Spatial Analysis of Multichannel Surface EMG in Hemiplegic Stroke

Interpreting Stroke-Impaired Electromyography Patterns through Explainable Artificial Intelligence

Electromyography (EMG) proves invaluable myoelectric manifestation in identifying neuromuscular alterations resulting from ischemic strokes, serving as a potential marker for diagnostics of gait impairments caused by ischemia. This study aims to develop an interpretable machine learning (ML) framework capable of distinguishing between the myoelectric patterns of stroke patients and those of healthy individuals through Explainable Artificial Intelligence (XAI) techniques. The research included 48 stroke patients (average age 70.6 years, 65% male) undergoing treatment at a rehabilitation center, alongside 75 healthy adults (average age 76.3 years, 32% male) as the control group. EMG signals were recorded from wearable devices positioned on the bicep femoris and lateral gastrocnemius muscles of both lower limbs during indoor ground walking in a gait laboratory. Boosting ML techniques were deployed to identify stroke-related gait impairments using EMG gait features. Furthermore, we employed XAI techniques, such as Shapley Additive Explanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME), and Anchors to interpret the role of EMG variables in the stroke-prediction models. Among the ML models assessed, the GBoost model demonstrated the highest classification performance (AUROC: 0.94) during cross-validation with the training dataset, and it also overperformed (AUROC: 0.92, accuracy: 85.26%) when evaluated using the testing EMG dataset. Through SHAP and LIME analyses, the study identified that EMG spectral features contributing to distinguishing the stroke group from the control group were associated with the right bicep femoris and lateral gastrocnemius muscles. This interpretable EMG-based stroke prediction model holds promise as an objective tool for predicting post-stroke gait impairments. Its potential application could greatly assist in managing post-stroke rehabilitation by providing reliable EMG biomarkers and address potential gait impairment in individuals recovering from ischemic stroke.

Advances in EMG measurement techniques, analysis procedures, and the impact of muscle mechanics on future requirements for the methodology

Muscular coordination enables locomotion and interaction with the environment. For more than 50 years electromyography (EMG) has provided insights into the central nervous system control of individual muscles or muscle groups, enabling both fine and gross motor functions. This information is available either at individual motor units (Mus) level or on a more global level from the coordination of different muscles or muscle groups. In particular, non-invasive EMG methods such as surface EMG (sEMG) or, more recently, spatial mapping methods (High-Density EMG - HDsEMG) have found their place in research into biomechanics, sport and exercise, ergonomics, rehabilitation, diagnostics, and increasingly for the control of technical devices. With further technical advances and a growing understanding of the relationship between EMG and movement task execution, it is expected that with time, especially non-invasive EMG methods will become increasingly important in movement sciences. However, while the total number of publications per year on non-invasive EMG methods is growing exponentially, the number of publications on this topic in journals with a scope in movement sciences has stagnated in the last decade. This review paper contextualizes non-invasive EMG development over the last 50 years, highlighting methodological progress. Changes in research topics related to non-invasive EMG were identified. Today non-invasive EMG procedures are increasingly used to control technical devices, where muscle mechanics have a minor influence. In movement science, however, the effect of muscle mechanics on the EMG signal cannot be neglected. This explains why non-invasive EMG's relevance in movement sciences has not developed as expected.

Surface electromyography characteristics of patients with anterior cruciate ligament injury in different rehabilitation phases

Background: Anterior cruciate ligament reconstruction (ACLR) is a common treatment for anterior cruciate ligament (ACL) injury. However, after ACLR, a significant proportion of patients do not return to pre-injury levels. Research on muscle function during movement has important implications in rehabilitation.

Methods: Sixty patients with unilateral ACL injury were recruited for this study and assigned into three groups: group A, individuals with an ACL injury before 6 months; group B, individuals with ACLR from 6 months to 1 year; and group C, individuals with ACLR 1 year later. Surface electromyography (SEMG) signals were collected from the bilateral rectus femoris (RF), vastus medialis (VM), vastus lateralis (VL), biceps femoris (BF), and semitendinosus (ST). The tasks performed during the experiment included straight leg raising (SLR) training at 30°, SLR training at 60°, ankle dorsiflexion, walking, and fast walking.

