Mechanomyography-Based Metric Scale for Spasticity: A Pilot Descriptive Observational Study

Author:

dos Santos Elgison L.12ORCID,Scheeren Eduardo M.2ORCID,Nogueira-Neto Guilherme N.2ORCID,Krueger Eddy34ORCID,Peixoto Nathalia5ORCID,Nohama Percy26ORCID

Affiliation:

1. Centro Universitário Internacional Uninter, Curitiba 80020-000, PR, Brazil

2. Graduate Program in Health Technology, Pontifícia Universidade Católica do Paraná, Curitiba 80215-901, PR, Brazil

3. Anatomy Department, State University of Londrina, Londrina 86057-970, PR, Brazil

4. Graduate Program in Electrical Engineering, State University of Londrina, Londrina 86057-970, PR, Brazil

5. Department of Bioengineering, George Mason University, Fairfax, VA 22030, USA

6. Graduate Program in Electrical and Computing Engineering, Universidade Tecnológica Federal do Paraná, Curitiba 80230-901, PR, Brazil

Abstract

(1) Background: The Modified Ashworth Scale (MAS) is commonly used clinically to evaluate spasticity, but its qualitative nature introduces subjectivity. We propose a novel metric scale to quantitatively measure spasticity using mechanomyography (MMG) to mitigate these subjective effects. (2) Methods: The flexor and extensor muscles of knee and elbow joints were assessed with the Modified Ashworth Scale (MAS) during the acquisition of mechanomyography (MMG) data. The median absolute amplitude of the MMG signals was utilized as a key descriptor. An algorithm was developed to normalize the MMG signals to a universal gravitational (G) acceleration scale, aligning them with the limits and range of MAS. (3) Results: We evaluated 34 lower and upper limbs from 22 volunteers (average age 39.91 ± 13.77 years) of both genders. Polynomial regression provided the best fit (R2 = 0.987), with negligible differences (mean of 0.001 G) between the MAS and MMG. We established three numerical sets for the median, minimum, and maximum MMG(G) values corresponding to each MAS range, ensuring consistent alignment of the Modified Ashworth levels with our proposed scale. (4) Conclusions: Muscle spasticity can now be quantitatively and semi-automatically evaluated using our algorithm and instrumentation, enhancing the objectivity and reliability of spasticity assessments.

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

MDPI AG

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