Improving Head Orientation Prediction with Electromyography Signals in a Virtual Reality Flight Simulator

DOI

10.2991/nceece-15.2016.290How to use a DOI?

Keywords

head tracking; electromyography; virtual reality; time-delay compensation; Kalman filter.

Abstract

As the control input of the virtual reality flight simulator, precise head tracking with no time-delay is essential for user immersion and training effect. We present the results of applying a modified Kalman filter to improve head orientation prediction. A piecewise constant acceleration approach with an electromyography based input estimation is suggested. Head angular acceleration is estimated by a trained feed-forward neural network and fed into the modified Kalman filter. Experimental results show that the proposed method tracks head motion precisely under both smooth and abrupt motion conditions.

Copyright

© 2016, 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  - Dongsu Wu
AU  - Peng Li
AU  - Lin Wang
AU  - Lihao Liu
AU  - Hongbin Gu
PY  - 2015/12
DA  - 2015/12
TI  - Improving Head Orientation Prediction with Electromyography Signals in a Virtual Reality Flight Simulator
BT  - Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering
PB  - Atlantis Press
SP  - 1607
EP  - 1611
SN  - 2352-5401
UR  - https://doi.org/10.2991/nceece-15.2016.290
DO  - 10.2991/nceece-15.2016.290
ID  - Wu2015/12
ER  -