OmniVib: Towards Cross-body Spatiotemporal Vibrotactile Notifications for Mobile Phones

OmniVib: Towards Cross-body Spatiotemporal Vibrotactile Notifications for Mobile Phones

Authors

Jessalyn Alvina, Simon T. Perrault, Thijs Roumen, Shengdong Zhao, Maryam Azh, Morten Fjeld

Paper

Video

Abstract

Previous research has shown that one’s palm can reliably recognize 10 or more spatiotemporal vibrotactile patterns. However, recognition of the same patterns on other body parts is unknown. In this paper, we investigate how users perceive spatiotemporal vibrotactile patterns on the arm, palm, thigh, and waist. Results of the first two experiments indicate that precise recognition of either position or orientation is difficult across multiple body parts. Nonetheless, users were able to distinguish whether two vibration pulses were from the same location when played in quick succession. Based on this finding, we designed eight spatiotemporal vibrotactile patterns and evaluated them in two additional experiments. The results demonstrate that these patterns can be reliably recognized (>80%) across the four tested body parts, both in the lab and in a more realistic context.

Shen

Shen is an HCI professor at the National University of Singapore working on realizing his vision of HeadsUp Computing, a new Interaction paradigm that can transform the way we live and interact with computers. In his free time, Shen loves to read, run, spend time with family and friends, and explore nature.

Leave a Reply