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Review
. 2024 Mar 1;65(3):141-149.
doi: 10.4103/singaporemedj.SMJ-2023-189. Epub 2024 Mar 26.

Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes

Kye Won Park  1 , Maryam S Mirian  1 , Martin J McKeown  1   2
Affiliations
Review

Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes

Kye Won Park et al. Singapore Med J. .

Abstract

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.

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Conflict of interest statement

There are no conflicts of interest.

Figures

Figure 1
Figure 1
Flow chart shows the literature search flow. ET: essential tremor, PD: Parkinson’s disease
Figure 2
Figure 2
The three-step scheme of pipelines for the video-based movement disorder monitoring system.
See this image and copyright information in PMC

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