The effect of signal acquisition and processing choices on ApEn values: Towards a “gold standard” for distinguishing effort levels from isometric force records

Sex differences of signal complexity at resting-state functional magnetic resonance imaging and their associations with the estrogen-signaling pathway in the brain

Sex differences in the brain have been widely reported and may hold the key to elucidating sex differences in many medical conditions and drug response. However, the molecular correlates of these sex differences in structural and functional brain measures in the human brain remain unclear. Herein, we used sample entropy (SampEn) to quantify the signal complexity of resting-state functional magnetic resonance imaging (rsfMRI) in a large neuroimaging cohort (N = 1,642). The frontoparietal control network and the cingulo-opercular network had high signal complexity while the cerebellar and sensory motor networks had low signal complexity in both men and women. Compared with those in male brains, we found greater signal complexity in all functional brain networks in female brains with the default mode network exhibiting the largest sex difference. Using the gene expression data in brain tissues, we identified genes that were significantly associated with sex differences in brain signal complexity. The significant genes were enriched in the gene sets that were differentially expressed between the brain cortex and other tissues, the estrogen-signaling pathway, and the biological function of neural plasticity. In particular, the G-protein-coupled estrogen receptor 1 gene in the estrogen-signaling pathway was expressed more in brain regions with greater sex differences in SampEn. In conclusion, greater complexity in female brains may reflect the interactions between sex hormone fluctuations and neuromodulation of estrogen in women.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-023-09954-y.

Sex differences in knee extensor torque control

There is currently equivocal evidence regarding sex-related differences in measures of muscle force and torque control. To that end, we investigated sex differences in knee extensor muscle torque control, using both magnitude- and complexity-based measures, across contraction intensities typical of activities of daily living. 50 participants (25 male, median age [and interquartile range] 23.0 [20.0-33.0]; 25 female, median age [and interquartile range] 21.0 [20.0-40.5]) performed a series of intermittent isometric knee extensor contractions at 10, 20 and 40% maximal voluntary contraction (MVC). Torque was measured in N·m and torque control was quantified according to the magnitude (standard deviation [SD], coefficient of variation [CV]) and complexity (approximate entropy [ApEn], detrended fluctuation analysis [DFA] α) of torque fluctuations. Males exhibited a significantly greater absolute magnitude (i.e., SD) of knee extensor torque fluctuations during contractions at 10% (P = 0.011), 20% (P = 0.002) and 40% MVC (P = 0.003), though no sex differences were evident when fluctuations were normalised to mean torque output (i.e., CV). Males exhibited significantly lower ApEn during contractions at 10% (P = 0.002) and 20% MVC (P = 0.024) and significantly greater DFA α during contractions at 10% (P = 0.003) and 20% MVC (P = 0.001). These data suggest sex differences in muscle torque control strategies and highlight the need to consider both the magnitude and complexity of torque fluctuations when examining sex differences in muscle force control.

Prolonged static stretching increases the magnitude and decreases the complexity of knee extensor muscle force fluctuations

Static stretching decreases maximal muscle force generation in a dose-response manner, but its effects on the generation of task-relevant and precise levels of submaximal force, i.e. force control, is unclear. We investigated the effect of acute static stretching on knee extensor force control, quantified according to both the magnitude and complexity of force fluctuations. Twelve healthy participants performed a series of isometric knee extensor maximal voluntary contractions (MVCs) and targeted intermittent submaximal contractions at 25, 50 and 75% MVC (3 x 6 seconds contraction separated by 4 seconds rest, with 60 seconds rest between each intensity) prior to, and immediately after, one of four continuous static stretch conditions: 1) no stretch; 2) 30-second stretch; 3) 60-second stretch; 4) 120-second stretch. The magnitude of force fluctuations was quantified using the standard deviation (SD) and coefficient of variation (CV), while the complexity of fluctuations was quantified using approximate entropy (ApEn) and detrended fluctuation analysis (DFA) α. These measures were calculated using the steadiest 5 seconds of the targeted submaximal contractions at each intensity (i.e., that with the lowest SD). Significant decreases in MVC were evident following the 30, 60 and 120-second stretch conditions (all P < 0.001), with a significant correlation observed between stretch duration and the magnitude of decrease in MVC (r = -0.58, P < 0.001). The 120-second stretch resulted in significant increases in SD at 50% MVC (P = 0.007) and CV at 50% (P = 0.009) and 75% MVC (P = 0.005), and a significant decrease in ApEn at 75% MVC (P < 0.001). These results indicate that the negative effects of prolonged static stretching extend beyond maximal force generation tasks to those involving generation of precise levels of force during moderate- to high-intensity submaximal contractions.