Results: In the maximum muscle strength test, the affected side of the BF in group A (199.4 ± 177.12) was significantly larger than in group B (53.91 ± 36.61, p = 0.02) and group C (75.08 ± 59.7, p = 0.023). In the walking test, the contralateral side of the RF in group B (347.53 ± 518.88) was significantly greater than that in group C (139.28 ± 173.78, p = 0.029). In the SLR training (60°) test, the contralateral side of the RF in group C (165.37 ± 183.06) was significantly larger than that in group A (115.09 ± 62.47, p = 0.023) and smaller than that in group B (226.21 ± 237.17, p = 0.046); In the ankle dorsiflexion training test, the contralateral side of the RF in group B (80.37 ± 87.9) was significantly larger than that in group C (45.61 ± 37.93, p = 0.046).

Conclusion: This study showed the EMG characteristics of patients with ACL injury helped to determine which muscle requires more training and which exercise model would be best suited for intervention.

Muscle innervation zone estimation from monopolar high-density M-waves using principal component analysis and radon transform

This study examined methods for estimating the innervation zone (IZ) of a muscle using recorded monopolar high density M waves. Two IZ estimation methods based on principal component analysis (PCA) and Radon transform (RT) were examined. Experimental M waves, acquired from the biceps brachii muscles of nine healthy subjects were used as testing data sets. The performance of the two methods was evaluated by comparing their IZ estimations with manual IZ detection by experienced human operators. Compared with manual detection, the agreement rate of the estimated IZs was 83% and 63% for PCA and RT based methods, respectively, both using monopolar high density M waves. In contrast, the agreement rate was 56% for cross correlation analysis using bipolar high density M waves. The mean difference in estimated IZ location between manual detection and the tested method was 0.12 ± 0.28 inter-electrode-distance (IED) for PCA, 0.33 ± 0.41 IED for RT and 0.39 ± 0.74 IED for cross correlation-based methods. The results indicate that the PCA based method was able to automatically detect muscle IZs from monopolar M waves. Thus, PCA provides an alternative approach to estimate IZ location of voluntary or electrically-evoked muscle contractions, and may have particular value for IZ detection in patients with impaired voluntary muscle activation.

Translation of surface electromyography to clinical and motor rehabilitation applications: The need for new clinical figures

Advanced sensors/electrodes and signal processing techniques provide powerful tools to analyze surface electromyographic signals (sEMG) and their features, to decompose sEMG into the constituent motor unit action potential trains, and to identify synergies, neural muscle drive, and EEG-sEMG coherence. However, despite thousands of articles, dozens of textbooks, tutorials, consensus papers, and European and International efforts, the translation of this knowledge into clinical activities and assessment procedures has been very slow, likely because of lack of clinical studies and competent operators in the field. Understanding and using sEMG-based hardware and software tools requires a level of knowledge of signal processing and interpretation concepts that is multidisciplinary and is not provided by most academic curricula in physiotherapy, movement sciences, neurophysiology, rehabilitation, sport, and occupational medicine. The chasm existing between the available knowledge and its clinical applications in this field is discussed as well as the need for new clinical figures. The need for updating the training of physiotherapists, neurophysiology technicians, and clinical technologists is discussed as well as the required competences of trainers and trainees. Indications and examples are suggested and provide a basis for addressing the problem. Two teaching examples are provided in the Supplementary Material.

Effects of kinesio taping therapy on gait and surface electromyography in stroke patients with hemiplegia

Background: The application of Kinesio Taping (KT) on the lower extremity of stroke patients can improve the quality of somatosensory information by activating lower extremity muscles involved in postural control. Gait analysis and surface electromyography (SEMG) are valuable in assessing the motor ability of the lower extremities.

Objective: This study aimed to investigate the effects of KT therapy on gait and SEMG in stroke patients with hemiplegia.

