Nonlinear surface EMG analysis to detect changes of motor unit conduction velocity and synchronization

Impact of acute hypoxic exposure on neuromuscular and hemodynamic responses during step intensity dynamic constant external resistance leg extension exercise

OBJECTIVES

This study examined the effects of acute normoxic and hypoxic exposure on neuromuscular and hemodynamic physiological responses performed during dynamic step muscle actions.

METHODS

Thirteen recreationally active men (mean ± SD age: 21.2 ± 2.9 yrs) performed dynamic leg extensions unilaterally under Normoxic (FiO2 = 21 %) and Hypoxic (FiO2 = 13 %) conditions in a randomized order at 20 %, 40 %, 60 %, 80 %, and 100 % of their maximal strength. Electromyographic (EMG) amplitude, EMG frequency, (Oxygenated and Deoxygenated hemoglobin; OxyHb, DeoxyHb), Total hemoglobin (TotalHb), and skeletal muscle tissue oxygenation status (StO2) were measured from the vastus lateralis during all contractions.

RESULTS

There were no detectable differences in the neuromuscular responses between normoxia and hypoxia for EMG amplitude (p = 0.37-0.74) and frequency (p = 0.17-0.83). For EMG amplitude there were general increases with intensity (p < 0.01-0.03). EMG frequency remained similar from 20% to 80% and then increased at 100 % effort (p = 0.02). There was no significant difference in patterns of responses for OxyHb (p = 0.870) and TotalHb (p = 0.200) between normoxia and hypoxia. StO2 (p = 0.028) decreased and DeoxyHb (p = 0.006) increased under hypoxia compared to normoxia during dynamic step muscle actions performed in a randomized order.

CONCLUSION

Unlike fatigue, acute hypoxemia in an unfatigued state does not impact the localized neuromuscular responses, but minimally impacts the hemodynamic responses.

Corticomuscular cross-recurrence analysis reveals between-limb differences in motor control among individuals with ACL reconstruction

Surgical reconstruction of the anterior cruciate ligament (ACL) and subsequent physical therapy can help athletes return to competition; however, re-injury rates remain disproportionately high due, in part, to lingering biomechanical and neurological factors that are not fully addressed during rehabilitation. Prior reports indicate that individuals exhibit altered electrical activity in both brain and muscle after ACL reconstruction (ACLR). In this investigation, we aimed to extend existing approaches by introducing a novel non-linear analysis of corticomuscular dynamics, which does not assume oscillatory coupling between brain and muscle: Corticomuscular cross-recurrence analysis (CM-cRQA). Our findings indicate that corticomuscular dynamics vary significantly between involved (injured) and uninvolved legs of participants with ACLR during voluntary isometric contractions between the brain and both the vastus medialis and lateralis. This finding points to a potential lingering neural deficit underlying re-injury for athletes after surgical reconstruction, namely the dynamical structure of neuromuscular (brain to quad muscle) coordination, which is significantly asymmetric, between limbs, in those who have ACLR.

Spatially repeatable components from ultrafast ultrasound are associated with motor unit activity in human isometric contractions. J Neural Eng 2023;20:046016. [PMID: 37437598 DOI: 10.1088/1741-2552/ace6fc]

Objective.Ultrafast ultrasound (UUS) imaging has been used to detect intramuscular mechanical dynamics associated with single motor units (MUs). Detecting MUs from ultrasound sequences requires decomposing a velocity field into components, each consisting of an image and a signal. These components can be associated with putative MU activity or spurious movements (noise). The differentiation between putative MUs and noise has been accomplished by comparing the signals with MU firings obtained from needle electromyography (EMG). Here, we examined whether the repeatability of the images over brief time intervals can serve as a criterion for distinguishing putative MUs from noise in low-force isometric contractions.Approach.UUS images and high-density surface EMG (HDsEMG) were recorded simultaneously from 99 MUs in the biceps brachii of five healthy subjects. The MUs identified through HDsEMG decomposition were used as a reference to assess the outcomes of the ultrasound-based components. For each contraction, velocity sequences from the same eight-second ultrasound recording were separated into consecutive two-second epochs and decomposed. To evaluate the repeatability of components' images across epochs, we calculated the Jaccard similarity coefficient (JSC). JSC compares the similarity between two images providing values between 0 and 1. Finally, the association between the components and the MUs from HDsEMG was assessed.Main results.All the MU-matched components had JSC > 0.38, indicating they were repeatable and accounted for about one-third of the HDsEMG-detected MUs (1.8 ± 1.6 matches over 4.9 ± 1.8 MUs). The repeatable components (JSC > 0.38) represented 14% of the total components (6.5 ± 3.3 components). These findings align with our hypothesis that intra-sequence repeatability can differentiate putative MUs from noise and can be used for data reduction.Significance.This study provides the foundation for developing stand-alone methods to identify MU in UUS sequences and towards real-time imaging of MUs. These methods are relevant for studying muscle neuromechanics and designing novel neural interfaces.

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.

The use of non-linear tools to analyze the variability of force production as an index of fatigue: A systematic review

Background: Fatigue is a process that results in a decreased ability to produce force, and which could eventually affect performance and increase the risk of injury. Force variability analysis has been proposed to describe the level of fatigue with the purpose of detecting the development of fatigue. Variability is credited to play a functional and adaptive role through which the components of a system self-organize to solve a motor problem. Non-linear tools have been applied to analyze the variability of physiological signals, revealing that the structure of motor fluctuations provides relevant information about the functional role of variability. It has been suggested that the presence of lower complexity in the variability structure could reveal a less functional and adaptative state (e.g., ageing or illness). In the last years, an increased number of studies have applied these techniques to force variability analysis in relation to fatigue. Objective: To provide an overview of the current knowledge on the use of non-linear tools on force variability as a fatigue index. Methods: Following PRISMA guidelines, a systematic search of SPORTDiscus, Scopus, Web of Science and PubMed was carried out. Studies included were: a) original studies that analyzed the effect of fatigue on humans during an action focused on force production; b) published studies with their title and abstract in English; c) studies that applied non-linear tools on a signal directly related to force production. Results: Twenty-five studies were included in this review. The relationship between fatigue and the complexity of force variability, the type of action and relative intensity, the nature of the signal and the non-linear tools used, and the methods of data acquisition and processing were identified. Conclusion: The articles reviewed suggest that fatigue leads to a decrease in complexity mostly in isometric contractions, but this is not as clear in dynamic contractions. This fatigue-induced loss of complexity seems to be a result of changes in the nervous system at the central level, albeit triggered by peripheral mechanisms. It should be noted that non-linear tools are affected by the relative intensity of contraction, non-stationarity, and the acquisition and treatment of the signal.

