for Myoelectric Prostheses [PDF]
JPO Journal of Prosthetics and Orthotics, 2013 Pattern recognition-based control of myoelectric prostheses offers amputees a natural, intuitive way of controlling the increasing functionality of modern myoelectric prostheses. While this approach to prosthesis control is certainly attractive, it is a significant departure from existing control methods.
Powell, M.A., Thakor, N.V.
openaire +2 more sources
Handwritten Digits Recognition From sEMG: Electrodes Location and Feature Selection
IEEE Access, 2023 Despite hand gesture recognition is a widely investigated field, the design of myoelectric architectures for detecting finer motor task, like the handwriting, is less studied. However, writing tasks involving cognitive loads represent an important aspect
Andrea Tigrini +7 more
doaj +1 more source
Adapting myoelectric control in real-time using a virtual environment
Journal of NeuroEngineering and Rehabilitation, 2019 Background Pattern recognition technology allows for more intuitive control of myoelectric prostheses. However, the need to collect electromyographic data to initially train the pattern recognition system, and to re-train it during prosthesis use, adds ...
Richard B. Woodward, Levi J. Hargrove
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, 2023 A major barrier to the commercialization of pattern recognition (PR)-based myoelectric prostheses is the lack of robustness to confounding factors such as electrode shift which has been lingering for years.
Oyemakinde, T.T. +5 more
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Feasibility study on the application of a spiking neural network in myoelectric control systems
Frontiers in Neuroscience, 2023 In recent years, the effectiveness of a spiking neural network (SNN) for Electromyography (EMG) pattern recognition has been validated, but there is a lack of comprehensive consideration of the problems of heavy training burden, poor robustness, and high
Antong Sun +4 more
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Analysis of electrode shift effects on wavelet features embedded in a myoelectric pattern recognition system. [PDF]
Assist Technol, 2014 Myoelectric pattern recognition systems can translate muscle contractions into prosthesis commands; however, the lack of long-term robustness of such systems has resulted in low acceptability.
Fontana JM, Chiu AW.
europepmc +2 more sources
Scientific Reports, 2021 Individuals with upper extremity (UE) amputation abandon prostheses due to challenges with significant device weight—particularly among myoelectric prostheses—and limited device dexterity, durability, and reliability among both myoelectric and body ...
Kristin E. Yu +9 more
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IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022 Gestural interfaces based on surface electromyographic (sEMG) signal have been widely explored. Nevertheless, due to the individual differences in the sEMG signals, it is very challenging for a myoelectric pattern recognition control system to adapt ...
Xuan Zhang +5 more
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