基于自适应Chirplet分解的偏瘫肌强直症状评估

为对偏瘫患者的痉挛性肌强直症状进行定量评价,设计了一种基于自适应Ch irp let(线性调频小波)分解的表面肌电信号处理方法。采集了15例偏瘫患者在上肢单关节神经康复机器人上做肘关节被动屈伸动作时肱二头肌的表面肌电信号。通过比较不同患者的最优Ch irp let时频参数,量化评价患者肌强直症状。结果表明:通过该方法得到的患者在出现肌强直症状时的肌纤维放电时间与患者相应的简式Fug l-M eyer运动功能评价(上肢)分数存在较好的线性关系,可以从一个方面反映偏瘫患者患侧上肢的运动功能。

Estimation of hemiplegia patients' myotonic reactions based on adaptive Chirplet decomposition

A surface electromyography(SEMG) analysis method was designed based on adaptive Chirplet decomposition to quantitatively estimate hemiplegia patients' myotonic reactions.15 hemiplegia patients were recruited to participate in a test using a one-joint rehabilitation training robot which collected SEMG signals from the biceps muscles of their arms.The myotonic reaction was then studied by comparing the optimal Chirplet time and frequency parameters and checked using Fugl-Meyer assessment.The results indicate that the discharge time of the muscle fibre obtained using this method is linearly related to the Fugl-Meyer assessment score,which quantitatively expresses the patients' motor functions.