Inter-Gender sEMG Evaluation of Central and Peripheral Fatigue in Biceps Brachii of Young Healthy Subjects

Neurophysiological indices for split phenomena: correlation with age and sex and potential implications in amyotrophic lateral sclerosis

Background

Split phenomena (SP) are characterized by patterns of differential muscle wasting and atrophy, which are highly prevalent in amyotrophic lateral sclerosis (ALS) patients. Several neurophysiological indicators, including the split-hand index (SHI), split-leg index (SLI), and split-elbow index (SEI), have been proposed to assess SP. Nevertheless, their cutoff values and the impact of age and sex on these measures remain unclear.

Methods

We prospectively collected neurophysiological data from 300 healthy adult subjects. The following indices were measured from compound muscle action potentials (CMAPs): SHI [abductor pollicis brevis (APBcmap) x first dorsal interosseous (FDI)cmap/adductor digiti minimi (ADMcmap)], SEI (BICEPScmap/TRICEPScmap), SLI (extensor digit brevis (EDB)cmap/abductor Hallucis (AH)cmap), and the neurophysiological ratios APBcmap /ADMcmap and FDIcmap/ADMcmap. Multiple linear regression analysis was used to investigate the association between age, sex, CMAPs, and neurophysiological indicators.

Results

The median SHI was 10.4, with a median APBcmap/ADMcmap ratio of 0.9 and a median FDIcmap/ADMcmap ratio of 1.2. The median SEI was 1.6 (IQR:1.1-2.4) and the median SLI was 0.7 (IQR:0.5-1.0). Negative associations were observed between age, most of the CMAPs, and all the neurophysiological indices, except for SLI. The male subjects exhibited significantly higher CMAP values for the first dorsal interosseous (FDI), biceps, and SHI compared to the female participants.

Conclusion

Our findings highlight the importance of age- and sex-adjusted normative data for SP indices, which could enhance their diagnostic accuracy and clinical utility in patients with ALS. The SL index appears to be the most reliable indicator, as it showed no significant association with age or sex.

Acute outcomes of acupuncture and dry needling over peripheral acute fatigue in untrained healthy volunteers: A randomized controlled clinical trial

Peripheral acute fatigue (PAF) is defined as when the skeletal muscle is incapable of generating power. We aimed to investigate the acute effects of traditional Chinese acupuncture (TCA) and dry needling (DN) over PAF induced on the biceps brachii of untrained healthy volunteers. We conducted a randomized, single-blind controlled clinical trial. All volunteers (n = 45) underwent fatigue induction protocols repeated before and after treatment with TCA (TCA group; TCAg; n = 15), DN (DN group; DNg; n = 15), and rest (control group; Cg; n = 15). Assessments of PAF, skin temperature, and exercise time occur before and after each event: 1st fatigue induction (FI), treatment, and 2nd FI. We used repeated measures ANOVA adjusted with Bonferroni post hoc test to determine any change in tested variables (PAF-VAS, PAF-EMG, and skin temperature) at different time points compared to the baseline. Paired Samples t-test was used for the variable exercise times. All statistical tests considered' the significance level at p ≤ 0,05. There was no difference between groups in acute fatigue recovery (p = 0.19). All intragroup analyses were significant (p ≤ 0.05) and all volunteers show a reduction in fatigue perception after treatment (p ≤ 0,05), however, exercise time did not ameliorate after TCA or DN (p > 0.77). A single session of TCA and, DN can equally reduce fatigue, temperature, and exercise time over PAF induced on biceps brachii of untrained healthy volunteers.

Linear spectrum and non-linear complexity features of lumbar muscle surface electromyography between people with and without non-specific chronic low back pain during Biering-Sorensen test

PURPOSE

This study aimed to investigate the electromyographic parameters of lumbar muscles during the Biering-Sorensen test (BST) in people with and without non-specific chronic low back pain (NCLBP).

