基于智能手机的帕金森病监测:定量手部震颤严重程度和药物疗效的准实验研究。
Smartphone-Based Monitoring of Parkinson Disease: Quasi-Experimental Study to Quantify Hand Tremor Severity and Medication Effectiveness.
机构信息
University of Oulu, Oulu, Finland.
University of Siegen, Siegen, Germany.
出版信息
JMIR Mhealth Uhealth. 2020 Nov 26;8(11):e21543. doi: 10.2196/21543.
BACKGROUND
Hand tremor typically has a negative impact on a person's ability to complete many common daily activities. Previous research has investigated how to quantify hand tremor with smartphones and wearable sensors, mainly under controlled data collection conditions. Solutions for daily real-life settings remain largely underexplored.
OBJECTIVE
Our objective was to monitor and assess hand tremor severity in patients with Parkinson disease (PD), and to better understand the effects of PD medications in a naturalistic environment.
METHODS
Using the Welch method, we generated periodograms of accelerometer data and computed signal features to compare patients with varying degrees of PD symptoms.
RESULTS
We introduced and empirically evaluated the tremor intensity parameter (TIP), an accelerometer-based metric to quantify hand tremor severity in PD using smartphones. There was a statistically significant correlation between the TIP and self-assessed Unified Parkinson Disease Rating Scale (UPDRS) II tremor scores (Kendall rank correlation test: z=30.521, P<.001, τ=0.5367379; n=11). An analysis of the "before" and "after" medication intake conditions identified a significant difference in accelerometer signal characteristics among participants with different levels of rigidity and bradykinesia (Wilcoxon rank sum test, P<.05).
CONCLUSIONS
Our work demonstrates the potential use of smartphone inertial sensors as a systematic symptom severity assessment mechanism to monitor PD symptoms and to assess medication effectiveness remotely. Our smartphone-based monitoring app may also be relevant for other conditions where hand tremor is a prevalent symptom.
背景
手部震颤通常会对个人完成许多常见日常活动的能力产生负面影响。先前的研究已经调查了如何使用智能手机和可穿戴传感器对手部震颤进行量化,主要是在受控的数据采集条件下。针对日常生活实际环境的解决方案在很大程度上仍未得到充分探索。
目的
我们的目标是监测和评估帕金森病(PD)患者的手部震颤严重程度,并在自然环境中更好地了解 PD 药物的作用。
方法
我们使用 Welch 方法生成加速度计数据的周期图,并计算信号特征,以比较具有不同 PD 症状程度的患者。
结果
我们引入并经验性地评估了震颤强度参数(TIP),这是一种基于智能手机的加速度计指标,用于量化 PD 患者手部震颤的严重程度。TIP 与自我评估的帕金森病统一评定量表(UPDRS)II 震颤评分之间存在统计学上显著的相关性(Kendall 等级相关检验:z=30.521,P<.001,τ=0.5367379;n=11)。对“用药前”和“用药后”条件的分析表明,在具有不同僵硬和运动迟缓程度的参与者中,加速度计信号特征存在显著差异(Wilcoxon 等级和检验,P<.05)。
结论
我们的工作表明,智能手机惯性传感器具有作为一种系统性症状严重程度评估机制的潜力,可以远程监测 PD 症状并评估药物效果。我们基于智能手机的监测应用程序可能也与其他手部震颤是常见症状的疾病相关。