Crosstalk in Mechanomyographic Signals From Elbow Flexor Muscles During Submaximal to Maximal Isometric Flexion, Pronation, and Supination Torque Tasks

MMG-Based Knee Dynamic Extension Force Estimation Using Cross-Talk and IGWO-LSTM

Mechanomyography (MMG) is an important muscle physiological activity signal that can reflect the amount of motor units recruited as well as the contraction frequency. As a result, MMG can be utilized to estimate the force produced by skeletal muscle. However, cross-talk and time-series correlation severely affect MMG signal recognition in the real world. These restrict the accuracy of dynamic muscle force estimation and their interaction ability in wearable devices. To address these issues, a hypothesis that the accuracy of knee dynamic extension force estimation can be improved by using MMG signals from a single muscle with less cross-talk is first proposed. The hypothesis is then confirmed using the estimation results from different muscle signal feature combinations. Finally, a novel model (improved grey wolf optimizer optimized long short-term memory networks, i.e., IGWO-LSTM) is proposed for further improving the performance of knee dynamic extension force estimation. The experimental results demonstrate that MMG signals from a single muscle with less cross-talk have a superior ability to estimate dynamic knee extension force. In addition, the proposed IGWO-LSTM provides the best performance metrics in comparison to other state-of-the-art models. Our research is expected to not only improve the understanding of the mechanisms of quadriceps contraction but also enhance the flexibility and interaction capabilities of future rehabilitation and assistive devices.

Effects of blood flow restriction training on muscle fitness and cardiovascular risk of obese college students

Purpose: The aim of this study was to investigate the effect of blood flow restriction (BFR) combined with low-intensity resistance training (RT) on cardiovascular risk factors in obese individuals. Methods: Twenty-six male obese college students were recruited and randomly assigned to a control group (CON, n = 8), a low-intensity RT group (RT, n = 9), and a combined BFR training and low-intensity RT group (BFRT, n = 9). Results: The subjects in BFRT group showed significant reductions in body fat percentage and waist-to-hip ratio and a significant increase in lean mass and muscle mass; the peak torque, peak power, and endurance ratio of knee extensors and elbow flexors were significantly upregulated; the root mean square (RMS) for the medial femoral muscle, lateral femoral muscle and biceps significantly increased; the diastolic blood pressure (DBP) showed a significant decrease. The BFRT group also showed significant up-regulations in RMS of the difference between the adjacent R-R intervals (RMSSD), high-frequency power (HF) of parasympathetic modulatory capacity, the standard deviation of R-R intervals (SDNN) of overall heart rate variability (HRV) changes and low-frequency power (LF) of predominantly sympathetic activity. In addition, glycated hemoglobin (HbA1C), insulin resistance index (HOMA-IR) and fasting blood glucose (FBG) were all significantly downregulated in BFRT group. In parallel, low-density lipoprotein (LDL-C) significantly reduced while high-density lipoprotein (HDL-C) significantly increased in BFRT group. Conclusion: BFR combined with low-intensity RT training effectively improved body composition index, increased muscle mass, improved neuromuscular activation, enhanced muscle strength and endurance, which in turn improved abnormal glucolipid metabolism and enhanced cardiac autonomic regulation.

Analysis of anthropometrics and mechanomyography signals as forearm flexion, pronation and supination torque predictors

This study aimed to analyze anthropometrics and mechanomyography (MMG) signals as forearm flexion, pronation, and supination torque predictors. 25 young, healthy, male participants performed isometric forearm flexion, pronation, and supination tasks from 20 to 100% maximal voluntary isometric contraction (MVIC) while maintaining 90° at the elbow joint. Nine anthropometric measures were recorded, and MMG signals from the biceps brachii (BB), brachialis (BRA), and brachioradialis (BRD) muscles were digitally acquired using triaxial accelerometers. These were then correlated with torque values. Significant positive correlations were found for arm circumference (CA) and MMG root mean square (RMS) values with flexion torque. Flexion torque might be predicted using CA (r = 0.426–0.575), a pseudo for muscle size while MMG_RMS (r = 0.441), an indication of muscle activation.