We study the changes of Motor Unit (MU) filters in MU identification from high-density surface electromyograms recorded during isokinetic dynamic contractions of biceps brachii muscle. We demonstrate ...that these changes can be predicted for limited changes of the joint angle by linearly extrapolating previously recorded changes, allowing for the linear prediction-correction paradigm of MU filter updating. We then demonstrate the efficiency of this paradigm by implementing MU filter updating by the Kalman filter and integrating it into the previously published Convolution Kernel Compensation (CKC) MU identification method. When compared to the original CKC method and the previously published cyclostationary CKC method devoted to MU identification in repeated dynamic contractions, the Kalman based MU filter prediction yielded a superior precision of MU firing tracking in dynamic contractions. In the case of relatively fast biceps brachii contractions with full elbow flexion and extension in 2s, the Kalman based MU filter prediction tracked 21.3 ± 1.8 MUs with an average sensitivity of 95.6 ± 7.0% and precision of 96.5 ± 3.5%. In the same conditions, the original CKC method identified 7.1 ± 2.0 MUs with an average sensitivity of 62.7 ± 20.1% and precision of 98.1 ± 3.9%, whereas cyclostationary CKC tracked 18.9 ± 2.0 MUs with an average sensitivity of 91.8 ± 12.2% and precision of 94.7 ± 5.1%.
This study aimed to investigate the effect of milk fat globule membrane (MFGM) supplementation on motor unit adaptation following resistance training in older adults. Twenty‐five older males and ...females took MFGM (n = 12) or a placebo (PLA; n = 12) while performing 8 weeks of isometric knee extension training. During the training, the motor unit firing pattern during submaximal contractions, muscle thickness, and maximal muscle strength of knee extensor muscles were measured every 2 weeks. None of the measurements showed significant differences in muscle thickness or maximal muscle strength (MVC) between the two groups (p > .05). Significant decreases in motor unit firing rate following the intervention were observed in PLA, that is, 14.1 ± 2.7 pps at 0 weeks to 13.0 ± 2.4 pps at 4 weeks (p = .003), but not in MFGM (14.4 ± 2.5 pps to 13.8 ± 1.9 pps). Motor unit firing rates in MFGM were significantly higher than those in PLA at 2, 4, 6, and 8 weeks of the intervention, that is, 15.1 ± 2.3 pps in MFGM and 14.5 ± 3.3 pps in PLA at 70% of MVC for motor units recruited at 40% of MVC at 6 weeks (p = .034). Significant differences in firing rates among motor units with different recruitment thresholds were newly observed following the resistance training intervention in MFGM, indicating that motor unit firing pattern is changed in this group. These results suggest that motor unit adaptation following resistance training is modulated by MFGM supplementation in older adults.
The positive effect of milk fat globule membrane (MFGM) supplementation with exercise on age‐related dysfunctions in neuromuscular system had been reported in animal and human studies. This study found that MFGM supplementation with exercise can modify adaptations in motor unit firing pattern in older adults. Whereas the same exercise regimen was applied, different neural adaptation may be able to induce by ingestion of MFGM in older adults.
This research explores the utilization of ridge extraction techniques for the identification of activated motor units from heat map images generated by source localization of high density surface ...electromyogram (HD-sEMG) signals. The primary objective of this research is to accurately determine the number of activated motor units in these images, facilitating enhanced understanding of neuromuscular activities. The study involves the application of two ridge detection approaches: the first employs Otsu's thresholding in conjunction with the watershed algorithm, while the second utilizes the Hessian matrix. By applying these methods, the aim is to enhance the accuracy of identifying ridges associated with activated motor units in the heat map images. Following ridge extraction, two methods are employed to estimate the number of motor units within the images. The first method employs the K-Nearest Neighbors (KNN) algorithm, demonstrating promising accuracy in determining the count of motor units. The second method involves the utilization of K-Means clustering; however, its performance is observed to be less consistent, especially when confronted with images containing more than two motor units. These findings underscore the importance of selecting appropriate analysis methods when working with complex neuromuscular data.
This contribution compares performances of nonnegative matrix factorization and high-density surface electromyogram (EMG) decomposition on EMG signals recoded from forearm muscles of young healthy ...subjects. During the EMG measurements, subjects performed dynamic wrist extensions and flexions and universal haptic device robot was used to oppose their movements and to measure wrist kinematics and excreted muscle forces. Recoded EMG signals were independently decomposed by Convolution Kernel Compensation technique and by alternating least squares non-negative matrix factorization. The identified motor unit discharge patterns were summed into cumulative spike trains and compared with non-negative components in each measurement. The results demonstrated good match (average correlation coefficient of 0.92 ± 0.06), but several discrepancies between the identified components have also been observed. In particular, when limiting the time support of identified components to active EMG signal portions only, the average correlation coefficient dropped to 0.72 ±0.20.
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