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Rock-Paper-Scissors Prediction Experiments using Muscle Activations

Authors
Jang, GihoChoi, YoungjinQu, Zhihua
Issue Date
Oct-2012
Publisher
IEEE
Citation
2012 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), pp.5133 - 5134
Indexed
SCIE
SCOPUS
Journal Title
2012 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
Start Page
5133
End Page
5134
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/36310
DOI
10.1109/IROS.2012.6386264
ISSN
2153-0858
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%.
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ERICA 공학대학 (DEPARTMENT OF ROBOT ENGINEERING)
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