BUSCADOR RECOLECTA

An analytical derivation of the EMG signal's amplitude probability density function (EMG PDF) is presented and used to study how an EMG signal builds-up, or fills, as the degree of muscle contraction increases. The EMG PDF is found to change from a semi-degenerate distribution to a Laplacian-like distribution and finally to a Gaussian-like distribution. We present a measure, the EMG filling factor, to quantify the degree to which an EMG signal has been built-up. This factor is calculated from the ratio of two non-central moments of the rectified EMG signal. The curve of the EMG filling factor as a function of the mean rectified amplitude shows a progressive and mostly linear increase during early recruitment, and saturation is observed when the EMG signal distribution becomes approximately Gaussian. Having presented the analytical tools used to derive the EMG PDF, we demonstrate the usefulness of the EMG filling factor and curve in studies with both simulated signals and real signals obtained from the tibialis anterior muscle of 10 subjects. Both simulated and real EMG filling curves start within the 0.2 to 0.35 range and rapidly rise towards 0.5 (Laplacian) before stabilizing at around 0.637 (Gaussian). Filling curves for the real signals consistently followed this pattern (100% repeatability within trials in 100% of the subjects). The theory of EMG signal filling derived in this work provides (a) an analytically consistent derivation of the EMG PDF as a function of motor unit potentials and motor unit firing patterns; (b) an explanation of the change in the EMG PDF according to degree of muscle contraction; and (c) a way (the EMG filling factor) to quantify the degree to which an EMG signal has been built-up., This work was supported by the Ministerio de Ciencia e Innovacion of the Spanish Government under Grant PID2019-109062RB-I00.

Introduction Under isometric conditions, the increase in muscle force is accompanied by a reduction in the fbers’ length.
The efects of muscle shortening on the compound muscle action potential (M wave) have so far been investigated only by
computer simulation. This study was undertaken to assess experimentally the M-wave changes caused by brief voluntary
and stimulated isometric contractions.
Methods Two diferent methods of inducing muscle shortening under isometric condition were adopted: (1) applying a
brief (1 s) tetanic contraction and (2) performing brief voluntary contractions of diferent intensities. In both methods,
supramaximal stimulation was applied to the brachial plexus and femoral nerves to evoke M waves. In the frst method,
electrical stimulation (20 Hz) was delivered with the muscle at rest, whereas in the second, stimulation was applied while
participants performed 5-s stepwise isometric contractions at 10, 20, 30, 40, 50, 60, 70, and 100% MVC. The amplitude and
duration of the frst and second M-wave phases were computed.
Results The main fndings were: (1) on application of tetanic stimulation, the amplitude of the M-wave frst phase decreased
(~10%, P<0.05), that of the second phase increased (~50%, P<0.05), and the M-wave duration decreased (~20%, P<0.05)
across the frst fve M waves of the tetanic train and then plateaued for the subsequent responses; (2) when superimposing
a single electrical stimulus on muscle contractions of increasing forces, the amplitude of the M-wave frst phase decreased
(~20%, P<0.05), that of the second phase increased (~30%, P<0.05), and M-wave duration decreased (~30%, P<0.05)
as force was raised from 0 to 60–70% MVC force.
Conclusions The present results will help to identify the adjustments in the M-wave profle caused by muscle shortening
and also contribute to diferentiate these adjustments from those caused by muscle fatigue and/or changes in Na+–K+ pump
activity., Open Access funding provided by Universidad Pública de Navarra. This work has been supported by the Spanish Ministry of Science and Innovation under the project PID2019-109062RB-I00.

Removing artifacts from nearby motor units is one of the main objectives when processing scanning-EMG recordings. Methods such as median filtering or masked least-squares smoothing (MLSS) can be used to eliminate artifacts in recordings with just one discharge of the motor unit potential (MUP) at each location. However, more effective artifact removal can be achieved if several discharges per position are recorded. In this case, processing usually involves averaging the discharges available at each position and then applying a median filter in the spatial dimension. The main drawback of this approach is that the median filter tends to distort the signal waveform. In this paper, we present a new algorithm that operates on multiple discharges simultaneously and in the spatial dimension. We refer to this algorithm as the multi masked least-squares smoothing (MMLSS) algorithm: an extension of the MLSS algorithm for the case of multiple discharges. The algorithm is tested using simulated scanning-EMG signals in different recording conditions, i.e., at different levels of muscle contraction and for different numbers of discharges per position. Results demonstrate that the algorithm eliminates artifacts more effectively than any previously available method and does so without distorting the waveform of the signal., This work has been supported by the Spanish Ministry of Science and Innovation under the project PID2019-109062RB-I00.

