Motor unit number estimation based on high-density surface electromyography decomposition

Sarcopenia Diagnostic Technique Based on Artificial Intelligence Using Bio-signal of Neuromuscular System: A Proof-of-Concept Study

In this paper, we propose an artificial intelligence (AI)-based sarcopenia diagnostic technique for stroke patients utilizing bio-signals from the neuromuscular system. Handgrip, skeletal muscle mass index, and gait speed are prerequisite components for sarcopenia diagnoses. However, measurement of these parameters is often challenging for most hemiplegic stroke patients. For these reasons, there is an imperative need to develop a sarcopenia diagnostic technique that requires minimal volitional participation but nevertheless still assesses the muscle changes related to sarcopenia. The proposed AI diagnostic technique collects motor unit responses from stroke patients in a resting state via stimulated muscle contraction signals (SMCSs) recorded from surface electromyography while applying electrical stimulation to the muscle. For this study, we extracted features from SMCS collected from stroke patients and trained our AI model for sarcopenia diagnosis. We validated the performance of the trained AI models for each gender against other diagnostic parameters. The accuracy of the AI sarcopenia model was 96%, and 95% for male and females, respectively. Through these results, we were able to provide preliminary proof that SMCS could be a potential surrogate biomarker to reflect sarcopenia in stroke patients.

Enhanced Dynamic Surface EMG Decomposition Using the Non-Negative Matrix Factorization and Three-Dimensional Motor Unit Localization

OBJECTIVE

Surface electromyography (sEMG) signal decomposition is of great importance in examining neuromuscular diseases and neuromuscular research, especially dynamic sEMG decomposition is even more technically challenging.

METHODS

A novel two-step sEMG decomposition approach was developed. The linear minimum mean square error estimation was first employed to extract estimated firing trains (EFTs) from the eigenvector matrices constructed using the non-negative matrix factorization (NMF). The firing instants of each EFT were then classified into motor units (MUs) according to their specific three-dimensional (3D) space position. The performance of the proposed approach was evaluated using simulated and experimentally recorded sEMG.

RESULTS

The simulation results demonstrated that the proposed approach can reconstruct MUAPTs with true positive rates of 89.12 ± 2.71%, 94.34 ± 1.85% and 95.45 ± 2.11% at signal-to-noise ratios of 10, 20, and 30 dB, respectively. The experimental results also demonstrated a high decomposition accuracy of 90.13 ± 1.31% in the two-source evaluation, and a high accuracy of 91.86 ± 1.14% in decompose-synthesize-decompose- compare evaluation.

CONCLUSIONS

The adoption of NMF reduces the dimension of random pattern under the restriction of non-negativity, as well as keeps the information unchanged as much as possible. The 3D space information of MUs enhances the classification accuracy by tackling the issue of relative movements between MUs and electrodes during dynamic contractions. The accuracy achieved in this study demonstrates the good performance and reliability of the proposed decomposition algorithm in dynamic surface EMG decomposition.

SIGNIFICANCE

The spatiotemporal information is applied to the dynamic surface EMG decomposition.

MUNIX repeatability evaluation method based on FastICA demixing

To enhance the reproducibility of motor unit number index (MUNIX) for evaluating neurological disease progression, this paper proposes a negative entropy-based fast independent component analysis (FastICA) demixing method to assess MUNIX reproducibility in the presence of inter-channel mixing of electromyography (EMG) signals acquired by high-density electrodes. First, composite surface EMG (sEMG) signals were obtained using high-density surface electrodes. Second, the FastICA algorithm based on negative entropy was employed to determine the orthogonal projection matrix that minimizes the negative entropy of the projected signal and effectively separates mixed sEMG signals. Finally, the proposed experimental approach was validated by introducing an interrelationship criterion to quantify independence between adjacent channel EMG signals, measuring MUNIX repeatability using coefficient of variation (CV), and determining motor unit number and size through MUNIX. Results analysis shows that the inclusion of the full (128) channel sEMG information leads to a reduction in CV value by $1.5 \pm 0.1$ and a linear decline in CV value with an increase in the number of channels. The correlation between adjacent channels in participants decreases by $0.12 \pm 0.05$ as the number of channels gradually increases. The results demonstrate a significant reduction in the number of interrelationships between sEMG signals following negative entropy-based FastICA processing, compared to the mixed sEMG signals. Moreover, this decrease in interrelationships becomes more pronounced with an increasing number of channels. Additionally, the CV of MUNIX gradually decreases with an increase in the number of channels, thereby optimizing the issue of abnormal MUNIX repeatability patterns and further enhancing the reproducibility of MUNIX based on high-density surface EMG signals.

