OmniVib: Towards cross-body spatiotemporal vibrotactile notifications for mobile phones
Paper in proceedings, 2015

- 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.


J. Alvina

National University of Singapore (NUS)

Laboratoire de Recherche en Informatique

S. T. Perrault

National University of Singapore (NUS)

T. Roumen

National University of Singapore (NUS)

S. D. Zhao

National University of Singapore (NUS)

M. Azh

National University of Singapore (NUS)

Morten Fjeld

Chalmers, Applied Information Technology (Chalmers), Interaction Design (Chalmers)

33rd Annual CHI Conference on Human Factors in Computing Systems, CHI 2015; Seoul; South Korea; 18 April 2015 through 23 April 2015

Vol. 2015-April 2487-2496
978-145033145-6 (ISBN)

Subject Categories

Human Computer Interaction

Electrical Engineering, Electronic Engineering, Information Engineering





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