Detection of Unconscious Movements with RGB-D Camera for Objective Ride Comfort Evaluation

Abstract

The previous studies reported a high correlation between the frequencies of the unconscious movements and participants' subjective ratings. Then, we have tried to develop other techniques that facilitate the digitization of participants' movements. For example, the method using body pressure distribution measurement system, and flex sensors have been reported. As these were instrument contact-constrained methods, this paper developed a measurement system that automatically extracts and classifies unconscious movements in a non-contact and non-constraint manner. In the accuracy evaluation experiment, the participants were asked to drive a driving simulator for 60 minutes and were captured with the developed system and a conventional video camera. As a result, the accuracy was insufficient, and there were two error types. The first error (false positive) was a case in which the program falsely detected the occurrence of a motion even though no unconscious movement occurred. The second one (false negative) was the opposite error, where the result incorrectly indicates the absence of movements when the movement was happening. By applying the proposed countermeasures to reduce these errors, the recognition accuracy of unconscious movements can be improved and applied to the objective evaluation of riding comfort.

Keywords: Ride comfort evaluation, Image processing, Skeleton pose estimation, Driving simulator, Fidget

DOI: 10.54941/ahfe1003787