A scoping review of current and emerging techniques for evaluation of peripheral nerve health, degeneration, and regeneration: part 1, neurophysiology

Peripheral neuroregeneration research and therapeutic options are expanding exponentially. With this expansion comes an increasing need to reliably evaluate and quantify nerve health. Valid and responsive measures that can serve as biomarkers of the nerve status are essential for both clinical and research purposes for diagnosis, longitudinal follow-up, and monitoring the impact of any intervention. Furthermore, such biomarkers can elucidate regeneration mechanisms and open new avenues for research. Without these measures, clinical decision-making falls short, and research becomes more costly, time-consuming, and sometimes infeasible. As a companion to Part 2, which is focused on non-invasive imaging, Part 1 of this two-part scoping review systematically identifies and critically examines many current and emerging neurophysiological techniques that have the potential to evaluate peripheral nerve health, particularly from the perspective of regenerative therapies and research.

A Novel Analysis of Compound Muscle Action Potential Scan: Staircase Function Fitting and StairFit Motor Unit Number Estimation

Compound muscle action potential (CMAP) scan provides a detailed stimulus-response curve for examination of neuromuscular disease. The objective of the study is to develop a novel CMAP scan analysis to extract motor unit number estimation (MUNE) and other physiological or diagnostic information. A staircase function was used as the basic mathematical model of the CMAP scan. An optimal staircase function fitting model was estimated for each given number of motor units, and the fitting model with the minimum number of motor units that meets a predefined error requirement was accepted. This yields MUNE as well as the spike amplitude and activation threshold of each motor unit that contributes to the CMAP scan. The significance of the staircase function fit was confirmed using simulated CMAP scans with different motor unit number (20, 50, 100 and 150) and baseline noise (1 µV, 5 µV and 10 µV) inputs, in terms of MUNE performance, repeatability, and the test-retest reliability. For experimental data, the average MUNE of the first dorsal interosseous muscle derived from the staircase function fitting was 57.5 ± 26.9 for the tested spinal cord injury subjects, which was significantly lower than 101.2 ± 16.9, derived from the control group (p < 0.001). The staircase function fitting provides an appropriate approach to CMAP scan processing, yielding MUNE and other useful parameters for examination of motor unit loss and muscle fiber reinnervation.

Motor Unit Number Estimation in Spastic Biceps Brachii Muscles of Chronic Stroke Survivors Before and After BoNT Injection

OBJECTIVE

The study aims to characterize the motor unit (MU) loss in spastic biceps brachii muscle (BBM) of chronic stroke survivors before and after botulinum neurotoxin (BoNT) injection.

METHODS

High-density weighted average (HDWA) motor unit number estimation (MUNE) was employed to estimate the number of functioning motor units of BBMs of eight chronic stroke survivors 1-week before (1st visit) and 3-week after (2nd visit) BoNT injection based on the surface electromyography (sEMG) signals recorded during voluntary contraction and supramaximal electrical stimulation.

RESULT

Significant lower MUNE was estimated from the spastic BBMs compared to the non-spastic MUNEs during two visits. A surprisingly higher MUNE was obtained from the spastic side during the 2nd visit after BoNT injection.

CONCLUSIONS

The HDWA MUNE technique can be employed to characterize the motor unit loss in spastic muscle caused by upper motor neuro lesions at contraction level up to 30% MVC, but may fail to detect the MU loss caused by the chemodenervation effect of BoNT due to the non-uniform denervation of small and large size MUs.

SIGNIFICANCE

This study presents the first effort to evaluate the applicability of HDWA MUNE technique to characterize the MU loss in the spastic muscle following stroke and the subsequent BoNT injection for the treatment of post-stroke spasticity. The finding of this study suggests that HDWA MUNE can be a sensitive approach to detect the MU loss in spastic muscles after stroke, but the large inter-subject MUNE variability after the BoNT injection should be interpreted with caution.