Torque Regulation Is Influenced by the Nature of the Isometric Contraction

The present study aimed to investigate the effects of a continuous visual feedback and the isometric contraction nature on the complexity and variability of force. Thirteen healthy and young male adults performed three MVCs followed by three submaximal isometric force tasks at a target force of 40% of their MVC for 30 s, as follows: (i) push isometric task with visual feedback (P_visual); (ii) hold isometric task with visual feedback (H_visual); (iii) hold isometric task without visual feedback (H_non-visual). Force complexity was evaluated through sample entropy (SampEn) of the force output. Force variability was analyzed through the coefficient of variation (CV). Results showed that differences were task-related, with P_visual showing higher complexity (i.e., higher SampEn) and decreased variability (i.e., lower CV) when compared with the remaining tasks. Additionally, no significant differences were found between the two hold isometric force tasks (i.e., no influence of visual feedback). Our results are promising as we showed these two isometric tasks to induce different motor control strategies. Furthermore, we demonstrated that visual feedback's influence is also dependent on the type of isometric task. These findings should motivate researchers and physiologists to shift training paradigms and incorporate different force control evaluation tasks.

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.

The Neuromuscular Fatigue-Induced Loss of Muscle Force Control

Neuromuscular fatigue is characterised not only by a reduction in the capacity to generate maximal muscle force, but also in the ability to control submaximal muscle forces, i.e., to generate task-relevant and precise levels of force. This decreased ability to control force is quantified according to a greater magnitude and lower complexity (temporal structure) of force fluctuations, which are indicative of decreased force steadiness and adaptability, respectively. The "loss of force control" is affected by the type of muscle contraction used in the fatiguing exercise, potentially differing between typical laboratory tests of fatigue (e.g., isometric contractions) and the contractions typical of everyday and sporting movements (e.g., dynamic concentric and eccentric contractions), and can be attenuated through the use of ergogenic aids. The loss of force control appears to relate to a fatigue-induced increase in common synaptic input to muscle, though the extent to which various mechanisms (afferent feedback, neuromodulatory pathways, cortical/reticulospinal pathways) contribute to this remains to be determined. Importantly, this fatigue-induced loss of force control could have important implications for task performance, as force control is correlated with performance in a range of tasks that are associated with activities of daily living, occupational duties, and sporting performance.

Educational Psychology Analysis Method for Extracting Students' Facial Information Based on Image Big Data

At present, most of the research on academic emotions focuses on the concept, current situation, and relevance. There are not many researches on the application of artificial intelligence-based neural network facial expression recognition technology in practical teaching. With reference to image-based big data, this research integrates the application of artificial intelligence facial expression recognition technology with the research on educational theory and applies information technology to the actual teaching process, in order to promote the optimization of the teaching process and improve the learning effect. Method. A Hadoop cluster consisting of 3 nodes is built on the Linux system, and the environment required for Opencv execution is compiled for each node, which provides support for subsequent parallel optimization, feature extraction, feature fusion, and recognition of student facial images. The image data type and input and output format based on MapReduce framework are designed, and the image data is optimized by means of serialized files. The color features, texture features, and Sift features of students' facial images and common distractors were analyzed. A parallel extraction framework of student facial image features is designed, and based on this, the student facial image feature extraction under Hadoop platform is implemented. This paper proposes a dynamic sequential facial expression recognition method that combines shallow and deep features with an attention mechanism. The relative position of facial landmarks and local area texture features based on FACS represent shallow-level features. At the same time, the structure of ALexNet is improved to extract the deep features of sequence images to express high-level semantic features. The effectiveness of the facial expression recognition system is improved by introducing three attention mechanisms: self-attention, weight-attention, and convolutional attention. Results/Discussion. Through the analysis of the teaching effect, we found that when teachers can obtain the correct student's academic mood, they can intervene on the students' positive academic mood. The purpose of the intervention is to improve the positive academic emotions of students. After the students receive the intervention, their academic emotions are also improved and are positively correlated with their academic performance. Through the analysis of teaching effect, the research can achieve the predetermined goal. From the specific teaching effect of this study, it is concluded that in classroom teaching, teachers should devote energy to intervene in students' positive academic emotions, in order to improve students' positive academic emotions, which will improve students' academic performance and teaching.

