Changes in muscle activity during the flexion and extension phases of arm cycling as an effect of power output are muscle-specific

Neuromechanical Differences between Pronated and Supinated Forearm Positions during Upper-Body Wingate Tests

Arm-cycling is a versatile exercise modality with applications in both athletic enhancement and rehabilitation, yet the influence of forearm orientation remains understudied. Thus, this study aimed to investigate the impact of forearm position on upper-body arm-cycling Wingate tests. Fourteen adult males (27.3 ± 5.8 years) underwent bilateral assessments of handgrip strength in standing and seated positions, followed by pronated and supinated forward arm-cycling Wingate tests. Electromyography (EMG) was recorded from five upper-extremity muscles, including anterior deltoid, triceps brachii lateral head, biceps brachii, latissimus dorsi, and brachioradialis. Simultaneously, bilateral normal and propulsion forces were measured at the pedal-crank interface. Rate of perceived exertion (RPE), power output, and fatigue index were recorded post-test. The results showed that a pronated forearm position provided significantly (p < 0.05) higher normal and propulsion forces and triceps brachii muscle activation patterns during arm-cycling. No significant difference in RPE was observed between forearm positions (p = 0.17). A positive correlation was found between seated handgrip strength and peak power output during the Wingate test while pronated (dominant: p = 0.01, r = 0.55; non-dominant: p = 0.03, r = 0.49) and supinated (dominant: p = 0.03, r = 0.51; don-dominant: p = 0.04, r = 0.47). Fatigue changed the force and EMG profile during the Wingate test. In conclusion, this study enhances our understanding of forearm position's impact on upper-body Wingate tests. These findings have implications for optimizing training and performance strategies in individuals using arm-cycling for athletic enhancement and rehabilitation.

Evaluation of stretch reflex synergies in the upper limb using principal component analysis (PCA)

The dynamic nature of movement and muscle activation emphasizes the importance of a sound experimental design. To ensure that an experiment determines what we intend, the design must be carefully evaluated. Before analyzing data, it is imperative to limit the number of outliers, biases, and skewness. In the present study, a simple center-out experiment was performed by 16 healthy volunteers. The experiment included three load conditions, two preparatory delays, two perturbations, and four targets placed along a diagonal path on a 2D plane. While the participants performed the tasks, the activity of seven arm muscles were monitored using surface electromyography (EMG). Principal component analysis (PCA) was used to evaluate the study design, identify muscle synergies, and assess the effects of individual quirks. With PCA, we can identify the trials that trigger stretch reflexes and pinpoint muscle synergies. The posterior deltoid, triceps long head, and brachioradialis were engaged when targets were in the direction of muscle shortening and the perturbation was applied in the opposite direction. Similarly, the pectoralis and anterior deltoid were engaged when the targets were in the direction of muscle shortening and the perturbation was applied in the opposite direction. The stretch reflexes were not triggered when the perturbation brought the hand in the direction of, or into the target, except if the muscle was pre-loaded. The use of PCA was also proven valuable when evaluating participant performance. While individual quirks are to be expected, failure to perform trials as expected can adversely affect the study results.

Evolution of muscle coordination and mechanical output following four weeks of arm cranking submaximal training

Muscle synergies is extensively studied to understand how the neuromusculoskeletal system deals with abundancy. The synergies represent covariant muscles that acts as building blocks for movement production. Nevertheless, little is known on how those synergies evolve following training, learning and expertise. This study reports the influence a 4-weeks submaximal training of arm-cranking on novice participants' muscle synergies.

METHODS

12 participants performed 8 sessions of submaximal training for 4 weeks. One session consisted in two 30-second-maximal power tests followed by six 2-minutes-bouts at 30% of maximal recorded power. Cranking torque and EMG of 11 muscles were recorded during the entire protocol. After EMG normalization, muscle synergies were extracted using NNMF. Similarity was computed using cross-correlation and cosine similarities and statistical evolution across training was tested using repeated measured ANOVA.

RESULTS

While maximal power increased across training days nor torque management, EMG or muscle synergies were significantly affected by submaximal training. Nevertheless, results suggest slights modifications of muscle synergies across day despite to non-significant differences.

