Spasticity assessment based on the Hilbert-Huang transform marginal spectrum entropy and the root mean square of surface electromyography signals: a preliminary study

Biomedical Engineering Online
Baohua HuYong Wang

Abstract

Most of the objective and quantitative methods proposed for spasticity measurement are not suitable for clinical application, and methods for surface electromyography (sEMG) signal processing are mainly limited to the time-domain. This study aims to quantify muscle activity in the time-frequency domain, and develop a practical clinical method for the objective and reliable evaluation of the spasticity based on the Hilbert-Huang transform marginal spectrum entropy (HMSEN) and the root mean square (RMS) of sEMG signals. Twenty-six stroke patients with elbow flexor spasticity participated in the study. The subjects were tested at sitting position with the upper limb stretched towards the ground. The HMSEN of the sEMG signals obtained from the biceps brachii was employed to facilitate the stretch reflex onset (SRO) detection. Then, the difference between the RMS of a fixed-length sEMG signal obtained after the SRO and the RMS of a baseline sEMG signal, denoted as the RMS difference (RMSD), was employed to evaluate the spasticity level. The relations between Modified Ashworth Scale (MAS) scores and RMSD were investigated by Ordinal Logistic Regression (OLR). Goodness-of-fit of the OLR was obtained with Hosmer-Lemeshow test. The HMSE...Continue Reading

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Citations

Jan 11, 2020·Frontiers in Systems Neuroscience·Nishant Rao, Pranav J Parikh
Jun 2, 2020·Journal of Neural Engineering·Zhaohui LiMingxin Liu
Nov 6, 2020·Neurological Sciences : Official Journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology·Sara HalakooShapour Jaberzadeh
Aug 14, 2021·Developmental Neurorehabilitation·Giulia Armani-FranceschiRita Lucena
Sep 4, 2021·Neurological Sciences : Official Journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology·Fatemeh EhsaniShapour Jaberzadeh

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Software Mentioned

Microsoft Foundation Classes
MedCalc
R package generalhoslem
R
SPSS
MAS

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