HCApr 28, 2020
A Review of Surface Haptics:Enabling Tactile Effects on Touch SurfacesCagatay Basdogan, Frederic Giraud, Vincent Levesque et al.
We review the current technology underlying surface haptics that converts passive touch surfaces to active ones (machine haptics), our perception of tactile stimuli displayed through active touch surfaces (human haptics), their potential applications (human-machine interaction), and finally the challenges ahead of us in making them available through commercial systems. This review primarily covers the tactile interactions of human fingers or hands with surface-haptics displays by focusing on the three most popular actuation methods: vibrotactile, electrostatic, and ultrasonic.
HCSep 12, 2018
Driving Skill Modeling Using Neural Networks for Performance-based Haptic AssistanceHojin Lee, Hyoungkyun Kim, Seungmoon Choi
This paper addresses a data-driven framework, modeling expert driving skills for performance-based haptic assistance using neural networks (NNs). We have built a haptic driving training simulator to collect expert driving data and to provide proper haptic feedback. We establish an expert driving skill model by training NNs with the collected data. Then, the skill model is applied to performance-based haptic assistance to provide optimized references of the steering/pedaling movements. We evaluate the skill model and its application to performance-based haptic assistance in two user experiments. The results of the first experiment demonstrate that our skill model has appropriately captured experts' steering/pedaling skills. The results of the second experiment show that our performance-based haptic assistance can help novice drivers perform steering as expert drivers, but cannot assist their pedaling performance.