{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T03:08:37Z","timestamp":1773803317210,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2024,7,29]],"date-time":"2024-07-29T00:00:00Z","timestamp":1722211200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Institute of Health Research (NIHR)","award":["PF-PDF-1898"],"award-info":[{"award-number":["PF-PDF-1898"]}]},{"name":"National Institute of Health Research (NIHR)","award":["PF-CRA-2073"],"award-info":[{"award-number":["PF-CRA-2073"]}]},{"name":"Northumbria University","award":["PF-PDF-1898"],"award-info":[{"award-number":["PF-PDF-1898"]}]},{"name":"Northumbria University","award":["PF-CRA-2073"],"award-info":[{"award-number":["PF-CRA-2073"]}]},{"name":"Parkinson\u2019s Foundation","award":["PF-PDF-1898"],"award-info":[{"award-number":["PF-PDF-1898"]}]},{"name":"Parkinson\u2019s Foundation","award":["PF-CRA-2073"],"award-info":[{"award-number":["PF-CRA-2073"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Falls are a major concern for people with Parkinson\u2019s disease (PwPD), but accurately assessing real-world fall risk beyond the clinic is challenging. Contemporary technologies could enable the capture of objective and high-resolution data to better inform fall risk through measurement of everyday factors (e.g., obstacles) that contribute to falls. Wearable inertial measurement units (IMUs) capture objective high-resolution walking\/gait data in all environments but are limited by not providing absolute clarity on contextual information (i.e., obstacles) that could greatly influence how gait is interpreted. Video-based data could compliment IMU-based data for a comprehensive free-living fall risk assessment. The objective of this study was twofold. First, pilot work was conducted to propose a novel artificial intelligence (AI) algorithm for use with wearable video-based eye-tracking glasses to compliment IMU gait data in order to better inform free-living fall risk in PwPD. The suggested approach (based on a fine-tuned You Only Look Once version 8 (YOLOv8) object detection algorithm) can accurately detect and contextualize objects (mAP50 = 0.81) in the environment while also providing insights into where the PwPD is looking, which could better inform fall risk. Second, we investigated the perceptions of PwPD via a focus group discussion regarding the adoption of video technologies and AI during their everyday lives to better inform their own fall risk. This second aspect of the study is important as, traditionally, there may be clinical and patient apprehension due to ethical and privacy concerns on the use of wearable cameras to capture real-world video. Thematic content analysis was used to analyse transcripts and develop core themes and categories. Here, PwPD agreed on ergonomically designed wearable video-based glasses as an optimal mode of video data capture, ensuring discreteness and negating any public stigma on the use of research-style equipment. PwPD also emphasized the need for control in AI-assisted data processing to uphold privacy, which could overcome concerns with the adoption of video to better inform IMU-based gait and free-living fall risk. Contemporary technologies (wearable video glasses and AI) can provide a holistic approach to fall risk that PwPD recognise as helpful and safe to use.<\/jats:p>","DOI":"10.3390\/s24154914","type":"journal-article","created":{"date-parts":[[2024,7,29]],"date-time":"2024-07-29T16:37:17Z","timestamp":1722271037000},"page":"4914","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Using Video Technology and AI within Parkinson\u2019s Disease Free-Living Fall Risk Assessment"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5726-5606","authenticated-orcid":false,"given":"Jason","family":"Moore","sequence":"first","affiliation":[{"name":"Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]},{"given":"Yunus","family":"Celik","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]},{"given":"Samuel","family":"Stuart","sequence":"additional","affiliation":[{"name":"Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"},{"name":"Department of Neurology, Oregon Health & Science University, Portland, OR 97239, USA"}]},{"given":"Peter","family":"McMeekin","sequence":"additional","affiliation":[{"name":"Department of Nursing, Midwifery and Health, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3155-122X","authenticated-orcid":false,"given":"Richard","family":"Walker","sequence":"additional","affiliation":[{"name":"Northumbria Healthcare NHS Foundation Trust, Newcastle upon Tyne NE27 0QJ, UK"},{"name":"Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne NE2 4AX, UK"}]},{"given":"Victoria","family":"Hetherington","sequence":"additional","affiliation":[{"name":"Cumbria, Northumberland Tyne and Wear NHS Foundation Trust, Wolfson Research Centre, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 9AS, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4049-9291","authenticated-orcid":false,"given":"Alan","family":"Godfrey","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.parkreldis.2018.07.008","article-title":"Gait characteristics and falls in Parkinson\u2019s disease: A systematic review and meta-analysis","volume":"57","author":"Creaby","year":"2018","journal-title":"Park. 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