DISCUSSION

Despite the strong complexity of the upper limbs anatomy, our results showed that training didn't induce significant changes in movement realization (mechanical and coordination level). A low-dimensional organization of muscle synergies is selected from the first day and kept through the following training days, despite slight but non-significant modifications.This study supports the hypothesis that motor control for movement production could be simplify using low-dimensional building blocks (muscle synergies). Such building blocks allow stability in movement execution and are slightly adjusted to fit movement requirements with training.

Subject specific muscle synergies and mechanical output during cycling with arms or legs

Background

Upper (UL) and lower limb (LL) cycling is extensively used for several applications, especially for rehabilitation for which neuromuscular interactions between UL and LL have been shown. Nevertheless, the knowledge on the muscular coordination modality for UL is poorly investigated and it is still not known whether those mechanisms are similar or different to those of LL. The aim of this study was thus to put in evidence common coordination mechanism between UL and LL during cycling by investigating the mechanical output and the underlying muscle coordination using synergy analysis.

Methods

Twenty-five revolutions were analyzed for six non-experts' participants during sub-maximal cycling with UL or LL. Crank torque and muscle activity of eleven muscles UL or LL were recorded. Muscle synergies were extracted using nonnegative matrix factorization (NNMF) and group- and subject-specific analysis were conducted.

Results

Four synergies were extracted for both UL and LL. UL muscle coordination was organized around several mechanical functions (pushing, downing, and pulling) with a proportion of propulsive torque almost 80% of the total revolution while LL muscle coordination was organized around a main function (pushing) during the first half of the cycling revolution. LL muscle coordination was robust between participants while UL presented higher interindividual variability.

Discussion

We showed that a same principle of muscle coordination exists for UL during cycling but with more complex mechanical implications. This study also brings further results suggesting each individual has unique muscle signature.

Proposed Fatigue Index for the Objective Detection of Muscle Fatigue Using Surface Electromyography and a Double-Step Binary Classifier

The objective detection of muscle fatigue reports the moment at which a muscle fails to sustain the required force. Such a detection prevents any further injury to the muscle following fatigue. However, the objective detection of muscle fatigue still requires further investigation. This paper presents an algorithm that employs a new fatigue index for the objective detection of muscle fatigue using a double-step binary classifier. The proposed algorithm involves analyzing the acquired sEMG signals in both the time and frequency domains in a double-step investigation. The first step involves calculating the value of the integrated EMG (IEMG) to determine the continuous contraction of the muscle being investigated. It was found that the IEMG value continued to increase with prolonged muscle contraction and progressive fatigue. The second step involves differentiating between the high-frequency components (HFC) and low-frequency components (LFC) of the EMG, and calculating the fatigue index. Basically, the segmented EMG signal was filtered by two band-pass filters separately to produce two sub-signals, namely, a high-frequency sub-signal (HFSS) and a low-frequency sub-signal (LFSS). Then, the instantaneous mean amplitude (IMA) was calculated for the two sub-signals. The proposed algorithm indicates that the IMA of the HFSS tends to decrease during muscle fatigue, while the IMA of the LFSS tends to increase. The fatigue index represents the difference between the IMA values of the LFSS and HFSS, respectively. Muscle fatigue was found to be present and was objectively detected when the value of the proposed fatigue index was equal to or greater than zero. The proposed algorithm was tested on 75 EMG signals that were extracted from 75 middle deltoid muscles. The results show that the proposed algorithm had an accuracy of 94.66% in distinguishing between conditions of muscle fatigue and non-fatigue.

Analysis of Upper Limbs Target-Reaching Movement and Muscle Co-Activation in Patients with First Time Stroke for Rehabilitation Progress Monitoring

In this paper, the authors analysed changes occurring during the rehabilitation processes in patients after early stroke based on analysis of their upper limbs’ target-reaching movement and muscle co-activation. Ischemic stroke often results in reduced mobility of the upper extremities and frequently is a cause for long-term disability. The ever-developing technology of 3D movement analysis and miniaturisation of equipment for testing the bioelectrical activity of muscles can help to assess the progress of rehabilitation. The aim of this study was to examine the use of analysis of target-reaching movement indicators and muscle co-activation for diagnosing the rehabilitation process in post-stroke patients. Twenty ischemic stroke patients in the early post-stroke phase (up to three months after the stroke), and twenty healthy subjects (the control group) took part in the experiments. The novel approach of the proposed research proved the usefulness of this approach in the diagnosis of the rehabilitation efficiency of rehabilitation in early post-stroke phase patients.