Evaluation method of motor unit number index based on optimal muscle strength combination

Repeatability is an important attribute of motor unit number index (MUNIX) technology. This paper proposes an optimal contraction force combination for MUNIX calculation in an effort to improve the repeatability of this technology. In this study, the surface electromyography (EMG) signals of the biceps brachii muscle of eight healthy subjects were initially recorded with high-density surface electrodes, and the contraction strength was the maximum voluntary contraction force of nine progressive levels. Then, by traversing and comparing the repeatability of MUNIX under various combinations of contraction force, the optimal combination of muscle strength is determined. Finally, calculate MUNIX using the high-density optimal muscle strength weighted average method. The correlation coefficient and the coefficient of variation are utilized to assess repeatability. The results show that when the muscle strength combination is 10, 20, 50 and 70% of the maximum voluntary contraction force, the repeatability of MUNIX is greatest, and the correlation between MUNIX calculated using this combination of muscle strength and conventional methods is high (PCC > 0.99), the repeatability of the MUNIX method improved by 11.5-23.8%. The results indicate that the repeatability of MUNIX differs for various combinations of muscle strength and that MUNIX, which is measured with a smaller number and lower-level contractility, has greater repeatability.

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 < 0.05), whereas their motor unit size index (MUSIX) scores were positively correlated with the course the of disease (p < 0.05). MUNIX sum scores were correlated with SBMAFRS scores (r = 0.714, p < 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.

CMAP Scan Examination of the First Dorsal Interosseous Muscle After Spinal Cord Injury

The study assessed motor unit loss in muscles paralyzed by spinal cord injury (SCI) using a novel compound muscle action potential (CMAP) scan examination. The CMAP scan of the first dorsal interosseous (FDI) muscle was applied in tetraplegia (n = 13) and neurologically intact (n = 13) subjects. MScanFit was used for estimating motor unit numbers in each subject. The D50 value of the CMAP scan was also calculated. We observed a significant decrease in both CMAP amplitude and motor unit number estimation (MUNE) in paralyzed FDI muscles, as compared with neurologically intact muscles. Across all subjects, the CMAP (negative peak) amplitude was 8.01 ± 3.97 mV for the paralyzed muscles and 16.75 ± 3.55 mV for the neurologically intact muscles (p < 0.001). The CMAP scan resulted in a MUNE of 59 ± 37 for the paralyzed muscles, much lower than 108 ± 21 for the neurologically intact muscles (p < 0.001). No significant difference in D50 was observed between the two groups (p = 0.2). For the SCI subjects, there was no significant correlation between MUNE and CMAP amplitude, or any of the clinical assessments including pinch force, grip force, the Graded Redefined Assessment of Strength, Sensibility and Prehension (GRASSP) score, and SCI duration (p > 0.05). The findings provide an evidence of motor unit loss in the FDI muscles of individuals with tetraplegia, which may contribute to weakness and other hand function deterioration. The CMAP scan offers several practical benefits compared with the traditional MUNE techniques because it is noninvasive, automated and can be performed within several minutes.

Assessment of grip-motion characteristics in carpal tunnel syndrome patients using a novel finger grip dynamometer system

Background

Grip strength measurement is widely used in daily medical practice, and it has been reported that the grip strength decreases in patients with carpal tunnel syndrome (CTS). However, conventional grip dynamometers evaluate only the maximum power of total grip strength and cannot measure the time course of grip motion. In this report, we aimed to determine the grip characteristics of CTS patients by measuring the time course of each finger’s grip motion and to analyze the relationship between finger grip strength and subjective symptoms using this new grip system.

Methods

The grip strength of each finger was measured using the new grip system that has four pressure sensors on the grip parts of each finger of the Smedley grip dynamometer. We analyzed the time course of grip motion and relationship between finger grip strength and subjective symptoms in 104 volunteer and 51 CTS hands. The Japanese Society for Surgery of the Hand version of the Carpal Tunnel Syndrome Instrument (CTSI-JSSH) and the Disability of Arm, Shoulder, and Hand questionnaire (DASH) were used as subjective evaluation scores.

Results

In the CTS group, the grip time with the index, middle, and ring fingers was longer, and the time at which strength was lost after reaching the maximum was earlier. Patients with severe subjective symptoms tended to not use the index and middle fingers during grip motion.

