Objective Assessment of Spasticity With a Method Based on a Human Upper Limb Model

被引:25
作者
Ang, Wei Sin [1 ]
Geyer, Hartmut [2 ]
Chen, I-Ming [3 ]
Ang, Wei Tech [3 ]
机构
[1] Nanyang Polytech, Sch Engn, Singapore 569830, Singapore
[2] Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA
[3] Nanyang Technol Univ, Sch Mech & Aerosp Engn, Singapore 639798, Singapore
关键词
Rehabilitation robotics; simulation; biomedical engineering; SURFACE MYOELECTRIC SIGNALS; STRETCH REFLEX THRESHOLD; MODIFIED ASHWORTH SCALE; AMBULATORY MEASUREMENT; PENDULUM TEST; ELBOW KINEMATICS; MUSCLE STRENGTH; PART II; SHOULDER; MOTION;
D O I
10.1109/TNSRE.2018.2821197
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
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 (p approximate to 0.0003). These findings suggest that the model has the potential to complement the existing practices by providing an alternative evaluation method.
引用
收藏
页码:1414 / 1423
页数:10
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