Identification of Vibrotactile Flow Patterns on a Handheld Haptic Device
PubDate: October 2020
Teams: Beihang Univeristy
Writers: Yijie Gong; Dangxiao Wang; Qiqi Guo; Hu Luo; Yuru Zhang; Jing Xiao
In order to present abundant vibrotactile patterns on VR handheld controllers, it is critical to understand human’s perceptual performance of vibrotactile cues. In this study, a compact cylindrical handheld stylus with five vibrotactile motors was developed. 24 vibrotactile flow patterns in 3 dimensions were designed by using the five motors, including four parameters: the geometric topology of the flow, flow direction, inter-stimulus-interval (ISI) and repetitive times of the flow. Furthermore, 10 patterns were selected from that 24 patterns to compose an easier candidate group for the recognition. User studies were performed to measure the correct rate of identifying a specific pattern from all the 24 or 10 candidate patterns after one-hour training. Compared with the 24 candidates identification, significant improvement was observed for the correct rate of identifying a specific flow pattern from 10 candidate patterns. Analysis of error patterns reveals that vibration propagation and phantom sensation due to the ISI difference are the main influences of the correct rates. These findings might provide design guidelines for VR handheld controllers with vibrotactile feedback.