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Portable Upper-limb Muscle Tone Assessment by Integrating Multi-sensor Signals
Yue Zhang1,2, Ying Zheng1, Hao ShangGuan3
1College of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350108, China.
Annals of Biomedical Engineering
|February 23, 2026
Summary
This study developed a new platform using biomechanical and surface electromyography (sEMG) data for objective muscle tone assessment. The method shows high accuracy, offering a reliable alternative to the subjective Modified Ashworth Scale (MAS) for hypertonia diagnosis.
Area of Science:
- Biomedical Engineering
- Rehabilitation Technology
- Neurology
Background:
- Traditional hypertonia diagnosis relies on the subjective Modified Ashworth Scale (MAS), which is limited by inter-rater variability.
- Previous attempts to quantify muscle tone using force sensors and surface electromyography (sEMG) have faced challenges in reliability and validity.
- There is a need for an objective and quantitative method for assessing upper-limb muscle tone to improve diagnostic accuracy.
Purpose of the Study:
- To develop a simple and effective platform integrating biomechanical and sEMG data for upper-limb muscle tone assessment.
- To provide an objective and quantitative evaluation method for muscle tone, overcoming the limitations of subjective clinical scales.
- To enhance the diagnostic accuracy and reliability of hypertonia assessment.
Main Methods:
- A detection platform was designed to collect biomechanical and sEMG data from 59 participants (49 patients, 10 healthy controls).
- Data were collected at varying movement speeds (15°/s, 20°/s, 25°/s) and subjected to feature extraction, signal processing, and statistical analysis.
- Dimensionality reduction was employed to optimize features, which were then integrated into a classification algorithm.
Main Results:
- Extracted features significantly differentiated patients with hypertonia from healthy individuals (p < 0.01).
- A strong correlation was found between the extracted features and Modified Ashworth Scale (MAS) scores (p < 0.01), confirming method reliability.
- The classification algorithm demonstrated high consistency with clinical evaluations, indicating potential for clinical application.
Conclusions:
- The developed platform offers an objective and quantitative approach to muscle tone assessment, moving beyond subjective MAS evaluations.
- This method enhances diagnostic accuracy, providing a more reliable basis for hypertonia diagnosis and treatment planning.
- The findings promise to optimize clinical decision-making and improve patient management and therapeutic strategies in hypertonia care.
