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Video Movement Analysis Using Smartphones ViMAS: A Pilot Study
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基于智能手机的手动功能评估:系统审查

Yan Fu1, Yuxin Zhang1, Bing Ye2,3

  • 1School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.

Journal of medical Internet research
|September 16, 2024
PubMed
概括
此摘要是机器生成的。

智能手机提供了一个有希望的,可访问的工具来评估手的功能,利用内置的传感器,如加速度计和摄像头. 机器学习方法有效地分析这些数据,用于疾病检测和严重程度评估.

关键词:
数字健康数字健康手功能的评估手功能的评估.移动健康 移动健康 移动健康 移动健康移动健康的移动健康手机电话 手机电话手机电话康复康复康复康复康复康复基于智能手机的传感器

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科学领域:

  • 生物医学工程 生物医学工程
  • 数字健康数字健康
  • 康复技术 康复技术 康复技术

背景情况:

  • 传统的手部功能评估在有效性,可靠性和数据管理方面面临挑战.
  • 智能手机提供了一个具有成本效益和可访问的解决方案,用于客观地评估手部功能.
  • 使用内置的智能手机传感器可以克服传统评估方法的局限性.

研究的目的:

  • 系统地审查和评估基于智能手机的手动功能评估现有研究.
  • 用智能手机技术识别常见的手部功能障碍和评估方法.

主要方法:

  • 在8个数据库中进行了全面的文献搜索.
  • 通过使用混合方法评估工具选和评估研究.
  • 数据提取集中在研究特征,传感器和分析方法 (统计和机器学习) 上.

主要成果:

  • 包括46项研究,确定了11种类型的手部功能障碍和6种特定的功能障碍.
  • 加速度计和摄像头是最常用的智能手机传感器.
  • 机器学习算法显示出疾病检测,严重程度评估和预测的前景.

结论:

  • 基于智能手机的评估是评估手部功能的可行和有前途的方法.
  • 机器学习对于使用智能手机数据对手部功能障碍水平的分类是有效的.
  • 未来的研究应该专注于建立一个黄金标准,利用多个传感器,并开发实时ML应用程序用于康复.