Muscle activation and electromyography studies

The paper proposes a method combining EMG signal decomposition and realistic motoneuron modeling to estimate the firing behavior of entire motoneuron pools in humans.

The paper tracks motor units in non-human primates during force contractions, finding stable recruitment order and a dominant neural component for force control.

The paper shows that humans cannot easily control individual motor units independently, as their activation is governed by a shared input signal and changes in de-recruitment order.

This study examines sex differences in central and peripheral fatigue during sustained isometric ankle plantar flexion, finding similar fatigue mechanisms between males and females despite greater fatigability in males.

This study examines sex-specific differences in muscle activation patterns during locomotion in young and older adults using muscle synergies.

This paper uses a deep learning model to estimate muscle activation from EMG signals, showing improved performance over traditional methods in predicting joint kinematics and force.

This study uses EEG to analyze brainwave changes during a prolonged intermittent motor task, showing variations in theta, alpha, and beta power spectral densities related to increasing fatigue levels.

This study investigates whether corticospinal excitability changes during residual force enhancement and finds no significant differences between stretch-hold and fixed-end contractions.

This paper applies machine learning to model musculoskeletal transformations in the human arm and hand, showing that both gradient boosting and neural networks can accurately predict muscle length and moment arm relationships.

This paper develops MuscleNET, a machine learning framework that maps sEMG signals to biomechanical variables, showing real-time performance and effectiveness in motor control applications.

This study records magnetic and electric fields during a muscle reflex to analyze action potential dynamics and muscle structure.

This study investigates how prior muscle lengthening or shortening affects perception of effort during isometric contractions, finding that effort perception varies with torque and EMG levels.

The paper assesses inter-operator reliability in decomposing HDsEMG into motor unit spike trains, finding high agreement across operators.

This study uses a mathematical model of rat muscle to show that increased synchronization of motor unit firings increases force variability, with slow motor units contributing most to tremor during weak contractions.

This study shows that persistent inward currents (PICs) in human plantar flexor motor units increase with voluntary drive during isometric contractions.

This study tests an artificial sensory feedback system providing joint speed information for myoelectric prosthesis control and finds modest improvements in reaching errors after perturbed control.

This study identifies individual muscle activation signatures using EMG data and shows their consistency across tasks and days.

This paper develops a biophysical model showing how muscle spindle afferent firing patterns emerge from muscle mechanics and neuromechanical interactions.

This study compares muscle activation patterns during treadmill and overground locomotion, finding that treadmill movement results in more regular and temporally shifted motor primitives.

This paper investigates pitfalls in fractal analysis of EMG data during mouse locomotion and provides recommendations to avoid misinterpretation of Higuchis fractal dimension and Hurst exponent.

This study evaluates if incorporating muscle synergies into static optimization improves muscle activation predictions during gait, finding no improvement but noting potential benefits for control applications.

The paper examines muscle co-variation in rats during locomotion, finding that co-variation patterns suggest neural regulation of internal joint stresses rather than simplification of task performance.

This paper introduces head magnetomyography (hMMG) to monitor whole-head muscular activity, demonstrating its ability to decode stimulus valence and detect previously neglected neck muscle activity.

This study uses information decomposition of EMG data to analyze functional interactions between muscles during postural tasks, revealing task-dependent changes in neural networks.

This paper presents a comprehensive mathematical model of surface EMG and force generation in skeletal muscles, integrating previous models and demonstrating its ability to reproduce physiological effects and generate synthetic data.

The paper shows that history-dependent muscle spindle Ia afferent firing rates in relaxed rat muscle mirror muscle fiber forces, which are masked by noncontractile tissue forces.

This study examines how fatigue affects muscle synergy recruitment but not structure during upper limb movements using EMG data and non-negative matrix factorization.

This study examines how gravitational and dynamic muscle torque components relate to static and phasic muscle activity during reaching movements.