Biomedical Applications using Hand Gesture with Electromyography Control Signal

Biomedical Applications using Hand Gesture with Electromyography Control Signal

Vaishali M. Gulhane 1, Dr. Amol Kumbhare2

Computational Intelligence and Machine Learning . 2022 October ; 3(2): 24-29. Published online October 2022

doi.org/10.36647/CIML/03.02.A005

Abstract : Wearables developed for human body signal detection receive increasing attention in the current decade. Compared to implantable sensors, wearables are more focused on body motion detection, which can support human–machine interaction (HMI) and biomedical applications. In wearables, electromyography (EMG), force myography (FMG), and electrical impedance tomography (EIT) based body information monitoring technologies are broadly presented. In the literature, all of them have been adopted for many similar application scenarios, which easily confuses researchers when they start to explore the area. Hence, in this article, we review the three technologies in detail, from basics including working principles, device architectures, interpretation algorithms, application examples, merits and drawbacks, to state-of-the-art works, challenges remaining to be solved and the outlook of the field. We believe the content in this paper could help readers create a whole image of designing and applying the three technologies in relevant scenarios.

Keyword : FMG; EMG; EIT; biological signal; human–system interactivities.