Methods: Twenty-one stroke patients were included in the study. KT was applied to the lower extremities of the hemiplegic side. Quantitative gait parameters were measured by a gait analysis system (IDEEA, by MiniSun, United States) and activation of the lower extremity muscles were evaluated by the SEMG (Trigno™ Wireless Systems, Delsys Inc., United States) before and after taping. Step length, stride length, pulling acceleration, swing power, ground impact, and energy expenditure were used to evaluate when patients walk as usual. SEMG signals were collected from the anterior bilateral tibialis (TA) and the lateral gastrocnemius (LG). The root mean square (RMS) value was used to assess muscle activity. SEMG signals were examined before and after KT treatment in three different locomotor conditions of the patients: walking at a natural speed, walking with a weight of 5 kg, dual-tasking walking (walking + calculation task) while carrying a weight of 5 kg. The calculation task was to ask the patients to calculate the result of subtracting 7 from 100 and continuing to subtract 7 from the resulting numbers. Comparisons between two normally distributed samples (before and after KT treatment) were evaluated using the two-tailed, paired Student’s t-test.

Results: Stride length (0.89 ± 0.19 vs. 0.96 ± 0.23; p = 0.029), pulling acceleration (0.40 ± 0.21 vs. 1.11 ± 0.74; p = 0.005), and swing power (0.42 ± 0.24 vs. 1.14 ± 0.72; p = 0.004) improved in the hemiplegia side after KT treatment. The RMS value of TA SEMG signals in the limbs on the hemiplegia side decreased after KT treatment during dual-tasking walking carrying a weight of 5 kg (3.65 ± 1.31 vs. 2.93 ± 0.95; p = 0.030).

Conclusion: KT treatment is effective in altering gait and SEMG characteristics in stroke patients with hemiplegia.

Fundamental Concepts of Bipolar and High-Density Surface EMG Understanding and Teaching for Clinical, Occupational, and Sport Applications: Origin, Detection, and Main Errors

Surface electromyography (sEMG) has been the subject of thousands of scientific articles, but many barriers limit its clinical applications. Previous work has indicated that the lack of time, competence, training, and teaching is the main barrier to the clinical application of sEMG. This work follows up and presents a number of analogies, metaphors, and simulations using physical and mathematical models that provide tools for teaching sEMG detection by means of electrode pairs (1D signals) and electrode grids (2D and 3D signals). The basic mechanisms of sEMG generation are summarized and the features of the sensing system (electrode location, size, interelectrode distance, crosstalk, etc.) are illustrated (mostly by animations) with examples that teachers can use. The most common, as well as some potential, applications are illustrated in the areas of signal presentation, gait analysis, the optimal injection of botulinum toxin, neurorehabilitation, ergonomics, obstetrics, occupational medicine, and sport sciences. The work is primarily focused on correct sEMG detection and on crosstalk. Issues related to the clinical transfer of innovations are also discussed, as well as the need for training new clinical and/or technical operators in the field of sEMG.

A Randomized Controlled Trial of Repetitive Peripheral Magnetic Stimulation applied in Early Subacute Stroke: Effects on Severe Upper-limb Impairment

OBJECTIVES

Repetitive peripheral magnetic stimulation (rPMS) is a non-invasive method that activates peripheral nerves and enhances muscle strength. This study aimed to investigate the effect of rPMS applied in early subacute stroke on severe upper extremity impairment.

DESIGN

Randomized controlled trial.

SETTING

Rehabilitation department of a university hospital.

SUBJECTS

People aged 30-80 years with no practical arm function within four weeks of a first stroke.

INTERVENTIONS

Participants were randomly assigned to either the rPMS group (n = 24, 20Hz and 2400 pulses of rPMS to triceps brachii and extensor digitorum muscles daily for two weeks in addition to conventional physiotherapy) or the control group (n = 20, conventional physiotherapy).

MAIN MEASURES

The primary outcome was the upper extremity motor section of Fugl-Meyer Assessment after treatment. Secondary outcomes included Barthel Index and root mean square of surface electromyography for muscle strength and stretch-induced spasticity of critical muscles of the upper extremity. Data presented: mean (SD) or median (IQR).

RESULTS

The rPMS group showed more significant improvements in the Fugl-Meyer Assessment (12.5 (2.5) vs. 7.0 (1.4), P < 0.001), Barthel Index (15 (5) vs. 10 (3.7), P < 0.001), and strength-root mean square (biceps brachii: 20.5 (4.8) vs. 6.2 (2.7), p < 0.001; triceps brachii: 14.9 (5.8) vs. 4.3 (1.2), p < 0.001; flexor digitorum: 5.1 (0.8) vs. 4.0 (1.1), p < 0.001) compared with the control group.

