A Preliminary Study on the Use of HD-sEMG for the Functional Imaging of Equine Superficial Muscle Activation during Dynamic Mobilization Exercises.

Superficial skeletal muscle activation is associated with an electric activity. Bidimensional High-Density Surface Electromyography (HD-sEMG) is a non-invasive technique that uses a grid of equally spaced electrodes applied on the skin surface to detect and portray superficial skeletal muscle activation. The goal of the study was to evaluate the feasibility of HD-sEMG to detect electrical activation of skeletal muscle and its application during rehabilitation exercises in horses. To fulfil this aim, activation of the superficial descending pectoral and external abdominal oblique core muscles were measured using HD-sEMG technology during dynamic mobilization exercises to induce lateral bending and flexion/extension tasks of the trunk. Masseter muscle was instrumented during mastication as a control condition. A 64 surface EMG channel wireless system was used with a single 64 electrode grid or a pair of 32 electrode grids. HD-sEMG provided unique information on the muscular activation onset, duration, and offset, along each motor task, and permitting inferences about the motor control strategy actuated by the central nervous system. Signals were further processed to obtain firing frequencies of few motor-neurons. Estimation of electromyographic amplitude and spectral parameters allowed detecting the onset of muscular fatigue during the motor tasks performed. HD-sEMG allows the assessment of muscular activation in horses performing specific motor tasks, supporting its future application in clinical and research settings.

Right Heart Thrombus in an Adult COVID-19 Patient: A Case Report.

INTRODUCTION: Right heart thrombus (RiHTh) can be considered a rare and severe condition associated with thromboembolic phenomena. A case is described of a COVID-19 patient presenting with an isolated thrombus in the right ventricle. CASE PRESENTATION: An 80-years-old Caucasian male was admitted in an intensive care unit (ICU) for COVID-19 related acute respiratory distress syndrome. The patient showed signs of hemodynamic instability, elevated cardiac troponin I and altered coagulation. On further assessment, a thrombotic mass near the apex of the right ventricle was detected. Moreover, the apex and the anteroseptal wall of the right ventricle appeared akinetic. Following the administration of a therapeutic dose of unfractionated heparin over a forty-eight hour period, re-evaluation of the right chambers showed that the thrombotic mass had resolved entirely. CONCLUSION: COVID-19 patients could constitute a population at risk of RiHTh. Routine use of echocardiography and a multidisciplinary approach can improve the management of this condition.

Technology and instrumentation for detection and conditioning of the surface electromyographic signal: state of the art.

The aim of this review is to present the state of the art of the technology of detection and conditioning systems for surface electromyography (sEMG). The first part of the manuscript focuses on the sEMG electrode system technology: the electrode classification, impedance, noise, transfer function, the spatial filtering effect of surface electrode configurations, the effects of electrode geometry, and location on the recorded sEMG signal. Examples of experimental sEMG signals are provided to show the potential value of high-density sEMG electrode grids and multichannel amplifiers that allow to add spatial information to the temporal information content of the sEMG signal. Furthermore, the results of a simple simulation are reported, in order to emphasize the effects of the subcutaneous tissue layers and of the detection volume on the recorded sEMG signal. The second part of the manuscript focuses on the sEMG amplifier technology: the front end amplifier characteristics for signal conditioning, the methods for stimulation artifact reduction, filtering methods, safety requirements, and the methods for analog-to-digital conversion of the sEMG signal.

Time-frequency analysis and estimation of muscle fiber conduction velocity from surface EMG signals during explosive dynamic contractions.

Time-frequency analysis of the surface electromyographic (EMG) signal is used to assess muscle fiber membrane properties during dynamic contractions. The aim of this study was to compare the direct estimation of average muscle fiber conduction velocity (CV) with instantaneous mean frequency (iMNF) of surface EMG signals in isometric and explosive dynamic contractions. The muscles investigated were the vastus lateralis and medialis of both thighs in 12 male subjects. The isometric contractions were at linearly increasing force (0-100% of the maximal voluntary contraction in 10s). The explosive contractions were performed on a multipurpose ergometer-dynamometer (MED). The subject, sitting on the MED, performed six explosive contractions, separated by 2 min rest, by pushing against two force platforms and thrusting himself backwards with the maximum possible speed, while completely extending his legs. The estimated CV significantly increased with force in both the isometric (mean+/-S.D., from 3.24+/-0.34 to 5.12+/-0.31 m/s for vastus lateralis and from 3.17+/-0.26 to 5.11+/-0.34 m/s for vastus medialis, with force in the range 10-100% of the maximal voluntary contraction level) and explosive contractions (from 4.36+/-0.49 to 5.00+/-0.47 m/s for vastus lateralis, and from 4.32+/-0.46 to 4.94+/-0.44 m/s for vastus medialis, with force in the range 17.5-100% of maximal thrusting force). Moreover, estimated CV was not significantly different at the maximal force in the two exercises. On the contrary, iMNF, computed from the Choi-Williams time-frequency transform, was significantly lower in the explosive (57.7+/-8.2 and 66.5+/-10.3 Hz for vastus laterialis and medialis, respectively) than in the isometric exercises (73.7+/-9.2 and 75.0+/-8.5 Hz for vastus laterialis and medialis, respectively) and did not change with force in any of the conditions. It was concluded that EMG spectral features provide different information with respect to average muscle fiber CV in dynamic contractions. Thus, in general, they cannot be used to infer CV changes during the exertion of a dynamic task. A joint analysis of CV and EMG spectral features is necessary in this type of contractions.

Assessment of average muscle fiber conduction velocity from surface EMG signals during fatiguing dynamic contractions.

In this paper, we propose techniques of surface electromyographic (EMG) signal detection and processing for the assessment of muscle fiber conduction velocity (CV) during dynamic contractions involving fast movements. The main objectives of the study are: 1) to present multielectrode EMG detection systems specifically designed for dynamic conditions (in particular, for CV estimation); 2) to propose a novel multichannel CV estimation method for application to short EMG signal bursts; and 3) to validate on experimental signals different choices of the processing parameters. Linear adhesive arrays of electrodes are presented for multichannel surface EMG detection during movement. A new multichannel CV estimation algorithm is proposed. The algorithm provides maximum likelihood estimation of CV from a set of surface EMG signals with a window limiting the time interval in which the mean square error (mse) between aligned signals is minimized. The minimization of the windowed mse function is performed in the frequency domain, without limitation in time resolution and with an iterative computationally efficient procedure. The method proposed is applied to signals detected from the vastus laterialis and vastus medialis muscles during cycling at 60 cycles/min. Ten subjects were investigated during a 4-min cycling task. The method provided reliable assessment of muscle fatigue for these subjects during dynamic contractions.