A Wearable Non-Visual Guidance System with an Inspectable Spatial-Cue Core

Abstract Wearable assistance for blind and low-vision users must convert egocentric perception into interpretable action cues. This paper presents a three-node guidance system comprising smart glasses, an RK3588 edge unit, and a four-motor wristband. RGB-D/stereo perception, YOLO11s detection, metric depth estimation, and 3D back-projection produce task-specific spatial relations. An upstream cue core validates task intent, entity, mode, relation, and state before transmitting vector packets over BLE; the wristband applies roll compensation and renders directional haptic feedback. Placement-level relative-vector errors are 1.13 ± 0.38, 1.66 ± 0.47, and 1.76 ± 0.30 cm at nominal 30, 50, and 70 cm placements (n = 15 per distance). Grasping succeeds in 37/40 trials under a 60 s timeout. A supplementary study report compares smart glasses and a white cane in 100 participants, including 50 blind and 50 low-vision participants, using a counterbalanced mixed design and collision counts as the primary outcome. In the blind group, mean collision counts are 4.46 with glasses and 12.54 with the cane; the report gives t(49) = 30.92, p < 0.001, and Cohen’s d = 4.37. In the low-vision group, the mean paired difference is 0.14 collisions, with a reported 90% confidence interval of [−0.01, 0.29], meeting the specified ±1.5-collision equivalence criterion. The reported age-adjusted group-by-device interaction is significant (F (1, 97) = 412.5, p < 0.001), supporting visual-status-dependent benefit. By integrating performance indicators and behavioral outcomes, this multidimensional framework provides a practical tool for evaluating wearable assistive systems, supports safer and more effective autonomous assistance, and contributes to broader human–machine interaction research.

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Publication Details

Journal
Research Square
Published
2026-11-06
DOI
https://doi.org/10.21203/rs.3.rs-11251351/v1
Primary Topic
Tactile and Sensory Interactions
Type
preprint
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preprint

A Wearable Non-Visual Guidance System with an Inspectable Spatial-Cue Core

Wenxuan Ma, Shurui Zhang, Yang Gao, Yirui Yuan et al.
1 links
Research Square
Tactile and Sensory Interactions
preprint

A Wearable Non-Visual Guidance System with an Inspectable Spatial-Cue Core

Wenxuan Ma, Shurui Zhang, Yang Gao, Yirui Yuan, Chenghang Li, Fan Wang
preprint en

Abstract

Abstract Wearable assistance for blind and low-vision users must convert egocentric perception into interpretable action cues. This paper presents a three-node guidance system comprising smart glasses, an RK3588 edge unit, and a four-motor wristband. RGB-D/stereo perception, YOLO11s detection, metric depth estimation, and 3D back-projection produce task-specific spatial relations. An upstream cue core validates task intent, entity, mode, relation, and state before transmitting vector packets over BLE; the wristband applies roll compensation and renders directional haptic feedback. Placement-level relative-vector errors are 1.13 ± 0.38, 1.66 ± 0.47, and 1.76 ± 0.30 cm at nominal 30, 50, and 70 cm placements (n = 15 per distance). Grasping succeeds in 37/40 trials under a 60 s timeout. A supplementary study report compares smart glasses and a white cane in 100 participants, including 50 blind and 50 low-vision participants, using a counterbalanced mixed design and collision counts as the primary outcome. In the blind group, mean collision counts are 4.46 with glasses and 12.54 with the cane; the report gives t(49) = 30.92, p < 0.001, and Cohen’s d = 4.37. In the low-vision group, the mean paired difference is 0.14 collisions, with a reported 90% confidence interval of [−0.01, 0.29], meeting the specified ±1.5-collision equivalence criterion. The reported age-adjusted group-by-device interaction is significant (F (1, 97) = 412.5, p < 0.001), supporting visual-status-dependent benefit. By integrating performance indicators and behavioral outcomes, this multidimensional framework provides a practical tool for evaluating wearable assistive systems, supports safer and more effective autonomous assistance, and contributes to broader human–machine interaction research.

Research Square
Wuhan University (CN), Southern Medical University (CN), South China University of Technology (CN)
Good health and well-being
Tactile and Sensory Interactions
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