Variability and Complexity of Knee Neuromuscular Control during an Isometric Task in Uninjured Physically Active Adults: A Secondary Analysis Exploring Right/Left and Dominant/Nondominant Asymmetry

Work is needed to better understand the control of knee movement and knee health. Specifically, work is needed to further understand knee muscle force control variability and complexity and how it is organized on both sides of the body. The purpose of this study was to explore side-to-side comparisons of magnitude- and complexity-based measures of knee muscle force control to support future interpretations of complexity-based analyses and clinical reasoning in knee injury control. Participants (male/female n = 11/5) performed constant-force isometric efforts at 50% maximal effort. Force variability was quantified during the constant-force efforts using a coefficient of variation (CV%) and force complexity using approximate entropy (ApEn) and detrended fluctuation analysis (DFA) α. Outcomes were right/left and dominant/nondominant group-level and individual-level comparisons. A limb-symmetry index was calculated for each variable and clinically significant absolute asymmetry was defined (>15%). The only significant side-to-side difference was for right/left DFA α (p = 0.00; d = 1.12). Maximum absolute asymmetries were (right/left, dominant/nondominant): CV 18.2%, 18.0%; ApEn 34.5%, 32.3%; DFA α 4.9%, 5.0%. Different side-to-side comparisons yield different findings. Consideration for how side-to-side comparisons are performed (right/left, dominant/nondominant) is required. Because a significant difference existed for complexity but not variability, this indicates that both complexity-based and magnitude-based measures should be used when studying knee muscle force control.

Different unilateral force control strategies between athletes and non-athletes

This study investigated continuous visuomotor tracking capabilities between athletes and non-athlete controls using isometric force control paradigm. Nine female athletes and nine female age-matched controls performed unilateral hand-grip force control tasks with their dominant and non-dominant hands at 10% and 40% of maximal voluntary contraction (MVC), respectively. Three conventional outcome measures on force control capabilities included mean force, force accuracy, and force variability, and we additionally calculated two nonlinear dynamics variables including force regularity using sample entropy and force stability using maximal Lyapunov exponent. Finally, we performed correlation analyses to determine the relationship between nonlinear dynamics variables and conventional measures for each group. The findings indicated that force control capabilities as indicated by three conventional measures were not significantly different between athlete and non-athlete control groups. However, the athletes revealed less force regularity and greater force stability across hand conditions and targeted force levels than those in non-athlete controls. The correlation analyses found that increased force regularity (i.e., less sample entropy values) at 10% of MVC and decreased force regularity (i.e., greater sample entropy values) at 40% of MVC were significantly related to improved force accuracy and variability for the athlete group, and these patterns were not observed in the non-athlete control group. These findings suggested that the athletes may use different adaptive force control strategies as indicated by nonlinear dynamics tools.

Shoulder movement complexity in the aging shoulder: A cross-sectional analysis and reliability assessment

Healthy individuals perform a task such as hitting the head of a nail with an infinite coordination spectrum. This motor redundancy is healthy and allows for learning through exploration and uniform load distribution across muscles. Assessing movement complexity within repetitive movement trajectories may provide insight into the available motor redundancy during aging. We quantified complexity of repetitive arm elevation trajectories in the aging shoulder and assessed test-retest reliability of this quantification. In a cross-sectional study using 3D-electromagnetic tracking, 120 asymptomatic subjects, aged between 18 and 70 years performed repetitive abduction and forward/anteflexion movements. Movement complexity was calculated using the Approximate Entropy (ApEn-value): [0,2], where lower values indicate reduced complexity. Thirty-three participants performed the protocol twice, to determine reliability (intraclass correlation coefficient [ICC]). The association between age and ApEn was corrected for task characteristics (e.g., sample length) with multiple linear regression analysis. Reproducibility was determined using scatter plots and ICC's. Higher age was associated with lower ApEn-values during abduction (unstandardized estimate: -0.003/year; 95% confidence interval: [-0.005; -0.002]; p < .001). ICC's revealed poor to good reliability depending on differences in sample length between repeated measurements. The results may imply more stereotype movement during abduction in the ageing shoulder, making this movement prone to the development of shoulder complaints. Future studies may investigate the pathophysiology and clinical course of shoulder complaints by assessment of movement complexity. To this end, the ApEn-value calculated over repetitive movement trajectories may be used, although biasing factors such as sample length should be taken into account.

