Abstract
The purpose of this study was to examine the correlation between metabolic cost and muscle activity, with a focus on frequency of EMG signals during walking at different speeds. The findings will be valuable in rehabilitating individuals who suffer from gait-related disorders. Nine participants were recruited. In the first session of data collection, each participant performed a ten-meter walk test determining their average walking speed. Using these average walking speeds, six more speeds were subsequently established during the second session. In the second session, subjects walked for four minutes at each of the six speeds while EMG data was collected from the dominant lower leg muscles, specifically the lateral gastrocnemius (GAS-L) and the anterior tibialis (AT), and oxygen respiration was measured by open-circuit spirometry. Energy expenditure was estimated as the Cost of Transport (COT). The EMG data was analyzed using power spectral density (PSD), and extracted features in the frequency domain, such as Area Under the Curve (PSD-AUC) and Maximal Distance Between Two Points Before and After PSD Peak (MDPSD). The results indicate that PSD-AUC is a better measure than MDPSD for muscle activation frequency. PSD-AUC demonstrated an increasing curvilinear trend (R2=0.93 and 0.77, 2nd order polynomial fit) for both the GAS-L and AT, respectively. However, the AT displayed higher variability. MDPSD exhibited more non-linearity (R2=0.17-28, 2nd order polynomial fit) than PSD-AUC, but MDPSD demonstrated statistically significant differences (p
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Muscle Activation Frequency Relationship With Cost Of Transport at Increasing Walking Speed Reveals Interplay of Both Active and Passive Dynamics
The purpose of this study was to examine the correlation between metabolic cost and muscle activity, with a focus on frequency of EMG signals during walking at different speeds. The findings will be valuable in rehabilitating individuals who suffer from gait-related disorders. Nine participants were recruited. In the first session of data collection, each participant performed a ten-meter walk test determining their average walking speed. Using these average walking speeds, six more speeds were subsequently established during the second session. In the second session, subjects walked for four minutes at each of the six speeds while EMG data was collected from the dominant lower leg muscles, specifically the lateral gastrocnemius (GAS-L) and the anterior tibialis (AT), and oxygen respiration was measured by open-circuit spirometry. Energy expenditure was estimated as the Cost of Transport (COT). The EMG data was analyzed using power spectral density (PSD), and extracted features in the frequency domain, such as Area Under the Curve (PSD-AUC) and Maximal Distance Between Two Points Before and After PSD Peak (MDPSD). The results indicate that PSD-AUC is a better measure than MDPSD for muscle activation frequency. PSD-AUC demonstrated an increasing curvilinear trend (R2=0.93 and 0.77, 2nd order polynomial fit) for both the GAS-L and AT, respectively. However, the AT displayed higher variability. MDPSD exhibited more non-linearity (R2=0.17-28, 2nd order polynomial fit) than PSD-AUC, but MDPSD demonstrated statistically significant differences (p