Advanced Hand Gesture Prediction Robust to Electrode Shift with an Arbitrary Angle
| Autor: | Linyong Shen, Zhenjin Xu, Zhen Zhang, Jinwu Qian |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry electrode shift 020207 software engineering 02 engineering and technology lcsh:Chemical technology Biochemistry Atomic and Molecular Physics and Optics Article Analytical Chemistry simplified rapid correction sEMG Electrode 0202 electrical engineering electronic engineering information engineering lcsh:TP1-1185 020201 artificial intelligence & image processing Computer vision hand gesture prediction Artificial intelligence synchronous gesture Electrical and Electronic Engineering Peak location business Instrumentation Gesture |
| Zdroj: | Sensors (Basel, Switzerland) Sensors, Vol 20, Iss 4, p 1113 (2020) Sensors Volume 20 Issue 4 |
| ISSN: | 1424-8220 |
| Popis: | Recent advances in myoelectric controlled techniques have made the surface electromyogram (sEMG)-based sensing armband a promising candidate for acquiring bioelectric signals in a simple and convenient way. However, inevitable electrode shift as a non-negligible defect commonly causes a trained classifier requiring continuous recalibrations. In this study, a novel hand gesture prediction is firstly proposed it is robust to electrode shift with arbitrary angle. Unlike real-time recognition which outputs target gestures only after the termination of hand motions, our proposed advanced prediction can provide the same results, even before the completion of signal collection. Moreover, by combining interpolated peak location and preset synchronous gesture, the developed simplified rapid electrode shift detection and correction at random rather than previous fixed angles are realized. Experimental results demonstrate that it is possible to achieve both electrode shift detection with high precision and gesture prediction with high accuracy. This study provides a new insight into electrode shift robustness which brings gesture prediction a step closer to practical applications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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