Department of Mechanical Engineering, University of Texas at Austin, 204 E Dean Keeton St, Austin, TX, 78712, USA.
St. David's Rehabilitation Hospital, St. David's Medical Center, 919 E 32nd St, Austin, TX, 78705, USA.
J Neuroeng Rehabil. 2020 Feb 7;17(1):15. doi: 10.1186/s12984-020-0655-0.
While therapy is an important part of the recovery process, there is a lack of quantitative data detailing the "dosage" of therapy received due to the limitations on in/outpatient accessibility and mobility. Advances in wearable sensor technology have allowed us to obtain an unprecedented glimpse into joint-level kinematics in an unobtrusive manner. The objective of this observational longitudinal pilot study was to evaluate the relations between lower body joint kinematics during therapy and functional gait recovery over the first three months after stroke.
Six individuals with subacute stroke (< 1 month) were monitored for a total of 59 one-hour physical therapy sessions including gait and non-gait activities. Participants donned a heart rate monitor and an inertial motion capture system to measure full lower body joint kinematics during each therapy session. Linear mixed regression models were used to examine relations between functional gait recovery (speed) and activity features including total joint displacements, defined as amount of motion (AoM), step number, change in heart rate (∆HR), and types of tasks performed.
All activity features including AoM, step number, types of tasks performed (all p < 0.01), and ∆HR (p < 0.05) showed strong associations with gait speed. However, AoM (R = 32.1%) revealed the greatest explained variance followed by step number (R = 14.1%), types of tasks performed (R = 8.0%) and ∆HR (R = 5.8%). These relations included both gait and non-gait tasks. Contrary to our expectations, we did not observe a greater relation of functional recovery to motion in the impaired limb (R = 27.8%) compared to the unimpaired limb (R = 32.9%).
This proof-of-concept study shows that recording joint kinematics during gait therapy longitudinally after stroke is feasible and yields important information for the recovery process. These initial results suggest that compared to step number, more holistic outcome measures such as joint motions may be more informative and help elucidate the dosage of therapy.
尽管治疗是康复过程中的重要组成部分,但由于门诊和移动性的限制,缺乏详细描述治疗“剂量”的定量数据。可穿戴传感器技术的进步使我们能够以一种不引人注目的方式前所未有地了解关节水平的运动学。本观察性纵向初步研究的目的是评估治疗过程中下肢关节运动学与中风后前三个月功能步态恢复之间的关系。
6 名亚急性中风(<1 个月)患者接受了总共 59 次 1 小时的物理治疗,包括步态和非步态活动。参与者在每次治疗期间佩戴心率监测器和惯性运动捕捉系统,以测量整个下肢关节运动学。线性混合回归模型用于检查功能步态恢复(速度)与活动特征之间的关系,包括总关节位移(定义为运动幅度(AoM))、步数、心率变化(∆HR)和执行的任务类型。
所有活动特征,包括 AoM、步数、执行的任务类型(所有 p <0.01)和 ∆HR(p <0.05)均与步态速度密切相关。然而,AoM(R = 32.1%)显示出最大的解释方差,其次是步数(R = 14.1%)、执行的任务类型(R = 8.0%)和 ∆HR(R = 5.8%)。这些关系包括步态和非步态任务。与我们的预期相反,我们没有观察到功能恢复与受损肢体(R = 27.8%)的运动相比,与未受损肢体(R = 32.9%)的运动具有更大的关系。
本概念验证研究表明,中风后纵向记录步态治疗期间的关节运动学是可行的,并为康复过程提供了重要信息。这些初步结果表明,与步数相比,更全面的结果测量指标,如关节运动,可能更具信息量,并有助于阐明治疗的剂量。