Instituto de Medicina Molecular, 1649-028 Lisbon, Portugal.
CNS-Campus Neurológico, 2560-280 Torres Vedras, Portugal.
Sensors (Basel). 2021 Jul 21;21(15):4972. doi: 10.3390/s21154972.
Mobile health (mHealth) has emerged as a potential solution to providing valuable ecological information about the severity and burden of Parkinson's disease (PD) symptoms in real-life conditions. : The objective of our study was to explore the feasibility and usability of an mHealth system for continuous and objective real-life measures of patients' health and functional mobility, in unsupervised settings. : Patients with a clinical diagnosis of PD, who were able to walk unassisted, and had an Android smartphone were included. Patients were asked to answer a daily survey, to perform three weekly active tests, and to perform a monthly in-person clinical assessment. Feasibility and usability were explored as primary and secondary outcomes. An exploratory analysis was performed to investigate the correlation between data from the mKinetikos app and clinical assessments. : Seventeen participants (85%) completed the study. Sixteen participants (94.1%) showed a medium-to-high level of compliance with the mKinetikos system. A 6-point drop in the total score of the Post-Study System Usability Questionnaire was observed. : Our results support the feasibility of the mKinetikos system for continuous and objective real-life measures of a patient's health and functional mobility. The observed correlations of mKinetikos metrics with clinical data seem to suggest that this mHealth solution is a promising tool to support clinical decisions.
移动医疗 (mHealth) 已成为提供有关帕金森病 (PD) 症状严重程度和负担的有价值的生态信息的潜在解决方案,可在现实生活条件下实现。我们的研究目的是探索一种 mHealth 系统在非监督环境下对患者健康和功能移动性进行连续和客观的实时测量的可行性和可用性。纳入了具有临床诊断的 PD 患者,这些患者能够独立行走,并且拥有 Android 智能手机。要求患者每天回答一次调查,每周进行三次主动测试,每月进行一次现场临床评估。将可行性和可用性作为主要和次要结果进行了探索。还进行了探索性分析,以研究 mKinetikos 应用程序数据与临床评估之间的相关性。十七名参与者(85%)完成了研究。十六名参与者(94.1%)对 mKinetikos 系统表现出中高水平的依从性。在研究后系统可用性问卷的总分中观察到 6 分的下降。我们的研究结果支持 mKinetikos 系统用于对患者健康和功能移动性进行连续和客观的实时测量的可行性。观察到的 mKinetikos 指标与临床数据之间的相关性似乎表明,这种 mHealth 解决方案是支持临床决策的有前途的工具。