Altered neuromuscular control in the vastus medialis following anterior cruciate ligament injury: A recurrence quantification analysis of electromyogram recruitment

BACKGROUND

Neuromuscular deficits exist following anterior cruciate ligament (ACL) injury. To observe these deficits, we examined nonlinear characteristics of vastus medialis electromyography (EMG) signals during submaximal isometric knee extensor contractions. Our purpose was to examine if determinism and entropy in EMG signals reflected neuromuscular control deficits in individuals with ACL-deficient limbs.

METHODS

24 participants (12 male, 12 female, mean age = 18.8 ± 3.1 years) with unilaterally injured ACLs and 25 age-similar healthy controls (11 male, 14 female, mean age = 18.8 ± 3.1 years) volunteered. Isometric knee extensions were tested at 10%, 25%, 35%, and 50% maximum voluntary contractions. Surface electrodes adhered over the vastus medialis captured EMG signals. EMG data were processed with recurrence quantification analyses. Specifically, determinism (an index of system predictability) and entropy (an index of system disorder) were calculated from recurrence plots.

FINDINGS

Determinism and entropy in EMG signals were lower in the injured than uninjured limb, and lower than that from healthy controls (P < .05).

INTERPRETATION

Vastus medialis EMG signals from the injured limb were less predictable and less complex than those from healthy limbs. The findings reflect impaired neuromuscular control in the injured limb's quadriceps and are consistent with a 'loss of complexity' hypothesis in physiologic signals emanating from pathologic states. Determinism and entropy in EMG signals may represent biomarkers of one's neuromuscular control system.

Electrophysiological and functional signs of Guillain-Barré syndrome predicted by a multiscale neuromuscular computational model

Objective. The diagnosis of nerve disorders in humans has relied heavily on the measurement of electrical signals from nerves or muscles in response to electrical stimuli applied at appropriate locations on the body surface. The present study investigated the demyelinating subtype of Guillain-Barré syndrome using multiscale computational model simulations to verify how demyelination of peripheral axons may affect plantar flexion torque as well as the ongoing electromyogram (EMG) during voluntary isometric or isotonic contractions. Approach. Changes in axonal conduction velocities, mimicking those found in patients with the disease at different stages, were imposed on a multiscale computational neuromusculoskeletal model to simulate subjects performing unipodal plantar flexion force and position tasks. Main results. The simulated results indicated changes in the torque signal during the early phase of the disease while performing isotonic tasks, as well as in torque variability after partial conduction block while performing both isometric and isotonic tasks. Our results also indicated changes in the root mean square values and in the power spectrum of the soleus EMG signal as well as changes in the synchronisation index computed from the firing times of the active motor units. All these quantitative changes in functional indicators suggest that the adoption of such additional measurements, such as torques and ongoing EMG, could be used with advantage in the diagnosis and be relevant in providing extra information for the neurologist about the level of the disease. Significance. Our findings enrich the knowledge of the possible ways demyelination affects force generation and position control during plantarflexion. Moreover, this work extends computational neuroscience to computational neurology and shows the potential of biologically compatible neuromuscular computational models in providing relevant quantitative signs that may be useful for diagnosis in the clinic, complementing the tools traditionally used in neurological electrodiagnosis.

Usefulness of Surface Electromyography Complexity Analyses to Assess the Effects of Warm-Up and Stretching during Maximal and Sub-Maximal Hamstring Contractions: A Cross-Over, Randomized, Single-Blind Trial

This study aimed to apply different complexity-based methods to surface electromyography (EMG) in order to detect neuromuscular changes after realistic warm-up procedures that included stretching exercises. Sixteen volunteers conducted two experimental sessions. They were tested before, after a standardized warm-up, and after a stretching exercise (static or neuromuscular nerve gliding technique). Tests included measurements of the knee flexion torque and EMG of biceps femoris (BF) and semitendinosus (ST) muscles. EMG was analyzed using the root mean square (RMS), sample entropy (SampEn), percentage of recurrence and determinism following a recurrence quantification analysis (%Rec and %Det) and a scaling parameter from a detrended fluctuation analysis. Torque was significantly greater after warm-up as compared to baseline and after stretching. RMS was not affected by the experimental procedure. In contrast, SampEn was significantly greater after warm-up and stretching as compared to baseline values. %Rec was not modified but %Det for BF muscle was significantly greater after stretching as compared to baseline. The a scaling parameter was significantly lower after warm-up as compared to baseline for ST muscle. From the present results, complexity-based methods applied to the EMG give additional information than linear-based methods. They appeared sensitive to detect EMG complexity increases following warm-up.

Detecting anatomical characteristics of single motor units by combining high density electromyography and ultrafast ultrasound: a simulation study

Muscle force production is the result of a sequence of electromechanical events that translate the neural drive issued to the motor units (MUs) into tensile forces on the tendon. Current technology allows this phenomenon to be investigated non-invasively. Single MU excitation and its mechanical response can be studied through high-density surface electromyography (HDsEMG) and ultrafast ultrasound (US) imaging respectively. In this study, we propose a method to integrate these two techniques to identify anatomical characteristics of single MUs. Specifically, we tested two algorithms, combining the tissue velocity sequence (TVS, obtained from ultrafast US images), and the MU firings (extracted from HDsEMG decomposition). The first is the Spike Triggered Averaging (STA) of the TVS based on the occurrences of individual MU firings, while the second relies on the correlation between the MU firing patterns and the TVS spatio-temporal independent components (STICA). A simulation model of the muscle contraction was adapted to test the algorithms at different degrees of neural excitation (number of active MUs) and MU synchronization. The performances of the two algorithms were quantified through the comparison between the simulated and the estimated characteristics of MU territories (size, location). Results show that both approaches are negatively affected by the number of active MU and synchronization levels. However, STICA provides a more robust MU territory estimation, outperforming STA in all the tested conditions. Our results suggest that spatio-temporal independent component decomposition of TVS is a suitable approach for anatomical and mechanical characterization of single MUs using a combined HDsEMG and ultrafast US approach.

