This study presents a novel algorithm for the automatic detection of motor unit (MU) fractions within the motor unit potential (MUP) scans derived from multiscanning EMG recordings. MU fractions are spatially distinct regions identified in the MUP scans that reflect the distribution of muscle fibres within each MU. Multiscanning EMG allows recording multiple MUPs simultaneously in a single recording, improving efficiency and reducing patient discomfort. The algorithm combines amplitude thresholding, morphological operations, and connected component analysis to identify MU fractions. Algorithm performance was evaluated using MUP scans from tibialis anterior muscles of five healthy individuals. The analysis was performed in two ways: the first included all the fractions detected automatically, and the second included only those fractions detected in both the automatic and the ground truth. Additionally, the association between muscle depth, number of MU fractions, and signal-to-noise ratio (SNR) of the recorded signals was analysed. T-tests showed no statistically significant difference between the algorithm and ground truth for both start and end markers. ANOVA indicated that muscle depth did not affect the signal-to-noise ratio (f = 1.06, p = 0.35). Overall, the algorithm reliably identified MU fractions. The proposed automatic method accurately detects MU fractions, providing a valuable tool for analysing motor unit activity in clinical and research settings.

INTRODUCTION:Commercial electromyographic recording systems usually include two different methods for jitter measurement, based on peaks or threshold-crossing. There is reported evidence that the measurements obtained with both methods from discharges recorded with concentric needle electrodes offer comparable results, but this evidence is scarce. This study aimed to replicate such studies and extract conclusions related to the use of the two methods. METHODS:129 EMG recordings were obtained from 12 patients using concentric needle electrodes (0.02 mm2), filtered at 1000 Hz and oversampled to 200 kHz. The recordings were aligned using either peak or threshold-crossing methods. Jitter was measured using both methods and obtained as mean consecutive differences (MCD). Statistical analyses included Anderson-Darling, Wilcoxon, and linear regression tests. RESULTS:Of the 129 recordings, 49 (38 %) were excluded for presenting contaminated waveforms. MCD values were similar in the two methods, with a median difference of -0.92 µs. The Wilcoxon test confirmed this difference (p = 0.0002). The regression yielded a high coefficient of determination (R2 = 0.994) and a slope of 0.989. CONCLUSION:No significant differences were found between the two jitter measurement methods. Variations were only a few µs, not enough to affect pathological jitter diagnosis. Both methods are valid for clinical use.

INTRODUCTION/AIMS:The way in which the EMG signal is progressively filled with motor unit potentials during increasing voluntary contraction provides valuable information about the motor units (MUs) in a muscle. Here, we demonstrate the application of the EMG filling method to detect MU loss and remodeling in patients with chronic radiculopathy. METHODS:Concentric needle EMG signals were recorded from the tibialis anterior of 19 radiculopathy patients and 18 healthy controls during voluntary ramped contractions increasing from 0 to maximum. The EMG filling process was analyzed by measuring the EMG filling factor and EMG amplitude during the contraction. RESULTS:The way in which the filling factor increased with increasing force differed (p < 0.001) between healthy controls (exponential filling curve) and radiculopathy patients (linear curve). The extent to which the EMG envelope amplitude increased throughout the ramp contraction was markedly greater (p < 0.001) in healthy controls (6.1-fold increase) compared to patients (0.5-fold increase). The filling factor at maximal effort was significantly higher in healthy controls than in patients (0.53 ± 0.04 vs. 0.45 ± 0.09, p < 0.001). The EMG filling analysis revealed clear signs of MU loss and remodeling in 85% of patients. DISCUSSION:The EMG filling analysis is a fast and accessible approach to detect MU loss in radiculopathy patients. Moreover, it provides information about the MU remodeling process and the type of motor units that are predominantly lost in the neurogenic condition.

