Related Experiment Video
Updated: Dec 5, 2025
Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
Published on: March 28, 2025
A Novel Method for Individual Age Group Determination Based on the Hand Muscle Synergy
Arash Maghsoudi1, Fereidoon Nowshiravan Rahatabad1, Parisa Rangraz1
1Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Background:
As people get older, muscles become more synchronized and cooperate to accomplish an activity, so the main purpose of this research is to determine the relationship between changes in age and the amount of muscle synergy. The presence of muscle synergies has been long considered in the movement control as a mechanism for reducing the degree of freedom of the motor system.
Methods:
By combining these synergies, a wide range of complex movements can be produced. Muscle synergies are often extracted from the electromyogram (EMG) signal. One of the most common methods for extracting synergies is the nonnegative matrix factorization. In this research, the EMG signal is obtained from individuals from different age groups (namely 15-20 years, 25-30 years, and 35-40 years), and after preprocessing, the muscular synergies are extracted. By processing and studying these synergies.
Results:
It was observed that there is a significant difference between the muscular synergy of different age groups. Furthermore, there was a significant difference in the mean value of synergy coefficients in each group, especially in motions that were accompanied by force.
Conclusion:
This result candidates this parameter as a biomarker to differentiate and recognize the effects of age on the individual's muscular signal. In the best case, using the synergy tool, classification of the age of persons can be done by 77%.
