Legendre Polynomial Fitting-Based Permutation Entropy Offers New Insights into the Influence of Fatigue on Surface Electromyography (sEMG) Signal Complexity.

In a recently published work, we introduced local Legendre polynomial fitting-based permutation entropy (LPPE) as a new complexity measure for quantifying disorder or randomness in time series. LPPE benefits from the ordinal pattern (OP) concept and incorporates a natural, aliasing-free multiscaling effect by design. The current work extends our previous study by investigating LPPE's capability to assess fatigue levels using both synthetic and real surface electromyography (sEMG) signals.

Comparison of the Accuracy of Ground Reaction Force Component Estimation between Supervised Machine Learning and Deep Learning Methods Using Pressure Insoles.

The three Ground Reaction Force (GRF) components can be estimated using pressure insole sensors. In this paper, we compare the accuracy of estimating GRF components for both feet using six methods: three Deep Learning (DL) methods (Artificial Neural Network, Long Short-Term Memory, and Convolutional Neural Network) and three Supervised Machine Learning (SML) methods (Least Squares, Support Vector Regression, and Random Forest (RF)). Data were collected from nine subjects across six activities: normal and slow walking, static with and without carrying a load, and two Manual Material Handling activities.

Impact of PCA Pre-Normalization Methods on Ground Reaction Force Estimation Accuracy.

Ground reaction force (GRF) components can be estimated using insole pressure sensors. Principal component analysis in conjunction with machine learning (PCA-ML) methods are widely used for this task. PCA reduces dimensionality and requires pre-normalization.

On the Genuine Relevance of the Data-Driven Signal Decomposition-Based Multiscale Permutation Entropy.

Ordinal pattern-based approaches have great potential to capture intrinsic structures of dynamical systems, and therefore, they continue to be developed in various research fields. Among these, the permutation entropy (PE), defined as the Shannon entropy of ordinal probabilities, is an attractive time series complexity measure. Several multiscale variants (MPE) have been proposed in order to bring out hidden structures at different time scales.

'Le regard des autres': the experience of walking in social environments as a person with Parkinson's disease.

Objective: To examine the experience of people with Parkinson's disease when walking in different social situations, and improve understanding of how this affects participation in meaningful activity.

Methods: A convenience sample of fourteen people with Parkinson's disease and a history of gait dysfunction was recruited. In-depth interviews and direct observations were conducted in the participants' home environments.

The Refined Composite Downsampling Permutation Entropy Is a Relevant Tool in the Muscle Fatigue Study Using sEMG Signals.

Surface electromyography (sEMG) is a valuable technique that helps provide functional and structural information about the electric activity of muscles. As sEMG measures output of complex living systems characterized by multiscale and nonlinear behaviors, Multiscale Permutation Entropy (MPE) is a suitable tool for capturing useful information from the ordinal patterns of sEMG time series. In a previous work, a theoretical comparison in terms of bias and variance of two MPE variants-namely, the refined composite MPE (rcMPE) and the refined composite downsampling (rcDPE), was addressed.

The Impact of Linear Filter Preprocessing in the Interpretation of Permutation Entropy.

Permutation Entropy (PE) is a powerful tool for measuring the amount of information contained within a time series. However, this technique is rarely applied directly on raw signals. Instead, a preprocessing step, such as linear filtering, is applied in order to remove noise or to isolate specific frequency bands.

Improvement of Statistical Performance of Ordinal Multiscale Entropy Techniques Using Refined Composite Downsampling Permutation Entropy.

Multiscale Permutation Entropy (MPE) analysis is a powerful ordinal tool in the measurement of information content of time series. MPE refinements, such as Composite MPE (cMPE) and Refined Composite MPE (rcMPE), greatly increase the precision of the entropy estimation by modifying the original method. Nonetheless, these techniques have only been proposed as algorithms, and are yet to be described from the theoretical perspective.

A new detection method for EMG activity monitoring.

This paper introduces a new approach for electromyography (EMG) activity monitoring based on an improved version of the adaptive linear energy detector (ALED), a widely used technique in voice activity detection. More precisely, we propose a modified ALED technique (named M-ALED) to improve the method's robustness with respect to noise. To achieve this objective, M-ALED relies on the Teager-Kaiser operator for signal pre-conditioning to increase the SNR and uses the order statistics to gain robustness against the signal's impulsiveness.

On the Statistical Properties of Multiscale Permutation Entropy: Characterization of the Estimator's Variance.

