{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T16:07:03Z","timestamp":1790179623961,"version":"4.1.0"},"reference-count":33,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T00:00:00Z","timestamp":1725926400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010052","name":"Northumbria University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010052","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.fr","clinicalkey.jp","clinicalkey.es","clinicalkey.com.au","clinicalkey.com","maturitas.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Maturitas"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1016\/j.maturitas.2024.108116","type":"journal-article","created":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T17:21:42Z","timestamp":1725988902000},"page":"108116","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":6,"special_numbering":"C","title":["Better understanding fall risk: AI-based computer vision for contextual gait assessment"],"prefix":"10.1016","volume":"189","author":[{"given":"Jason","family":"Moore","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"McMeekin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samuel","family":"Stuart","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rosie","family":"Morris","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunus","family":"Celik","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Walker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Victoria","family":"Hetherington","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alan","family":"Godfrey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"2","key":"10.1016\/j.maturitas.2024.108116_bb0005","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1093\/ageing\/afp223","article-title":"Ageing, neurodegeneration and Parkinson\u2019s disease","volume":"39","author":"Hindle","year":"2010","journal-title":"Age Ageing"},{"issue":"7","key":"10.1016\/j.maturitas.2024.108116_bb0010","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1016\/S1474-4422(19)30044-4","article-title":"Gait impairments in Parkinson\u2019s disease","volume":"18","author":"Mirelman","year":"2019","journal-title":"Lancet Neurol."},{"key":"10.1016\/j.maturitas.2024.108116_bb0015","doi-asserted-by":"crossref","unstructured":"M. A. Brodie et al., \"Gait as a biomarker? Accelerometers reveal that reduced movement quality while walking is associated with Parkinson's disease, ageing and fall risk,\" in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014: IEEE, pp. 5968\u20135971.","DOI":"10.1109\/EMBC.2014.6944988"},{"issue":"12","key":"10.1016\/j.maturitas.2024.108116_bb0020","doi-asserted-by":"crossref","first-page":"3529","DOI":"10.3390\/s20123529","article-title":"Gait analysis in Parkinson\u2019s disease: an overview of the most accurate markers for diagnosis and symptoms monitoring","volume":"20","author":"Di Biase","year":"2020","journal-title":"Sensors"},{"key":"10.1016\/j.maturitas.2024.108116_bb0025","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.maturitas.2017.03.317","article-title":"Wearables for independent living in older adults: gait and falls","volume":"100","author":"Godfrey","year":"2017","journal-title":"Maturitas"},{"key":"10.1016\/j.maturitas.2024.108116_bb0030","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.neubiorev.2016.02.012","article-title":"Gait and cognition: mapping the global and discrete relationships in ageing and neurodegenerative disease","volume":"64","author":"Morris","year":"2016","journal-title":"Neurosci. Biobehav. Rev."},{"issue":"4","key":"10.1016\/j.maturitas.2024.108116_bb0035","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.ijge.2013.03.005","article-title":"Gait disorders in Parkinson\u2019s disease: assessment and management","volume":"7","author":"Chen","year":"2013","journal-title":"Int. J. Gerontol."},{"issue":"2","key":"10.1016\/j.maturitas.2024.108116_bb0040","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/S0966-6362(00)00062-X","article-title":"Evaluation of an instrumented walkway for measurement of the kinematic parameters of gait","volume":"12","author":"Cutlip","year":"2000","journal-title":"Gait Posture"},{"issue":"1","key":"10.1016\/j.maturitas.2024.108116_bb0045","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2474-5-13","article-title":"Test-retest reliability of temporal and spatial gait characteristics measured with an instrumented walkway system (GAITRite\u00ae)","volume":"5","author":"Van Uden","year":"2004","journal-title":"BMC Musculoskelet. Disord."