Physiological complexity: influence of ageing, disease and neuromuscular fatigue on muscle force and torque fluctuations

NEW FINDINGS

What is the topic of this review? Physiological complexity in muscle force and torque fluctuations, specifically the quantification of complexity, how neuromuscular complexityis altered by perturbations and the potential mechanism underlying changes in neuromuscular complexity. What advances does it highlight? The necessity to calculate both magnitude- and complexity-based measures for the thorough evaluation of force/torque fluctuations. Also the need for further research on neuromuscular complexity, particularly how it relates to the performance of functional activities (e.g. manual dexterity, balance, locomotion).

ABSTRACT

Physiological time series produce inherently complex fluctuations. In the last 30 years, methods have been developed to characterise these fluctuations, and have revealed that they contain information about the function of the system producing them. Two broad classes of metrics are used: (1) those which quantify the regularity of the signal (e.g. entropy metrics); and (2) those which quantify the fractal properties of the signal (e.g. detrended fluctuation analysis). Using these techniques, it has been demonstrated that ageing results in a loss of complexity in the time series of a multitude of signals, including heart rate, respiration, gait and, crucially, muscle force or torque output. This suggests that as the body ages, physiological systems become less adaptable (i.e. the systems' ability to respond rapidly to a changing external environment is diminished). More recently, it has been shown that neuromuscular fatigue causes a substantial loss of muscle torque complexity, a process that can be observed in a few minutes, rather than the decades it requires for the same system to degrade with ageing. The loss of torque complexity with neuromuscular fatigue appears to occur exclusively above the critical torque (at least for tasks lasting up to 30 min). The loss of torque complexity can be exacerbated with previous exercise of the same limb, and reduced by the administration of caffeine, suggesting both peripheral and central mechanisms contribute to this loss. The mechanisms underpinning the loss of complexity are not known but may be related to altered motor unit behaviour as the muscle fatigues.

Reduced force entropy in subacromial pain syndrome: A cross-sectional analysis

BACKGROUND

Generating a force at the hand requires moments about multiple joints by a theoretically infinite number of arm and shoulder muscle force combinations. This allows for learning and adaptation and can possibly be captured using the complexity (entropy) of an isometrically generated force curve. Patients with Subacromial Pain Syndrome have difficulty to explore alternative, pain-avoiding, motor strategies and we questioned whether loss of motor complexity may contribute to this. We assessed whether patients with Subacromial Pain Syndrome have reduced entropy of an isometrically generated abduction and adduction force curve.

METHODS

Forty patients and thirty controls generated submaximal isometric ab- and adduction force at the wrist. The force curve was characterized by the magnitude of force variability [standard deviation and coefficient of variation], and the entropy (complexity) of force variability [approximate entropy].

FINDINGS

Patients showed reduced entropy both during the abduction (-0.16, confidence interval: [-0.33; -0.00], p: 0.048) and adduction task (-0.20, confidence interval: [-0.37; -0.03], p: 0.024) and reduced force variability during abduction (standard deviation: -0.006, confidence interval: [-0.011; -0.001], p: 0.013 and coefficient of variation: -0.51, confidence interval: [-0.93; -0. 10], p: 0.016).

INTERPRETATIONS

Isometric force curves of patients with Subacromial Pain Syndrome show reduced complexity compared to asymptomatic controls, which may indicate more narrow and stereotype use of motor options. In future studies, it should be investigated whether the finding of reduced force (motor) entropy indicates functional decline, contributing to decreased ability to acquire and optimize motor strategies in Subacromial Pain Syndrome.

