Meng Lin, Li Xinge, Zhang Xiaofei, Pang Jun, Chen Lei, Xu Rui
Annu Int Conf IEEE Eng Med Biol Soc. 2024 Jul;2024:1-4. doi: 10.1109/EMBC53108.2024.10782221.
The assessment of motor fluctuation is essential for patients with Parkinson's Disease (PD). However, the clinical scales are unable to sufficiently reflect motor fluctuations due to their lower sensitivity to subtle changes. Therefore, in this study, we proposed an inertial-based gait normalcy index (GNI) derived from deviations of gait spatiotemporal parameters related to a healthy age-matched baseline. Eight PD patients were recruited and performed straight-walking and turning tasks under constrained and unconstrained scenarios 4 hours before and after the medication at hourly intervals. The results demonstrated that the GNI could efficiently reflect the motor fluctuation after the medication (p<0.05) and PD patients perform their actual gait ability during the unconstrained straight walking scenarios. The GNI under unconstrained straight walking had a significantly positive high correlation with the UPDRS III score (R = 0.880, p = 0.047). The proposed method has great potential in monitoring motor fluctuation during daily unconstrained activities by providing a more comprehensive biomarker in the future.
对帕金森病（PD）患者而言，评估运动波动至关重要。然而，临床量表对细微变化的敏感性较低，无法充分反映运动波动情况。因此，在本研究中，我们提出了一种基于惯性的步态正常指数（GNI），该指数源自与年龄匹配的健康基线相比的步态时空参数偏差。招募了8名PD患者，让他们在服药前和服药后每小时一次的时间间隔内，在受限和非受限场景下进行直线行走和转弯任务。结果表明，GNI能够有效反映服药后的运动波动（p<0.05），且PD患者在非受限直线行走场景中展现出其实际步态能力。非受限直线行走时的GNI与统一帕金森病评定量表第三部分（UPDRS III）评分呈显著正相关（R = 0.880，p = 0.047）。未来，通过提供更全面的生物标志物，所提出的方法在监测日常非受限活动期间的运动波动方面具有巨大潜力。
