Literature DB >> 31414614

A low-cost, wearable sEMG sensor for upper limb prosthetic application.

Alok Prakash1, Bindu Kumari1, Shiru Sharma1.   

Abstract

This paper proposes a low-cost and sensitive surface electromyography (sEMG) sensor for the myoelectric prosthesis. The sensor consists of a skin interface, signal conditioning circuitry and power supply unit all encased in a single package. The tuned RC parameters based envelope detection scheme employed in the sensor enables faster as well as reliable recognition of EMG signal patterns regardless of its strength and subject variability. The output performance of the developed sensor was compared with a commercial EMG sensor regarding signal-to-noise ratio (SNR), amplitude sensitivity and response time. EMG signals with both the devices were acquired for 10 subjects (three amputees and seven healthy subjects), to perform this comparative analysis. The results showed 4× greater SNR values and 50% higher sensitivity of the developed sensor than the commercial EMG sensor. Also, the proposed sensor was 57% faster than the commercial sensor in producing the output response. The sensor was successfully tested on amputees for controlling a 3D printed hand prototype utilising a proportional control strategy. The enhanced output parameters of the sensor were responsible for smooth, faster and intuitive actuation of the prosthetic hand fingers.

Keywords:  Surface electromyography; control; myoelectric prosthesis; response time; sensitivity

Mesh:

Year:  2019        PMID: 31414614     DOI: 10.1080/03091902.2019.1653391

Source DB:  PubMed          Journal:  J Med Eng Technol        ISSN: 0309-1902


  3 in total

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Authors:  Alok Prakash; Shiru Sharma
Journal:  Phys Eng Sci Med       Date:  2021-01-19

2.  Combining Action Observation Treatment with a Brain-Computer Interface System: Perspectives on Neurorehabilitation.

Authors:  Fabio Rossi; Federica Savi; Andrea Prestia; Andrea Mongardi; Danilo Demarchi; Giovanni Buccino
Journal:  Sensors (Basel)       Date:  2021-12-20       Impact factor: 3.576

3.  Design and Evaluation of a Custom-Made Electromyographic Biofeedback System for Facial Rehabilitation.

Authors:  Kathrin Machetanz; Florian Grimm; Ruth Schäfer; Leonidas Trakolis; Helene Hurth; Patrick Haas; Alireza Gharabaghi; Marcos Tatagiba; Georgios Naros
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  3 in total

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