Effect of optimal filtering parameters for autoregressive model AR(p) on motor unit action potential signal

Error is one element of the autoregressive (AR) model, which is supposed to be white noise. Correspondingly assumption that white noise error is a normal distribution in electromyography (EMG) estimation is one of the common causes for error maximization. This paper presents the effect of a suitable choice of filtering function based on the non-invasive analysis properties of motor unit action potential signal, extracted from a non-invasive method-the high spatial resolution (HSR) electromyography (EMG), recorded during low-level isometric muscle contractions. The final prediction error procedure is used to find the number of parameters in the model. The error signal parameter, the simulated deviation from the actual signals, is suitably filtered to obtain optimally appropriate estimates of the parameters of the automatic regression model. It is filtered to acquire optimally appropriate estimates of the parameters of the automatic regression model. Then appropriate estimates of spectral power shapes are obtained with a high degree of efficiency compared with the robust method under investigation. Extensive experiment results for the proposed technique have shown that it provides a robust and reliable calculation of model parameters. Moreover, estimates of power spectral profiles were evaluated efficiently.

Blockade of 5-HT2 receptors suppresses rate of torque development and motor unit discharge rate during rapid contractions

Serotonin (5-HT) is a neuromodulator that is critical for regulating the excitability of spinal motoneurons and the generation of muscle torque. However, the role of 5-HT in modulating human motor unit activity during rapid contractions has yet to be assessed. Nine healthy participants (23.7 ± 2.2 yr) ingested 8 mg of the competitive 5-HT2 antagonist cyproheptadine in a double-blinded, placebo-controlled, repeated-measures experiment. Rapid dorsiflexion contractions were performed at 30%, 50% and 70% of maximal voluntary contraction (MVC), where motor unit activity was assessed by high-density surface electromyographic decomposition. A second protocol was performed where a sustained, fatigue-inducing dorsiflexion contraction was completed prior to undertaking the same 30%, 50% and 70% MVC rapid contractions and motor unit analysis. Motor unit discharge rate (p < 0.001) and rate of torque development (RTD; p = 0.019) for the unfatigued muscle were both significantly lower for the cyproheptadine condition. Following the fatigue inducing contraction, cyproheptadine reduced motor unit discharge rate (p < 0.001) and RTD (p = 0.024), where the effects of cyproheptadine on motor unit discharge rate and RTD increased with increasing contraction intensity. Overall, these results support the viewpoint that serotonergic effects in the central nervous system occur fast enough to regulate motor unit discharge rate during rapid powerful contractions.

A computational approach for generating continuous estimates of motor unit discharge rates and visualizing population discharge characteristics

Objective: Successive improvements in high density surface electromyography and decomposition techniques have facilitated an increasing yield in decomposed motor unit (MU) spike times. Though these advancements enhance the generalizability of findings and promote the application of MU discharge characteristics to inform the neural control of motor output, limitations remain. Specifically, 1) common approaches for generating smooth estimates of MU discharge rates introduce artifacts in quantification, which may bias findings, and 2) discharge characteristics of large MU populations are often difficult to visualize. Approach: In the present study, we propose support vector regression (SVR) as an improved approach for generating smooth continuous estimates of discharge rate and compare the fit characteristics of SVR to traditionally used methods, including Hanning window filtering and polynomial regression. Furthermore, we introduce ensembles as a method to visualize the discharge characteristics of large MU populations. We define ensembles as the average discharge profile of a subpopulation of MUs, composed of a time normalized ensemble average of all units within this subpopulation. Analysis was conducted with MUs decomposed from the tibialis anterior (N = 2128), medial gastrocnemius (N = 2673), and soleus (N = 1190) during isometric plantarflexion and dorsiflexion contractions. Main Result: Compared to traditional approaches, we found SVR to alleviate commonly observed inaccuracies and produce significantly less absolute fit error in the initial phase of MU discharge and throughout the entire duration of discharge. Additionally, we found the visualization of MU populations as ensembles to intuitively represent population discharge characteristics with appropriate accuracy for visualization. Significance: The results and methods outlined here provide an improved method for generating estimates of MU discharge rate with SVR and present a unique approach to visualizing MU populations with ensembles. In combination, the use of SVR and generation of ensembles represent an efficient method for rendering population discharge characteristics.

Effects of muscle shortening on single-fiber, motor unit, and compound muscle action potentials

Even under isometric conditions, muscle contractions are associated with some degree of fiber shortening. The effects of muscle shortening on extracellular electromyographic potentials have not been characterized in detail. Moreover, the anatomical, biophysical, and detection factors influencing the muscle-shortening effects have been neither identified nor understood completely. Herein, we investigated the effects of muscle shortening on the amplitude and duration characteristics of single-fiber, motor unit, and compound muscle action potentials. We found that, at the single-fiber level, two main factors influenced the muscle-shortening effects: (1) the electrode position and distance relative to the myotendinous zone and (2) the electrode distance to the maxima of the dipole field arising from the stationary dipole created at the fiber-tendon junction. Besides, at the motor unit and muscle level, two additional factors were involved: (3) the overlapping between the propagating component of some fibers with the non-propagating component of other fibers and (4) the spatial spreading of the fiber-tendon junctions. The muscle-shortening effects depend critically on the electrode longitudinal distance to the myotendinous zone. When the electrode was placed far from the myotendinous zone, muscle shortening resulted in an enlargement and narrowing of the final (negative) phase of the potential, and this enlargement became less pronounced as the electrode approached the fiber endings. For electrode locations close to the myotendinous zone, muscle shortening caused a depression of both the main (positive) and final (negative) phases of the potential. Beyond the myotendinous zone, muscle shortening led to a decrease of the final (positive) phase. The present results provide reference information that will help to identify changes in MUPs and M waves due to muscle shortening, and thus to differentiate these changes from those caused by muscle fatigue. Graphical abstract

Application Value of the Motor Unit Number Index in Patients With Kennedy Disease

The aim of this study was to evaluate the usefulness of the motor unit number index (MUNIX) technique in Kennedy disease (KD) and test the correlation between the MUNIX and other clinical parameters. The MUNIX values of the bilateral deltoid, abductor digiti minimi (ADM), quadriceps femoris (QF), and tibialis anterior (TA) were determined and compared with the course of the disease. The MUNIX sum score was calculated by adding the MUNIX values of these 8 muscles. Disability was evaluated using the spinal and bulbar muscular atrophy functional rating scale (SBMAFRS). The MUNIX scores of patients with KD were negatively correlated with the course of the disease (p &lt; 0.05), whereas their motor unit size index (MUSIX) scores were positively correlated with the course the of disease (p &lt; 0.05). MUNIX sum scores were correlated with SBMAFRS scores (r = 0.714, p &lt; 0.05). MUNIX was more sensitive than compound muscle action potentials or muscle strength as an indicator of neuron loss and axonal collateral reinnervation. The MUNIX sum score is an objective and a reliable indicator of disease progression, and it is a potential choice for therapeutic clinical trials. The MUNIX can assess the functional loss of motor axons and is correlated with disability. The MUNIX sum score may be especially suitable as an objective parameter.