{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T19:44:28Z","timestamp":1789674268472,"version":"4.0.1"},"reference-count":37,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2023,12,4]],"date-time":"2023-12-04T00:00:00Z","timestamp":1701648000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Australian Government Research Training Program (RTP) Scholarship"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Individuals who are Blind and Visually Impaired (BVI) take significant risks and dangers on obstacles, particularly when they are unaccompanied. We propose an intelligent head-mount device to assist BVI people with this challenge. The objective of this study is to develop a computationally efficient mechanism that can effectively detect obstacles in real time and provide warnings. The learned model aims to be both reliable and compact so that it can be integrated into a wearable device with a small size. Additionally, it should be capable of handling natural head turns, which can generally impact the accuracy of readings from the device\u2019s sensors. Over thirty models with different hyper-parameters were explored and their key metrics were compared to identify the most suitable model that strikes a balance between accuracy and real-time performance. Our study demonstrates the feasibility of a highly efficient wearable device that can assist BVI individuals in avoiding obstacles with a high level of accuracy.<\/jats:p>","DOI":"10.3390\/s23239598","type":"journal-article","created":{"date-parts":[[2023,12,4]],"date-time":"2023-12-04T05:28:21Z","timestamp":1701667701000},"page":"9598","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Intelligent Head-Mounted Obstacle Avoidance Wearable for the Blind and Visually Impaired"],"prefix":"10.3390","volume":"23","author":[{"given":"Peijie","family":"Xu","sequence":"first","affiliation":[{"name":"School of Computing Technologies, Royal Melbourne Institute of Technology (RMIT) University, Melbourne, VIC 3000, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andy","family":"Song","sequence":"additional","affiliation":[{"name":"School of Computing Technologies, Royal Melbourne Institute of Technology (RMIT) University, Melbourne, VIC 3000, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computing Technologies, Royal Melbourne Institute of Technology (RMIT) University, Melbourne, VIC 3000, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e130","DOI":"10.1016\/S2214-109X(20)30425-3","article-title":"Trends in prevalence of blindness and distance and near vision impairment over 30 years: An analysis for the Global Burden of Disease Study","volume":"9","author":"Bourne","year":"2021","journal-title":"Lancet Glob. 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