CONCLUSION

In patients with no functional arm movement, rPMS of upper limb extensors improves arm function and muscle strength for grip and elbow flexion and extension.

Neurophysiological Factors Affecting Muscle Innervation Zone Estimation Using Surface EMG: A Simulation Study

Surface electromyography (EMG) recorded by a linear or 2-dimensional electrode array can be used to estimate the location of muscle innervation zones (IZ). There are various neurophysiological factors that may influence surface EMG and thus potentially compromise muscle IZ estimation. The objective of this study was to evaluate how surface-EMG-based IZ estimation might be affected by different factors, including varying degrees of motor unit (MU) synchronization in the case of single or double IZs. The study was performed by implementing a model simulating surface EMG activity. Three different MU synchronization conditions were simulated, namely no synchronization, medium level synchronization, and complete synchronization analog to M wave. Surface EMG signals recorded by a 2-dimensional electrode array were simulated from a muscle with single and double IZs, respectively. For each situation, the IZ was estimated from surface EMG and compared with the one used in the model for performance evaluation. For the muscle with only one IZ, the estimated IZ location from surface EMG was consistent with the one used in the model for all the three MU synchronization conditions. For the muscle with double IZs, at least one IZ was appropriately estimated from interference surface EMG when there was no MU synchronization. However, the estimated IZ was different from either of the two IZ locations used in the model for the other two MU synchronization conditions. For muscles with a single IZ, MU synchronization has little effect on IZ estimation from electrode array surface EMG. However, caution is required for multiple IZ muscles since MU synchronization might lead to false IZ estimation.

Physiologic signaling and viability of the muscle cuff regenerative peripheral nerve interface (MC-RPNI) for intact peripheral nerves

Background. Robotic exoskeleton devices have become a promising modality for restoration of extremity function in individuals with limb loss or functional weakness. However, there exists no consistent or reliable way to record efferent motor action potentials from intact peripheral nerves to control device movement. Peripheral nerve motor action potentials are similar in amplitude to that of background noise, producing an unfavorable signal-to-noise ratio (SNR) that makes these signals difficult to detect and interpret. To address this issue, we have developed the muscle cuff regenerative peripheral nerve interface (MC-RPNI), a construct consisting of a free skeletal muscle graft wrapped circumferentially around an intact peripheral nerve. Over time, the muscle graft regenerates, and the intact nerve undergoes collateral axonal sprouting to reinnervate the muscle. The MC-RPNI amplifies efferent motor action potentials by several magnitudes, thereby increasing the SNR, allowing for higher fidelity signaling and detection of motor intention. The goal of this study was to characterize the signaling capabilities and viability of the MC-RPNI over time.Methods. Thirty-seven rats were randomly assigned to one of five experimental groups (Groups A-E). For MC-RPNI animals, their contralateral extensor digitorum longus (EDL) muscle was harvested and trimmed to either 8 mm (Group A) or 13 mm (Group B) in length, wrapped circumferentially around the intact ipsilateral common peroneal (CP) nerve, secured, and allowed to heal for 3 months. Additionally, one 8 mm (Group C) and one 13 mm (Group D) length group had an epineurial window created in the CP nerve immediately preceding MC-RPNI creation. Group E consisted of sham surgery animals. At 3 months, electrophysiologic analyses were conducted to determine the signaling capabilities of the MC-RPNI. Additionally, electromyography and isometric force analyses were performed on the CP-innervated EDL to determine the effects of the MC-RPNI on end organ function. Following evaluation, the CP nerve, MC-RPNI, and ipsilateral EDL muscle were harvested for histomorphometric analysis.Results. Study endpoint analysis was performed at 3 months post-surgery. All rats displayed visible muscle contractions in both the MC-RPNI and EDL following proximal CP nerve stimulation. Compound muscle action potentials were recorded from the MC-RPNI following proximal CP nerve stimulation and ranged from 3.67 ± 0.58 mV to 6.04 ± 1.01 mV, providing efferent motor action potential amplification of 10-20 times that of a normal physiologic nerve action potential. Maximum tetanic isometric force (F_o) testing of the distally-innervated EDL muscle in MC-RPNI groups producedF_o(2341 ± 114 mN-2832 ± 102 mN) similar to controls (2497 ± 122 mN), thus demonstrating that creation of MC-RPNIs did not adversely impact the function of the distally-innervated EDL muscle. Overall, comparison between all MC-RPNI sub-groups did not reveal any statistically significant differences in signaling capabilities or negative effects on distal-innervated muscle function as compared to the control group.Conclusions. MC-RPNIs have the capability to provide efferent motor action potential amplification from intact nerves without adversely impacting distal muscle function. Neither the size of the muscle graft nor the presence of an epineurial window in the nerve had any significant impact on the ability of the MC-RPNI to amplify efferent motor action potentials from intact nerves. These results support the potential for the MC-RPNI to serve as a biologic nerve interface to control advanced exoskeleton devices.