Recruitment order of motor neurons promoted by epidural stimulation in individuals with spinal cord injury

Spinal cord epidural stimulation (scES) combined with activity-based training can promote motor function recovery in individuals with motor complete spinal cord injury (SCI). The characteristics of motor neuron recruitment, which influence different aspects of motor control, are still unknown when motor function is promoted by scES. Here, we enrolled five individuals with chronic motor complete SCI implanted with a scES unit to study the recruitment order of motor neurons during standing enabled by scES. We recorded high-density electromyography (HD-EMG) signals on the vastus lateralis muscle, and inferred the order of recruitment of motor neurons from the relation between amplitude and conduction velocity of the scES-evoked EMG responses along the muscle fibers. Conduction velocity of scES-evoked responses was modulated over time, while stimulation parameters and standing condition remained constant, with average values ranging between 3.0±0.1 and 4.4±0.3 m/s. We found that the human spinal circuitry receiving epidural stimulation can promote both orderly (according to motor neuron size) and inverse trends of motor neuron recruitment, and that the engagement of spinal networks promoting rhythmic activity may favor orderly recruitment trends. Conversely, the different recruitment trends did not appear to be related with time since injury or scES implant, nor to the ability to achieve independent knees extension, nor to the conduction velocity values. The proposed approach can be implemented to investigate the effects of stimulation parameters and training-induced neural plasticity on the characteristics of motor neuron recruitment order, contributing to improve mechanistic understanding and effectiveness of epidural stimulation-promoted motor recovery after SCI.

A Statistical Method for Exploratory Data Analysis Based on 2D and 3D Area under Curve Diagrams: Parkinson's Disease Investigation

A statistical method for exploratory data analysis based on 2D and 3D area under curve (AUC) diagrams was developed. The method was designed to analyze electroencephalogram (EEG), electromyogram (EMG), and tremorogram data collected from patients with Parkinson's disease. The idea of the method of wave train electrical activity analysis is that we consider the biomedical signal as a combination of the wave trains. The wave train is the increase in the power spectral density of the signal localized in time, frequency, and space. We detect the wave trains as the local maxima in the wavelet spectrograms. We do not consider wave trains as a special kind of signal. The wave train analysis method is different from standard signal analysis methods such as Fourier analysis and wavelet analysis in the following way. Existing methods for analyzing EEG, EMG, and tremor signals, such as wavelet analysis, focus on local time-frequency changes in the signal and therefore do not reveal the generalized properties of the signal. Other methods such as standard Fourier analysis ignore the local time-frequency changes in the characteristics of the signal and, consequently, lose a large amount of information that existed in the signal. The method of wave train electrical activity analysis resolves the contradiction between these two approaches because it addresses the generalized characteristics of the biomedical signal based on local time-frequency changes in the signal. We investigate the following wave train parameters: wave train central frequency, wave train maximal power spectral density, wave train duration in periods, and wave train bandwidth. We have developed special graphical diagrams, named AUC diagrams, to determine what wave trains are characteristic of neurodegenerative diseases. In this paper, we consider the following types of AUC diagrams: 2D and 3D diagrams. The technique of working with AUC diagrams is illustrated by examples of analysis of EMG in patients with Parkinson's disease and healthy volunteers. It is demonstrated that new regularities useful for the high-accuracy diagnosis of Parkinson's disease can be revealed using the method of analyzing the wave train electrical activity and AUC diagrams.

Which subject-related variables contribute to movement variability during a simulated repetitive and standardised occupational task? Recurrence quantification analysis of surface electromyographic signals

Movement variability is a component of human movement. This study applied recurrence quantification analysis (RQA) on electromyographic signals to determine the effects of two types of variables on movement variability during a short, simulated repetitive and standardised occupational clip-fitting task. The electrical activity of six muscles in the dominant upper limb was recorded in 21 participants. Variables related to the task performance (insertion force and movements performed when fitting clips) affected RQA measures: recurrence rate (RR), percentage of determinism (DET) and diagonal line length entropy (ENT). Variables related to participant's characteristics (sex, age, and BMI) affected only DET and ENT. A constrasting variability was observed such as a high-DET value combined with a high-ENT value and inversely. Variables affected mainly the recurrences organisation of the more distal muscles. Even if movement variability is complex, it should be considered by ergonomists and work place designers to better understanding of operators' movements. Practitioner summary: It is essential to consider the complexity of operators' movement variability to understand their activities. Based on intrinsic movement variability knowledge, ergonomists and work place designers will be able to modulate the movement variability by acting on workstation designs and occupational organisation with the aim of preserving operators' health. Abbreviations: RR: recurrence rate; DET: percentage of determinism; ENT: diagonal line length entropy; BMI: body mass index; FDS: flexor digitorum superficialis; EXT: extensor digitorum communis; BIC: biceps brachii; TRI: triceps brachii; DEL: deltoideus anterior; TRA: trapezius pars descendens; F: female; M: male; S: supinated; P: pronated; CM: continuous movement; DM: discontinuous movement.

Analysis and Biophysics of Surface EMG for Physiotherapists and Kinesiologists: Toward a Common Language With Rehabilitation Engineers

