Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.
Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Sensors (Basel). 2021 Apr 10;21(8):2661. doi: 10.3390/s21082661.
Freezing of gait (FOG), a debilitating symptom of Parkinson's disease (PD), can be safely studied using the stepping in place (SIP) task. However, clinical, visual identification of FOG during SIP is subjective and time consuming, and automatic FOG detection during SIP currently requires measuring the center of pressure on dual force plates. This study examines whether FOG elicited during SIP in 10 individuals with PD could be reliably detected using kinematic data measured from wearable inertial measurement unit sensors (IMUs). A general, logistic regression model (area under the curve = 0.81) determined that three gait parameters together were overall the most robust predictors of FOG during SIP: arrhythmicity, swing time coefficient of variation, and swing angular range. Participant-specific models revealed varying sets of gait parameters that best predicted FOG for each participant, highlighting variable FOG behaviors, and demonstrated equal or better performance for 6 out of the 10 participants, suggesting the opportunity for model personalization. The results of this study demonstrated that gait parameters measured from wearable IMUs reliably detected FOG during SIP, and the general and participant-specific gait parameters allude to variable FOG behaviors that could inform more personalized approaches for treatment of FOG and gait impairment in PD.
冻结步态（FOG）是帕金森病（PD）的一种使人虚弱的症状，可以使用原地踏步（SIP）任务安全地进行研究。然而，临床中，视觉识别 SIP 中的 FOG 是主观且耗时的，而目前自动检测 SIP 中的 FOG 需要测量双压力板上的压力中心。本研究探讨了在 10 名 PD 患者进行 SIP 时，是否可以使用可穿戴惯性测量单元传感器（IMU）测量的运动学数据可靠地检测到 FOG。一般的逻辑回归模型（曲线下面积=0.81）确定，三个步态参数一起是总体上最能预测 SIP 中 FOG 的最有力指标：节律性、摆动时间变异系数和摆动角度范围。针对每个参与者的特定模型揭示了最佳预测 FOG 的不同步态参数集，突出了可变的 FOG 行为，并在 10 名参与者中的 6 名中表现出同等或更好的性能，这表明了个性化模型的机会。这项研究的结果表明，可穿戴 IMU 测量的步态参数可以可靠地检测 SIP 中的 FOG，而一般和参与者特定的步态参数暗示了 FOG 行为的可变性，这可以为 PD 中 FOG 和步态障碍的更个性化治疗方法提供信息。