Permutation Entropy (PE) and Multiscale Permutation Entropy (MPE) have been extensively used in the analysis of time series searching for regularities. Although PE has been explored and characterized, there is still a lack of theoretical background regarding MPE. Therefore, we expand the available MPE theory by developing an explicit expression for the estimator's variance as a function of time scale and ordinal pattern distribution.

"The whole perimeter is difficult": Parkinson's disease and the conscious experience of walking in everyday environments.

This study sought to characterize the way patients with Parkinson's disease consciously perceive and respond to their surroundings while walking in everyday situations. A qualitative research program designed around an ecological data collection protocol was employed. A convenience sample of 14 patients with a diagnosis of Parkinson's disease and a history of gait difficulties were recruited.

Decomposition of Multi-Channel Intramuscular EMG Signals by Cyclostationary-Based Blind Source Separation.

We propose a novel decomposition method for electromyographic signals based on blind source separation. Using the cyclostationary properties of motor unit action potential trains (MUAPt), it is shown that the MUAPt can be decomposed by joint diagonalization of the cyclic spatial correlation matrix of the observations. After modeling the source signals, we provide the proof of orthogonality of the sources and of their delayed versions in a cyclostationary context.

Effect of pedaling cadence on muscle oxygenation during high-intensity cycling until exhaustion: a comparison between untrained subjects and triathletes.

Purpose: The aim of this study was to compare the muscle oxygenation between trained and untrained subjects during heavy exercise until exhaustion at two extreme pedaling cadences using a NIRS system.

Methods: Nine untrained male subjects and nine male competitive triathletes cycled until exhaustion at an intensity corresponding to 90 % of the power output achieved at peak oxygen uptake at 40 and 100 rpm. Gas exchanges were measured breath-by-breath during each exercise.

Naturalistic study of rider's behaviour in initial training in France: evidence of limitations in the educational content.

This paper analyses motorcycle educational content in a number of French motorcycle schools on the basis of a naturalistic study of riders' and trainers' behaviour. The aim is to specify the situations delivered in motorcycle schools and to study the rider's activity in these situations. The methodology includes ethnographic observation within the motorcycle schools and the longitudinal monitoring of 14 trainee motorcyclists during their initial training.

The vastus lateralis neuromuscular activity during all-out cycling exercise.

Objective: The objective of this work was to study modifications in motor control through surface electromyographic (sEMG) activity during a very short all-out cycling exercise.

Methods: Twelve male cyclists (age 23+/-4 years) participated in this study. After a warm-up period, each subject performed three all-out cycling exercises of 6s separated by 2 min of complete rest.

The change in spatial distribution of upper trapezius muscle activity is correlated to contraction duration.

The aim of the study was to confirm the hypothesis that the longer a contraction is sustained, the larger are the changes in the spatial distribution of muscle activity. For this purpose, surface electromyographic (EMG) signals were recorded with a 13 x 5 grid of electrodes from the upper trapezius muscle of 11 healthy male subjects during static contractions with shoulders 90 degrees abducted until endurance. The entropy (degree of uniformity) and center of gravity of the EMG root mean square map were computed to assess spatial inhomogeneity in muscle activation and changes over time in EMG amplitude spatial distribution.

An EMG fractal indicator having different sensitivities to changes in force and muscle fatigue during voluntary static muscle contractions.

During a sustained contraction, electromyographic signals (EMGs) undergo a spectral compression. This fatigue behaviour induces a shift of the mean and the median frequencies to lower frequencies. On the other hand, several studies conclude that the mean/median frequency can increase, decrease or remain constant with an increasing force level.

Neuromuscular response of young boys versus men during sustained maximal contraction.

Purpose: This study was designed to compare neuromuscular response between boys and men during sustained maximal voluntary contraction (MVC).

Methods: Fifteen boys (YB, 10.5 +/- 0.

Differences in strength and surface electromyogram characteristics between pre-pubertal gymnasts and untrained boys during brief and maintained maximal isometric voluntary contractions.

The present study was aimed at investigating differences of maximal strength (F(max)) of the elbow flexors and characteristics of the surface electromyogram (EMG) between six gymnasts (G) and six untrained (UT) 10-year-old boys during brief and maintained maximal voluntary isometric contraction (MVC). The F(max) was estimated during 5 s MVC (maximal test, MT) and normalized to the cross sectional area (CSA) of the arm. The EMG signal of the biceps brachii was recorded during MT and during a 25 s maintained MVC (fatigue test).