Recent decades have seen a move toward evidence-based medicine to inform the clinical decision-making process with reproducible findings from high-quality research studies. There is a need for objective, quantitative measurement tools to increase the reliability and reproducibility of studies evaluating the efficacy of healthcare interventions, particularly in the field of physical and rehabilitative medicine. Surface electromyography (sEMG) is a non-invasive measure of muscle activity that is widely used in research but is under-utilized as a clinical tool in rehabilitative medicine. Other types of electrophysiological signals (e.g., electrocardiography, electroencephalography, intramuscular EMG) are commonly recorded by healthcare practitioners, however, sEMG has yet to successfully transition to clinical practice. Surface EMG has clear clinical potential as an indicator of muscle activation, however reliable extraction of information requires knowledge of the appropriate methods for recording and analyzing sEMG and an understanding of the underlying biophysics. These concepts are generally not covered in sufficient depth in the standard curriculum for physiotherapists and kinesiologists to encourage a confident use of sEMG in clinical practice. In addition, the common perception of sEMG as a specialized topic means that the clinical potential of sEMG and the pathways to application in practice are often not apparent. The aim of this paper is to address barriers to the translation of sEMG by emphasizing its benefits as an objective clinical tool and by overcoming its perceived complexity. The many useful clinical applications of sEMG are highlighted and examples provided to illustrate how it can be implemented in practice. The paper outlines how fundamental biophysics and EMG signal processing concepts could be presented to a non-technical audience. An accompanying tutorial with sample data and code is provided which could be used as a tool for teaching or self-guided learning. The importance of observing sEMG in routine use in clinic is identified as an essential part of the effective communication of sEMG recording and signal analysis methods. Highlighting the advantages of sEMG as a clinical tool and reducing its perceived complexity could bridge the gap between theoretical knowledge and practical application and provide the impetus for the widespread use of sEMG in clinic.

Training induced fatigability assessed by sEMG in Pre-Olympic ice-skaters

The aim of this study was to investigate the size of the change and asymmetry in fatigability of gluteus maximus muscles during endurance training in short-track. The research has taken into account the position of athletes during skating and the problem of fatigue and pain in these muscles. The research covered involved eight female athletes of the Polish National Team in short track, which had been prepared to the Olympic Games in PyeongChang. The surface electromyography (sEMG) system was used to measure fatigue of right and left gluteus maximus muscles, in the modified Biering–Sorensen test. The test was conducted five times during the training: before training, after warmup, and after each of 3 series of the endurance training. Comparing the mean frequency of the surface electromyography power spectrum of the test, statistically significant reduction of the average frequency value of the right muscle from 55.61 ± 7.08 to 48.64 ± 4.48 Hz and left muscle from 58.78 ± 4.98 to 53.18 ± 4.62 Hz was reported, which prove the muscle fatigue. In subsequent series tests, the sEMG signal frequency of begin decrease more than the end of the each measurement, which determines the fatigue threshold. The size of the d Cohen effect in fatigue drops along with subsequent five tests during the training. Skaters has higher frequency reduction of the right lower limb, which indicates its greater fatigue during skateing. The fatigue and asymmetry in muscle observed in short-track has implications for training and performance.

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.

Inertial Sensors Embedded in Smartphones as a Tool for Fatigue Assessment Based on Acceleration in Survivors of Breast Cancer

BACKGROUND

Cancer-related fatigue is a symptom commonly reported in survivors of breast cancer and is the most variable symptom. Besides questionnaires like PIPER to assess cancer-related fatigue, there is a need to objectively measure fatigue.

OBJECTIVE

The aim of this study was to assess the physiological dimension of fatigue based on acceleration during a 30-second maximal sit-to-stand test.

DESIGN

This was a cross-sectional study.

METHODS

Linear acceleration from a smartphone placed on the sternum was recorded in 70 survivors of breast cancer. Fourth-degree polynomial adjustment from the acceleration signal to the vertical and anterior-posterior axis was calculated. The fatigue temporal cut-off point was detected as a change in the curve slope of the first maximum point of acceleration.

RESULTS

Women were aged 51.8 (8.9) years with a body mass index of 25.4 (5.1) Kg/m2. They performed 23.6 (6.57) number of repetitions. The mean fatigue cut-off point from the total sample was 10.2 (3.1) seconds.

LIMITATIONS

Further research should employ time-prolonged tests to study acceleration behavior beyond 30 seconds as well as include a physiological criterion that justifies the nonlinear saturation of the acceleration-based criterion.

CONCLUSIONS

This study assessed fatigue through a low-cost and easy-to-use methodology during a functional and widely used test such as 30-second maximal sit-to-stand. This would allow clinicians to assess fatigue in a short-effort exercise to individualize exercise prescription dose, measure changes during intervention, and track fatigue objectively throughout survivorship.

Implementation and experimental validation of surface electromyogram and force model of Tibialis Anterior muscle for examining muscular factors

This study reports a surface electromyogram and force of contraction model. The objective was to investigate the effect of changes in the size, type and number of motor units in the Tibialis Anterior muscle to surface electromyogram and force of dorsiflexion. A computational model to simulate surface electromyogram and associated force of contraction by the Tibialis Anterior muscle was developed. This model was simulated for isometric dorsiflexion, and comparative experiments were conducted for validation. Repeated simulations were performed to investigate the different parameters and evaluate inter-experimental variability. An equivalence statistical test and the Bland–Altman method were used to observe the significance between the simulated and experimental data. Simulated and experimentally recorded data had high similarity for the three measures: maximal power of power spectral density ( p < 0.0001), root mean square of surface electromyogram ( p < 0.0001) and force recorded at the footplate ( p < 0.03). Inter-subject variability in the experimental results was in-line with the variability in the repeated simulation results. This experimentally validated computational model for the surface electromyogram and force of the Tibialis Anterior muscle is significant as it allows the examination of three important muscular factors associated with ageing and disease: size, fibre type and number of motor units.

Cognitive stress changes the attributes of the three heads of the triceps brachii during muscle fatigue

INTRODUCTION

Cognitive stress (CS) changes the peripheral attributes of a muscle, but its effect on multi-head muscles has not been investigated. The objective of the current research was to investigate the impact of CS on the three heads of the triceps brachii (TB) muscle.

METHODS

Twenty-five young and healthy university students performed a triceps push-down exercise at 45% one repetition maximum (1RM) with and without CS until task failure, and the rate of fatigue (ROF), endurance time (ET) and number of repetitions (NR) for both exercises were analyzed. In addition, the first and last six repetitions of each exercise were considered non-fatiguing (NF) and fatiguing (Fa), respectively, and the root mean square (RMS), mean power frequency (MPF) and median frequency (MDF) for each exercise repetition were evaluated.

RESULTS

The lateral and long head showed significant differences (P<0.05) in the ROF between the two exercises, and all the heads showed significant (P<0.05) differences in the RMS between the two exercises under NF conditions. Only the long head showed a significant difference (P<0.05) in the MPF and MDF between the two exercises. CS increases the ET (24.74%) and NR (27%) of the exercise. The three heads showed significant differences (P<0.05) in the RMS, MPF and MDF under all exercise conditions.

