Impaired regulation post-stroke of motor unit firing behavior during volitional relaxation of knee extensor torque assessed using high density surface EMG decomposition

The Relationship Between Blood Flow and Motor Unit Firing Rates in Response to Fatiguing Exercise Post-stroke

We quantified the relationship between the change in post-contraction blood flow with motor unit firing rates and metrics of fatigue during intermittent, sub-maximal fatiguing contractions of the knee extensor muscles after stroke. Ten chronic stroke survivors (>1-year post-stroke) and nine controls participated. Throughout fatiguing contractions, the discharge timings of individual motor units were identified by decomposition of high-density surface EMG signals. After five consecutive contractions, a blood flow measurement through the femoral artery was obtained using an ultrasound machine and probe designed for vascular measurements. There was a greater increase of motor unit firing rates from the beginning of the fatigue protocol to the end of the fatigue protocol for the control group compared to the stroke group (14.97 ± 3.78% vs. 1.99 ± 11.90%, p = 0.023). While blood flow increased with fatigue for both groups (p = 0.003), the magnitude of post-contraction blood flow was significantly greater for the control group compared to the stroke group (p = 0.004). We found that despite the lower magnitude of muscle perfusion through the femoral artery in the stroke group, blood flow has a greater impact on peripheral fatigue for the control group; however, we observed a significant correlation between change in blood flow and motor unit firing rate modulation (r² = 0.654, p = 0.004) during fatigue in the stroke group and not the control group (r² = 0.024, p < 0.768). Taken together, this data showed a disruption between motor unit firing rates and post-contraction blood flow in the stroke group, suggesting that there may be a disruption to common inputs to both the reticular system and the corticospinal tract. This study provides novel insights in the relationship between the hyperemic response to exercise and motor unit firing behavior for post-stroke force production and may provide new approaches for recovery by improving both blood flow and muscle activation simultaneously.

Multiparameter Electromyography Analysis of the Masticatory Muscle Activities in Patients with Brainstem Stroke at Different Head Positions

The performance of the masticatory muscle is frequently affected and presents high heterogeneity poststroke. Surface electromyography (EMG) is widely used to quantify muscle movement patterns. However, only a few studies applied EMG analysis on the research of masticatory muscle activities poststroke, and most of which used single parameter—root mean squares (RMS). The aim of this study was to fully investigate the performance of masticatory muscle at different head positions in healthy subjects and brainstem stroke patients with multiparameter EMG analysis. In this study, 15 healthy subjects and six brainstem stroke patients were recruited to conduct maximum voluntary clenching at five different head positions: upright position, left rotation, right rotation, dorsal flexion, and ventral flexion. The EMG signals of bilateral temporalis anterior and masseter muscles were recorded, and parameters including RMS, median frequency, and fuzzy approximate entropy of the EMG signals were calculated. Two-way analysis of variance (ANOVA) with repeated measures and Bonferroni post hoc test were used to evaluate the effects of muscle and head position on EMG parameters in the healthy group, and the non-parametric Wilcoxon signed rank test was conducted in the patient group. The Welch–Satterthwaite t-test was used to compare the between-subject difference. We found a significant effect of subject and muscles but no significant effect of head positions, and the masticatory muscles of patients after brainstem stroke performed significantly different from healthy subjects. Multiparameter EMG analysis might be an informative tool to investigate the neural activity related movement patterns of the deficient masticatory muscles poststroke.

The potential for understanding the synaptic organization of human motor commands via the firing patterns of motoneurons

Motoneurons are unique in being the only neurons in the CNS whose firing patterns can be easily recorded in human subjects. This is because of the one-to-one relationship between the motoneuron and muscle cell behavior. It has long been appreciated that the connection of motoneurons to their muscle fibers allows their action potentials to be amplified and recorded, but only recently has it become possible to simultaneously record the firing pattern of many motoneurons via array electrodes placed on the skin. These firing patterns contain detailed information about the synaptic organization of motor commands to the motoneurons. This review focuses on parameters in these firing patterns that are directly linked to specific features of this organization. It is now well established that motor commands consist of three components, excitation, inhibition, and neuromodulation; the importance of the third component has become increasingly evident. Firing parameters linked to each of the three components are discussed, along with consideration of potential limitations in their utility for understanding the underlying organization of motor commands. Future work based on realistic computer simulations of motoneurons may allow quantitative "reverse engineering" of human motoneuron firing patterns to provide good estimates of the relative amplitudes and temporal patterns of all three components of motor commands.

A preliminary evaluation of myoelectrical energy distribution of the front neck muscles in pharyngeal phase during normal swallowing

Pharyngeal phase is a central hub of swallowing in which food bolus pass through from the oral cavity to the esophageal. Proper understanding of the muscular activities in the pharyngeal phase is useful for assessing swallowing function and the occurrence of dysphagia in humans. In this study, high-density (HD) surface electromyography (sEMG) was used to study the muscular activities in the pharyngeal phase during swallowing tasks involving three healthy male subjects. The root mean square (RMS) of the HD sEMG data was computed by using a series of segmented windows as myoelectrical energy. And the RMS of each window covering all channels (16×5) formed a matrix. During the pharyngeal phase of swallowing, three of the matrixes were chosen and normalized to obtain the HD energy maps and the statistical parameter. The maps across different viscosity levels offered the energy distribution which showed the muscular activities of the left and right sides of the front neck muscles. In addition, the normalized average RMS (NARE) across different viscosity levels revealed a left-right significant correlation (r=0.868±0.629, p<;0.01) quantitatively, while it showed even stronger correlation when swallowing water. This pilot study suggests that HD sEMG would be a potential tool to evaluate muscular activities in pharyngeal phase during normal swallowing. Also, it might provide useful information for dysphagia diagnosis.

Denoising of HD-sEMG signals using canonical correlation analysis

High-density surface electromyography (HD-sEMG) is a recent technique that overcomes the limitations of monopolar and bipolar sEMG recordings and enables the collection of physiological and topographical informations concerning muscle activation. However, HD-sEMG channels are usually contaminated by noise in an heterogeneous manner. The sources of noise are mainly power line interference (PLI), white Gaussian noise (WGN) and motion artifacts (MA). The spectral components of these disruptive signals overlap with the sEMG spectrum which makes classical filtering techniques non effective, especially during low contraction level recordings. In this study, we propose to denoise HD-sEMG recordings at 20 % of the maximum voluntary contraction by using a second-order blind source separation technique, named canonical component analysis (CCA). For this purpose, a specific and automatic canonical component selection, using noise ratio thresholding, and a channel selection procedure for the selective version (sCCA) are proposed. Results obtained from the application of the proposed methods (CCA and sCCA) on realistic simulated data demonstrated the ability of the proposed approach to retrieve the original HD-sEMG signals, by suppressing the PLI and WGN components, with high accuracy (for five different simulated noise dispersions using the same anatomy). Afterward, the proposed algorithms are employed to denoise experimental HD-sEMG signals from five healthy subjects during biceps brachii contractions following an isometric protocol. Obtained results showed that PLI and WGN components could be successfully removed, which enhances considerably the SNR of the channels with low SNR and thereby increases the mean SNR value among the grid. Moreover, the MA component is often isolated on specific estimated sources but requires additional signal processing for a total removal. In addition, comparative study with independent component analysis, CCA-wavelet and CCA-empirical mode decomposition (EMD) proved a higher efficiency of the presented method over existing denoising techniques and demonstrated pointless a second filtering stage for denoising HD-sEMG recordings at this contraction level.