Muscle fatigue assessment through electrodermal activity analysis during isometric contraction

We studied the effects of muscle fatigue on the Autonomic Nervous System (ANS) dynamics. Specifically, we monitored the electrodermal activity (EDA) on 32 healthy subjects performing isometric biceps contraction. As assessed by means of an electromyography (EMG) analysis, 15 subjects showed muscle fatigue and 17 did not. EDA signals were analyzed using the recently proposed cvxEDA model in order to decompose them into their phasic and tonic components and extract effective features to study ANS dynamics. A statistical comparison between the two groups of subjects was performed. Results revealed that relevant phasic EDA features significantly increased in the fatigued group. Moreover, a pattern recognition system was applied to the EDA dataset in order to automatically discriminate between fatigued and non-fatigued subjects. The proposed leave-one-subject-out KNN classifier showed an accuracy of 75.69%. These results suggest the use of EDA as correlate of muscle fatigue, providing integrative information to the standard indices extracted from the EMG signals

Assessment of muscle fatigue during isometric contraction using autonomic nervous system correlates

Muscle fatigue is a complex phenomenon that results in a reduction of the maximal voluntary force. Measuring muscle fatigue can be a challenging task that may involve the use of intramuscular electrodes (i.e., intramuscular electromyography (EMG)) or complex acquisition techniques. In this study, we propose an alternative non-invasive methodology for muscle fatigue detection relying on the analysis of two autonomic nervous system (ANS) correlates, i.e., the electrodermal activity (EDA) and heart rate variability (HRV) series. Based on standard surface EMG analysis, we divided 32 healthy subjects performing isometric biceps contraction into two groups: a fatigued group and a non-fatigued group. EDA signals were analyzed using the recently proposed cvxEDA model in order to derive phasic and tonic components and extract effective features to study ANS dynamics. Furthermore, HRV series were processed to derive several features defined in the time and frequency domains able to estimate the cardiovascular autonomic regulation. A statistical comparison between the fatigued and the non-fatigued groups was performed for each ANS feature, and two EDA features, i.e., the tonic variability and the phasic response rate, showed significant differences. Moreover, a pattern recognition procedure was applied to the combined EDA-HRV feature-set to automatically discern between fatigued and non-fatigued subjects. The proposed SVM classifier, following a recursive feature elimination stage, exhibited a maximal balanced accuracy of 83.33%. Our results demonstrate that muscle fatigue could be identified in a non-invasive fashion through effective EDA and HRV processing

筋収縮維持可能なmotor point追従刺激を用いた機能的電気刺激についての研究

　機能的電気刺激(以下FES)により連続的な筋収縮を行うと，FESによる筋収縮が弱化し運動誘発を起こしにくくなるという問題がある．これは臨床において，リハビリテーションを継続する時間やリハビリテーション中の安定的な運動補助に影響を与える可能性がある．　本研究は，FESによる筋収縮を持続的に誘発可能とすることを目的にしている．FESによる筋収縮の持続性向上のためNguyenらはSpatially distributed sequential stimulation (SDSS)を提案している． SDSSは下腿三頭筋において外側筋と内側筋とで刺激する筋肉を時間的に切り替える手法である．しかし，上腕二頭筋や上腕三頭筋，前脛骨筋といった筋肉は外側筋や内側筋が存在しないためSDSSを適用することはできず，SDSSは適用範囲に問題点かあると考えられる．　本研究は，FESによる筋収縮を持続的に誘発可能とするために多点表面電極を用いたMotor Pointの移動に応じた機能的電気刺激手法を提案する(以下Motor Point Tracking Stimulation: MPT)．Motor Pointとは一つの運動神経から複数の運等神経に分岐する分岐点で，Motor Pointの刺激によって筋収縮を生じやすくする位置のことである．Motor Pointに電気刺激することで筋収縮が小さいエネルギーで誘発できることが分かっている．その為Motor Pointの移動に依らずMotor Pointを刺激することで筋収縮を持続的に誘発できることが考えられる．　MPTの筋収縮の持続性を評価するためにMPTによる求心性収縮を継続した際の関節駆動域の時間変化について刺激位置を変化させない刺激及び異なった順序で刺激位置を変化させる刺激に対して比較した．結果としてMPTではほとんどの被験者において(5人7人中)比較対象と比べ関節駆動域の向上が確認できた．　これらの結果からMotor Pointに追従するように刺激位置を変化させることでFESによる筋収縮の持続性は改善することが確認できた．電気通信大学201