CONCLUSION

A lower ROF was obtained with CS. In addition, the RMS was found to be better approximator of CS, whereas MPF and MDF were more resistant to the effect of CS. The results showed that the three heads worked independently under all conditions, and the non-synergist and synergist head pairs showed similar behavior under Fa conditions. The findings from this study provide additional insights regarding the functioning of each TB head.

The Influence of Force Level and Motor Unit Coherence on Nonlinear Surface EMG Features Examined Using Model Simulation

Nonlinear features extracted from surface EMG signals have been previously used to infer information on coherent or synchronous activity in the underlying motor unit discharges. However, it has not yet been assessed how these features are affected by the density of the surface EMG signal, and whether changes in the level of muscle activation can influence the effective detection of correlated motor unit firing. To examine this, a motoneuron pool model receiving a beta-band modulated cortical input was used to generate correlated motor unit firing trains. These firing trains were convolved with motor unit action potentials generated from an anatomically accurate electrophysiological model of the first dorsal interosseous muscle. The sample entropy (SampEn) and percentage determinism (%DET) of recurrence quantification analysis were calculated from the composite surface EMG signals, for signals comprised of both correlated and uncorrelated motor unit firing trains. The results show that although both SampEn and %DET are influenced by motor unit coherence, they are differentially affected by muscle activation and motor unit distribution. The results also suggest that sample entropy may provide a more accurate assessment of the underlying motor unit coherence than percentage determinism, as it is less sensitive to factors unrelated to motor unit synchrony.

Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study

The latest studies of the 30-second sit-to-stand (30-STS) test aim to describe it by employing kinematic variables, muscular activity, or fatigue through electromyography (EMG) instead of a number of repetitions. The aim of the present study was to develop a detection system based on acceleration measured using a smartphone to analyze fatigue during the 30-STS test with surface electromyography as the criterion. This case study was carried out on one woman, who performed eight trials. EMG data from the lower limbs and trunk muscles, as well as trunk acceleration were recorded. Both signals from eight trials were preprocessed, being averaged and temporarily aligned. The EMG signal was processed, calculating the spectral centroid (SC) by Discrete Fourier Transform, while the acceleration signal was processed by Discrete Wavelet Transform to calculate its energy percentage. Regarding EMG, fatigue in the vastus medialis of the quadriceps appeared as a decrease in SC, with a descending slope of 12% at second 12, indicating fatigue. However, acceleration analysis showed an increase in the percentage of relative energy, acting like fatigue firing at second 19. This assessed fatigue according to two variables of a different nature. The results will help clinicians to obtain information about fatigue using an accessible and inexpensive device, i.e., as a smartphone.

Beta-band motor unit coherence and nonlinear surface EMG features of the first dorsal interosseous muscle vary with force

Motor unit firing times are weakly coupled across a range of frequencies during voluntary contractions. Coherent activity within the beta-band (15-35 Hz) has been linked to oscillatory cortical processes, providing evidence of functional connectivity between the motoneuron pool and motor cortex. The aim of this study was to investigate whether beta-band motor unit coherence is altered with increasing abduction force in the first dorsal interosseous muscle. Coherence between motor unit firing times, extracted from decomposed surface electromyography (EMG) signals, was investigated in 17 subjects at 10, 20, 30, and 40% of maximum voluntary contraction. Corresponding changes in nonlinear surface EMG features (specifically sample entropy and determinism, which are sensitive to motor unit synchronization) were also examined. A reduction in beta-band and alpha-band coherence was observed as force increased [F(3, 151) = 32, P < 0.001 and F(3, 151) = 27, P < 0.001, respectively], accompanied by corresponding changes in nonlinear surface EMG features. A significant relationship between the nonlinear features and motor unit coherence was also detected (r = -0.43 ± 0.1 and r = 0.45 ± 0.1 for sample entropy and determinism, respectively; both P < 0.001). The reduction in beta-band coherence suggests a change in the relative contribution of correlated and uncorrelated presynaptic inputs to the motoneuron pool, and/or a decrease in the responsiveness of the motoneuron pool to synchronous inputs at higher forces. The study highlights the importance of considering muscle activation when investigating changes in motor unit coherence or nonlinear EMG features and examines other factors that can influence coherence estimation.NEW & NOTEWORTHY Intramuscular alpha- and beta-band coherence decreased as muscle contraction force increased. Beta-band coherence was higher in groups of high-threshold motor units than in simultaneously active lower threshold units. Alterations in motor unit coherence with increases or decreases in force and with the onset of fatigue were accompanied by corresponding changes in surface electromyography sample entropy and determinism. Mixed-model analysis indicated mean firing rate and number of motor units also influenced the coherence estimate.

An Android Application for Estimating Muscle Onset Latency using Surface EMG Signal

BACKGROUND

Electromyography (EMG) signal processing and Muscle Onset Latency (MOL) are widely used in rehabilitation sciences and nerve conduction studies. The majority of existing software packages provided for estimating MOL via analyzing EMG signal are computerized, desktop based and not portable; therefore, experiments and signal analyzes using them should be completed locally. Moreover, a desktop or laptop is required to complete experiments using these packages, which costs.

OBJECTIVE

Develop a non-expensive and portable Android application (app) for estimating MOL via analyzing surface EMG.

MATERIAL AND METHODS

A multi-layer architecture model was designed for implementing the MOL estimation app. Several Android-based algorithms for analyzing a recorded EMG signal and estimating MOL was implemented. A graphical user interface (GUI) that simplifies analyzing a given EMG signal using the presented app was developed too.

RESULTS

Evaluation results of the developed app using 10 EMG signals showed promising performance; the MOL values estimated using the presented app are statistically equal to those estimated using a commercial Windows-based surface EMG analysis software (MegaWin 3.0). For the majority of cases relative error <10%. MOL values estimated by these two systems are linearly related, the correlation coefficient value ~ 0.93. These evaluations revealed that the presented app performed as well as MegaWin 3.0 software in estimating MOL.

