DocumentCode :
2599182
Title :
Rock-paper-scissors prediction experiments using muscle activations
Author :
Jang, Giho ; Choi, Youngjin ; Qu, Zhihua
Author_Institution :
Dept. of Electron., Electr., Control & Instrum. Eng., Hanyang Univ., Seoul, South Korea
fYear :
2012
fDate :
7-12 Oct. 2012
Firstpage :
5133
Lastpage :
5134
Abstract :
Human motion prediction is becoming more and more important issue in the filed of wearable robots or biorobotics. This paper provides an initial experimental result for human motion prediction. In detail, the prediction method for ternary choice among rock-paper-scissors is presented using temporal patterns of muscle activations (Electromyography, in short EMG) controlling hand motion of subject. Initial burst part of EMG is prior to the onset of actual movement by dozens to hundreds milliseconds. Using this property, the proposed method makes the ternary choice prediction among rock-paper-scissors as soon as 10% motion variation of any finger is detected. It is shown experimentally that the success rate of the proposed prediction method is over 95%.
Keywords :
electromyography; intelligent robots; motion control; prediction theory; EMG; biorobotics; electromyography; hand motion control; human motion prediction; initial burst part; motion variation; muscle activations; muscle activations temporal patterns; rock-paper-scissors prediction experiments; ternary choice prediction; wearable robots; Electromyography; Games; Humans; Muscles; Rocks; Thumb; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on
Conference_Location :
Vilamoura
ISSN :
2153-0858
Print_ISBN :
978-1-4673-1737-5
Type :
conf
DOI :
10.1109/IROS.2012.6386264
Filename :
6386264
Link To Document :
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