Does Embodiment Matter to Biomechanics and Function? A Comparative Analysis of Head-Mounted and Hand-Held Assistive Devices for Individuals with Blindness and Low Vision

Visual assistive technologies, such as Microsoft Seeing AI, can improve access to environmental information for persons with blindness or low vision (pBLV). Yet, the physical and functional implications of different device embodiments remain unclear. In this study, 11 pBLV participants used Seeing AI on a hand-held smartphone and on a head-mounted ARx Vision system to perform six activities of daily living, while their movements were captured with Xsens motion capture. Functional outcomes included task time, success rate, and number of attempts, and biomechanical measures included joint range of motion, angular path length, working volume, and movement smoothness. The head-mounted system generally reduced upper-body movement and task time, especially for document-scanning style tasks, whereas the hand-held system yielded higher success rates for tasks involving small or curved text. These findings indicate that both embodiments are viable, but they differ in terms of physical demands and ease of use. Incorporating biomechanical measures into assistive technology evaluations can inform designs that optimise user experience by balancing functional efficiency, physical sustainability, and intuitive interaction.

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Publication Details

Journal
International Journal of Human-Computer Interaction
Published
2026-04-23
DOI
https://doi.org/10.1080/10447318.2026.2650557
Primary Topic
Tactile and Sensory Interactions
Type
article
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article

Does Embodiment Matter to Biomechanics and Function? A Comparative Analysis of Head-Mounted and Hand-Held Assistive Devices for Individuals with Blindness and Low Vision

Giles Hamilton-Fletcher, Gaurav Seth, Charles Leclercq
International Journal of Human-Computer Interaction
Tactile and Sensory Interactions
article

Does Embodiment Matter to Biomechanics and Function? A Comparative Analysis of Head-Mounted and Hand-Held Assistive Devices for Individuals with Blindness and Low Vision

Giles Hamilton-Fletcher, Gaurav Seth, Charles Leclercq
article en

Abstract

Visual assistive technologies, such as Microsoft Seeing AI, can improve access to environmental information for persons with blindness or low vision (pBLV). Yet, the physical and functional implications of different device embodiments remain unclear. In this study, 11 pBLV participants used Seeing AI on a hand-held smartphone and on a head-mounted ARx Vision system to perform six activities of daily living, while their movements were captured with Xsens motion capture. Functional outcomes included task time, success rate, and number of attempts, and biomechanical measures included joint range of motion, angular path length, working volume, and movement smoothness. The head-mounted system generally reduced upper-body movement and task time, especially for document-scanning style tasks, whereas the hand-held system yielded higher success rates for tasks involving small or curved text. These findings indicate that both embodiments are viable, but they differ in terms of physical demands and ease of use. Incorporating biomechanical measures into assistive technology evaluations can inform designs that optimise user experience by balancing functional efficiency, physical sustainability, and intuitive interaction.

International Journal of Human-Computer Interaction
AXON Neuroscience (Slovakia) (SK), Rusk Rehabilitation (US), New York University (US)
Openalex Percentile: Top 100%
Tactile and Sensory Interactions
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