EMG interference pattern analysis is routinely used in the assessment of motor neuron loss. We propose systematizing interference pattern analysis by recording an isometric ramp contraction of a muscle, from minimum to maximum activation level. Three EMG probability density function (PDF) shape descriptors are then employed to quantify the PDF evolution assessing EMG filling through contraction: filling factor, negentropy, and kurtosis. The three filling curves are fitted with an exponential model, and the decay constant parameters are employed to obtain a feature vector that characterizes the EMG filling behavior of the muscle. Results show a tendency of the filling curves to shorten and not reach saturation when neuropathy is simulated, and a subsequent dependency of the decay constant parameters with neuropathy progression. We demonstrate, with a set of real signals and through simulation experiments, the ability of the features to be used by a classification system to detect motor neuron loss. With the set of real signals (from 40 subjects with L5 radiculopathy and 40 healthy controls), results show a 0.86 sensibility and 0.84 specificity, indicating a promising performance when incorporated into clinical decision support systems.

The objective of this work was to extend the evaluation of a recently proposed method for estimating neuromuscular jitter within motor unit potential (MUP) trains extracted from muscles suffering neuromuscular junction disease. The method detects, within the MUP duration, "single-fiber" intervals that have likely been produced by single muscle fibers. Jitter is then estimated between pairs of these "single-fiber" intervals using an algorithm which incorporates the traditional mean consecutive difference (MCD) parameter. Electromyographic (EMG) recordings from facial muscles of 15 patients with symptoms related to myasthenia gravis were obtained. MUP trains were extracted using DQEMG software and manual jitter measures were obtained using an ad-hoc graphical interface, which emulates single fiber EMG protocols. Automatic measures for two different values of an internal threshold parameter were obtained and compared to manual measures. 5 %, 25 %, 75 % and 95 % percentiles for the differences between the automatic and manual jitter measurements were [-3.74, -1.47, 1.24, 3.47 μs] and [-6.45, -2.07, 1.65, 7.16 μs], for the two threshold values, respectively. Therefore, very small statistical and clinical differences were found between the automatic and manual jitter measures, supporting the method as an accurate tool for jitter assessment or as a guiding aid for manual procedures.

OBJECTIVES:The process by which the surface EMG signal is progressively filled up with motor unit potentials has so far been investigated only in the quadriceps muscles. However, the sEMG filling process is influenced by anatomical, physiological, and neural factors, and thus may be different for each muscle. Here, we sought to characterize the sEMG filling process of the tibialis anterior (TA) and compare it to that of the vastus lateralis (VL). METHODS:Surface EMG signals were recorded from the TA and VL muscles of healthy subjects as force was gradually increased from 0 to 80% MVC. The sEMG filling process was analyzed by measuring the EMG filling factor (FF), an index determined by the shape of the probability density function (PDF) of the sEMG signal. RESULTS:(1) The sEMG filling process showed significant differences between the TA and VL muscles (p < 0.05). (2) In the TA, the degree of sEMG filling at the onset of the contraction was low (FF < 0.45) for 72 % of male subjects and 53 % of female subjects, whereas, in the VL, the degree of initial sEMG filling was low for 89 % of male subjects, but only in 12 % of female subjects. (3) In the TA, the sEMG at high forces (>40 % MVC) contained spikes with largely different amplitudes (FF ∼ 0.5), whereas, in the VL, the sEMG contained spikes with comparable amplitudes (FF ∼ 0.63). CONCLUSIONS:(1) At high forces, the TA PDF was close to Laplacian, whilst the VL PDF was nearly Gaussian; (2) The sEMG filling curves are more informative in the TA than in the VL; (3) The sEMG filling process is muscle and gender specific.

OBJECTIVES:The progression of recruitment of motor unit potentials (MUPs) during increasing voluntary contraction can provide important information about the motor units (MUs) innervating a muscle. Here, we described a method to quantitate the recruitment level of the intramuscular electromyographic (iEMG) signal during an increasing force level. METHODS:Concentric needle EMG signals were recorded from the tibialis anterior of healthy subjects as force was gradually increased from 0 to maximum force. The iEMG filling process was analyzed by measuring the EMG filling factor (FF), calculated from the mean rectified iEMG and the root mean square iEMG. RESULTS:(1) The iEMG activity at low contraction forces was "discrete" (FF<0.3) for all participants. (2) The iEMG activity at maximal effort was "full" (FF>0.5) for 83 % of the participants, whereas it was "incompletely-reduced" (0.3

