2011 Fiscal Year Final Research Report

Hand Motion Recognition Using Multiple Biosignals Measured from an Forearm

Research Project

Project/Area Number	22800087
Research Category	Grant-in-Aid for Research Activity Start-up
Allocation Type	Single-year Grants
Research Field	Rehabilitation science/Welfare engineering
Research Institution	National Institute of Advanced Industrial Science and Technology
Principal Investigator	YOSHIKAWA Masahiro 独立行政法人産業技術総合研究所, 知能システム研究部門, 産総研特別研究員 (40584511)
Project Period (FY)	2010 – 2011
Keywords	動作認識 / 生体信号 / ヒューマンインタフェース / ハイブリッドセンサ
Research Abstract	Many hand motion recognition methods using Electromyogram(EMG) signals have been developed. Because most studies used only surface EMG signals from a forearm, available motion-related information was limited. In this research we propose a SVM(Support Vector Machine) based hand motion recognition method using hybrid sensors. The hybrid sensor consists of an EMG sensor and an optical distance sensor, and can measure myoelectric activities and distance between the sensor and the skin surface at the same time. To examine the effectiveness of our method, we performed hand motion recognition experiments with four subjects. Experimental results showed that our method using hybrid sensors can improve motion recognition accuracy compared to when using only EMG signals.