},{"issue":"5","key":"10.1016\/j.maturitas.2024.108116_bb0050","doi-asserted-by":"crossref","first-page":"274","DOI":"10.3109\/03091902.2014.909540","article-title":"Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analysis","volume":"38","author":"Pfister","year":"2014","journal-title":"J. Med. Eng. Technol."},{"key":"10.1016\/j.maturitas.2024.108116_bb0055","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.medengphy.2020.11.005","article-title":"Gait analysis in neurological populations: progression in the use of wearables","volume":"87","author":"Celik","year":"2021","journal-title":"Med. Eng. Phys."},{"key":"10.1016\/j.maturitas.2024.108116_bb0060","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.gaitpost.2018.05.025","article-title":"IMU-based gait analysis in lower limb prosthesis users: comparison of step demarcation algorithms","volume":"64","author":"Bastas","year":"2018","journal-title":"Gait Posture"},{"issue":"3","key":"10.1016\/j.maturitas.2024.108116_bb0065","doi-asserted-by":"crossref","first-page":"908","DOI":"10.3390\/s22030908","article-title":"Reliability of IMU-based gait assessment in clinical stroke rehabilitation","volume":"22","author":"Felius","year":"2022","journal-title":"Sensors"},{"key":"10.1016\/j.maturitas.2024.108116_bb0070","doi-asserted-by":"crossref","unstructured":"A. Godfrey, S. Del Din, G. Barry, J. C. Mathers, and L. Rochester, \"Within trial validation and reliability of a single tri-axial accelerometer for gait assessment,\" in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014: IEEE, pp. 5892\u20135895.","DOI":"10.1109\/EMBC.2014.6944969"},{"issue":"9","key":"10.1016\/j.maturitas.2024.108116_bb0075","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.1002\/mds.26718","article-title":"Free-living monitoring of Parkinson\u2019s disease: lessons from the field","volume":"31","author":"Del Din","year":"2016","journal-title":"Mov. Disord."},{"key":"10.1016\/j.maturitas.2024.108116_bb0080","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.gaitpost.2016.11.024","article-title":"A model of free-living gait: a factor analysis in Parkinson\u2019s disease","volume":"52","author":"Morris","year":"2017","journal-title":"Gait Posture"},{"issue":"2","key":"10.1016\/j.maturitas.2024.108116_bb0085","doi-asserted-by":"crossref","first-page":"891","DOI":"10.3390\/s23020891","article-title":"Enhancing free-living fall risk assessment: contextualizing mobility based IMU data","volume":"23","author":"Moore","year":"2023","journal-title":"Sensors"},{"key":"10.1016\/j.maturitas.2024.108116_bb0090","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12883-019-1301-y","article-title":"Exploring the Parkinson patients\u2019 perspective on home-based video recording for movement analysis: a qualitative study","volume":"19","author":"de Vries","year":"2019","journal-title":"BMC Neurol."},{"issue":"1","key":"10.1016\/j.maturitas.2024.108116_bb0095","doi-asserted-by":"crossref","first-page":"1703","DOI":"10.1111\/ejn.13589","article-title":"Direct and indirect effects of attention and visual function on gait impairment in Parkinson\u2019s disease: influence of task and turning","volume":"46","author":"Stuart","year":"2017","journal-title":"Eur. J. Neurosci."},{"key":"10.1016\/j.maturitas.2024.108116_bb0100","doi-asserted-by":"crossref","unstructured":"J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, \"You only look once: Unified, real-time object detection,\" in Proceedings of the IEEE conference on computer vision and pattern recognition, 2016, pp. 779\u2013788.","DOI":"10.1109\/CVPR.2016.91"},{"issue":"1","key":"10.1016\/j.maturitas.2024.108116_bb0105","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1038\/s41746-024-01050-7","article-title":"Contextualizing remote fall risk: video data capture and implementing ethical AI","volume":"7","author":"Moore","year":"2024","journal-title":"npj Digital Med."},{"key":"10.1016\/j.maturitas.2024.108116_bb0110","unstructured":"J. Moore, P. McMeekin, S. Stuart, R. Walker, and A. Godfrey, \"Using video technology and AI within Parkinson's disease free-living fall risk assessment,\" Sensors, (In Press)."