Prediction of Myoelectric Biomarkers in Post-Stroke Gait

Electromyography (EMG) is sensitive to neuromuscular changes resulting from ischemic stroke and is considered a potential predictive tool of post-stroke gait and rehabilitation management. This study aimed to evaluate the potential myoelectric biomarkers for the classification of stroke-impaired muscular activity of the stroke patient group and the muscular activity of the control healthy adult group. We also proposed an EMG-based gait monitoring system consisting of a portable EMG device, cloud-based data processing, data analytics, and a health advisor service. This system was investigated with 48 stroke patients (mean age 70.6 years, 65% male) admitted into the emergency unit of a hospital and 75 healthy elderly volunteers (mean age 76.3 years, 32% male). EMG was recorded during walking using the portable device at two muscle positions: the bicep femoris muscle and the lateral gastrocnemius muscle of both lower limbs. The statistical result showed that the mean power frequency (MNF), median power frequency (MDF), peak power frequency (PKF), and mean power (MNP) of the stroke group differed significantly from those of the healthy control group. In the machine learning analysis, the neural network model showed the highest classification performance (precision: 88%, specificity: 89%, accuracy: 80%) using the training dataset and highest classification performance (precision: 72%, specificity: 74%, accuracy: 65%) using the testing dataset. This study will be helpful to understand stroke-impaired gait changes and decide post-stroke rehabilitation.

Surface EMG in Clinical Assessment and Neurorehabilitation: Barriers Limiting Its Use

This article addresses the potential clinical value of techniques based on surface electromyography (sEMG) in rehabilitation medicine with specific focus on neurorehabilitation. Applications in exercise and sport pathophysiology, in movement analysis, in ergonomics and occupational medicine, and in a number of related fields are also considered. The contrast between the extensive scientific literature in these fields and the limited clinical applications is discussed. The "barriers" between research findings and their application are very broad, and are longstanding, cultural, educational, and technical. Cultural barriers relate to the general acceptance and use of the concept of objective measurement in a clinical setting and its role in promoting Evidence Based Medicine. Wide differences between countries exist in appropriate training in the use of such quantitative measurements in general, and in electrical measurements in particular. These differences are manifest in training programs, in degrees granted, and in academic/research career opportunities. Educational barriers are related to the background in mathematics and physics for rehabilitation clinicians, leading to insufficient basic concepts of signal interpretation, as well as to the lack of a common language with rehabilitation engineers. Technical barriers are being overcome progressively, but progress is still impacted by the lack of user-friendly equipment, insufficient market demand, gadget-like devices, relatively high equipment price and a pervasive lack of interest by manufacturers. Despite the recommendations provided by the 20-year old EU project on "Surface EMG for Non-Invasive Assessment of Muscles (SENIAM)," real international standards are still missing and there is minimal international pressure for developing and applying such standards. The need for change in training and teaching is increasingly felt in the academic world, but is much less perceived in the health delivery system and clinical environments. The rapid technological progress in the fields of sensor and measurement technology (including sEMG), assistive devices, and robotic rehabilitation, has not been driven by clinical demands. Our assertion is that the most important and urgent interventions concern enhanced education, more effective technology transfer, and increased academic opportunities for physiotherapists, occupational therapists, and kinesiologists.

