UnifiedSense: Enabling Without-Device Gesture Interactions Using Over-the-shoulder Training Between Redundant Wearable Sensors
Article No.: 230, Pages 1 - 25
Abstract
Wearable devices allow quick and convenient interactions for controlling mobile computers. However, these interactions are often device-dependent, and users cannot control devices in a way they are familiar with if they do not wear the same wearable device. This paper proposes a new method, UnifiedSense, to enable device-dependent gestures even when the device that detects such gestures is missing by utilizing sensors on other wearable devices. UnifiedSense achieves this without explicit gesture training for different devices, by training its recognition model while users naturally perform gestures. The recognizer uses the gestures detected on the primary device (i.e., a device that reliably detects gestures) as labels for training samples and collects sensor data from all other available devices on the user. We conducted a technical evaluation with data collected from 15 participants with four types of wearable devices. It showed that UnifiedSense could correctly recognize 5 gestures (5 gestures × 5 configurations) with an accuracy of 90.9% (SD = 1.9%) without the primary device present.
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Take My Hand: Automated Hand-Based Spatial Guidance for the Visually Impaired
CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing SystemsTasks that involve locating objects and then moving hands to those specific locations, such as using touchscreens or grabbing objects on a desk, are challenging for the visually impaired. Over the years, audio guidance and haptic feedback have been a ...
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September 2023
1017 pages
Copyright © 2023 Owner/Author.
This work is licensed under a Creative Commons Attribution-NonCommercial International 4.0 License.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 13 September 2023
Published in PACMHCI Volume 7, Issue MHCI
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