CONCLUSION

Recent advances in smart portable devices such as mobile phones have shown the great capability of facilitating and decreasing the cost of analyzing biomedical signals, particularly in academic environments. Here, we developed an Android app for estimating MOL via analyzing the surface EMG signal. Performance is promising to use the app for teaching or research purposes.

Increased EMG intermuscular coherence and reduced signal complexity in Parkinson's disease

OBJECTIVES

To investigate differences in surface electromyography (EMG) features in individuals with idiopathic Parkinson's disease (PD) and aged-matched controls.

METHODS

Surface EMG was recorded during isometric leg extension in PD patients prior to, and after undergoing a locomotor training programme, and in aged-matched controls. Differences in EMG structure were quantified using determinism (%DET), sample entropy (SampEn) and intermuscular coherence.

RESULTS

%DET was significantly higher, and SampEn significantly lower, in PD patients. Intermuscular coherence was also significantly higher in the PD group in theta, alpha and beta frequency bands. %DET increased and SampEn decreased with increasing Movement-Disorder-Society UPDRS scores, while theta band coherence was significantly correlated with total MDS-UPDRS scores and torque variance. Neither %DET, SampEn nor intermuscular coherence changed in response to training.

CONCLUSIONS

The differences observed are consistent with increased synchrony among motor units within and across leg muscles in PD. Differences between EMG signals recorded from the PD and control groups persisted post-therapy, after improvements in walking capacity occurred.

SIGNIFICANCE

These results provide insight into changes in motoneuron activity in PD, demonstrate increased beta band intramuscular coherence in PD for the first time, and support the development of quantitative biomarkers for PD based on advanced surface EMG features.

A Novel Interpretation of Sample Entropy in Surface Electromyographic Examination of Complex Neuromuscular Alternations in Subacute and Chronic Stroke

The objective of this paper was to develop sample entropy (SampEn) as a novel surface electromyogram (EMG) biomarker to quantitatively examine post-stroke neuromuscular alternations. The SampEn method was performed on surface EMG interference patterns recorded from biceps brachii muscles of nine healthy control subjects, fourteen subjects with subacute stroke, and eleven subjects with chronic stroke, respectively. Measurements were collected during isometric contractions of elbow flexion at different constant force levels. By producing diagnostic decisions for individual muscles, two categories of abnormalities in some paretic muscles were discriminated in terms of abnormally increased and decreased SampEn. The efficiency of the SampEn was demonstrated by its comparable performance with a previously reported clustering index (CI) method. Mixed SampEn (or CI) patterns were observed in paretic muscles of subjects with stroke indicating complex neuromuscular changes at work as a result of a hemispheric brain lesion. Although both categories of SampEn (or CI) abnormalities were observed in both subacute and chronic stages of stroke, the underlying processes contributing to the SampEn abnormalities might vary a lot in stroke stage. The SampEn abnormalities were also found in contralateral muscles of subjects with chronic stroke indicating the necessity of applying interventions to contralateral muscles during stroke rehabilitation. Our work not only presents a novel method for quantitative examination of neuromuscular changes, but also explains the neuropathological mechanisms of motor impairments and offers guidelines for a better design of effective rehabilitation protocols toward improved motor recovery.

Assessing multiple muscle activation during squat movements with different loading conditions - an EMG study

Surface electromyography (EMG) is a valuable tool in clinical diagnostics and research related to human neuromotor control. Non-linear analysis of EMG data can help with detection of subtle changes of control due to changes of external or internal constraints during motor tasks. However, non-linear analysis is complex and results may be difficult to interpret, particularly in clinical environments. We developed a non-linear analysis tool (SYNERGOS) that evaluates multiple muscle activation (MMA) features and provides a single value for description of activation characteristics. To investigate the responsiveness of SYNERGOS to kinetic changes during cyclic movements, 13 healthy young adults performed squat movements under different loading conditions (100%-120% of body weight). We processed EMG data to generate SYNERGOS indices and used two-way repeated measures ANOVA to determine changes of MMA in response to loading conditions during movement. SYNERGOS values were significantly different for each loading condition. We concluded that the algorithm is sensitive to kinetic changes during cyclic movements, which may have implications for applications in a variety of experimental and diagnostic settings.

Spinal and supraspinal control of motor function during maximal eccentric muscle contraction: Effects of resistance training

Neuromuscular activity is suppressed during maximal eccentric (ECC) muscle contraction in untrained subjects owing to attenuated levels of central activation and reduced spinal motor neuron (MN) excitability indicated by reduced electromyography signal amplitude, diminished evoked H-reflex responses, increased autogenic MN inhibition, and decreased excitability in descending corticospinal motor pathways. Maximum ECC muscle force recorded during maximal voluntary contraction can be increased by superimposed electrical muscle stimulation only in untrained individuals and not in trained strength athletes, indicating that the suppression in MN activation is modifiable by resistance training. In support of this notion, maximum ECC muscle strength can be increased by use of heavy-load resistance training owing to a removed or diminished suppression in neuromuscular activity. Prolonged (weeks to months) of heavy-load resistance training results in increased H-reflex and V-wave responses during maximal ECC muscle actions along with marked gains in maximal ECC muscle strength, indicating increased excitability of spinal MNs, decreased presynaptic and/or postsynaptic MN inhibition, and elevated descending motor drive. Notably, the use of supramaximal ECC resistance training can lead to selectively elevated V-wave responses during maximal ECC contraction, demonstrating that adaptive changes in spinal circuitry function and/or gains in descending motor drive can be achieved during maximal ECC contraction in response to heavy-load resistance training.

Stroke-Related Changes in the Complexity of Muscle Activation during Obstacle Crossing Using Fuzzy Approximate Entropy Analysis

This study investigated the complexity of the electromyography (EMG) of lower limb muscles when performing obstacle crossing tasks at different heights in poststroke subjects versus healthy controls. Five poststroke subjects and eight healthy controls were recruited to perform different obstacle crossing tasks at various heights (randomly set at 10, 20, and 30% of the leg’s length). EMG signals were recorded from bilateral biceps femoris (BF), rectus femoris (RF), medial gastrocnemius, and tibialis anterior during obstacle crossing task. The fuzzy approximate entropy (fApEn) approach was used to analyze the complexity of the EMG signals. The fApEn values were significantly smaller in the RF of the trailing limb during the swing phase in poststroke subjects than healthy controls (p < 0.05), which may be an indication of smaller number and less frequent firing rates of the motor units. However, during the swing phase, there were non-significant increases in the fApEn values of BF and RF in the trailing limb of the stroke group compared with those of healthy controls, resulting in a coping strategy when facing challenging tasks. The fApEn values that increased with height were found in the BF of the leading limb during the stance phase and in the RF of the trailing limb during the swing phase (p < 0.05). The reason for this may have been a larger muscle activation associated with the increase in obstacle height. This study demonstrated a suitable and non-invasive method to evaluate muscle function after a stroke.

