Modeling of occupant’s head movement behavior in motion sickness study via time delay neural network

• Main Authors: Ariff, M.H.M (Author), Hassan, N. (Author), Saruchi, S.A (Author), Wahid, N. (Author), Zamzuri, H. (Author)
• Format: Article
• Language: English
• Published: SAGE Publications Ltd, 2020
• Subjects: Acceleration; correlation model; Correlation modeling; Diseases; head movement predictor; Head movements; head roll; lateral acceleration; Lateral acceleration; Motion sickness; Neural networks; Time delay; time delay neural network; Time delay neural networks; Timing circuits
• Online Access: View Fulltext in Publisher; View in Scopus
• ISBN: 00375497 (ISSN)
• ISSN: 00375497 (ISSN)
• DOI: 10.1177/0037549719862864

Passengers are more susceptible to experiencing motion sickness (MS) than drivers. The difference in the severity of MS is due to their different head movement behavior during curve driving. When negotiating a curve, the passengers tilt their heads towards the lateral acceleration direction while the drivers tilt their heads against it. Thus, to reduce the passengers’ level of MS, they need to reduce their head’s tilting angle towards the lateral acceleration direction. Designing MS minimization strategies is easier if the correlation between the head movement and lateral acceleration is known mathematically. Therefore, this paper proposes the utilization of a time delay neural network (TDNN) to model the correlation of the occupant’s head movement and lateral acceleration. An experiment was conducted to gather real-time data for the modeling process. The results show that TDNN manages to model the correlation by producing a similar output response to the actual response. Thus, it is expected that the correlation model could be used as an occupant’s head movement predictor tool in future studies of MS. © The Author(s) 2019.