College of Furnishings and Industrial Design, Nanjing Forestry University, Nanjing 210037, China.
Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Nanjing Forestry University, Nanjing 210037, China.
Sensors (Basel). 2023 Sep 5;23(18):7667. doi: 10.3390/s23187667.
The integration of wearable sensor technology and machine learning algorithms has significantly transformed the field of intelligent medical rehabilitation. These innovative technologies enable the collection of valuable movement, muscle, or nerve data during the rehabilitation process, empowering medical professionals to evaluate patient recovery and predict disease development more efficiently. This systematic review aims to study the application of wearable sensor technology and machine learning algorithms in different disease rehabilitation training programs, obtain the best sensors and algorithms that meet different disease rehabilitation conditions, and provide ideas for future research and development. A total of 1490 studies were retrieved from two databases, the Web of Science and IEEE Xplore, and finally 32 articles were selected. In this review, the selected papers employ different wearable sensors and machine learning algorithms to address different disease rehabilitation problems. Our analysis focuses on the types of wearable sensors employed, the application of machine learning algorithms, and the approach to rehabilitation training for different medical conditions. It summarizes the usage of different sensors and compares different machine learning algorithms. It can be observed that the combination of these two technologies can optimize the disease rehabilitation process and provide more possibilities for future home rehabilitation scenarios. Finally, the present limitations and suggestions for future developments are presented in the study.
可穿戴传感器技术与机器学习算法的融合，极大地改变了智能医疗康复领域。这些创新技术使得在康复过程中能够收集有价值的运动、肌肉或神经数据，使医疗专业人员能够更有效地评估患者的康复情况和预测疾病的发展。本系统综述旨在研究可穿戴传感器技术和机器学习算法在不同疾病康复训练计划中的应用，获取满足不同疾病康复条件的最佳传感器和算法，并为未来的研究和开发提供思路。从两个数据库 Web of Science 和 IEEE Xplore 共检索到 1490 项研究，最终选择了 32 篇文章。在本综述中，所选论文采用不同的可穿戴传感器和机器学习算法来解决不同的疾病康复问题。我们的分析重点关注所使用的可穿戴传感器的类型、机器学习算法的应用以及针对不同医疗状况的康复训练方法。它总结了不同传感器的使用情况并比较了不同的机器学习算法。可以看出，这两种技术的结合可以优化疾病康复过程，并为未来的家庭康复场景提供更多的可能性。最后，在研究中提出了当前的局限性和对未来发展的建议。
