Indices reflecting muscle contraction performance during exercise based on a combined electromyography and mechanomyography approach

Electromechanical efficiency index of skeletal muscle and its applicability: a systematic review

Introduction: The electromechanical efficiency of skeletal muscle represents the dissociation between electrical and mechanical events within a muscle. It has been widely studied, with varying methods for its measurement and calculation. For this reason, the purpose of this literature review was to integrate the available research to date and provide more insights about this measure. Methods: A systematic search of the literature was performed across three online databases: PubMed, ScienceDirect, and SPORTDiscus. This yielded 1284 reports, of which 10 met the inclusion criteria. Included studies have used different methods to measure the electromechanical efficiency (EME) index, including electromyography (EMG), mechanomyography and tensiomyography (TMG). Results: The EME index was used to assess muscle conditions such as muscle atrophy, pain syndromes, or to monitor rehabilitation in patients with knee problems, fatigue and the effects of exercise and rehabilitation. TMG has been shown to be one of the most reliable methods to obtain the EME index, but its use precludes obtaining the index during voluntary muscle contractions. Conclusion: Standardizing the EME index is crucial for its diverse applications in clinical, sport, and rehabilitation contexts. Future research should prioritize standardization of measurement protocols for establishing the most repeatable, and reliable approach that can be used for inter-individual comparisons or for assessing an individual for multiple times over a longer period. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023440333 Identifier: CRD42023440333.

Using force or EMG envelope as feedback signal for motor control system

PURPOSE

This work studied muscle neuro-mechanics during symmetrical up-going ramp (UGR) and down-going ramp (DGR).

AIM

to evaluate during the modulation of muscular action the outcome of force feedback (FF) or neural feedback (NF) on the behavior of the trailing signals - i.e. the EMG envelope (eEMG) for FF or force signal for NF.

METHOD

Subjects: 20. Investigated muscles: dorsal interosseous (FDI) and tibialis anterior (TA). Detected signals: force and EMG. Visual feedback: force (FF), eEMG (NF). Effort triangles: ramps duration 7.5 s, vertex at 50 and 100 % of the maximal voluntary action. Eventually, each subject performed FF50%, FF100%, NF50% and NF100% per each muscle. In each condition the areas beneath the force and eEMG signals were computed to calculate the ratios between the DGR and UGR values during the different tasks (force area DGR / force area UGR; eEMG area DGR / eEMG area UGR). Electro-mechanical coupling efficiency (EMCE) was estimated through the eEMG area / force area ratio for both UGR and DGR in each condition.

RESULTS

a) FF. FDI: eEMG area ratio was 0.84 ± 0.15 and 0.73 ± 0.17 for FF50% and FF100%, respectively. TA: eEMG area ratio was 0.88 ± 0.11 and 0.91 ± 0.17 for FF50% and FF100%, respectively. b) NF: FDI: force area ratio was 1.18 ± 0.13 and 1.17 ± 0.13 for NF50% and NF100%, respectively. TA: force area ratio was 1.17 ± 0.21 and 1.07 ± 0.19 for NF50% and NF100%, respectively. c) DGR EMCE was greater than UGR EMCE in all four tasks.

CONCLUSION

The influence of UGR on deployed EMCE in the following force decrement phase underpins the changes of trailing signals area during DGR. This underlines the necessity of a careful evaluation of the features of FF or NF for experimental studies or rehabilitation purposes involving the motor control system.