METHODS: The model was developed to estimate knee torque from experimentally derived MMG signals and other parameters related to torque production, including the knee angle and stimulation intensity, during NMES-assisted knee extension.
RESULTS: When the relationship between the actual and predicted torques was quantified using the coefficient of determination (R2), with a Gaussian support vector kernel, the R2 value indicated an estimation accuracy of 95% for the training subset and 94% for the testing subset while the polynomial support vector kernel indicated an accuracy of 92% for the training subset and 91% for the testing subset. For the Gaussian kernel, the root mean square error of the model was 6.28 for the training set and 8.19 for testing set, while the polynomial kernels for the training and testing sets were 7.99 and 9.82, respectively.
CONCLUSIONS: These results showed good predictive accuracy for SVR modelling, which can be generalized, and suggested that the MMG signals from paralyzed knee extensors are a suitable proxy for the NMES-assisted torque produced during repeated bouts of isometric knee extension tasks. This finding has potential implications for using MMG signals as torque sensors in NMES closed-loop systems and provides valuable information for implementing this method in research and clinical settings.
METHODS: Six individuals with chronic motor-complete spinal cord injury performed 30-min of sustained FES-leg cycling exercise on two days to induce muscle fatigue. Each participant performed maximum FES-evoked isometric knee extensions before and after the 30-min cycling to determine pre- and post- extension peak torque concomitant with mechanomyography changes.
FINDINGS: Similar to extension peak torque, normalized root mean squared (RMS) and mean power frequency (MPF) of the mechanomyography signal significantly differed in muscle activities between pre- and post-FES-cycling for each quadriceps muscle (extension peak torque up to 69%; RMS up to 80%, and MPF up to 19%). Mechanomyographic-RMS showed significant reduction during cycling with acceptable between-days consistency (intra-class correlation coefficients, ICC = 0.51-0.91). The normalized MPF showed a weak association with FES-cycling duration (ICC = 0.08-0.23). During FES-cycling, the mechanomyographic-RMS revealed greater fatigue rate for rectus femoris and greater fatigue resistance for vastus medialis in spinal cord injured individuals.
INTERPRETATION: Mechanomyographic-RMS may be a useful tool for examining real time muscle function of specific muscles during FES-evoked cycling in individuals with spinal cord injury.
METHODS: Eight incomplete SCI patients (mean age 50 years; 6 women) with stable SCI paraplegia (mean 6.75 years since injury) participated in the HIIT FES cycling (85%-90% peak Watts; 4 × 4-min intervals) three times a week (over 6 weeks). The main outcomes were adherence, participant acceptability, and adverse events. Secondary outcomes were muscle strength (peak torque) and leg volume changes.
RESULTS: Our findings revealed that the program was well-received by participants, with high levels of adherence, positive feedback, and satisfaction, suggesting that it could be a promising option for individuals seeking to enhance their lower body strength and muscle mass. Additionally, all participants successfully completed the training without any serious adverse events, indicating that the program is safe for use. Finally, we found that the 6-week HIIT FES leg cycling exercise program resulted in notable improvements in isometric peak torque of the quadriceps (range 13.9%-25.6%), hamstring muscle (18.2%-23.3%), and leg volume (1.7%-18.2%).
CONCLUSIONS: This study highlights HIIT FES leg cycling exercise program potential as an effective intervention for improving lower limb muscle function.