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

A KINEMATICALLY BASED ALGORITHM TO ESTIMATE THE ENERGY COST OF VARIABLE-SPEED SHUTTLE RUNNING

Changes of direction (CoDs) have a high metabolic and mechanical impact in field and court team sports, but the estimation of the associated workload is still inaccurate. The aim of this study is to establish a kinematic-based algorithm to determine the energy cost of running at variable speed with frequent 180° CoDs. Kinematic and metabolic data were simultaneously collected during 5-minutes 5+5 m shuttle run tests. Mechanical work computation was split into positive (eccentric) and negative (concentric) contributions. When compared to the actual energy cost, the estimation algorithm returned an error of 5%. This model constitutes the theoretical basis to extend the model from the laboratory to the field, obtaining an accurate measure of the workload of training and matches

DECELERATION COUNTS: ESTIMATING THE ENERGY COST OF SHUlTLE RUNNING FROM MECHANICAL WORK

To estimate the energetic requirements of 5-m shuttle running based on kinematic data, we devised a modified version of existing models for the estimation of the energy cost of gait. In our approach, negative/eccentric work during deceleration phases was added to positive/concentric work in propulsive phases. Ten subjects performed two 5-rnin trials at 50% and 75% of their maximal aerobic speed. The metabolic cost estimated from 30 kinematics was compared to that measured by a portable metabolimeter. The estimation error was 1.2 J/kg/s (7.3%): results encourage to apply this method for the estimation of the workload in sports involving frequent turns and changes of direction

On-sight and red-point climbing: changes in performance and route-finding ability in male advanced climbers

Aim: In lead climbing, the ascent of the route can be defined as on-sight or red-point. On-sight is the more challenging style since it demands greater physiological and psychological commitment. The differences between the two modes in advanced climbers have not been studied much. Two essential skills needed to optimize performance, in both on-sight and in red-point climbing, are route interpretation (RI) ability and movements sequence recall. Therefore, this study aimed to compare performance between on-sight and red-point ascent in advanced climbers and evaluate how a climber’s RI ability and movement sequences recall might change before and after on-sight and red-point climbing. Methods: Eighteen advanced male climbers (age 29.2 ± 4.7 years, body mass 67.8 ± 3.6 kg, stature 175.2 ± 2.4 cm, best red-point and on-sight grades 7b+/8a and 7a+/7b+, respectively) were video-recorded during the route ascent in on-sight and red-point modes to evaluate performance and to measure static and dynamic action times. RI ability and movement sequence recall were assessed before and after each climb. Level of anxiety was evaluated via a self-report questionnaire. Heart rate (fH), lactate concentration, ([La–]), and rating of perceived exertion (RPE) were detected during and after each climb. Results: Compared to on-sight, an improvement in performance was observed in a red-point climb: the ascent was faster (148.7 ± 13.6 s and 179.5 ± 12.5 s, respectively, P < 0.05), smoother (significant reduction in exploratory moves and in stops times, P < 0.05), less demanding physiologically (lower fHpeak and [La–]peak, P < 0.05), and psychologically (lower RPE, cognitive and somatic anxiety and higher self-confidence, P < 0.05). The RI ability was improved in red-point versus on-sight and, in the same mode, between pre and post ascent. Conclusion: Red-point climbing was found to be less demanding than on-sight, both physiologically and psychologically, under the conditions investigated by this study. Our findings suggest that RI is a trainable skill and underscore the importance of including specific techniques in training programs designed to improve interaction between perceptual, psychological, and physiological factors

A Preliminary Study

Bioelectrical Impedance Spectroscopy (BIS) allows assessing the composition of body districts noninvasively and quickly, potentially providing important physiological/clinical information. However, neither portable commercial instruments nor more advanced wearable prototypes simultaneously satisfy the demanding needs of unobtrusively tracking body fluid shifts in different segments simultaneously, over a broad frequency range, for long periods and with high measurements rate. These needs are often required to evaluate exercise tests in sports or rehabilitation medicine, or to assess gravitational stresses in aerospace medicine. Therefore, the aim of this work is to present a new wearable prototype for monitoring multi-segment and multi- frequency BIS unobtrusively over long periods. Our prototype guarantees low weight, small size and low power consumption. An analog board with current- injecting and voltage-sensing electrodes across three body segments interfaces a digital board that generates square-wave current stimuli and computes impedance at 10 frequencies from 1 to 796 kHz. To evaluate the information derivable from our device, we monitored the BIS of three body segments in a volunteer before, during and after physical exercise and postural shift. We show that it can describe the dynamics of exercise-induced changes and the effect of a sit-to-stand maneuver in active and inactive muscular districts separately and simultaneously