LEVEL OF EVIDENCE

Level II prognostic study.

Neural Signatures of Handgrip Fatigue in Type 1 Diabetic Men and Women

Type 1 diabetes (T1D) is associated with reduced muscular strength and greater muscle fatigability. Along with changes in muscular mechanisms, T1D is also linked to structural changes in the brain. How the neurophysiological mechanisms underlying muscle fatigue is altered with T1D and sex related differences of these mechanisms are still not well investigated. The aim of this study was to determine the impact of T1D on the neural correlates of handgrip fatigue and examine sex and T1D related differences in neuromuscular performance parameters, neural activation and functional connectivity patterns between the motor regions of the brain. Forty-two adults, balanced by condition (healthy vs T1D) and sex (male vs female), and performed submaximal isometric handgrip contractions until voluntary exhaustion. Initial strength, endurance time, strength loss, force variability, and complexity measures were collected. Additionally, hemodynamic responses from motor-function related cortical regions, using functional near-infrared spectroscopy (fNIRS), were obtained. Overall, females exhibited lower initial strength (p < 0.0001), and greater strength loss (p = 0.023) than males. While initial strength was significantly lower in the T1D group (p = 0.012) compared to the healthy group, endurance times and strength loss were comparable between the two groups. Force complexity, measured as approximate entropy, was found to be lower throughout the experiment for the T1D group (p = 0.0378), indicating lower online motor adaptability. Although, T1D and healthy groups fatigued similarly, only the T1D group exhibited increased neural activation in the left (p = 0.095) and right (p = 0.072) supplementary motor areas (SMA) over time. A sex × condition × fatigue interaction effect (p = 0.044) showed that while increased activation was observed in both T1D females and healthy males from the Early to Middle phase, this was not observed in healthy females or T1D males. These findings demonstrate that T1D adults had lower adaptability to fatigue which they compensated for by increasing neural effort. This study highlights the importance of examining both neural and motor performance signatures when investigating the impact of chronic conditions on neuromuscular fatigue. Additionally, the findings have implications for developing intervention strategies for training, rehabilitation, and ergonomics considerations for individuals with chronic conditions.

Effects of online-bandwidth visual feedback on unilateral force control capabilities

Purpose

The purpose of this study was to examine how different threshold ranges of online-bandwidth visual feedback influence unilateral force control capabilities in healthy young women.

Methods

Twenty-five right-handed young women (mean±standard deviation age = 23.6±1.5 years) participated in this study. Participants unilaterally executed hand-grip force control tasks with their dominant and non-dominant hands, respectively. Each participant completed four experimental blocks in a different order of block presentation for each hand condition: (a) 10% of maximum voluntary contraction (MVC) with ±5% bandwidth threshold range (BTR), (b) 10% of MVC with ±10% BTR, (c) 40% of MVC with ±5% BTR, and (d) 40% of MVC with ±10% BTR. Outcome measures on force control capabilities included: (a) force accuracy, (b) force variability, (c) force regularity, and (d) the number of times and duration out of BTR.

Results

The non-dominant hand showed significant improvements in force control capabilities, as indicated by higher force accuracy, less force variability, and decreased force regularity from ±10% BTR to ±5% BTR during higher targeted force level task. For both hands, the number of times and duration out of BTR increased from ±10% BTR to ±5% BTR.

Conclusions

The current findings suggested that the narrow threshold range of online-bandwidth visual feedback effectively revealed transient improvements in unilateral isometric force control capabilities during higher targeted force level tasks.

Complexity of knee extensor torque in patients with frailty syndrome: a cross-sectional study

BACKGROUND

Frailty syndrome is characterized by a marked reduction in physiological reserves and a clinical state of vulnerability to stress. Torque complexity analysis could reveal changes in the musculoskeletal systems that are the result of having the syndrome.

OBJECTIVE

The aim of this study was to evaluate the complexity of submaximal isometric knee extensor torque in frail, pre-frail, and non-frail older adults. A secondary aim was to analyze the torque complexity behavior in different force levels in each group.