Electrode Size and Placement for Surface EMG Bipolar Detection from the Brachioradialis Muscle: A Scoping Review

The brachioradialis muscle (BRD) is one of the main elbow flexors and is often assessed by surface electromyography (sEMG) in physiology, clinical, sports, ergonomics, and bioengineering applications. The reliability of the sEMG measurement strongly relies on the characteristics of the detection system used, because of possible crosstalk from the surrounding forearm muscles. We conducted a scoping review of the main databases to explore available guidelines of electrode placement on BRD and to map the electrode configurations used and authors’ awareness on the issues of crosstalk. One hundred and thirty-four studies were included in the review. The crosstalk was mentioned in 29 studies, although two studies only were specifically designed to assess it. One hundred and six studies (79%) did not even address the issue by generically placing the sensors above BRD, usually choosing large disposable ECG electrodes. The analysis of the literature highlights a general lack of awareness on the issues of crosstalk and the need for adequate training in the sEMG field. Three guidelines were found, whose recommendations have been compared and summarized to promote reliability in further studies. In particular, it is crucial to use miniaturized electrodes placed on a specific area over the muscle, especially when BRD activity is recorded for clinical applications.

Moving forward: methodological considerations for assessing corticospinal excitability during rhythmic motor output in humans

The use of transcranial magnetic stimulation to assess the excitability of the central nervous system to further understand the neural control of human movement is expansive. The majority of the work performed to-date has assessed corticospinal excitability either at rest or during relatively simple isometric contractions. The results from this work are not easily extrapolated to rhythmic, dynamic motor outputs, given that corticospinal excitability is task-, phase-, intensity-, direction-, and muscle-dependent (Power KE, Lockyer EJ, Forman DA, Button DC. Appl Physiol Nutr Metab 43: 1176-1185, 2018). Assessing corticospinal excitability during rhythmic motor output, however, involves technical challenges that are to be overcome, or at the minimum considered, when attempting to design experiments and interpret the physiological relevance of the results. The purpose of this narrative review is to highlight the research examining corticospinal excitability during a rhythmic motor output and, importantly, to provide recommendations regarding the many factors that must be considered when designing and interpreting findings from studies that involve limb movement. To do so, the majority of work described herein refers to work performed using arm cycling (arm pedaling or arm cranking) as a model of a rhythmic motor output used to examine the neural control of human locomotion.

The Effect of Crank Resistance on Arm Configuration and Muscle Activation Variances in Arm Cycling Movements

Arm cycling on an ergometer is common in sports training and rehabilitation protocols. The hand movement is constrained along a circular path, and the user is working against a resistance, maintaining a cadence. Even if the desired hand trajectory is given, there is the flexibility to choose patterns of joint coordination and muscle activation, given the kinematic redundancy of the upper limb. With changing external load, motor noise and changing joint stiffness may affect the pose of the arm even though the endpoint trajectory is unchanged. The objective of this study was to examine how the crank resistance influences the variances of joint configuration and muscle activation. Fifteen healthy participants performed arm cranking on an arm-cycle ergometer both unimanually and bimanually with a cadence of 60 rpm against three crank resistances. Joint configuration was represented in a 3-dimensional joint space defined by inter-segmental joint angles, while muscle activation in a 4-dimensional "muscle activation space" defined by EMGs of 4 arm muscles. Joint configuration variance in the course of arm cranking was not affected by crank resistance, whereas muscle activation variance was proportional to the square of muscle activation. The shape of the variance time profiles for both joint configuration and muscle activation was not affected by crank resistance. Contrary to the prevailing assumption that an increased motor noise would affect the variance of auxiliary movements, the influence of noise doesn't appear at the joint configuration level even when the system is redundant. Our results suggest the separation of kinematic- and force-control, via mechanisms that are compensating for dynamic nonlinearities. Arm cranking may be suitable when the aim is to perform training under different load conditions, preserving stable and secure control of joint movements and muscle activations.