Tutorial. Frequency analysis of the surface EMG signal: Best practices.

This tutorial is aimed primarily to non-engineers (clinical researchers, clinicians, neurophysiology technicians, ergonomists, movement and sport scientists, physical therapists) or beginners using, or planning to use, surface electromyography (sEMG) as a monitoring and assessment tool for muscle and neuromuscular evaluations in the prevention and rehabilitation fields. Its first purpose is to explain, with minimal mathematics, basic concepts related to: (a) time and frequency domain description of a signal, (b) Fourier transform, (c) amplitude, phase, and power spectrum of a signal, (d) sampling of a signal, (e) filtering of sEMG signals, (f) cross-spectrum and coherence between two signals, (g) signal stationarity and criteria for epoch selection, (h) myoelectric manifestations of muscle fatigue and (i) fatigue indices. These concepts are consolidated knowledge and are addressed and discussed with examples taken from the literature.

A Particle Swarm Optimised Independence Estimator for Blind Source Separation of Neurophysiological Time Series.

The decomposition of neurophysiological recordings into their constituent neural sources is of major importance to a diverse range of neuroscientific fields and neuroengineering applications. The advent of high density electrode probes and arrays has driven a major need for novel semi-automated and automated blind source separation methodologies that take advantage of the increased spatial resolution and coverage these new devices offer. Independent component analysis (ICA) offers a principled theoretical framework for such algorithms, but implementation inefficiencies often drive poor performance in practice, particularly for sparse sources.

Hand and distal joint tremor are most coherent with the activity of elbow flexors and wrist extensors in persons with essential tremor.

Essential tremor (ET) affects millions of people. Although frontline treatment options (medication, deep brain stimulation, and focused ultrasound ablation) have provided significant relief, many patients are unsatisfied with the outcomes. Peripheral suppression techniques, such as injections of botulinum toxin or sensory electrical stimulation of muscles, are gaining popularity, but could be optimized if the muscles most responsible for a patient's tremor were identified.

Essential Tremor accentuates the pattern of tremor-band coherence between upper-limb muscles.

Although Essential Tremor is one of the most common movement disorders, current treatment options are relatively limited. Peripheral tremor suppression methods have shown potential, but we do not currently know which muscles are most responsible for patients' tremor, making it difficult to optimize suppression methods. The purpose of this study was to quantify the relationships between the tremorogenic activity in muscles throughout the upper limb.

Blind identification of the spinal cord output in humans with high-density electrode arrays implanted in muscles.

Invasive electromyography opened a new window to explore motoneuron behavior in vivo. However, the technique is limited by the small fraction of active motoneurons that can be concurrently detected, precluding a population analysis in natural tasks. Here, we developed a high-density intramuscular electrode for in vivo human recordings along with a fully automatic methodology that could detect the discharges of action potentials of up to 67 concurrently active motoneurons with 99% accuracy.