Gait Gestures: Examining Stride and Foot Strike Variation as an Input Method While Walking

Walking is a cyclic pattern of alternating footstep strikes, with each pair of steps forming a stride, and a series of strides forming a gait. We conduct a systematic examination of different kinds of intentional variations from a normal gait that could be used as input actions without interrupting overall walking progress. A design space of 22 candidate Gait Gestures is generated by adapting previous standing foot input actions and identifying new actions possible in a walking context. A formative study (n=25) examines movement easiness, social acceptability, and walking compatibility with foot movement logging to calculate temporal and spatial characteristics. Using a categorization of these results, 7 gestures are selected for a wizard-of-oz prototype demonstrating an AR interface controlled by Gait Gestures for ordering food and audio playback while walking. As a technical proof-of-concept, a gait gesture recognizer is developed and tested using the formative study data.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3654777.3676342
Citations
6
Primary Topic
Balance, Gait, and Falls Prevention
Type
article
Field-Weighted Citation Impact
6.87
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article

Gait Gestures: Examining Stride and Foot Strike Variation as an Input Method While Walking

Daekun Kim, Daniel Vogel, Ryan Yen, Ching-Yi Tsai
6 citations
Balance, Gait, and Falls Prevention
6.87
article

Gait Gestures: Examining Stride and Foot Strike Variation as an Input Method While Walking

Daekun Kim, Daniel Vogel, Ryan Yen, Ching-Yi Tsai
article en
6 citations

Abstract

Walking is a cyclic pattern of alternating footstep strikes, with each pair of steps forming a stride, and a series of strides forming a gait. We conduct a systematic examination of different kinds of intentional variations from a normal gait that could be used as input actions without interrupting overall walking progress. A design space of 22 candidate Gait Gestures is generated by adapting previous standing foot input actions and identifying new actions possible in a walking context. A formative study (n=25) examines movement easiness, social acceptability, and walking compatibility with foot movement logging to calculate temporal and spatial characteristics. Using a categorization of these results, 7 gestures are selected for a wizard-of-oz prototype demonstrating an AR interface controlled by Gait Gestures for ordering food and audio playback while walking. As a technical proof-of-concept, a gait gesture recognizer is developed and tested using the formative study data.

University of Waterloo (CA), Princeton University (US)
Openalex Percentile: Top 3%
Balance, Gait, and Falls Prevention
6.87
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