189
Views
3
CrossRef citations to date
0
Altmetric
Innovation

Electromyography pattern-recognition based prosthetic limb control using various machine learning techniques

ORCID Icon, ORCID Icon & ORCID Icon
Pages 370-377 | Received 27 Sep 2020, Accepted 30 Mar 2022, Published online: 20 Apr 2022
 

Abstract

People who have lost their limbs to amputation and neurological disorders confront this loss every morning. As per the literature review, nearly 30% of the Indian population suffered from upper extremity amputation. As a coping-up measure, a force-controlled prosthetic limb has been developed to improve their self-reliance, quality of lifestyle and mental strength. The current prosthetic limb operation is done by residual muscle contraction, which contributes to the activation of the sensor and the motor. But there are some cons, the amputee does not know how much pressure needs to be exerted for holding various objects. Also, the amputee still has to undergo the surgical procedure. However, this paper proposes a way to predict the force which is needed to regulate the voltage for the servomotors using different Machine Learning (ML) regression approaches. Support Vector Regressor (SVR), Linear Regression and Random Forest models have been used to predict that force requirement. After comparing the results, the Random Forest model gave a highly accurate prediction of the force needed to control the voltage for the DC servomotors

Disclosure statement

No potential conflict of interest was reported by the author(s).

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.