Effects of Action Observation and Action Observation Combined with Motor Imagery on Maximal Isometric Strength

Action observation (AO) alone or combined with motor imagery (AO + MI) has been shown to engage the motor system. While recent findings support the potential relevance of both techniques to enhance muscle function, this issue has received limited scientific scrutiny. In the present study, we implemented a counterbalanced conditions design where 21 participants performed 10 maximal isometric contractions (12-s duration) of elbow flexor muscles against a force platform. During the inter-trial rest periods, participants completed i) AO of the same task performed by an expert athlete, ii) AO + MI, i.e. observation of an expert athlete while concurrently imagining oneself performing the same task, and iii) watching passively a video documentary about basketball shooting (Control). During force trials, we recorded the total force and integrated electromyograms from the biceps brachii and anterior deltoideus. We also measured skin conductance from two finger electrodes as an index of sympathetic nervous system activity. Both AO and AO + MI outperformed the Control condition in terms of total force (2.79–3.68%, p < 0.001). For all conditions, we recorded a positive relationship between the biceps brachii activation and the total force developed during the task. However, only during AO was a positive relationship observed between the activation of the anterior deltoideus and the total force. We interpreted the results with reference to the statements of the psycho-neuromuscular theory of mental practice. Present findings extend current knowledge regarding the priming effects of AO and AO + MI on muscle function, and may contribute to the optimization of training programs in sports and rehabilitation

Recognizing AR-guided manual tasks through autonomic nervous system correlates: A preliminary study

Optical see-through head-mounted displays (HMD) enable optical superposition of computer-generated virtual data onto the user's natural view of the real environment. This makes them the most suitable candidate to guide manual tasks, as for augmented reality (AR) guided surgery. However, most commercial systems have a single focal plane at around 2-3 m inducing 'vergence-accommodation conflict' and 'focal rivalry' when used to guide manual tasks. These phenomena can often cause visual fatigue and low performance. In this preliminary study, ten subjects performed a precision manual task in two conditions: with or without using the AR HMD. We demonstrated a significant deterioration of the performance using the AR-guided manual task. Moreover, we investigated the autonomic nervous system response through the analysis of the heart rate variability (HRV) and electrodermal activity (EDA) signals. We developed a pattern recognition system that was able to automatically recognize the two experimental conditions using only EDA and HRV data with an accuracy of 75%. Our learning algorithm highlighted two different physiological patterns combining parasympathetic and sympathetic informati

Validation of Shoulder Strain Index

Musculoskeletal disorders (MSDs) of shoulder are one of the most frequent and major causes of morbidity and pain among full-time workers in the USA. In 2018, shoulder disorders were the most severe type of MSDs in terms of lost workdays. Recent epidemiological studies have identified several biomechanical, organizational, and psychological factors that increase the risk of shoulder MSDs. Though multiple biomechanical studies have evaluated physical causal factors of shoulder MSDs with a goal of risk mitigation, literature lacks a standardized risk assessment tool. The main objective of this study was to validate a previously developed shoulder strain index. The strain index is based on the concept of shoulder stabilizing concavity compression mechanism. A two-fold process was used to conduct the validation: (1) Forty different forceful arm exertions characterized by two shoulder planes, two shoulder angles, two force levels, and five orthogonal directions of force exertion were modelled using a full body biomechanical modeling software (AnyBody Modeling System™). The magnitude and direction of internal joint reaction forces acting at glenohumeral joint were used to estimate the shoulder strain index. (2) The surface electromyography data recorded from seven shoulder stabilizing muscles were analyzed to estimate the total physiological demand on the shoulder complex. Statistical analysis was performed to understand the effect of forceful arm exertions on the strain index and to quantify its relationship with the shoulder physiological demand. The strain index was significantly affected by work-related factors such as shoulder plane, shoulder angle, force exertion level, and direction. The correlation coefficients of 0.7 (

Modulation of electrical stimulation applied to human physiology and clinical diagnostic

