The Entrainment Frequency of Cardiolocomotor Synchronization in Long-Distance Race Emerges Spontaneously at the Step Frequency

In forced conditions, where the heart rate and step frequency have been matched, cardiolocomotor synchronization (CLS) has been recognized. However, knowledge about the occurrence of CLS and its triggers in sports gesture in real contexts is little known. To address this gap, the current study tested the hypothesis that CLS in running spontaneous conditions would emerge at entrainment bands of muscle activation frequencies associated with a freely chosen step frequency. Sixteen male long-distance runners undertook treadmill assessments running ten three-minute bouts at different speeds (7, 7.5, 8, 9, 10, 11, 12, 13, 14, and 15 km c5h-1). Electrocardiography and surface electromyography were recorded simultaneously. The center frequency was the mean of the frequency spectrum obtained by wavelet decomposition, while CLS magnitude was determined by the wavelet coherence coefficient (WCC) between the electrocardiography and center frequency signals. The strength of CLS affected the entrainment frequencies between cardiac and muscle systems, and for WCC values greater than 0.8, the point from which we consider the emerging CLS, the entrainment frequency was between 2.7 and 2.8 Hz. The CLS emerged at faster speeds (13-15 km c5h-1) most prevalently but did not affect the muscle activation bands. Spontaneous CLS occurred at faster speeds predominantly, and the entrainment frequencies matched the locomotor task, with the entrainment bands of frequencies emerging around the step frequencies (2.7-2.8 Hz). These findings are compatible with the concept that interventions that determine optima conditions of CLS may potentiate the benefits of the cardiac and muscle systems synchronized in distance runners

Evaluation of Concavity Compression Mechanism as a Possible Predictor of Shoulder Muscle Fatigue

This study examined the lived experiences of American Muslim principals who serve in public schools post-9/11 to determine whether global events, political discourse, and the media coverage of Islam and Muslims have affected their leadership and spirituality. The aim of the study was to allow researchers and educators to gain an understanding of the adversities that American Muslims principals have experienced post-9/11 and to determine how to address these adversities, particularly through decisions about educational policy and district leadership. A total of 14 American Muslim school leaders who work in public schools post-9/11 across the United States participated in the study, and a phenomenological methodology was used to direct the data collection and coding. Edelman\u27s political spectacle theory served as the theoretical framework for the research. The findings yielded six themes of political climate, role of the media, inferior and foreign: being seen as the other, unconscious fear, spirituality, and education and communication over spectacle. Further, collective guilt and social responsibility emerged as two additional findings. The research suggests that political spectacle and its effects have a large impact on the lives of American Muslim principals, particularly in regard to their leadership and spirituality

Stand-alone wearable system for ubiquitous real-time monitoring of muscle activation potentials

Wearable technology is attracting most attention in healthcare for the acquisition of physiological signals. We propose a stand-alone wearable surface ElectroMyoGraphy (sEMG) system for monitoring the muscle activity in real time. With respect to other wearable sEMG devices, the proposed system includes circuits for detecting the muscle activation potentials and it embeds the complete real-time data processing, without using any external device. The system is optimized with respect to power consumption, with a measured battery life that allows for monitoring the activity during the day. Thanks to its compactness and energy autonomy, it can be used outdoor and it provides a pathway to valuable diagnostic data sets for patients during their own day-life. Our system has performances that are comparable to state-of-art wired equipment in the detection of muscle contractions with the advantage of being wearable, compact, and ubiquitous

Safety, Fear and Neuromuscular Responses after a Resisted Knee Extension Performed to Failure in Patients with Severe Haemophilia

Background: low–moderate intensity strength training to failure increases strength and muscle hypertrophy in healthy people. However, no study assessed the safety and neuromuscular response of training to failure in people with severe haemophilia (PWH). The purpose of the study was to analyse neuromuscular responses, fear of movement, and possible adverse effects in PWH, after knee extensions to failure. Methods: twelve severe PWH in prophylactic treatment performed knee extensions until failure at an intensity of five on the Borg CR10 scale. Normalised values of amplitude (nRMS) and neuromuscular fatigue were determined using surface electromyography for the rectus femoris, vastus medialis, and vastus lateralis. After the exercise, participants were asked about their perceived change in fear of movement, and to report any possible adverse effects. Results: Patients reported no adverse effects or increased fear. The nRMS was maximal for all the muscles before failure, the median frequency decreased, and wavelet index increased during the repetitions. The vastus lateralis demonstrated a higher maximum nRMS threshold and earlier fatigue, albeit with a lower and more progressive overall fatigue. Conclusions: severe PWH with adequate prophylactic treatment can perform knee extensions to task failure using a moderate intensity, without increasing fear of movement, or adverse effects

Longitudinal tracking of physiological state with electromyographic signals.

Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small platform. A LASSO regularization is performed to observe changes in relationship between electromyography features and force plate outcomes. SVM classifiers are employed to correctly identify the times at which these experiments are performed, which is important as these indicate a trajectory of adaptation

Mechanomyographic amplitude and frequency responses during dynamic muscle actions: a comprehensive review

The purpose of this review is to examine the literature that has investigated mechanomyographic (MMG) amplitude and frequency responses during dynamic muscle actions. To date, the majority of MMG research has focused on isometric muscle actions. Recent studies, however, have examined the MMG time and/or frequency domain responses during various types of dynamic activities, including dynamic constant external resistance (DCER) and isokinetic muscle actions, as well as cycle ergometry. Despite the potential influences of factors such as changes in muscle length and the thickness of the tissue between the muscle and the MMG sensor, there is convincing evidence that during dynamic muscle actions, the MMG signal provides valid information regarding muscle function. This argument is supported by consistencies in the MMG literature, such as the close relationship between MMG amplitude and power output and a linear increase in MMG amplitude with concentric torque production. There are still many issues, however, that have yet to be resolved, and the literature base for MMG during both dynamic and isometric muscle actions is far from complete. Thus, it is important to investigate the unique applications of MMG amplitude and frequency responses with different experimental designs/methodologies to continually reassess the uses/limitations of MMG

Mechanomyographic Parameter Extraction Methods: An Appraisal for Clinical Applications

The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity

Applications of EMG in Clinical and Sports Medicine

This second of two volumes on EMG (Electromyography) covers a wide range of clinical applications, as a complement to the methods discussed in volume 1. Topics range from gait and vibration analysis, through posture and falls prevention, to biofeedback in the treatment of neurologic swallowing impairment. The volume includes sections on back care, sports and performance medicine, gynecology/urology and orofacial function. Authors describe the procedures for their experimental studies with detailed and clear illustrations and references to the literature. The limitations of SEMG measures and methods for careful analysis are discussed. This broad compilation of articles discussing the use of EMG in both clinical and research applications demonstrates the utility of the method as a tool in a wide variety of disciplines and clinical fields

Classification of operator’s workload based on physiological response

People spend most of their lives at work, during which time they are exposed to mechanical and environmental conditions that can harm their health. This risk can occur in an hour- long or over long periods, even when performed at a light to moderate intensity due to cumulative fatigue. Several measures have been proposed in order to prevent or reduce fatigue-inducing repetitive work. However, these measures are essentially subjective or only measure fatigue locally. Wearables are an attractive solution to measure work-related fatigue globally and at any time. The purpose of this study is to quantify biosignals information for the determination of fatigue while performing repetitive work. Electrocardiogram (ECG), electromyography (EMG), respiratory inductance plethysmography (RIP) and Accelerometer (ACC) signals were collected from 25 healthy participants. The participants were instructed to perform a repetitive task after induced fatigue. Their biosignals were processed, and different families of features were extracted. These features were used to fit a classifier in order to evaluate fatigue. Self-Similarity Matrix (SSM) was used to select and segment the data in Baseline and Fatigue. Autocorrelation of inertial measures, respiratory synchrony, and the root mean square of the cardiovascular load features achieved 88% of accuracy. It was possible to verify that the ACC’s features lead to the best classification results, followed by the RIP, EMG and finally the ECG’s features. Multimodal data allows global classification of when a person is working after expe- riencing fatigue. Motor information contributes significantly to this classification due to compensations that occur while performing the repetitive task. More studies should be done to develop an index characterising the fatigue state.As pessoas passam a maior parte da sua vida a trabalhar. A exposição a condições mecânicas e ambientais no trabalho pode ser prejudicial à sua saúde. Este risco pode ocorrer devido à fadiga cumulativa. Lesões podem surgir tanto em curtos como em longos períodos, mesmo quando a tarefa tem uma intensidade leve a moderada. Várias medidas foram propostas para prevenir ou reduzir o trabalho repetitivo que induz fadiga, no entanto, estas medidas são essencialmente subjetivas ou apenas medem a fadiga localmente. Os wearables são uma solução interessante para medir a fadiga relacionada ao trabalho a nível global e em qualquer momento. O objetivo deste estudo foi quantificar informações de biosinais para a determinação da fadiga durante a realização de trabalhos repetitivos. Os sinais de eletrocardiograma (ECG), eletromiografia (EMG), pletismografia de indutância respiratória (RIP) e acelerómetro (ACC) foram recolhidos de 25 participantes saudáveis. Os participantes realizaram uma tarefa repetitiva onde fadiga foi provocada. Os biosinais foram processados, e diferentes famílias de métricas foram extraídas. Estas métricas foram usadas para classificar a fadiga. Recorreu-se a Matrizes de Auto-Similaridade (SSM) para selecionar e segmentar os dados em fadiga e não fadiga. A autocorrelação das medidas inerciais, a sincronia respiratória e o quadrado médio da raiz da carga cardiovascular alcançaram 88% de precisão. Foi possível verificar que as features do ACC tiveram os melhores resultados de classificação, seguindo-se do RIP, EMG e, por último, de ECG. Os dados multimodais permitiram a classificação global de quando uma pessoa está a trabalhar, após sentir fadiga. A informação motora contribui, significativamente, para esta classificação devido às compensações que ocorrem durante a realização da tarefa repetitiva. Futuro trabalho deve ser feito com fim a determinar um índice que possa caracterizar o estado de fadiga