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근육 부피 변화에 따른 손동작 분류 알고리즘을 기반으로 한 HCI 시스템의 개발
조은일(Eunil Cho),허정현(Jung Hyun Heo),이정직(Jeongjick Lee),윤영로(Young Ro Yoon) 대한인간공학회 2016 대한인간공학회 학술대회논문집 Vol.2016 No.11
Objective: The aim of this study is to propose alternative method about sensing muscle activity to classify hand gesture. When human act hand gesture, muscles will be contracted or relaxed. So we use ‘Conductive Rubber Cord’ to measure muscle volume change. Background: Different hand gesture shows different muscle volume change. And about same hand gesture shows very similar muscle volume change. Method: We determine 5 kinds of hand gestures and measure muscle volume change. So we suggest a parameter based on muscle volume change measured by conductive rubber cord. The work is based on two facts. One is that hand gesture or motion is controlled by fore arm and the other is that volume change of forearm occurs by doing hand motion. Based on these facts, we assume that a variety of hand gesture results in various volume change of forearm case by case. Results: The sensitivity of the classification used for the 5 kinds of hand gestures was 96.39%. Conclusion: Muscle volume change is not affected by electric signal or feature of human body. So it didn’t need preprocessing for separate parameter from undesirable signals. This means Muscle volume change is more useful than sEMG or other bio signal. Application: The results of this study might help to determine alternative method about sensing muscle activity. And it can be applied to develop controller for virtual-reality system.
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