The use, manipulation and application of electrical currents, as a controlled interference mechanism in the human body system, is currently a strong source of motivation to researchers in areas such as clinical, sports, neuroscience, amongst others. In electrical stimulation (ES), the current applied to tissue is traditionally controlled concerning stimulation amplitude, frequency and pulse-width. The main drawbacks of the transcutaneous ES are the rapid fatigue induction and the high discomfort induced by the non-selective activation of nervous fibers. There are, however, electrophysiological parameters whose response, like the response to different stimulation waveforms, polarity or a personalized charge control, is still unknown. The study of the following questions is of great importance: What is the physiological effect of the electric pulse parametrization concerning charge, waveform and polarity? Does the effect change with the clinical condition of the subjects? The parametrization influence on muscle recruitment can retard fatigue onset? Can parametrization enable fiber selectivity, optimizing the motor fibers recruitment rather than the nervous fibers, reducing contraction discomfort? Current hardware solutions lack flexibility at the level of stimulation control and physiological response assessment. To answer these questions, a miniaturized, portable and wireless controlled device with ES functions and full integration with a generic biosignals acquisition platform has been created. Hardware was also developed to provide complete freedom for controlling the applied current with respect to the waveform, polarity, frequency, amplitude, pulse-width and duration. The impact of the methodologies developed is successfully applied and evaluated in the contexts of fundamental electrophysiology, psycho-motor rehabilitation and neuromuscular disorders diagnosis. This PhD project was carried out in the Physics Department of Faculty of Sciences and Technology (FCT-UNL), in straight collaboration with PLUX - Wireless Biosignals S.A. company and co-funded by the Foundation for Science and Technology.Fundação para a Ciência e Tecnologia (FCT); PLUX - Wireless Biosignals, S.A.; FCT-UNL- CEFITE

Autonomic Regulation in Musculoskeletal Pain

713

Psychophysiological modelling and the measurement of fear conditioning

Quantification of fear conditioning is paramount to many clinical and translational studies on aversive learning. Various measures of fear conditioning co-exist, including different observables and different methods of pre-processing. Here, we first argue that low measurement error is a rational desideratum for any measurement technique. We then show that measurement error can be approximated in benchmark experiments by how closely intended fear memory relates to measured fear memory, a quantity that we term retrodictive validity. From this perspective, we discuss different approaches commonly used to quantify fear conditioning. One of these is psychophysiological modelling (PsPM). This builds on a measurement model that describes how a psychological variable, such as fear memory, influences a physiological measure. This model is statistically inverted to estimate the most likely value of the psychological variable, given the measured data. We review existing PsPMs for skin conductance, pupil size, heart period, respiration, and startle eye-blink. We illustrate the benefit of PsPMs in terms of retrodictive validity and translate this into sample size required to achieve a desired level of statistical power. This sample size can differ up to a factor of three between different observables, and between the best, and the current standard, data pre-processing methods

The Effects of Previous Concussions on the Physiological Complexity of Motor Output During a Continuous Isometric Visual-Motor Tracking Task

The majority of clinical impairments following a concussion resolve within 7-10 days. However, there is limited clarity as to long-term impact of this injury on neurocognitive function, motor control, and particularly integration of these domains. While repetitive head trauma is associated with numerous neurological disorders, the link is not well described. Visual-motor tracking tasks have been used to identify differences in visual processing, error detection, and fine motor control in aging and numerous pathologies. Examining the complexity of motor output from visual-motor tracking provides insight into multiple cognitive and motor function domains, and into fine motor control used for daily living, work, and sport. The purpose of this dissertation was, therefore, to: (1) use multiple regression to determine the extent to which concussion history and symptoms (loss of consciousness and amnesia) influence visual-motor task performance multiscale complexity, and (2) determine whether task performance complexity can distinguish, through logistic regression and prediction, between individuals with and without a history of concussion. In study 1, individuals with (n = 35) and without (n = 15) a history of concussion performed a visual-motor tracking task. Men and women exhibited linear decreases in task performance complexity, as well as midand high-frequency task performance components, with increasing numbers of concussions. However, men and women exhibited differing patterns, as did those with and without a history of concussion-related loss of consciousness. Finally, trial-to-trial complexity variability increased with increasing numbers of concussions. Findings indicate (1) a cumulative reduction in the way in which previously concussed individuals process and integrate visual information to guide behavior and (2) gender is an important consideration in concussion-related visual-motor outcomes. In Study 2, individuals with (n = 85) and without (n = 42) a history of concussion performed a visualmotor tracking task. Linear and nonlinear measures of task performance were used to build gender-specific logistic classification models using 10-fold cross-validation. When ensuring 80% sensitivity, the best models were 75-80% accurate in predicting a history of concussion. Such discrimination has clinical value in identifying individuals who merit further evaluation and observation over time for conditions related to repetitive head traumas