Real-time gait metric estimation for everyday gait training with wearable devices in people poststroke
Real-time gait metric estimation for everyday gait training with wearable devices in people poststroke
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DOI：
10.1017/wtc.2020.11
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发表时间：
2021-03-25
影响因子：
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通讯作者：
Walsh, Conor J.
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文献类型：
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作者：
Arens, Philipp;Siviy, Christopher;Walsh, Conor J.
中风后偏瘫患者行走缓慢、不对称、效率低下，严重影响日常生活活动。广泛的研究表明，功能性、高强度和特定任务的步态训练有助于有效的步态康复，我们小组的目标是用软机器人外衣鼓励这些特征。然而，标准的临床评估可能缺乏精确度和频率来检测常规步态训练和体外皮下辅助步态训练期间干预效果的细微变化，这可能会阻碍靶向治疗方案。在本文中，我们使用外衣集成的惯性传感器来重建与外周、足部间隙和步长相关的三个具有临床意义的步态指标。我们的方法使用身体两侧的瞬时信息来校正传感器漂移。这种方法使我们的方法对中风后不规则的行走条件具有鲁棒性，并可用于实时运动监测、体外辅助控制和生物反馈等实时应用。与基于实验室的光学运动捕捉相比，我们在8人中风后对我们的算法进行了验证。平均误差在0.2 cm以下(9.9%)，-0.6 cm(-3.5%)，-0.6 cm(-3.5%)，3.8 cm(3.6%)。一个单一参与者的案例研究展示了我们的技术在日常生活环境中的前景，方法是在繁忙的户外广场行走时检测外衣引起的步态变化。
Hemiparetic walking after stroke is typically slow, asymmetric, and inefficient, significantly impacting activities of daily living. Extensive research shows that functional, intensive, and task-specific gait training is instrumental for effective gait rehabilitation, characteristics that our group aims to encourage with soft robotic exosuits. However, standard clinical assessments may lack the precision and frequency to detect subtle changes in intervention efficacy during both conventional and exosuit-assisted gait training, potentially impeding targeted therapy regimes. In this paper, we use exosuit-integrated inertial sensors to reconstruct three clinically meaningful gait metrics related to circumduction, foot clearance, and stride length. Our method corrects sensor drift using instantaneous information from both sides of the body. This approach makes our method robust to irregular walking conditions poststroke as well as usable in real-time applications, such as real-time movement monitoring, exosuit assistance control, and biofeedback. We validate our algorithm in eight people poststroke in comparison to lab-based optical motion capture. Mean errors were below 0.2 cm (9.9%) for circumduction, -0.6 cm (-3.5%) for foot clearance, and 3.8 cm (3.6%) for stride length. A single-participant case study shows our technique's promise in daily-living environments by detecting exosuit-induced changes in gait while walking in a busy outdoor plaza.