Analysis of aging effect on lower limb muscle activity using short time Fourier transform and wavelet decomposition of electromyography signal

Abstract

The ubiquity of human knee osteoarthritis (OA) has increased among the elderly people worldwide. In this paper, the intended focus has been given to evaluate the consequence of aging on the lower limb (LL) muscle activities during sit-stand-sit perturbations. Eighty-four participants, including 51 eligible healthy subjects and 33 knee OA patients, took part in this study. The activity of the vastus lateralis, vastus medialis, rectus femoris, and the medial head of gastrocnemius muscles were evaluated using the surface electromyography (EMG) technology. Aging effects on the LL muscles were statistically analyzed by extracting the EMG features based on the conventional technique, short time Fourier transform (STFT) and Wavelet Transform (WT). Healthy subjects were categorized into three groups based on age. The Jarque–Bera test was performed for checking the normality of the dependent variables. To clarify the impact of aging statistically on muscle activity, the independent t-test was performed. The muscle activities of middle age and older age participants were identified to be considerably higher than those of young people. However, they were lower than those of the OA patients. Both the STFT and the WT performed as useful and powerful tools for analyzing EMG signals compared to the conventional filtering approach. The WT outperformed the STFT notably in statistical quantification of the aging effects on LL muscle activities.