Conclusions

This new system that measures each finger’s grip strength at one time and record the time course of grip motion could quantify a patient’s symptoms easily and objectively, which may contribute to the evaluation of hand function.

Neural control properties of the external anal sphincter in young and elderly women

AIMS

The prevalence of fecal incontinence (FI) increases with age and affects more than 15% of the elderly population. Sarcopenia, skeletal muscle structural, and functional decline with aging, is known to be caused by neuromuscular dysfunction. However, age-related alterations of the neuromuscular function of the external anal sphincter (EAS) have not been studied. This study aims to quantitatively characterize the effect of aging on the EAS by assessing the firing patterns and size of motor unit action potential (MUAP) using high-density surface electromyography (HD-sEMG) recording and analysis techniques.

METHODS

Thirteen young (31.0 ± 3.6 years) and 14 elderly (64.3 ± 6.2 years) healthy women were recruited for this study. EMG activity of the EAS during maximal voluntary contraction was recorded by a 64-Channel, HD-sEMG intra-rectal probe. HD-sEMG signals were decomposed into MUAP spike trains to extract the firing rate and amplitudes thereof.

RESULTS

HD-sEMG decomposition was successfully performed. For the young and elderly groups, mean motor unit (MU) firing rates of 11.4 ± 2.1 pulses per second (PPS) and 9.6 ± 2.3 PPS, and mean MUAP amplitudes of 45.2 ± 14.3 µV and 61.9 ± 21.2 µV were respectively obtained. Both the MU firing rate and MUAP amplitude were significantly different between two groups (P < .05). Moreover, the MUAP firing rate and amplitude correlated with age with a linear regression model (P < .05).

CONCLUSIONS

This study represents the first effort to examine the effect of aging on the neuromuscular function of EAS. Results suggest an age-related impairment of lower motor neuron descending excitation to the EAS with a compensatory increase in mean MU size.

Global Innervation Zone Identification With High-Density Surface Electromyography

OBJECTIVE

The aim of this study is to compare the performance of three strategies in determining the global innervation zone (IZ) distribution.

METHODS

High-density surface electromyography was recorded from the biceps brachii muscle of seven healthy subjects under isometric voluntary contractions at 20%, 50%, and 100% of the maximal voluntary contraction and supramaximal musculocutaneous nerve stimulations. IZs were detected: first, by visual identification in a column-specific manner (IZ-1D); second, based on decomposed bipolar mapping of motor unit action potentials (IZ-2D); and third, by source imaging in the three-dimensional muscle space (IZ-3D).

RESULTS

All three IZ detection approaches have exhibited excellent trial-to-trial repeatability. Consistent IZ results were found in the axial direction of the arm across all three approaches, yet a difference was observed in the mediolateral direction.

CONCLUSIONS

Among all three approaches, IZ-3D is capable of providing the most comprehensive information regarding the global IZ distribution, while maintaining high consistency with IZ-1D and IZ-2D results.

SIGNIFICANCE

IZ-3D approach can be a potential tool for global IZ imaging, which is critical to the clinical diagnosis and treatment of neuromuscular disorders.

Modern Theories of Pelvic Floor Support : A Topical Review of Modern Studies on Structural and Functional Pelvic Floor Support from Medical Imaging, Computational Modeling, and Electromyographic Perspectives

PURPOSE OF REVIEW

Weakened pelvic floor support is believed to be the main cause of various pelvic floor disorders. Modern theories of pelvic floor support stress on the structural and functional integrity of multiple structures and their interplay to maintain normal pelvic floor functions. Connective tissues provide passive pelvic floor support while pelvic floor muscles provide active support through voluntary contraction. Advanced modern medical technologies allow us to comprehensively and thoroughly evaluate the interaction of supporting structures and assess both active and passive support functions. The pathophysiology of various pelvic floor disorders associated with pelvic floor weakness is now under scrutiny from the combination of (1) morphological, (2) dynamic (through computational modeling), and (3) neurophysiological perspectives. This topical review aims to update newly emerged studies assessing pelvic floor support function among these three categories.