MATERIALS AND METHODS

Thirteen healthy controls and thirteen NCLBP patients participated in the current study, where they performed the 90s-BST, while the surface electromyography (sEMG) was recorded from the erector spinae (ES) at L1 and L3 level and lumbar multifidus (LM) at L5 level, bilaterally. Spectral and nonlinear analyses were applied by calculating mean power frequency (MPF), fractal dimension (FD) and the percentage of determinism (%DET) in the 10-second non-overlapping time-windows and EMG-EMG coherence during the first half and second half of the BST. Also, the slopes of the linear fitting curves of MPF, FD and %DET were calculated.

RESULTS

NCLBP group had significantly lower rates of changes in MPF, FD and %DET compared to asymptomatic controls in the ES(L3) and LM. Coherence in left-right LM and in the right ES-LM increased significantly in the gamma band in the Control group with no increase in the NCLBP group.

CONCLUSIONS

Our findings indicated that compared to people with NCLBP, the sEMG signals of lumbar muscles of people without NCLBP were more regular and less complex during the 90s-BST.

Deep transfer learning compared to subject-specific models for sEMG decoders

Objective. Accurate decoding of surface electromyography (sEMG) is pivotal for muscle-to-machine-interfaces and their application e.g. rehabilitation therapy. sEMG signals have high inter-subject variability, due to various factors, including skin thickness, body fat percentage, and electrode placement. Deep learning algorithms require long training time and tend to overfit if only few samples are available. In this study, we aim to investigate methods to calibrate deep learning models to a new user when only a limited amount of training data is available.Approach. Two methods are commonly used in the literature, subject-specific modeling and transfer learning. In this study, we investigate the effectiveness of transfer learning using weight initialization for recalibration of two different pretrained deep learning models on new subjects data and compare their performance to subject-specific models. We evaluate two models on three publicly available databases (non invasive adaptive prosthetics database 2-4) and compare the performance of both calibration schemes in terms of accuracy, required training data, and calibration time.Main results. On average over all settings, our transfer learning approach improves 5%-points on the pretrained models without fine-tuning, and 12%-points on the subject-specific models, while being trained for 22% fewer epochs on average. Our results indicate that transfer learning enables faster learning on fewer training samples than user-specific models.Significance. To the best of our knowledge, this is the first comparison of subject-specific modeling and transfer learning. These approaches are ubiquitously used in the field of sEMG decoding. But the lack of comparative studies until now made it difficult for scientists to assess appropriate calibration schemes. Our results guide engineers evaluating similar use cases.

Complexity Analysis of Surface Electromyography for Assessing the Myoelectric Manifestation of Muscle Fatigue: A Review

The surface electromyography (sEMG) records the electrical activity of muscle fibers during contraction: one of its uses is to assess changes taking place within muscles in the course of a fatiguing contraction to provide insights into our understanding of muscle fatigue in training protocols and rehabilitation medicine. Until recently, these myoelectric manifestations of muscle fatigue (MMF) have been assessed essentially by linear sEMG analyses. However, sEMG shows a complex behavior, due to many concurrent factors. Therefore, in the last years, complexity-based methods have been tentatively applied to the sEMG signal to better individuate the MMF onset during sustained contractions. In this review, after describing concisely the traditional linear methods employed to assess MMF we present the complexity methods used for sEMG analysis based on an extensive literature search. We show that some of these indices, like those derived from recurrence plots, from entropy or fractal analysis, can detect MMF efficiently. However, we also show that more work remains to be done to compare the complexity indices in terms of reliability and sensibility; to optimize the choice of embedding dimension, time delay and threshold distance in reconstructing the phase space; and to elucidate the relationship between complexity estimators and the physiologic phenomena underlying the onset of MMF in exercising muscles.

