Farabolini Gianmatteo, Baldini Nicolò, Pagano Alessandro, Andrenelli Elisa, Pepa Lucia, Morone Giovanni, Ceravolo Maria Gabriella, Capecci Marianna
Department of Experimental and Clinical Medicine, Politecnica delle Marche University, 60126 Ancona, Italy.
Department of Information Engineering, Politecnica delle Marche University, 60131 Ancona, Italy.
Sensors (Basel). 2025 Aug 8;25(16):4889. doi: 10.3390/s25164889.
Wearable sensors are a promising tool for the remote, continuous monitoring of motor symptoms and physical activity, especially in individuals with neurological or chronic conditions. Despite many experimental trials, clinical adoption remains limited. A major barrier is the lack of awareness and confidence among healthcare professionals in these technologies.
This systematic review analyzed the use of wearable sensors for continuous motor monitoring at home, focusing on their purpose, type, feasibility, and effectiveness in neurological, musculoskeletal, or rheumatologic conditions. This review followed PRISMA guidelines and included studies from PubMed, Scopus, and Web of Science.
Seventy-two studies with 7949 participants met inclusion criteria. Neurological disorders, particularly Parkinson's disease, were the most frequently studied. Common sensors included inertial measurement units (IMUs), accelerometers, and gyroscopes, often integrated into medical devices, smartwatches, or smartphones. Monitoring periods ranged from 24 h to over two years. Feasibility studies showed high patient compliance (≥70%) and good acceptance, with strong agreement with clinical assessments. However, only half of the studies were controlled trials, and just 5.6% were randomized.
Wearable sensors offer strong potential for real-world motor function monitoring. Yet, challenges persist, including ethical issues, data privacy, standardization, and healthcare access. Artificial intelligence integration may boost predictive accuracy and personalized care.
可穿戴传感器是一种很有前景的工具，可用于远程、持续监测运动症状和身体活动，尤其是对患有神经系统疾病或慢性病的个体。尽管进行了许多实验性试验，但临床应用仍然有限。一个主要障碍是医疗保健专业人员对这些技术缺乏认识和信心。
本系统评价分析了可穿戴传感器在家庭中用于持续运动监测的情况，重点关注其在神经、肌肉骨骼或风湿性疾病中的目的、类型、可行性和有效性。本评价遵循PRISMA指南，纳入了来自PubMed、Scopus和科学网的研究。
72项研究共7949名参与者符合纳入标准。神经系统疾病，尤其是帕金森病，是研究最频繁的疾病。常见的传感器包括惯性测量单元（IMU）、加速度计和陀螺仪，它们通常集成到医疗设备、智能手表或智能手机中。监测期从24小时到两年多不等。可行性研究表明患者依从性高（≥70%）且接受度良好，与临床评估高度一致。然而，只有一半的研究是对照试验，只有5.6%是随机试验。
可穿戴传感器在现实世界的运动功能监测方面具有强大潜力。然而，挑战依然存在，包括伦理问题、数据隐私、标准化和医疗保健获取。人工智能集成可能会提高预测准确性和个性化护理水平。