A computational model to investigate the effect of pennation angle on surface electromyogram of Tibialis Anterior

This study has described and experimentally validated the differential electrodes surface electromyography (sEMG) model for tibialis anterior muscles during isometric contraction. This model has investigated the effect of pennation angle on the simulated sEMG signal. The results show that there is no significant effect of pennation angle in the range 0° to 20° to the single fibre action potential shape recorded on the skin surface. However, the changes with respect to pennation angle are observed in sEMG amplitude, frequency and fractal dimension. It is also observed that at different levels of muscle contractions there is similarity in the relationships with Root Mean Square, Median Frequency, and Fractal Dimension of the recorded and simulated sEMG signals.

Effect of oral glucose supplementation on surface EMG during fatiguing dynamic exercise

The aim of this study was to examine the effect of oral glucose supplementation on the surface electromyographic (sEMG) signal recorded during a dynamic, fatiguing exercise protocol. Five healthy subjects participated in the study. Blood glucose concentration and sEMG signals from five upper leg muscles were recorded during a cycling exercise performed at 70% VO2peak until task failure, on two separate occasions. Glucose was consumed at 15 minute intervals throughout one trial. The median frequency of the sEMG was observed to increase progressively throughout the exercise, with a greater increase in the with glucose condition. This is in direct contrast to the typical decrease in median frequency known to occur during a fatiguing isometric contraction. The result may indicate an increase in Na+ - K+ - AT Pase activity during fatiguing dynamic exercise resulting in an increase in muscle fiber membrane excitability due to membrane hyperpolarization.

Measuring multiple neuromuscular activation using EMG - a generalizability analysis

Analysis of electromyography (EMG) data has been shown to be valuable in biomedical and clinical research. However, most analysis tools do not consider the non-linearity of EMG data or the synergistic effects of multiple neuromuscular activities. The SYNERGOS algorithm was developed to assess a single index based on non-linear analysis of multiple neuromuscular activation (MNA) of different muscles. This index has shown promising results in Parkinsonian gait, but it was yet to be explored whether the SYNERGOS index is generalizable. In this study, we evaluated generalizability of the SYNERGOS index over the course of several trials and over separate days with different walking speeds. Ten healthy adults aged from 18 to 40 years walked on a treadmill on two different days, while EMG data was collected from the upper and lower right leg. SYNERGOS indices were obtained and a generalizability analysis was conducted. The algorithm detected changes in MNA in response to altering gait speed and depicted a high generalizability coefficient ( ρ^2 ${\hat \rho ^2}$ ) of 0.823 with a standard error of 5.117 with nominal inter-trial or inter-day effects. We concluded SYNERGOS may be a valuable tool in EMG analysis due to its generalizability and its sensitivity to task modifications and associated neuromotor changes.

Effects of a Three-Set Tennis Match on Knee Kinematics and Leg Muscle Activation during the Tennis Serve

The purpose of this study was to determine the effect of a three-set tennis match on knee kinematics and leg muscle activation during the tennis serve in a real-time environment. Motion capture data and wireless electromyography of hamstrings and quadriceps muscles were collected from the back leg during the serve. A reduction of maximum knee flexion angle and a decrease of electromyography amplitudes in leg muscles were observed during the match. However, the knee angular velocity and the electromyography frequency of leg muscles remain unchanged throughout the match. The intermuscular compensation strategy to counteract fatigue might explain that the knee angular velocity was maintained despite reductions in knee flexion angle and electromyography activity of leg muscles.

Motor unit firing rates and synchronisation affect the fractal dimension of simulated surface electromyogram during isometric/isotonic contraction of vastus lateralis muscle

During fatiguing contractions, many adjustments in motor units behaviour occur: decrease in muscle fibre conduction velocity; increase in motor units synchronisation; modulation of motor units firing rate; increase in variability of motor units inter-spike interval. We simulated the influence of all these adjustments on synthetic EMG signals in isometric/isotonic conditions. The fractal dimension of the EMG signal was found mainly influenced by motor units firing behaviour, being affected by both firing rate and synchronisation level, and least affected by muscle fibre conduction velocity. None of the calculated EMG indices was able to discriminate between firing rate and motor units synchronisation.

Recurrence quantification analysis of surface electromyogram supports alterations in motor unit recruitment strategies by anodal transcranial direct current stimulation

PURPOSE

Recent evidence indicates that anodal transcranial direct current stimulation (tDCS) can selectively alter the EMG/force relationship of agonist arm muscles; however, the mechanisms mediating those changes are less clear. The purpose of this study was to evaluate the effect of anodal tDCS on motor unit synchronization by using a sophisticated non-linear EMG analysis called recurrence quantification analysis (RQA).

METHODS

Surface EMG signals were collected from the biceps brachii muscle of eighteen healthy young adults (9 tDCS and 9 control) at various force levels (12.5%, 25%, 37.5%, and 50% maximum) before and after the application of anodal tDCS over the primary motor cortex. RQA was employed to quantify the changes in percentage of determinism (% DET) and laminarity (% LAM) of the surface EMG signals, which are surrogate measures of motor unit synchronization.

RESULTS

RQA analyses indicated that the changes in % DET and % LAM scores were significantly higher in the tDCS group than in the control group (p < 0.05) and this effect was particularly pronounced at higher force levels.

CONCLUSION

The results of this study provide novel evidence supporting that anodal tDCS significantly alters motor unit firing strategies (i.e., the degree of synchronization) of the biceps brachii muscle.