A gel-free Ti3C2Tx-based electrode array for high-density, high-resolution surface electromyography

Wearable sensors for surface electromyography (EMG) are composed of single- to few-channel large-area contacts, which exhibit high interfacial impedance and require conductive gels or adhesives to record high-fidelity signals. These devices are also limited in their ability to record activation across large muscle groups due to poor spatial coverage. To address these challenges, we have developed a novel high-density EMG array based on titanium carbide (Ti3C2Tx) MXene encapsulated in parylene-C. Ti3C2Tx is a two-dimensional nanomaterial with excellent electrical, electrochemical, and mechanical properties, which forms colloidally stable aqueous dispersions, enabling safe, scalable solutions-processing. Leveraging the excellent combination of metallic conductivity, high pseudocapacitance, and ease of processability of Ti3C2Tx MXene, we demonstrate the fabrication of gel-free, high-density EMG arrays which are ~8 μm thick, feature 16 recording channels, and are highly skin-conformable. The impedance of Ti3C2Tx electrodes in contact with human skin is 100-1000x lower than the impedance of commercially-available electrodes which require conductive gels to be effective. Furthermore, our arrays can record high-fidelity, low-noise EMG, and can resolve muscle activation with improved spatiotemporal resolution and sensitivity compared to conventional gelled electrodes. Overall, our results establish Ti3C2Tx-based bioelectronic interfaces as a powerful platform technology for high-resolution, non-invasive wearable sensing technologies.

Age-related differences in bimanual coordination performance

Purpose. The purpose of this article was to determine how characteristics of bimanual coordination tasks affect the quality of performance and to determine the impact of these characteristics on muscular activation of the upper limbs, with consideration of age-related differences. Methods. The research was carried out on two groups consisting of 25 people aged 20-30 and 60-67 years. The subjects performed seven tasks that varied in coordination mode, tracking mode and outline-tracing. The main measures of task performance were calculated on the basis of the difference between the position of the target and tracing cursors. Cohen's d value was calculated to show differences in measures between groups. Results. There were higher values of error and variability measures for elderly people compared to young. Complex tasks showed the largest difficulty, which suggests that, when performed, such tasks have the greatest potential to improve coordination skills. Tasks during which both limbs contribute to the movement of one cursor proved the most appropriate. Conclusion. The tracking mode is of great importance for the quality of performance in motor coordination tasks, while the performance of tasks with imposed speed is much more strongly age-sensitive than performance with a freely chosen speed.

High-Density Surface EMG Denoising Using Independent Vector Analysis

High-density surface electromyography (HD-sEMG) can provide rich temporal and spatial information about muscle activation. However, HD-sEMG signals are often contaminated by power line interference (PLI) and white Gaussian noise (WGN). In the literature, independent component analysis (ICA) and canonical correlation analysis (CCA), as two popular used blind source separation techniques, are widely used for noise removal from HD-sEMG signals. In this paper, a novel method to remove PLI and WGN was proposed based on independent vector analysis (IVA). Taking advantage of both ICA and CCA, this method exploits the higher order and second-order statistical information simultaneously. Our proposed method was applied to both simulated and experimental EMG data for performance evaluation, which was at least 37.50% better than ICA and CCA methods in terms of relative root mean squared error and 28.84% better than ICA and CCA methods according to signal to noise ratio. The results demonstrated that our proposed method performed significantly better than either ICA or CCA. Specifically, the mean signal to noise ratio increased considerably. Our proposed method is a promising tool for denoising HD-sEMG signals while leading to a minimal distortion.

Wireless Epidermal Electromyogram Sensing System

Massive efforts to build walking aid platforms for the disabled have been made in line with the needs of the aging society. One of the core technologies that make up these platforms is a realization of the skin-like electronic patch, which is capable of sensing electromyogram (EMG) and delivering feedback information to the soft, lightweight, and wearable exosuits, while maintaining high signal-to-noise ratio reliably in the long term. The main limitations of the conventional EMG sensing platforms include the need to apply foam tape or conductive gel on the surface of the device for adhesion and signal acquisition, and also the bulky size and weight of conventional measuring instruments for EMG, limiting practical use in daily life. Herein, we developed an epidermal EMG electrode integrated with a wireless measuring system. Such the stretchable platform was realized by transfer-printing of the as-prepared EMG electrodes on a SiO2 wafer to a polydimethylsiloxane (PDMS) elastomer substrate. The epidermal EMG patch has skin-like properties owing to its unique mechanical characteristics: i) location on a neutral mechanical plane that enables high flexibility, ii) wavy design that allows for high stretchability. We demonstrated wireless EMG monitoring using our skin-attachable and stretchable EMG patch sensor integrated with the miniaturized wireless system modules.

