Caroppo Andrea, Manni Andrea, Rescio Gabriele, Carluccio Anna Maria, Siciliano Pietro Aleardo, Leone Alessandro
National Research Council of Italy, Institute for Microelectronics and Microsystems, 73100 Lecce, Italy.
Sensors (Basel). 2025 Jan 5;25(1):266. doi: 10.3390/s25010266.
In the medical field, there are several very different movement disorders, such as tremors, Parkinson's disease, or Huntington's disease. A wide range of motor and non-motor symptoms characterizes them. It is evident that in the modern era, the use of smart wrist devices, such as smartwatches, wristbands, and smart bracelets is spreading among all categories of people. This diffusion is justified by the limited costs, ease of use, and less invasiveness (and consequently greater acceptability) than other types of sensors used for health status monitoring. This systematic review aims to synthesize research studies using smart wrist devices for a specific class of movement disorders. Following PRISMA-S guidelines, 130 studies were selected and analyzed. For each selected study, information is provided relating to the smartwatch/wristband/bracelet model used (whether it is commercial or not), the number of end-users involved in the experimentation stage, and finally the characteristics of the benchmark dataset possibly used for testing. Moreover, some articles also reported the type of raw data extracted from the smart wrist device, the implemented designed algorithmic pipeline, and the data classification methodology. It turned out that most of the studies have been published in the last ten years, showing a growing interest in the scientific community. The selected articles mainly investigate the relationship between smart wrist devices and Parkinson's disease. Epilepsy and seizure detection are also research topics of interest, while there are few papers analyzing gait disorders, Huntington's Disease, ataxia, or Tourette Syndrome. However, the results of this review highlight the difficulties still present in the use of the smartwatch/wristband/bracelet for the identified categories of movement disorders, despite the advantages these technologies could bring in the dissemination of low-cost solutions usable directly within living environments and without the need for caregivers or medical personnel.
在医学领域，存在几种截然不同的运动障碍，如震颤、帕金森病或亨廷顿舞蹈症。它们具有一系列广泛的运动和非运动症状。显然，在现代，智能腕部设备，如智能手表、腕带和智能手环，正在各类人群中普及。这种普及是合理的，因为与用于健康状况监测的其他类型传感器相比，它们成本有限、使用方便且侵入性较小（因而可接受性更高）。本系统综述旨在综合利用智能腕部设备针对特定类别的运动障碍开展的研究。遵循PRISMA-S指南，选取并分析了130项研究。对于每项所选研究，提供了有关所使用的智能手表/腕带/手环型号（是否为商用）、参与实验阶段的最终用户数量，以及最终可能用于测试的基准数据集特征的信息。此外，一些文章还报告了从智能腕部设备提取的原始数据类型、所实施的设计算法流程以及数据分类方法。结果表明，大多数研究是在过去十年发表的，这表明科学界的兴趣在不断增加。所选文章主要研究智能腕部设备与帕金森病之间的关系。癫痫和癫痫发作检测也是感兴趣的研究课题，而分析步态障碍、亨廷顿舞蹈症、共济失调或妥瑞氏综合征的论文较少。然而，本综述的结果凸显了在将智能手表/腕带/手环用于已确定的运动障碍类别时仍然存在的困难，尽管这些技术在传播可直接在生活环境中使用且无需护理人员或医务人员的低成本解决方案方面可能具有优势。
