Surface EMG and intra-socket force measurement to control a prosthetic device

Joe Sanford; Rita Patterson; Dan Popa

doi:10.1117/12.2177399

18 June 2015 Surface EMG and intra-socket force measurement to control a prosthetic device

Joe Sanford; Rita Patterson; Dan Popa;

Author Affiliations +

Proceedings Volume 9494, Next-Generation Robotics II; and Machine Intelligence and Bio-inspired Computation: Theory and Applications IX; 94940C (2015) https://doi.org/10.1117/12.2177399
Event: SPIE Sensing Technology + Applications, 2015, Baltimore, Maryland, United States

Abstract

Surface electromyography (SEMG) has been shown to be a robust and reliable interaction method allowing for basic control of powered prosthetic devices. Research has shown a marked decrease in EMG-classification efficiency throughout activities of daily life due to socket shift and movement and fatigue as well as changes in degree of fit of the socket throughout the subject's lifetime. Users with the most severe levels of amputation require the most complex devices with the greatest number of degrees of freedom. Controlling complex dexterous devices with limited available inputs requires the addition of sensing and interaction modalities. However, the larger the amputation severity, the fewer viable SEMG sites are available as control inputs. Previous work reported the use of intra-socket pressure, as measured during wrist flexion and extension, and has shown that it is possible to control a powered prosthetic device with pressure sensors. In this paper, we present data correlations of SEMG data with intra-socket pressure data. Surface EMG sensors and force sensors were housed within a simulated prosthetic cuff fit to a healthy-limbed subject. EMG and intra-socket force data was collected from inside the cuff as a subject performed pre-defined grip motions with their dominant hand. Data fusion algorithms were explored and allowed a subject to use both intra-socket pressure and SEMG data as control inputs for a powered prosthetic device. This additional input modality allows for an improvement in input classification as well as information regarding socket fit through out activities of daily life.

Citation Download Citation

Joe Sanford, Rita Patterson, Dan Popa, "Surface EMG and intra-socket force measurement to control a prosthetic device", Proc. SPIE 9494, Next-Generation Robotics II; and Machine Intelligence and Bio-inspired Computation: Theory and Applications IX, 94940C (18 June 2015); doi: 10.1117/12.2177399; https://doi.org/10.1117/12.2177399

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