用无标记运动捕捉技术量化神经退行性疾病的功能表现:系统综述。

IF 5 Q1 GERIATRICS & GERONTOLOGY
JMIR Aging Pub Date : 2024-08-06 DOI:10.2196/52582
Julian Jeyasingh-Jacob, Mark Crook-Rumsey, Harshvi Shah, Theresita Joseph, Subati Abulikemu, Sarah Daniels, David J Sharp, Shlomi Haar
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引用次数: 0

摘要

背景:无标记运动捕捉(MMC)使用摄像机或深度传感器进行全身跟踪,是一种在社区环境中客观、无干扰地监测功能表现的有效方法,有助于痴呆等神经退行性疾病的临床决策:本系统性综述的主要目的是研究使用全身追踪技术对痴呆症、轻度认知障碍和帕金森病患者的功能表现进行量化的 MMC 应用:在 2022 年 11 月至 2023 年 2 月期间,对 Embase、MEDLINE、CINAHL 和 Scopus 数据库进行了系统检索,共获得 1595 项结果。纳入标准为MMC和全身追踪。共有 157 项研究被纳入全文筛选,其中 26 项符合筛选标准的合格研究被纳入综述。.结果:所选研究主要侧重于步态分析(24 项),同时也探讨了其他功能任务,如从坐到站(5 项)和原地踏步(1 项)。然而,所有纳入的研究均未对日常生活活动进行评估。各项研究的 MMC 模型各不相同,包括深度摄像头(18 项)与标准视频摄像头(5 项)或手机摄像头(2 项),并使用深度学习模型进行后处理。然而,只有 6 项研究与已建立的黄金标准动作捕捉模型进行了严格比较:尽管 MMC 有潜力成为分析痴呆症、轻度认知障碍和帕金森病患者运动和姿势的有效工具,但仍需进一步研究,以确定 MMC 在量化现实世界中的移动性和功能表现方面的临床实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Markerless Motion Capture to Quantify Functional Performance in Neurodegeneration: Systematic Review.

Background: Markerless motion capture (MMC) uses video cameras or depth sensors for full body tracking and presents a promising approach for objectively and unobtrusively monitoring functional performance within community settings, to aid clinical decision-making in neurodegenerative diseases such as dementia.

Objective: The primary objective of this systematic review was to investigate the application of MMC using full-body tracking, to quantify functional performance in people with dementia, mild cognitive impairment, and Parkinson disease.

Methods: A systematic search of the Embase, MEDLINE, CINAHL, and Scopus databases was conducted between November 2022 and February 2023, which yielded a total of 1595 results. The inclusion criteria were MMC and full-body tracking. A total of 157 studies were included for full-text screening, out of which 26 eligible studies that met the selection criteria were included in the review. .

Results: Primarily, the selected studies focused on gait analysis (n=24), while other functional tasks, such as sit to stand (n=5) and stepping in place (n=1), were also explored. However, activities of daily living were not evaluated in any of the included studies. MMC models varied across the studies, encompassing depth cameras (n=18) versus standard video cameras (n=5) or mobile phone cameras (n=2) with postprocessing using deep learning models. However, only 6 studies conducted rigorous comparisons with established gold-standard motion capture models.

Conclusions: Despite its potential as an effective tool for analyzing movement and posture in individuals with dementia, mild cognitive impairment, and Parkinson disease, further research is required to establish the clinical usefulness of MMC in quantifying mobility and functional performance in the real world.

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来源期刊
JMIR Aging
JMIR Aging Social Sciences-Health (social science)
CiteScore
6.50
自引率
4.10%
发文量
71
审稿时长
12 weeks
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