Rodríguez-Martín Daniel, Cabestany Joan, Pérez-López Carlos, Pie Marti, Calvet Joan, Samà Albert, Capra Chiara, Català Andreu, Rodríguez-Molinero Alejandro
Sense4Care S.L., Cornellà de Llobregat, Spain.
Technical Research Centre for Dependency Care and Autonomous Living, Universitat Politecnica de Catalunya, Barcelona, Spain.
Front Neurol. 2022 Jun 2;13:912343. doi: 10.3389/fneur.2022.912343. eCollection 2022.
In the past decade, the use of wearable medical devices has been a great breakthrough in clinical practice, trials, and research. In the Parkinson's disease field, clinical evaluation is time limited, and healthcare professionals need to rely on retrospective data collected through patients' self-filled diaries and administered questionnaires. As this often leads to inaccurate evaluations, a more objective system for symptom monitoring in a patient's daily life is claimed. In this regard, the use of wearable medical devices is crucial. This study aims at presenting a review on STAT-ON, a wearable medical device Class IIa, which provides objective information on the distribution and severity of PD motor symptoms in home environments. The sensor analyzes inertial signals, with a set of validated machine learning algorithms running in real time. The device was developed for 12 years, and this review aims at gathering all the results achieved within this time frame. First, a compendium of the complete journey of STAT-ON since 2009 is presented, encompassing different studies and developments in funded European and Spanish national projects. Subsequently, the methodology of database construction and machine learning algorithms design and development is described. Finally, clinical validation and external studies of STAT-ON are presented.
在过去十年中,可穿戴医疗设备的使用在临床实践、试验和研究方面取得了重大突破。在帕金森病领域,临床评估时间有限,医疗保健专业人员需要依赖通过患者自行填写的日记和发放的问卷收集的回顾性数据。由于这往往导致评估不准确,因此需要一个更客观的系统来监测患者日常生活中的症状。在这方面,可穿戴医疗设备的使用至关重要。本研究旨在对二类a级可穿戴医疗设备STAT-ON进行综述,该设备可提供帕金森病运动症状在家庭环境中的分布和严重程度的客观信息。该传感器分析惯性信号,并运行一组经过验证的机器学习算法。该设备的研发历时12年,本综述旨在收集在此时间范围内取得的所有成果。首先,介绍了STAT-ON自2009年以来的完整历程概要,包括在欧洲和西班牙国家资助项目中的不同研究和进展。随后,描述了数据库构建以及机器学习算法设计与开发的方法。最后,介绍了STAT-ON的临床验证和外部研究情况。