Cardiorespiratory and Metabolic Responses to Sinusoidal Exercise of Moderate Intensity: Reliability of the Measurements and the Effects of Fatigue

The cardiorespiratory and metabolic responses to sinusoidal exercise, in which work rate follows an oscillating pattern, have been proposed to assess the effectiveness of the cardiorespiratory adjustments. The repetition of successive sinusoidal periods permits to simultaneously reduce the influence of random fluctuations and accentuate the underlying physiological response. Data analysis has been often performed by overlapping and averaging successive cycles assuming no differences among them, thus excluding the possible presence of fatigue throughout successive cycles. After assessing the reliability of the measurements during sinusoidal exercise, this study sought to investigate the possible differences among subsequent cycles of sinusoidal work. Eleven active volunteers (age: 28±6 yrs., body mass: 73±7 kg; stature: 1.79±0.06 m, maximum oxygen uptake (VO2max): 52 ml·kg−1·min−1) participated to the study that was conducted in accordance with the Basic Principles of the Declaration of Helsinki. After determining individual VO2max and critical power (CP) on a cycle ergometer, they underwent sinusoidal work rates characterized by an amplitude (A), a midpoint (MP) and a period equal to ±50W, 50W below CP and 240s, respectively, up to exhaustion. On a different day, participants repeated the same experimental session for reliability purposes. Expiratory ventilation (VE), oxygen uptake (VO2), carbon dioxide output (VCO2), and heart rate (fH) responses were fitted by the sinewave function that minimized the residuals. A, MP and the time-delay (tD, the latency between mechanical work rate and physiological responses) of all parameters were determined for each cycle. Reliability assessment between day 1 and 2 was expressed as Cronbach’s a and intraclass correlation coefficient (ICC). A one-way ANOVA for repeated measures tested the presence of differences among cycles. Regression analysis was also applied to explore possible relationship between each variables and time. Reliability analysis revealed a very high to high ICC values for most of the parameters, with the exception of A for VO2 and VCO2 and tD for fH (moderate reliability). A of VE and fH response increased and decreased with time, respectively (p<0.05). MP of VE and fH showed a positive regression that led to significantly higher values in the last compared to the first cycle; on the contrary, no changes were observed among cycles in all other MP data. tD was similar in each cycle for all the investigated parameters despite a very slight negative regression found for VCO2. In conclusion, most of the physiological responses to moderate sinusoidal exercise exhibited a high to very high reliability. Some of the cardiorespiratory parameters showed significant changes with time throughout the sinusoidal exercise possibly due to the onset of fatigue. Therefore, an approach that overlaps and averages all the cycles together should not be performed to avoid wrong estimation of physiological responses to sinusoidal exercise, unless the averaging approach involves only the first cycles

Reliability of the Electromechanical Delay Components Assessment during the Relaxation Phase

The study aimed to assess by an electromyographic (EMG), mechanomyographic (MMG), and force-combined approach the electrochemical and mechanical components of the overall electromechanical delay during relaxation (R-EMD). Reliability of the measurements was also assessed. To this purpose, supramaximal tetanic stimulations (50 Hz) were delivered to the gastrocnemius medialis muscle of 17 participants. During stimulations, the EMG, MMG, and force signals were detected, and the time lag between EMG cessation and the beginning of force decay (Δt EMG-F, as temporal indicators of the electrochemical events) and from the initial force decrease to the largest negative peak of MMG signal during relaxation (Δt F-MMG, as temporal indicators of the mechanical events) was calculated, together with overall R-EMD duration (from EMG cessation to the largest MMG negative peak during relaxation). Peak force (pF), half relaxation time (HRT), and MMG peak-to-peak during the relaxation phase (R-MMG p-p) were also calculated. Test-retest reliability was assessed by Intraclass Correlation Coefficient (ICC). With a total R-EMD duration of 96.9 ± 1.9 ms, Δt EMG-F contributed for about 24% (23.4 ± 2.7 ms) while Δt F-MMG for about 76% (73.5 ± 3.2 ms). Reliability of the measurements was high for all variables. Our findings show that the main contributor to R-EMD is represented by the mechanical components (series elastic components and muscle fibres behaviour), with a high reliability level for this type of approach

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

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