METHODS

A cross-sectional study was conducted. Forty-two older adults were divided into three groups: non-frail (n=15), pre-frail (n=15), and frail (n=12). The data collected included body composition, five times sit-to-stand test, walking speed, and isometric knee extensor torque at 15, 30, and 40% of maximal voluntary contraction. The knee extensor torque variability was evaluated by coefficient of variation, and the torque complexity was evaluated by approximate entropy and sample entropy.

RESULTS

The frail group presented a reduction in body mass and peak torque value compared to the non-frail group. Also, the frail group showed worse physical performance (on the five times sit-to-stand test and walking speed) compared to the pre-frail and non-frail groups. In addition, the frail older adults showed reduced torque complexity compared to the non-frail group. Finally, the association between torque complexity and force levels remained similar in all groups.

CONCLUSION

Torque complexity is reduced in the presence of frailty syndrome.

Effects of Nonstationarity on Muscle Force Signals Regularity During a Fatiguing Motor Task

Physiological signals present fluctuations that can be assessed from their temporal structure, also termed complexity. The complexity of a physiological signal is usually quantified using entropy estimators, such as Sample Entropy. Recent studies have shown a loss of force signal complexity with the development of neuromuscular fatigue. However, these studies did not consider the stationarity of the force signals which is an important prerequisite of Sample Entropy measurements. Here, we investigated the effect of the potential nonstationarity of force signals on the kinetics of neuromuscular fatigue-induced change in force signal's complexity. Eleven men performed submaximal intermittent isometric contractions of knee extensors until exhaustion. Neuromuscular fatigue was assessed from changes in voluntary and electrically evoked contractions. Sample Entropy values were computed from submaximal force signals throughout the fatiguing task. The Dickey-Fuller test was used to statistically investigate the stationarity of force signals and the Empirical Mode Decomposition was applied to detrend these signals. Maximal voluntary force, central voluntary activation and muscle twitch decreased throughout the task (all ), indicating the development of global, central and peripheral fatigue, respectively. We found an increase in Sample Entropy with fatigue ( p = 0.024 ) when not considering the nonstationarity of force signals (i.e., 43% of nonstationary signals). After applying the Empirical Mode Decomposition, we found a decrease in Sample Entropy with fatigue ( p = 0.002 ). These findings confirm the presence of nonstationarity in force signals during submaximal isometric contractions which influences the kinetics of Sample Entropy with neuromuscular fatigue.

Relationship between muscle metabolic rate and muscle torque complexity during fatiguing intermittent isometric contractions in humans

To test the hypothesis that a system's metabolic rate and the complexity of fluctuations in the output of that system are related, thirteen healthy participants performed intermittent isometric knee extensor contractions at intensities where a rise in metabolic rate would (40% maximal voluntary contraction, MVC) and would not (20% MVC) be expected. The contractions had a 60% duty factor (6 sec contraction, 4 sec rest) and were performed until task failure or for 30 min, whichever occurred sooner. Torque and surface EMG signals were sampled continuously. Complexity and fractal scaling of torque were quantified using approximate entropy (ApEn) and the detrended fluctuation analysis (DFA) α scaling exponent. Muscle metabolic rate was determined using near-infrared spectroscopy. At 40% MVC, task failure occurred after (mean ± SD) 11.5 ± 5.2 min, whereas all participants completed 30 min of contractions at 20% MVC. Muscle metabolic rate increased significantly after 2 min at 40% MVC (2.70 ± 1.48 to 4.04 ± 1.23 %·s-1 , P < 0.001), but not at 20% MVC. Similarly, complexity decreased significantly at 40% MVC (ApEn, 0.53 ± 0.19 to 0.15 ± 0.09; DFA α, 1.37 ± 0.08 to 1.60 ± 0.09; both P < 0.001), but not at 20% MVC. The rates of change of torque complexity and muscle metabolic rate at 40% MVC were significantly correlated (ApEn, ρ = -0.63, P = 0.022; DFA, ρ = 0.58, P = 0.037). This study demonstrated that an inverse relationship exists between muscle torque complexity and metabolic rate during high-intensity contractions.

Exercise training in older adults, what effects on muscle force control? A systematic review of randomized clinical trials

AIM

To determine the magnitude of the effects of different exercise training (ET) modalities on variables of muscle force control in older adults.