Introduction: It has been shown that, for male subjects, the sEMG activity at low contraction forces is normally “pulsatile”, i.e., formed by a few large-amplitude MUPs, coming from the most superficial motor units. The subcutaneous layer thickness, known to be greater in females than males, influences the electrode detection volume. Here, we investigated the influence of the subcutaneous layer thickness on the type of sEMG activity (pulsatile vs. continuous) at low contraction forces.Methods: Voluntary surface EMG signals were recorded from the quadriceps muscles of healthy males and females as force was gradually increased from 0% to 40% MVC. The sEMG filling process was examined by measuring the EMG filling factor, computed from the non-central moments of the rectified sEMG signal.Results: 1) The sEMG activity at low contraction forces was “continuous” in the VL, VM and RF of females, whereas this sEMG activity was “pulsatile” in the VL and VM of males. 2) The filling factor at low contraction forces was lower in males than females for the VL (p = 0.003) and VM (p = 0.002), but not for the RF (p = 0.54). 3) The subcutaneous layer was significantly thicker in females than males for the VL (p = 0.001), VM (p = 0.001), and RF (p = 0.003). 4) A significant correlation was found in the vastus muscles between the subcutaneous layer thickness and the filling factor (p < 0.05).Discussion: The present results indicate that the sEMG activity at low contraction forces in the female quadriceps muscles is “continuous” due to the thick subcutaneous layer of these muscles, which impedes an accurate assessment of the sEMG filling process.

EMG filling curve characterizes the EMG filling process and EMG probability density function (PDF) shape change for the entire force range of a muscle.We aim to understand the relation between the physiological and recording variables, and the resulting EMG filling curves. We thereby present an analytical and simulation study to explain how the filling curve patterns relate to specific changes in the motor unit potential (MUP) waveforms and motor unit (MU) firing rates, the two main factors affecting the EMG PDF, but also to recording conditions in terms of noise level. We compare the analytical results with simulated cases verifying a perfect agreement with the analytical model. Finally, we present a set of real EMG filling curves with distinct patterns to explain the information about MUP amplitudes, MU firing rates, and noise level that these patterns provide in the light of the analytical study. Our findings reflect that the filling factor increases when firing rate increases or when newly recruited motor unit have potentials of smaller or equal amplitude than the former ones. On the other hand, the filling factor decreases when newly recruited potentials are larger in amplitude than the previous potentials. Filling curves are shown to be consistent under changes of the MUP waveform, and stretched under MUP amplitude scaling. Our findings also show how additive noise affects the filling curve and can even impede to obtain reliable information from the EMG PDF statistics.

Abstract Introduction The probability density function (PDF) of the surface electromyogram (sEMG) depends on contraction force. This dependence, however, has so far been investigated by having the subject generate force at a few fixed percentages of MVC. Here, we examined how the shape of the sEMG PDF changes with contraction force when this force was gradually increased from zero. Methods Voluntary surface EMG signals were recorded from the vastus lateralis of healthy subjects as force was increased in a continuous manner vs. in a step-wise fashion. The sEMG filling process was examined by measuring the EMG filling factor, computed from the non-central moments of the rectified sEMG signal. Results (1) In 84% of the subjects, as contraction force increased from 0 to 10% MVC, the sEMG PDF shape oscillated back and forth between the semi-degenerate and the Gaussian distribution. (2) The PDF–force relation varied greatly among subjects for forces between 0 and ~ 10% MVC, but this variability was largely reduced for forces above 10% MVC. (3) The pooled analysis showed that, as contraction force gradually increased, the sEMG PDF evolved rapidly from the semi-degenerate towards the Laplacian distribution from 0 to 5% MVC, and then more slowly from the Laplacian towards the Gaussian distribution for higher forces. Conclusions The study demonstrated that the dependence of the sEMG PDF shape on contraction force can only be reliably assessed by gradually increasing force from zero, and not by performing a few constant-force contractions. The study also showed that the PDF–force relation differed greatly among individuals for contraction forces below 10% MVC, but this variability was largely reduced when force increased above 10% MVC.