In an active motor unit (MU), the time intervals between the firings of its muscle fibers vary across successive MU
activations. This variability is called jitter and is increased in pathological processes that affect the neuromuscular junctions or terminal axonal segments of MUs. Traditionally, jitter has been measured using single fiber
electrodes (SFEs) and a difficult and subjective manual technique. SFEs are expensive and reused, implying a
potential risk of patient infection; so, they are being gradually substituted by safer, disposable, concentric needle
electrodes (CNEs). As CNEs are larger, voltage contributions from individual fibers of a MU are more difficult to
detect, making jitter measurement more difficult. This paper presents an automatic method to estimate jitter
from trains of motor unit potentials (MUPs), for both SFE and CNE records. For a MUP train, segments of MUPs
generated by single muscle fibers (SF MUP segments) are found and jitter is measured between pairs of these
segments. Segments whose estimated jitter values are not reliable, according to several SF MUP segment characteristics, are excluded. The method has been tested in several simulation studies that use mathematical models
of muscle fiber potentials. The results are very satisfactory in terms of jitter estimation error (less than 10% in
most of the cases studied) and mean number of valid jitter estimates obtained per simulated train (greater than
1.0 in many of the cases and less than 0.5 only in the most complicated). A preliminary study with real signals
was also performed, using 19 MUP trains from 3 neuropathic patients. Jitter measurements obtained by the
automatic method were compared with those extracted from a commercial system (Keypoint) and the edition and
supervision of an expert electromyographer. From these measurements 63% were taken from equivalent interval
pair sites within the time span of the MUP trains and, as such, were considered as compatible measurements.
Differences in jitter of these compatible measurements were very low (mean value of 1.3 μs, mean of absolute
differences of 2.97 μs, 25% and 75% percentile intervals of − 0.85 and 3.82 μs, respectively). Although new tests
with larger number of real recordings are still required, the method seems promising for clinical practice., This work has been supported by the Spanish Ministry of Science, Education, and Universities, under the “Salvador de Madariaga” 2018 Program and by the
Spanish Ministry of Education and Research, under the PID2019-109062RB-I00 project. Open Access funding provided by the Public University of Navarra.

This study was undertaken to investigate whether sarcolemmal excitability is impaired during a sustained low-force contraction [10% maximal voluntary contraction (MVC)] by assessing muscle conduction velocity and also by analyzing separately the first and second phases of the muscle compound action potential (M wave). Twenty-one participants sustained an isometric knee extension of 10% MVC for 3min. M waves were evoked by supramaximal single shocks to the femoral nerve given at 10-s intervals. The amplitude, duration, and area of the first and second M-wave phases were computed. Muscle fiber conduction velocity, voluntary surface electromyographic (EMG), perceived effort, MVC force, peak twitch force, and temperature were also recorded. The main findings were: (1) during the sustained contraction, conduction velocity remained unchanged. (2) The amplitude of the M-wave first phase decreased for the first ~30s (−7%, p<0.05) and stabilized thereafter, whereas the second phase amplitude increased for the initial ~30s (+7%, p<0.05), before stabilizing. (3) Both duration and area decreased steeply during the first ~30s, and then more gradually for the rest of the contraction. (4) During the sustained contraction, perceived effort increased fivefold, whereas knee extension EMG increased by ~10%. (5) Maximal voluntary force and peak twitch force decreased (respectively, −9% and −10%, p<0.05) after the low-force contraction. Collectively, the present results indicate that sarcolemmal excitability is well preserved during a sustained 10% MVC task. A depression of the M-wave first phase during a low-force contraction can occur even in the absence of changes in membrane excitability. The development of fatigue during a low-force contraction can occur without alteration of membrane excitability., This work has been supported by the Spanish Ministry of Science and Innovation under the project PID2019-109062RB-I00.