Radio-Controlled Car Operation Level Estimation with Physiological Index

DOI

10.2991/amcce-17.2017.163How to use a DOI?

Keywords

Radio-Controlled Car; sEMG; Eye Blink; Physiological Index

Abstract

Radio-controlled (RC) car is an interesting leisure activity. RC car motion is controlled by operator's hand. Left hand is to control the throttle and the right hand is to control the direction. A novel physiological index to assess the learning level of operator is proposed in this article. Twelve expert groups and 11 novice groups participated. Surface Electromyography (sEMG) of hands, heartbeats and the numbers of eye blink were measured to compare the differences between an expert group and a novice group. RC Car rap times were measured on three track types; hairpin corner, drag strip and S-bend. The average speed of expert and novice groups are 47.1 ± 3.2 km/hr and 24.2 ± 4.3 km/hr (p<0.001***). The heartbeats of the expert group were slower than those of the novice group (738.95 ± 26.63 ms vs. 680.50 ± 61.4 ms, p = 0.005**). The eye blinking rate of the expert group is less than that of the novice group (0.79 ± 0.65 vs. 1.84 ± 0.63, blinks/min, p<0.001***). Muscle activity of hairpin corner are 3.74±1.06 and 2.70±0.52 for expert group and a novice group (p<0.001***), median frequency of muscle activity of hairpin corner are183.64±42.22 and 220.34±19.87 for expert group and a novice group (p<0.001***). This study investigated that expert group can control RC car with higher attention, and delicate muscle contraction to gain a better RC rap time performance.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - KangMing Chang
AU  - SihHuei Chen
AU  - YangFan Lee
PY  - 2017/03
DA  - 2017/03
TI  - Radio-Controlled Car Operation Level Estimation with Physiological Index
BT  - Proceedings of the 2017 2nd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2017)
PB  - Atlantis Press
SP  - 919
EP  - 924
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-17.2017.163
DO  - 10.2991/amcce-17.2017.163
ID  - Chang2017/03
ER  -