Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes
Due to global ageing, the burden of chronic movement and neurological disorders (Parkinson’s disease and essential tremor) is rapidly increasing. Current diagnosis and monitoring of these disorders rely largely on face-to-face assessments utilising clinical rating scales, which are semi-subjective a...
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| Format: | Article |
| Language: | English |
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Wolters Kluwer – Medknow Publications
2024-03-01
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| Series: | Singapore Medical Journal |
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| Online Access: | https://journals.lww.com/10.4103/singaporemedj.SMJ-2023-189 |
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| _version_ | 1823863749125079040 |
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| author | Kye Won Park Maryam S Mirian Martin J McKeown |
| author_facet | Kye Won Park Maryam S Mirian Martin J McKeown |
| author_sort | Kye Won Park |
| collection | DOAJ |
| description | Due to global ageing, the burden of chronic movement and neurological disorders (Parkinson’s disease and essential tremor) is rapidly increasing. Current diagnosis and monitoring of these disorders rely largely on face-to-face assessments utilising clinical rating scales, which are semi-subjective and time-consuming. To address these challenges, the utilisation of artificial intelligence (AI) has emerged. This review explores the advantages and challenges associated with using AI-driven video monitoring to care for elderly patients with movement disorders. The AI-based video monitoring systems offer improved efficiency and objectivity in remote patient monitoring, enabling real-time analysis of data, more uniform outcomes and augmented support for clinical trials. However, challenges, such as video quality, privacy compliance and noisy training labels, during development need to be addressed. Ultimately, the advancement of video monitoring for movement disorders is expected to evolve towards discreet, home-based evaluations during routine daily activities. This progression must incorporate data security, ethical considerations and adherence to regulatory standards. |
| format | Article |
| id | doaj-art-300533cbf4da4b4688fb0f4c748ed486 |
| institution | Kabale University |
| issn | 0037-5675 2737-5935 |
| language | English |
| publishDate | 2024-03-01 |
| publisher | Wolters Kluwer – Medknow Publications |
| record_format | Article |
| series | Singapore Medical Journal |
| spelling | doaj-art-300533cbf4da4b4688fb0f4c748ed4862025-02-09T10:19:44ZengWolters Kluwer – Medknow PublicationsSingapore Medical Journal0037-56752737-59352024-03-0165314114910.4103/singaporemedj.SMJ-2023-189Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapesKye Won ParkMaryam S MirianMartin J McKeownDue to global ageing, the burden of chronic movement and neurological disorders (Parkinson’s disease and essential tremor) is rapidly increasing. Current diagnosis and monitoring of these disorders rely largely on face-to-face assessments utilising clinical rating scales, which are semi-subjective and time-consuming. To address these challenges, the utilisation of artificial intelligence (AI) has emerged. This review explores the advantages and challenges associated with using AI-driven video monitoring to care for elderly patients with movement disorders. The AI-based video monitoring systems offer improved efficiency and objectivity in remote patient monitoring, enabling real-time analysis of data, more uniform outcomes and augmented support for clinical trials. However, challenges, such as video quality, privacy compliance and noisy training labels, during development need to be addressed. Ultimately, the advancement of video monitoring for movement disorders is expected to evolve towards discreet, home-based evaluations during routine daily activities. This progression must incorporate data security, ethical considerations and adherence to regulatory standards.https://journals.lww.com/10.4103/singaporemedj.SMJ-2023-189artificial intelligencecomputer visionmovement disordersparkinson’s diseasevideo |
| spellingShingle | Kye Won Park Maryam S Mirian Martin J McKeown Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes Singapore Medical Journal artificial intelligence computer vision movement disorders parkinson’s disease video |
| title | Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes |
| title_full | Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes |
| title_fullStr | Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes |
| title_full_unstemmed | Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes |
| title_short | Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes |
| title_sort | artificial intelligence based video monitoring of movement disorders in the elderly a review on current and future landscapes |
| topic | artificial intelligence computer vision movement disorders parkinson’s disease video |
| url | https://journals.lww.com/10.4103/singaporemedj.SMJ-2023-189 |
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