Prediction of Muscle Fatigue during Minimally Invasive Surgery Using Recurrence Quantification Analysis

Due to its inherent complexity such as limited work volume and degree of freedom, minimally invasive surgery (MIS) is ergonomically challenging to surgeons compared to traditional open surgery. Specifically, MIS can expose performing surgeons to excessive ergonomic risks including muscle fatigue that may lead to critical errors in surgical procedures. Therefore, detecting the vulnerable muscles and time-to-fatigue during MIS is of great importance in order to prevent these errors. The main goal of this study is to propose and test a novel measure that can be efficiently used to detect muscle fatigue. In this study, surface electromyography was used to record muscle activations of five subjects while they performed fifteen various laparoscopic operations. The muscle activation data was then reconstructed using recurrence quantification analysis (RQA) to detect possible signs of muscle fatigue on eight muscle groups (bicep, triceps, deltoid, and trapezius). The results showed that RQA detects the fatigue sign on bilateral trapezius at 47.5 minutes (average) and bilateral deltoid at 57.5 minutes after the start of operations. No sign of fatigue was detected for bicep and triceps muscles of any subject. According to the results, the proposed novel measure can be efficiently used to detect muscle fatigue and eventually improve the quality of MIS procedures with reducing errors that may result from overlooked muscle fatigue.

Evaluating the Training Effects of Two Swallowing Rehabilitation Therapies Using Surface Electromyography--Chin Tuck Against Resistance (CTAR) Exercise and the Shaker Exercise

In this study, the efficacy of two dysphagia interventions, the Chin Tuck against Resistance (CTAR) and Shaker exercises, were evaluated based on two principles in exercise science-muscle-specificity and training intensity. Both exercises were developed to strengthen the suprahyoid muscles, whose contractions facilitate the opening of the upper esophageal sphincter, thereby improving bolus transfer. Thirty-nine healthy adults performed two trials of both exercises in counter-balanced order. Surface electromyography (sEMG) recordings were simultaneously collected from suprahyoid muscle group and sternocleidomastoid muscle during the exercises. Converging results using sEMG amplitude analyses suggested that the CTAR was more specific in targeting the suprahyoid muscles than the Shaker exercise. Fatigue analyses on sEMG signals further indicated that the suprahyoid muscle group were equally or significantly fatigued (depending on metric), when participants carried out CTAR compared to the Shaker exercise. Importantly, unlike during Shaker exercise, the sternocleidomastoid muscles were significantly less activated and fatigued during CTAR. Lowering the chin against resistance is therefore sufficiently specific and intense to fatigue the suprahyoid muscles.

Electromyographic evaluation of countermeasures during the terrestrial simulation of interplanetary spaceflight in Mars500 project

The efficiency of six countermeasures (CM) for muscle atrophy was compared over 520 days of confinement during the terrestrial simulation of round space flight to Mars using surface electromyography (sEMG). Three of CM were cyclic exercises (a motor-driven and leg-driven treadmill, cycle ergometer), resistive exercises (the multifunctional dynamometer for space-MDS, and expanders), and vibration platform. Each of CM was applied for each crew member (n=6) once over the experiment, for 70 days in a row, in prescribed order. sEMG was collected during the "force step test" in which the subject voluntarily produced pressure by lower limb, with minimal force increment. The mean frequency (MNF) and average amplitude of sEMG were analyzed. The MNF of sEMG decreased from 104.3±4.2 to 95.3±2.9Hz (P<0.05) in the soleus muscle after 70 days of exercising on the leg-driven treadmill and after 35 days-on vibration platform. It can be caused by earlier (10-250ms) recruitment of the soleus in respect with the medial gastronemius on the leg-driven treadmill, while on the motor-driven treadmill synergists activated synchronously. In other lower leg muscles, MNF decreased from 180 to 200 to 165-180Hz after 70 days of resistive exercises on the MDS device. CM caused no effect on sEMG amplitude. In conclusion, (1) the leg-driven treadmill, the MDS and vibration platform significantly depressed MNF of sEMG of lower extremity muscles; (2) the leg-driven treadmill and vibration platform specifically affected the soleus muscle. Therefore, these CM can be recommended for a more extensive use on ISS board.

Recurrence quantification analysis and support vector machines for golf handicap and low back pain EMG classification

The quantification of non-linear characteristics of electromyography (EMG) must contain information allowing to discriminate neuromuscular strategies during dynamic skills. There are a lack of studies about muscle coordination under motor constrains during dynamic contractions. In golf, both handicap (Hc) and low back pain (LBP) are the main factors associated with the occurrence of injuries. The aim of this study was to analyze the accuracy of support vector machines SVM on EMG-based classification to discriminate Hc (low and high handicap) and LBP (with and without LPB) in the main phases of golf swing. For this purpose recurrence quantification analysis (RQA) features of the trunk and the lower limb muscles were used to feed a SVM classifier. Recurrence rate (RR) and the ratio between determinism (DET) and RR showed a high discriminant power. The Hc accuracy for the swing, backswing, and downswing were 94.4±2.7%, 97.1±2.3%, and 95.3±2.6%, respectively. For LBP, the accuracy was 96.9±3.8% for the swing, and 99.7±0.4% in the backswing. External oblique (EO), biceps femoris (BF), semitendinosus (ST) and rectus femoris (RF) showed high accuracy depending on the laterality within the phase. RQA features and SVM showed a high muscle discriminant capacity within swing phases by Hc and by LBP. Low back pain golfers showed different neuromuscular coordination strategies when compared with asymptomatic.

The size and structure of arm movement variability decreased with work pace in a standardised repetitive precision task

Increased movement variability has been suggested to reduce the risk of developing musculoskeletal disorders caused by repetitive work. This study investigated the effects of work pace on arm movement variability in a standardised repetitive pipetting task performed by 35 healthy women. During pipetting at slow and fast paces differing by 15%, movements of arm, hand and pipette were tracked in 3D, and used to derive shoulder and elbow joint angles. The size of cycle-to-cycle motor variability was quantified using standard deviations of several kinematics properties, while the structure of variability was quantified using indices of sample entropy and recurrence quantification analysis. When pace increased, both the size and structure of motor variability in the shoulder and elbow decreased. These results suggest that motor variability drops when repetitive movements are performed at increased paces, which may in the long run lead to undesirable outcomes such as muscle fatigue or overuse.