In this paper we present an advanced application of a well-established algorithm to detect the duration of the motor unit potentials(MUPs) of a multiscanning-EMG. The established algorithm was initially formulated to calculate the duration of a single MUP recorded from a single point. About 30 MUPs were acquired from 5 healthy subjects while doing a small contraction in the tibialis anterior muscle. A manual “ground truth” of the duration positions (start and end markers) was obtained for each MUP by clinical experts. The algorithm was compared to a widely recognized MUP duration method and with the ground truth. Results from the new method are statistically closer shows much closeness to the ground-truth values than the second method, both in the start and the end marker determination. The mean error tent to be 1.2ms and 4.2ms for the start and the end markers in the correlation method compared to a 3.2ms and 8.2ms in the second method. The p_value of the ttest conducted to be close to 0 also support that the two methods are significantly different and our method has comparatively less error to that of the second algorithm. In summary, our enhanced algorithm not only outperforms traditional methods but also aligns closely with expert assessments that is a promising factor for the assessment of duration in clinical trials.

The World Health Organization (WHO) introduced a framework for healthy aging in 2015 that emphasizes functional ability instead of absence of disease. Healthy ageing is defined as "the process of building and maintaining the functional ability that enables well-being". This framework considers an individual's intrinsic capacity (IC), environment, and the interaction between them to determine functional ability. In this prospective cohort study, we investigated the link between mortality and various respiratory diseases in almost half a million adults who are part of the UK Biobank. We derived an IC score using measures from 4 of the 5 domains: two for psychological capacity, two for sensory capacity, two for vitality and one for locomotor capacity. The exposure variable in the study was the number of reported factors, which was summed and categorized into IC scores of zero, one, two, three, or at least four. The outcome was respiratory disease-related mortality, which was linked to national mortality records. The follow-up period started from participants' inclusion in the UK Biobank study (2006-2010) and ended on December 31, 2021, or the participant's death was censored. The average follow-up was 10.6 years (IQR 10.0; 11.3). During a median follow-up period of 10.6 years, 27,251 deaths were recorded. Out of these, 7.5% (2059) were primarily attributed to respiratory disease. The results showed that a higher IC score (+4 points) was associated with a significantly increased risk of respiratory disease mortality, with HRs of 3.34 [2.64 to 4.23] for men (C-index = 0.83) and 3.87 [2.86 to 5.23] for women (C-index = 0.84), independent of major confounding factors (P < 0.001). Our study provides evidence that lower levels of the WHO's IC construct are associated with increased risk of mortality and various adverse health outcomes. The IC construct, which is easily and inexpensively measured, holds great promise for transforming geriatric care worldwide, including in regions without established geriatric medicine.

INTRODUCTION:The EMG filling factor is an index to quantify the degree to which an EMG signal has been filled. Here, we tested the validity of such index to analyse the EMG filling process as contraction force was slowly increased.METHODS:Surface EMG signals were recorded from the quadriceps muscles of healthy subjects as force was gradually increased from 0 to 40% MVC. The sEMG filling process was analyzed by measuring the EMG filling factor (calculated from the non-central moments of the rectified sEMG).RESULTS:(1) As force was gradually increased, one or two prominent abrupt jumps in sEMG amplitude appeared between 0 and 10% of MVC force in all the vastus lateralis and medialis. (2) The jumps in amplitude were originated when a few large-amplitude MUPs, clearly standing out from previous activity, appeared in the sEMG signal. (3) Every time an abrupt jump in sEMG amplitude occurred, a new stage of sEMG filling was initiated. (4) The sEMG was almost completely filled at 2-12% MVC. (5) The filling factor decreased significantly upon the occurrence of an sEMG amplitude jump, and increased as additional MUPs were added to the sEMG signal. (6) The filling factor curve was highly repeatable across repetitions.CONCLUSIONS:It has been validated that the filling factor is a useful, reliable tool to analyse the sEMG filling process. As force was gradually increased in the vastus muscles, the sEMG filling process occurred in one or two stages due to the presence of abrupt jumps in sEMG amplitude.