Pedaling Performance Changing of Elite Cyclists Is Mainly Determined by the Fatigue of Hamstring and Vastus Muscles during Repeated Sprint Cycling Exercise

Repeated sprint cycling is an effective training method in promoting athletic performance of cyclists, which may induce severe fatigue of lower limb muscles. However, the relationship between the fatigue of each lower limb muscles and the changing of exercise performance remains unclear. In this study, ten cyclist volunteers performed a series of 6-second sprints with 24-s recovery for five times. Power, cadence, and EMG mean frequency (MNF) of each lower limb muscle group for every 2-second epoch, as well as the grey relational grade between exercise performance and MNF of each lower limb muscle group during the whole process were calculated. It has been found that MNF of Rectus femoris (RF), Vastus (VAS), Gastrocnemius (GAS), and the hamstring muscle group (HAM) showed significant negative correlation with the increase in both sprint number and intrasprint duration time, while the grey relational grade of HAM and VAS was higher than that of other muscles. The results demonstrated that the exercise performance of both power and cadence were most closing related to the fatigue degree of HAM and VAS during repeated sprint cycling exercise.

Essential Amino Acids (EAA) Mixture Supplementation: Effects of an Acute Administration Protocol on Myoelectric Manifestations of Fatigue in the Biceps Brachii After Resistance Exercise

Background: The purpose of this study was to investigate the acute effects of a single oral administration of an essential amino acids enriched mixture (EAA) on myoelectric descriptors of fatigue and maximal force production after a resistance exercise protocol (REP). Methods: Twenty adult males (age: 27 ± 6 years; body mass: 72.7 ± 7.50 kg; height: 1.76 ± 0.06 m) were enrolled in a double-blind crossover placebo-controlled study. Subjects were randomized to receive EAA mix (0.15 g/kg BM) or a placebo (PLA) in two successive trials 7 days apart. In both trials subjects completed a REP 2 h after the ingestion of the EAA mix or PLA. Before ingestion and after REP subjects performed isometric contractions of the dominant upper limb with the elbow joint at 120 degrees: (1) two maximal voluntary contractions (MVCs) for 2-3 s; (2) at 20% MVC for 90 s; (3) at 60% MVC until exhaustion. Mean values of MVC, conduction velocity initial values (CV), fractal dimension initial values (FD), their rates of change (CV slopes, FD slopes) and the Time to perform the Task (TtT) were obtained from a multichannel surface electromyography (sEMG) recording technique. Basal blood lactate (BL) and BL after REP were measured. Results: Following REP a significant decrease of MVC was observed in PLA (P < 0.05), while no statistical differences were found in EAA between pre-REP and post-REP. After REP, although a significant increase in BL was found in both groups (P < 0.0001) a higher BL Δ% was observed in PLA compared to EAA (P < 0.05). After REP, at 60% MVC a significant increase of CV rate of change (P < 0.05) was observed in PLA but not in EAA. At the same force level TtT was longer in EAA compared to PLA, with a significant TtT Δ% between groups (P < 0.001). Conclusion: Acute EAA enriched mix administration may prevent the loss of force-generating capacity during MVC following a REP. During isometric contraction at 60% MVC after REP the EAA mix may maintain CV rate of change values with a delay in the TtT failure.

Relationship between Isometric Muscle Force and Fractal Dimension of Surface Electromyogram

The relationship between fractal dimension of the surface electromyogram (sEMG) and the intensity of muscle contraction is still controversial in simulated and experimental conditions. To support the use of fractal analysis to investigate myoelectric fatigue, it is crucial to establish the interdependence between fractal dimension and muscle contraction intensity. We analyzed the behavior of fractal dimension, conduction velocity, mean frequency, and average rectified value in twenty-eight volunteers at nine levels of isometric force. sEMG was obtained using bidimensional arrays in the biceps brachii muscle. The values of fractal dimension and mean frequency increased with force unless a plateau was reached at 30% maximal voluntary contraction. Overall, our findings suggest that, above a certain level of force, the use of fractal dimension to evaluate the myoelectric manifestations of fatigue may be considered, regardless of muscle contraction intensity.