Limitations of the Perceptual Deadband Approach for Haptic Data Compression

A perceptual adaptive sampling approach is used for haptic data reduction for a typical teleoperation application. The approach is based on the Weber’s law of perception and is widely named as the “perceptual deadband” approach. The approach transmits only those samples which are perceptually significant from the last perceived stimulus. Hence, the approach considers that the perception of the current stimulus depends on the last perceived force. In this work, we question this consideration and hypothesize that the perception of a change in stimulus is a function of the current and previous stimulus (irrespective of whether it is perceived or not). For the purpose, an extensive psychophysical experiment is designed where users are subjected to a stair-case force stimuli and are asked to respond to the change in stimuli. Perceived and non-perceived responses are recorded for several users. A machine learning classifier is trained to predict the label of the responses. Our findings suggest that the perception of the current force stimulus depends on the previous force stimuli, hence it validates our hypothesis that the assumption of the current structure of the perceptual deadband approach for haptic data reduction has limitations.