METHODS

Relevant articles were searched in PubMed, Web of Science, Science Direct and Scopus, using the keywords: Aged AND "Exercise Movement Techniques" AND ("Complexity of torque" OR "Complexity of force" OR "Variability of torque" OR "Variability of force" OR "Force Steadiness" OR "Force fluctuations"). To be included in the full analysis, the studies had to be randomized controlled trials in which older adults were submitted to ET programs and muscle force control assessment.

RESULTS

The searches resulted in 702 articles from which 6 met all the inclusion criteria. The trials involved 171 healthy and functionally limited older adults (71.64 ± 1.53 years). Studies included resistance, steadiness and functional training programs. Training sessions were 2-3 time per week, lasted 6-16 months with intensities determined as percentage of the one repetition maximum loads. There is a heterogeneity regarding experimental set-up and data analysis parameters between studies. The findings show an improved muscle force control in older adults after ET. Such response is better evidenced by the assessment of the coefficient of variation (CV) of the force signals. There is moderate evidence that resistance training programs are effective to decrease CV of knee extensor force signals at lower force targets.

CONCLUSIONS

The findings from this review suggest that ET programs are effective to improve muscle force control in older adults.

Effects of ipsilateral and contralateral fatigue and muscle blood flow occlusion on the complexity of knee-extensor torque output in humans

NEW FINDINGS

What is the central question of this study? We addressed the question "what role do central and peripheral fatigue mechanisms play in the fatigue-induced loss of isometric torque complexity?" What is the main finding and its importance? When the contralateral limb is fatigued, the complexity of isometric torque output is unaffected even if the blood flow to the contralateral limb is occluded, which suggests that neither central fatigue nor afferent feedback from ischaemic muscle influences the complexity of torque output in an otherwise fresh muscle.

ABSTRACT

Neuromuscular fatigue reduces the temporal structure, or complexity, of torque output during muscular contractions. To determine whether the fatigue-induced loss of torque complexity could be accounted for by central or peripheral factors, nine healthy participants performed four experimental trials involving intermittent isometric contractions of the knee extensors at 50% of the maximal voluntary contraction torque. These trials involved: (i) two bouts of contractions to failure using the right leg separated by 3 min recovery (IPS); (ii) the same protocol but with cuff occlusion during the 3 min recovery (IPS-OCC); (iii) contractions of the left leg to failure, followed 1 min later by contractions of the right leg to failure (CONT); and (iv) the same protocol but with cuff occlusion applied to the left leg throughout both the recovery period and right leg contractions (CONT-OCC). Supramaximal electrical stimulation during maximal voluntary contractions was used to determine the degree of central and peripheral fatigue, whilst complexity was determined using approximate entropy (ApEn) and detrended fluctuation analysis α exponent (DFA α). Neuromuscular fatigue was consistently associated with a loss of torque complexity in all conditions [e.g. IPS bout 1, ApEn from (mean ± SD) 0.46 ± 0.14 to 0.12 ± 0.06 (P < 0.001)]. In IPS-OCC, occlusion abolished the recovery from fatigue, and torque complexity remained at the values observed at task failure in the preceding bout (IPS-OCC bout 2, first minute 0.14 ± 0.03, P < 0.001). Prior contralateral contractions, with or without blood flow occlusion, had no effect on torque complexity.

Joint Moment-Angle Properties of the Hip Extensors in Subjects With and Without Patellofemoral Pain

Strength deficits of hip extension in individuals with patellofemoral syndrome are commonly reported in literature. No literature to date has examined these deficits with variable positions of the knee and hip; altering knee angle alters the length and therefore potentially the force produced by the biarticular muscles. Beyond strength, neuromuscular control can also be assessed through the analysis of isometric joint moment steadiness. Subjects consisted of a group of individuals with patellofemoral syndrome (n = 9), and a group of age- and size-matched controls with no symptoms (n = 9). Maximum isometric joint moments for hip extension were measured at 4 points within the joint's range of motion, at 2 different knee positions (0° and 90°) for each group. The joint moment signals were analyzed by computing signal Coefficient of Variation (CV). The results indicate that no significant differences were found between the groups of subjects for the hip extension moments when the knee was extended. However, there was a significant difference between the groups for the joint moments of hip extension with the knee flexed at all 4 hip positions. Results also showed hip extension CV values to be significantly higher in the patellofemoral group compared with the control group, indicating greater signal noise and therefore poorer neuromuscular control of the hip extensor musculature. This study demonstrated that individuals with patellofemoral syndrome have reduced hip extension strength and reduced neuromuscular control with the knee flexed compared with a control group. These results have implications for the etiology of patellofemoral syndrome and its rehabilitation.