Abstract Background The World Health Organization proposed the concept of intrinsic capacity (IC; the composite of all the physical and mental capacities of the individual) as central for healthy ageing. However, little research has investigated the interaction and joint associations of IC with cardiovascular disease (CVD) incidence and CVD mortality in middle‐ and older‐aged adults. Methods Using data from 443 130 UK Biobank participants, we analysed seven biomarkers capturing the level of functioning of five domains of IC to calculate a total IC score (ranging from 0 [better IC] to +4 points [poor IC]). Associations between IC score and incidence of six long‐term CVD conditions (hypertension, stroke/transient ischaemic attack stroke, peripheral vascular disease, atrial fibrillation/flutter, coronary artery disease and heart failure), and grouped mortality from these conditions were estimated using Cox proportional models, with a 1‐year landmark analysis to triangulate the findings. Results Over 10.6 years of follow‐up, CVD morbidity grouped (n = 384 380 participants for the final analytic sample) was associated with IC scores (0 to +4): mean hazard ratio (HR) [95% confidence interval, CI] 1.11 [1.08–1.14], 1.20 [1.16–1.24], 1.29 [1.23–1.36] and 1.56 [1.45–1.59] in men (C‐index = 0.68), and 1.17 [1.13–1.20], 1.30 [1.26–1.36], 1.52 [1.45–1.59] and 1.78 [1.67–1.89] in women (C‐index = 0.70). In regard to mortality, our results indicated that the higher IC score (+4 points) was associated with a significant increase in subsequent CVD mortality (mean HR [95% CI]: 2.10 [1.81–2.43] in men [C‐index = 0.75] and 2.29 [1.85–2.84] in women [C‐index = 0.78]). Results of all sensitivity analyses by full sample, sex and age categories were largely consistent independent of major confounding factors (P < 0.001). Conclusions IC deficit score is a powerful predictor of functional trajectories and vulnerabilities of the individual in relation to CVD incidence and premature death. Monitoring an individual's IC score may provide an early‐warning system to initiate preventive efforts.

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.

Introduction: There is no complete understanding of the way in which the surface EMG signal progressively fills with motor unit potentials (MUPs) as contraction force increases slowly. We sought to investigate this sEMG filling process.Methods: Surface EMG signals were recorded from the quadriceps muscles of healthy subjects as force was gradually increased from 0 to 40% MVC. The sEMG filling process was analyzed by measuring the EMG filling factor (calculated from the non-central moments of the rectified sEMG signal).Results: (1) As force was gradually increased, one or two prominent abrupt jumps in sEMG amplitude appeared between 0 and 10% of MVC force (mean 2.5% MVC) in all the vastus lateralis and medialis.(2) The jumps in amplitude were originated when a few large-amplitude MUPs, clearly standing out from the previous sEMG activity or from noise, appeared in the sEMG signal.(3) Every time an abrupt jump in sEMG amplitude occurred, a new stage of sEMG filling was initiated.(4) The sEMG was almost completely filled at 2-12% MVC.Conclusions: As force was gradually increased in the vastus muscles, the sEMG filling process occurred in one or two stages due to the presence of abrupt jumps in sEMG amplitude. The sEMG signal was almost completely filled at very low forces. The filling factor is a useful promising tool to analyse the EMG filling process.

Under isometric conditions, the increase in muscle force is accompanied by a reduction in the fibers’ length. The effects 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. Two different 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 different intensities. In both methods, supramaximal stimulation was applied to the brachial plexus and femoral nerves to evoke M waves. In the first 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

INTRODUCTION:In the compound muscle action potential (M wave) recorded using the belly-tendon configuration, the contribution of the tendon electrode is assumed to be negligible compared to the belly electrode. We tested this assumption by placing the reference electrode at a distant (contralateral) site, which allowed separate recording of the belly and tendon contributions. METHODS:M waves were recorded at multiple selected sites over the right quadriceps heads and lower leg using two different locations for the reference electrode: the ipsilateral (right) and contralateral (left) patellar tendon. The general parameters of the M wave (amplitude, area, duration, latency, and frequency) were measured. RESULTS:(1) The tendon potential had a small amplitude (<30%) compared to the belly potential; (2) Changing the reference electrode from the ipsilateral to the contralateral patella produced moderate changes in the M wave recorded over the innervation zone, these changes affecting significantly the amplitude of the M-wave second phase (p = 0.006); (3) Using the contralateral reference system allowed recording of short-latency components occurring immediately after the stimulus artefact, which had the same latency and amplitude (p = 0.18 and 0.25, respectively) at all recording sites over the leg. CONCLUSIONS:The potential recorded at the "tendon" site after femoral nerve stimulation is small (compared to the belly potential), but not negligible, and makes a significant contribution to the second phase of belly-tendon M wave. Adopting a distant (contralateral) reference allowed recording of far-field components that may aid in the understanding of the electrical formation of the M wave.