IEEE Trans Neural Syst Rehabil Eng. 2018 Jul;26(7):1414-1423. doi: 10.1109/TNSRE.2018.2821197.
This paper presents a method based on a human upper limb model that assesses the severity of spasticity in patients with stroke objectively. The kinematic model consists of four moving segments connected by four joints. The joint torques are computed using inverse dynamics with measurements from three inertial measurement units (IMUs) attached to the participant's upper limb. The muscle activations are estimated using the joint torques via a musculoskeletal model which consists of 22 muscles. The severity of spasticity is then quantified by measuring the tonic stretch reflex threshold (TSRT) of the participant. 15 patient participants participated in the experiments where they were assessed by two qualified therapists using modified Ashworth scale (MAS), and their motions and EMG signals were captured at the same time. Using the upper limb model, the TSRT of each patient was measured and ranked. The estimated muscle activation profiles have a high correlation (0.707) to the EMG signal profiles. The null hypothesis that the rankings of the severity using the model and the MAS assessment have no correlation has been tested, and was rejected convincingly ( ). These findings suggest that the model has the potential to complement the existing practices by providing an alternative evaluation method.
本文提出了一种基于人体上肢模型的方法,可客观评估脑卒中患者的痉挛严重程度。运动学模型由四个通过四个关节连接的运动段组成。关节转矩通过将测量到的三个惯性测量单元(IMU)附着在参与者的上肢上的测量值应用逆动力学计算得出。肌肉激活是通过肌骨骼模型利用关节转矩进行估计的,该模型由 22 块肌肉组成。然后通过测量参与者的紧张性牵张反射阈值(TSRT)来量化痉挛的严重程度。15 名患者参与者参与了实验,由两名合格的治疗师使用改良的 Ashworth 量表(MAS)进行评估,同时还记录了他们的运动和肌电图信号。使用上肢模型测量并对每个患者的 TSRT 进行了排序。估计的肌肉激活曲线与肌电图信号曲线具有很高的相关性(0.707)。模型和 MAS 评估的严重程度排序没有相关性的零假设被有力地拒绝了()。这些发现表明,该模型有可能通过提供替代评估方法来补充现有实践。