Movement analysis to indicate discomfort in vehicle seats

Mansfield, N.J. ORCID: 0000-0001-6769-1721, Sammonds, G., Darwazeh, N., Massoud, S., Mocio, A., Patel, T. and Sehdev, A., 2017. Movement analysis to indicate discomfort in vehicle seats. In: 1st International Comfort Congress, Salerno, Italy, 7-8 June 2017.

PubSub8576_Mansfield.pdf - Published version

Download (3MB) | Preview


Long distance travel is associated with discomfort and fatigue. It is a significant challenge to design a seat that remains comfortable for the occupant over the several hours required for many long-distance journeys. When designing seats, an indication of the perception of comfort/discomfort can be useful either for research and development purposes or potentially for automated systems to take actions that might mitigate discomfort. This paper considered a system that uses measurements of body movement in a seat to provide an objective measure of perceptions of discomfort. The system uses cameras and image processing to recognize when a seat occupant makes a movement in the seat which could be associated with relief of discomfort. The system was validated using a laboratory driving simulator. 10 participants volunteered to complete a study in which they drove for 90 minutes and gave subjective ratings of discomfort every 10 minutes, whilst also being observed using the camera system. It was shown that using a simple algorithm an association could be made between the movements of the driver and subjective ratings of discomfort. However, there remain challenges to improve reliability, optimize movement detection thresholds, and to make it more
robust to naturalistic driving scenarios.

Item Type: Conference contribution
Creators: Mansfield, N.J., Sammonds, G., Darwazeh, N., Massoud, S., Mocio, A., Patel, T. and Sehdev, A.
Date: June 2017
Divisions: Schools > School of Science and Technology
Record created by: Linda Sullivan
Date Added: 16 Jun 2017 15:33
Last Modified: 16 Jun 2017 15:38

Actions (login required)

Edit View Edit View


Views per month over past year


Downloads per month over past year