Spatial navigation in simulated prosthetic vision(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2026年第7期
- Page:
- 879-888
- Research Field:
- 医学影像物理
- Publishing date:
Info
- Title:
- Spatial navigation in simulated prosthetic vision
- Author(s):
- CUI Xiaochen1; ZHAO Ying1; ZHANG Yan2; DAI Tingting1
- 1. School of Digital and Intelligent Industry, Inner Mongolia University of Science and Technology, Baotou 014010, China 2. School of Computer and Information Engineering, Qilu Institute of Technology, Jinan 250200, China
- Keywords:
- Keywords: simulated prosthetic vision spatial navigation scene cognition route-retracing image processing strategy
- PACS:
- R318.18；TP391.9
- DOI:
- DOI:10.3969/j.issn.1005-202X.2026.07.007
- Abstract:
- Abstract: Objective To assist prosthesis users in exploring unfamiliar environments with restricted fields of view, this study proposes an image optimization strategy for simulated prosthetic vision and validates it through relevant spatial navigation tasks. Methods A series of urban scenes under simulated prosthetic vision were constructed in Unity via an image-processing strategy integrating semantic segmentation and edge-enhanced representation based on depth perception fusion. Twenty participants were recruited to complete a route-retracing task and picture- and sequence-recognition tests in the urban scenes under simulated prosthetic vision. Behavioral performance and recognition scores acquired under the proposed strategy were compared with those obtained from an unprocessed visual condition using nonparametric statistical analyses. Results The proposed image optimization strategy outperformed the unprocessed method in terms of navigation efficiency and path fidelity. After image processing, the median collision count for the route-retracing task was reduced by 5, and the dispersion of collisions (interquartile range, IQR) was reduced by 68.2%. The total task completion time was shortened by 59.27 s, with a 54.5% reduction in dispersion and the decision-making time was reduced by 19.49 s, with a 35.0% reduction in dispersion. The total travel distance was decreased by 44.45 m, with a 16.1% reduction route deviation rate was declined by 57.9%, and the dispersion of route deviation was reduced by 73.1% and the increase in route deviation was reduced by 45%. For scene cognition, there was a 17.19% increase in picture recognition scores and a 10.71% increase in sequence recognition scores, with a 22.6% reduction in dispersion. Conclusion The proposed image optimization strategy significantly enhances spatial navigation performance, reduces inter-subject variability under simulated prosthetic vision, and exhibits more prominent targeted optimization effects, particularly for participants with prolonged task completion duration. These findings can serve as a reference for strategy selection in similar tasks.
Last Update: 2026-07-22