Movement and Gait Lab, Sana-Krankenhaus Rummelsberg, 90592 Schwarzenbruck, Germany.
Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 91052 Erlangen, Germany.
Sensors (Basel). 2021 Nov 18;21(22):7680. doi: 10.3390/s21227680.
Digital technologies provide the opportunity to analyze gait patterns in patients with Parkinson's Disease using wearable sensors in clinical settings and a home environment. Confirming the technical validity of inertial sensors with a 3D motion capture system is a necessary step for the clinical application of sensor-based gait analysis. Therefore, the objective of this study was to compare gait parameters measured by a mobile sensor-based gait analysis system and a motion capture system as the gold standard. Gait parameters of 37 patients were compared between both systems after performing a standardized 5 × 10 m walking test by reliability analysis using intra-class correlation and Bland-Altman plots. Additionally, gait parameters of an age-matched healthy control group ( = 14) were compared to the Parkinson cohort. Gait parameters representing bradykinesia and short steps showed excellent reliability (ICC > 0.96). Shuffling gait parameters reached ICC > 0.82. In a stridewise synchronization, no differences were observed for gait speed, stride length, stride time, relative stance and swing time ( > 0.05). In contrast, heel strike, toe off and toe clearance significantly differed between both systems ( < 0.01). Both gait analysis systems distinguish Parkinson patients from controls. Our results indicate that wearable sensors generate valid gait parameters compared to the motion capture system and can consequently be used for clinically relevant gait recordings in flexible environments.
数字技术为在临床环境和家庭环境中使用可穿戴传感器分析帕金森病患者的步态模式提供了机会。使用 3D 运动捕捉系统确认惯性传感器的技术有效性是基于传感器的步态分析临床应用的必要步骤。因此,本研究的目的是比较基于移动传感器的步态分析系统和运动捕捉系统(金标准)测量的步态参数。通过使用组内相关系数和 Bland-Altman 图进行可靠性分析,对 37 名患者在进行标准化的 5×10m 行走测试后,对两种系统的步态参数进行了比较。此外,还将年龄匹配的健康对照组(n=14)的步态参数与帕金森组进行了比较。代表运动迟缓性和短步幅的步态参数具有极好的可靠性(ICC>0.96)。拖曳步态参数的 ICC>0.82。在步幅同步中,步态速度、步长、步时、相对支撑和摆动时间没有差异(>0.05)。相比之下,足跟触地、脚趾离地和脚趾离地间隙在两种系统之间存在显著差异(<0.01)。两种步态分析系统都能将帕金森病患者与对照组区分开来。我们的结果表明,与运动捕捉系统相比,可穿戴传感器可以生成有效的步态参数,因此可以用于灵活环境中的临床相关步态记录。