},{"issue":"2","key":"10.1016\/j.maturitas.2024.108116_bb0115","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1016\/j.gaitpost.2012.02.019","article-title":"An enhanced estimate of initial contact and final contact instants of time using lower trunk inertial sensor data","volume":"36","author":"McCamley","year":"2012","journal-title":"Gait Posture"},{"issue":"1","key":"10.1016\/j.maturitas.2024.108116_bb0120","doi-asserted-by":"crossref","first-page":"N1","DOI":"10.1088\/1361-6579\/38\/1\/N1","article-title":"Detecting free-living steps and walking bouts: validating an algorithm for macro gait analysis","volume":"38","author":"Hickey","year":"2016","journal-title":"Physiol. Meas."},{"key":"10.1016\/j.maturitas.2024.108116_bb0125","unstructured":"G. Jocher, A. Chaurasia, and J. Qiu, \"YOLO by Ultralytics,\" 2023. [Online]. Available: https:\/\/github.com\/ultralytics\/ultralytics."},{"issue":"3","key":"10.1016\/j.maturitas.2024.108116_bb0130","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.gaitpost.2005.10.002","article-title":"\u201cEvidence for a link between changes to gaze behaviour and risk of falling in older adults during adaptive locomotion,\u201d (in eng)","volume":"24","author":"Chapman","year":"2006","journal-title":"Gait Posture"},{"issue":"12","key":"10.1016\/j.maturitas.2024.108116_bb0135","doi-asserted-by":"crossref","first-page":"2216","DOI":"10.3390\/ijerph16122216","article-title":"Falls in Parkinson\u2019s disease subtypes: risk factors, locations and circumstances","volume":"16","author":"Pelicioni","year":"2019","journal-title":"Int. J. Environ. Res. Public Health"},{"issue":"1","key":"10.1016\/j.maturitas.2024.108116_bb0140","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1177\/0031512518814608","article-title":"Influence of Parkinson\u2019s disease on judging stair step height: exploratory study","volume":"126","author":"da Concei\u00e7\u00e3o","year":"2019","journal-title":"Percept. Mot. Skills"},{"issue":"7","key":"10.1016\/j.maturitas.2024.108116_bb0145","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1111\/ejn.13864","article-title":"Saccade frequency response to visual cues during gait in Parkinson\u2019s disease: the selective role of attention","volume":"47","author":"Stuart","year":"2018","journal-title":"Eur. J. Neurosci."},{"key":"10.1016\/j.maturitas.2024.108116_bb0150","doi-asserted-by":"crossref","unstructured":"J. Moore et al., \"Enhancing fall risk assessment: instrumenting vision with deep learning during walks,\" J. Neuroeng. Rehabil., vol. 21, no. 1, p. 106, 2024\/06\/22 2024, doi: https:\/\/doi.org\/10.1186\/s12984-024-01400-2.","DOI":"10.1186\/s12984-024-01400-2"},{"key":"10.1016\/j.maturitas.2024.108116_bb0155","doi-asserted-by":"crossref","unstructured":"A. Godfrey et al., \"Towards holistic free-living assessment in Parkinson's disease: Unification of gait and fall algorithms with a single accelerometer,\" in 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 16\u201320 Aug. 2016 2016, pp. 651\u2013654, doi: https:\/\/doi.org\/10.1109\/EMBC.2016.7590786.","DOI":"10.1109\/EMBC.2016.7590786"},{"key":"10.1016\/j.maturitas.2024.108116_bb0160","doi-asserted-by":"crossref","DOI":"10.1016\/j.ibmed.2023.100103","article-title":"Toward enhanced free-living fall risk assessment: data mining and deep learning for environment and terrain classification","volume":"8","author":"Moore","year":"2023","journal-title":"Intelligence-Based Medicine"},{"issue":"11","key":"10.1016\/j.maturitas.2024.108116_bb0165","doi-asserted-by":"crossref","first-page":"2827","DOI":"10.1093\/brain\/aww175","article-title":"\u201cVisual dysfunction in Parkinson\u2019s disease,\u201d (in eng)","volume":"139","author":"Weil","year":"2016","journal-title":"Brain"}],"container-title":["Maturitas"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0378512224002111?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0378512224002111?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,9,25]],"date-time":"2024-09-25T21:05:51Z","timestamp":1727298351000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0378512224002111"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11]]},"references-count":33,"alternative-id":["S0378512224002111"],"URL":"https:\/\/doi.org\/10.1016\/j.maturitas.2024.108116","relation":{},"ISSN":["0378-5122"],"issn-type":[{"value":"0378-5122","type":"print"}],"subject":[],"published":{"date-parts":[[2024,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Better understanding fall risk: AI-based computer vision for contextual gait assessment","name":"articletitle","label":"Article Title"},{"value":"Maturitas","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.maturitas.2024.108116","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"108116"}}