IEEE Trans Neural Syst Rehabil Eng. 2018 Jul;26(7):1424-1434. doi: 10.1109/TNSRE.2018.2838767.
To facilitate stretch reflex onset (SRO) detection and improve accuracy and reliability of spasticity assessment in clinical settings, a new method to measure dynamic stretch reflex threshold (DSRT) based on Hilbert-Huang transform marginal spectrum entropy (HMSEN) of surface electromyography (sEMG) signals and a portable system to quantify modified Ashworth scale (MAS) for spasticity assessment were developed. The sEMG signals were divided into frames using a fixed-length sliding window, and the HMSEN of each frame was calculated. An adaptive threshold was set to measure the DSRT. The HMSEN based method can quantify muscle activity through time-frequency and nonlinear dynamics analysis, therefore providing deeper insight about the spastic muscle mechanisms during stretching and a reliable SRO detection method. Experimental results revealed that the HMSEN based method could reliably detect the SRO and measure the DSRT (recognition rate: 95.45%), and could achieve improved performance over the time-domain based method. There was a strong correlation ( to -0.900) between the MAS scores and the DSRT index, and the test-retest reliability was high. Additionally, limitations of the MAS were analyzed. This paper indicates that the presented framework can provide a promising tool to measure DSRT and a clinical quantitative approach for spasticity assessment.
为了促进牵张反射起始（SRO）的检测，并提高临床痉挛评估的准确性和可靠性，提出了一种新的基于表面肌电信号（sEMG）希尔伯特-黄变换边际谱熵（HMSEN）测量动态牵张反射阈值（DSRT）的方法，并开发了一种用于量化改良 Ashworth 量表（MAS）的便携式系统。使用固定长度滑动窗口将 sEMG 信号划分为帧，并计算每个帧的 HMSEN。设置自适应阈值以测量 DSRT。基于 HMSEN 的方法可以通过时频和非线性动力学分析来量化肌肉活动，因此可以深入了解伸展过程中痉挛肌肉的机制，并提供可靠的 SRO 检测方法。实验结果表明，基于 HMSEN 的方法可以可靠地检测 SRO 并测量 DSRT（识别率：95.45%），并且在性能上优于基于时域的方法。MAS 评分与 DSRT 指数之间存在很强的相关性（to -0.900），测试-重测可靠性较高。此外，还分析了 MAS 的局限性。本文表明，所提出的框架可以为测量 DSRT 提供一种有前景的工具，并为痉挛评估提供一种临床定量方法。
