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Перспективи діагностики рухових розладів за допомогою методів комп’ютерного зору на базі мобільного пристрою

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dc.contributor.authorАндрущенко, М. А.uk
dc.contributor.authorСеліванова, К. Г.uk
dc.contributor.authorAndrushchenko, M. A.en
dc.contributor.authorSelivanova, K. G.en
dc.titleПерспективи діагностики рухових розладів за допомогою методів комп’ютерного зору на базі мобільного пристроюuk
dc.title.alternativeProspects for diagnosis of movement disorders using computer vision methods based on a mobile deviceen
dc.date.issued2024
dc.publisherВінницький національний технічний університетuk
dc.identifier.citationАндрущенко М. А., Селіванова К. Г. Перспективи діагностики рухових розладів за допомогою методів комп’ютерного зору на базі мобільного пристрою // Оптико-електроннi iнформацiйно-енергетичнi технологiї. 2024. № 2. С. 96-103. URI: https://oeipt.vntu.edu.ua/index.php/oeipt/article/view/734.uk
dc.relation.ispartofОптико-електроннi iнформацiйно-енергетичнi технологiї. № 2 : 96-103.uk
dc.relation.urihttps://oeipt.vntu.edu.ua/index.php/oeipt/article/view/734
dc.identifier.doihttps://doi.org/10.31649/1681-7893-2024-48-2-96-103
dc.identifier.issn2311-2662
dc.identifier.udc[004.93:615.47]
dc.identifier.urihttps://ir.lib.vntu.edu.ua/handle/123456789/55760
dc.description.abstractУ науковій роботі було досліджено безмаркерні технології відеоаналізу засновані на аналізі взаємного розташування неоднорідних частин зображень об’єкта на послідовних кадрах. Сучасні системи відеозахоплення руху є вже готовими кластерами точок у вигляді пластинок із розміщеними на них чотирма маркерами для довгих сегментів кінцівок, «шапочки» з маркерами для голови і т. ін. Було вивчено основні моделі, що використовуються у мобільних пристроях для оцінки рухів верхніх кінцівок та біомеханіки переміщення суглобів у реальному часі, а саме PoseNet, MoveNet Thunder, MoveNet Lightning, а також BlazePose у версіях Light, Full та Heavy. Моделі були оцінені за такими ключовими характеристиками, як швидкість роботи, вплив на пристрій та підтримка апаратного прискорення.uk
dc.description.abstractThe research work investigated markerless video analysis technologies based on the analysis of the relative position of heterogeneous parts of object images in successive frames. Modern video motion capture systems are ready-made clusters of points in the form of plates with four markers for long limb segments, a ‘cap’ with markers for the head, etc. The main models used in mobile devices to estimate the movements of the upper limbs and the biomechanics of joint movement in real time were studied, namely PoseNet, MoveNet Thunder, MoveNet Lightning, and BlazePose in Light, Full, and Heavy versions. The models were evaluated for key characteristics such as speed, device impact, and support for hardware acceleration.en
dc.subjectохорона здоров’яuk
dc.subjectсистеми охорони здоров’яuk
dc.subjectфізична реабілітаціяuk
dc.subjectмедичні інформаційні системиuk
dc.subjectкомп’ютерний зірuk
dc.subjectмобільні застосункиuk
dc.subjectбезмаркерні методи відстеження рухівuk
dc.subjectдіагностикаuk
dc.subjectрухові розлади.uk
dc.subjecthealthcareen
dc.subjecthealthcare systemsen
dc.subjectphysical rehabilitationen
dc.subjectmedical information systemsen
dc.subjectcomputer visionen
dc.subjectmobile applicationsen
dc.subjectmarkerless motion trackingen
dc.subjectdiagnosticsen
dc.subjectmovement disorders.en
dc.typeArticle, professional native edition
dc.typeArticle
dc.language.isoukuk
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dc.date.accessioned2026-10-22T08:18:04Z

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Оптико-електронні інформаційно-енергетичні технології. 2024. № 2