Effect of parameter selection on entropy calculation for long walking trials

It is sometimes difficult to obtain uninterrupted data sets that are long enough to perform nonlinear analysis, especially in pathological populations. It is currently unclear as to how many data points are needed for reliable entropy analysis. The aims of this study were to determine the effect of changing parameter values of m, r, and N on entropy calculations for long gait data sets using two different modes of walking (i.e., overground versus treadmill). Fourteen young adults walked overground and on a treadmill at their preferred walking speed for one-hour while step time was collected via heel switches. Approximate (ApEn) and sample entropy (SampEn) were calculated using multiple parameter combinations of m, N, and r. Further, r was tested under two cases r*standard deviation and r constant. ApEn differed depending on the combination of r, m, and N. ApEn demonstrated relative consistency except when m=2 and the smallest r values used (rSD=0.015*SD, 0.20*SD; rConstant=0 and 0.003). For SampEn, as r increased, SampEn decreased. When r was constant, SampEn demonstrated excellent relative consistency for all combinations of r, m, and N. When r constant was used, overground walking was more regular than treadmill. However, treadmill walking was found to be more regular when using rSD for both ApEn and SampEn. For greatest relative consistency of step time data, it was best to use a constant r value and SampEn. When using entropy, several r values must be examined and reported to ensure that results are not an artifact of parameter choice.

Fatigue reduces the complexity of knee extensor torque fluctuations during maximal and submaximal intermittent isometric contractions in man

Neuromuscular fatigue increases the amplitude of fluctuations in torque output during isometric contractions, but the effect of fatigue on the temporal structure, or complexity, of these fluctuations is not known. We hypothesised that fatigue would result in a loss of temporal complexity and a change in fractal scaling of the torque signal during isometric knee extensor exercise. Eleven healthy participants performed a maximal test (5 min of intermittent maximal voluntary contractions, MVCs), and a submaximal test (contractions at a target of 40% MVC performed until task failure), each with a 60% duty factor (6 s contraction, 4 s rest). Torque and surface EMG signals were sampled continuously. Complexity and fractal scaling of torque were quantified by calculating approximate entropy (ApEn), sample entropy (SampEn) and the detrended fluctuation analysis (DFA) scaling exponent α. Fresh submaximal contractions were more complex than maximal contractions (mean ± SEM, submaximal vs. maximal: ApEn 0.65 ± 0.09 vs. 0.15 ± 0.02; SampEn 0.62 ± 0.09 vs. 0.14 ± 0.02; DFA α 1.35 ± 0.04 vs. 1.55 ± 0.03; all P < 0.005). Fatigue reduced the complexity of submaximal contractions (ApEn to 0.24 ± 0.05; SampEn to 0.22 ± 0.04; DFA α to 1.55 ± 0.03; all P < 0.005) and maximal contractions (ApEn to 0.10 ± 0.02; SampEn to 0.10 ± 0.02; DFA α to 1.63 ± 0.02; all P < 0.01). This loss of complexity and shift towards Brownian-like noise suggests that as well as reducing the capacity to produce torque, fatigue reduces the neuromuscular system's adaptability to external perturbations.

Paretic hand unimanual force control: Improved submaximal force production and regularity

The purpose was to investigate force control capabilities in paretic hands during unimanual movements after coupled bimanual movement training and neuromuscular stimulation on impaired muscles. Nineteen chronic stroke participants completed 90 min of rehabilitation per week for six consecutive weeks. Before and after training, volunteers performed unimanual submaximal force control tasks at 5% and 50% of maximum voluntary contraction with their paretic and non-paretic hands. Force control measures included submaximal force production, force variability, accuracy, and regularity. Two major findings on paretic hands after training revealed: (a) greater submaximal force production across force levels and (b) less regular force outputs. Paretic hand control improved after coupled bimanual movement training as evidenced by submaximal force production and force regularity.