RECENT FINDINGS

A literature search was performed with emphasis on (1) medical imaging studies that assess pelvic floor muscle architecture, (2) subject-specific computational modeling studies that address new topics such as modeling muscle contractions, and (3) pelvic floor neurophysiology studies that report novel devices or findings such as high-density surface electromyography techniques. We found that recent computational modeling studies are featured with more realistic soft tissue constitutive models (e.g., active muscle contraction) as well as an increasing interest in simulating surgical interventions (e.g., artificial sphincter). Diffusion tensor imaging provides a useful non-invasive tool to characterize pelvic floor muscles at the microstructural level, which can be potentially used to improve the accuracy of the simulation of muscle contraction. Studies using high-density surface electromyography anal and vaginal probes on large patient cohorts have been recently reported. Influences of vaginal delivery on the distribution of innervation zones of pelvic floor muscles are clarified, providing useful guidance for a better protection of women during delivery. We are now in a period of transition to advanced diagnostic and predictive pelvic floor medicine. Our findings highlight the application of diffusion tensor imaging, computational models with consideration of active pelvic floor muscle contraction, high-density surface electromyography, and their potential integration, as tools to push the boundary of our knowledge in pelvic floor support and better shape current clinical practice.

Effect of static and dynamic muscle stretching as part of warm up procedures on knee joint proprioception and strength

BACKGROUND

The importance of warm up procedures prior to athletic performance is well established. A common component of such procedures is muscle stretching. There is conflicting evidence regarding the effect of static stretching (SS) as part of warm up procedures on knee joint position sense (KJPS) and the effect of dynamic stretching (DS) on KJPS is currently unknown. The aim of this study was to determine the effect of dynamic and static stretching as part warm up procedures on KJPS and knee extension and flexion strength.

METHODS

This study had a randomised cross-over design and ten healthy adults (20±1years) attended 3 visits during which baseline KJPS, at target angles of 20° and 45°, and knee extension and flexion strength tests were followed by 15min of cycling and either a rest period (CON), SS, or DS and repeat KJPS and strength tests. All participants performed all conditions, one condition per visit.

RESULTS

There were warm up×stretching type interactions for KJPS at 20° (p=0.024) and 45° (p=0.018), and knee flexion (p=0.002) and extension (p<0.001) strength. The SS and DS improved KJPS but CON condition did not and SS decreased strength. No change in strength was present for DS or CON.

CONCLUSIONS

Both SS and DS improve KJPS as part of pre-exercise warm up procedures. However, the negative impact of SS on muscle strength limits the utility of SS before athletic performance. If stretching is to be performed as part of a warm up, DS should be favoured over SS.

Improving the repeatability of Motor Unit Number Index (MUNIX) by introducing additional epochs at low contraction levels

OBJECTIVE

To evaluate the repeatability of (Motor Unit Number Index) MUNIX under repeatability conditions, specify the origin of variations and provide strategies for quality control.

METHODS

MUNIX calculations were performed on the bicep brachii muscles of eight healthy subjects. Negative effect of suboptimal electrode positions on MUNIX accuracy was eliminated by employing the high-density surface electromyography technique. MUNIX procedures that utilized a variety of surface interferential pattern (SIP) epoch recruitment strategies (including the original MUNIX procedure, two proposed improvement strategies and their combinations) were described. For each MUNIX procedure, ten thousands of different SIP pools were constructed by randomly recruiting necessary SIP epochs from a large SIP epoch pool (3 datasets, 9 independent electromyography recordings at different contraction levels per dataset and 10 SIP epochs per recording) and implemented for MUNIX calculation. The repeatability of each MUNIX procedure was assessed by summarizing the resulting MUNIX distribution and compared to investigate the effect of SIP epoch selection strategy on repeatability performance.

RESULTS

SIP epochs selected at lower contraction levels have a stronger influence on the repeatability of MUNIX than those selected at higher contraction levels. MUNIX under repeatability conditions follows a normal distribution and the standard deviation can be significantly reduced by introducing more epochs near the MUNIX definition line.

CONCLUSIONS

The MUNIX technique shows an inherent variation attributable to SIP epochs at low contraction levels. It is recommended that more epochs should be sampled at these low contraction levels to improve the repeatability.

SIGNIFICANCE

The present study thoroughly documented the inherent variation of MUNIX and the causes, and offered practical solutions to improve the repeatability of MUNIX.