Shear Waves Reveal Viscoelastic Changes in Skeletal Muscles After Hemispheric Stroke

We investigated alterations in material properties such as elasticity and viscoelasticity of stroke-affected muscles using ultrasound induced shear waves and mechanical models. We used acoustic radiation force to generate shear waves along fascicles of biceps muscles and measured their propagation velocity. The shear wave data were collected in muscles of 13 hemiplegic stroke survivors under passive conditions at 90°, 120°, and 150° elbow flexion angles. In a viscoelastic medium, as opposed to a purely elastic medium, the shear wave propagation velocity depends on the frequency content of the induced wave. Therefore, in addition to the shear wave group velocity (GpV), we also estimated a frequency-dependent phase velocity (PhV). We found significantly higher GpVs and PhVs in stroke-affected muscles ( ). The velocity data were used to estimate shear elasticity and viscosity using an elastic and viscoelastic material models. A pure elastic model showed increased shear elasticity in stroke-affected muscles ( ). The Voigt model estimates of viscoelastic properties were also significantly different between the stroke-impaired and non-impaired muscles. We observed significantly larger model-estimated viscosity values on the stroke-affected side at elbow flexion angles of 120° and 150°. Furthermore, the creep behavior (tissue strain resulting from the application of sudden constant stress) of the model was also different between muscles of the paretic and non-paretic side. We speculate that these changes are associated with the structural disruption of muscles after stroke and may potentially affect force generation from muscle fibers as well as transmission of force to tendons.

Effect of Botulinum Toxin on the Spatial Distribution of Biceps Brachii EMG Activity Using a Grid of Surface Electrodes: A Case Study

Botulinum toxin (BT) is widely prescribed by physicians for managing spasticity post stroke. In an ongoing study, we examine the spatial pattern of muscle activity in biceps brachii of stroke survivors before and after receiving BT, examined over the course of 11 weeks (2 weeks before - 9 weeks after). We hypothesize that BT alters muscle electrophysiology by disrupting fiber neuromuscular transmission in an inhomogeneous manner and we seek to detect these changes using grid surface electromyography (sEMG). Also, we obtained B-mode ultrasound images to have an accurate interpretation of sEMG data by looking at the fiber angle and subcutaneous fat thickness distribution across muscle. Here, we are reporting a single case where a chronic stroke survivor received BT injection in the biceps brachii (BB). A 16x8 sEMG electrode grid was used to capture the muscle activity distribution of BB during sustained non-fatiguing isometric contraction at 40% of maximal voluntary (MVC) elbow flexion. We obtained the root mean squared (RMS) maps of the signal recorded at each of the $16 \times 8$ electrodes. We observed substantial changes in the RMS pattern of BB muscle after receiving BT. More than 80% decrease in sEMG amplitude (RMS) was observed for the channels around the BT injection site as well as about 74% elbow flexion force reduction at the time point of 3-4 weeks post-injection. We also found significant differences between the spatial voluntary activation pattern of pre and post BT RMS maps. We further observed a non-uniform effect and recovery caused by the BT on the distribution of muscle activity. In conclusion, we observed evidence of alteration of the amplitude and pattern of muscle activity after botulinum toxin injection and can document the capability of grid recordings to detect these pattern changes. Our major goals target further investigation to provide an indepth understanding of the effect of botulinum toxin injection at motor unit level.

Muscle recruitment and coordination during upper-extremity functional tests

Performance-based tests, such as the Jebsen Taylor Hand Function Test or Chedoke Arm and Hand Activity Inventory, are commonly used to assess functional performance after neurologic injury. However, the muscle activity required to execute these tasks is not well understood, even for unimpaired individuals. The purpose of this study was to evaluate unimpaired muscle recruitment and coordination of the dominant and non-dominant limbs during common clinical tests. Electromyography (EMG) recordings from eight arm muscles were monitored bilaterally for twenty unimpaired participants while completing these tests. Average signal magnitudes, activation times, and cocontraction levels were calculated from the filtered EMG data, normalized by maximum voluntary isometric contractions (MVICs). Overall, performance of these functional tests required low levels of muscle activity, with average EMG magnitudes less than 6.5% MVIC for all tests and muscles, except the extensor digitorum, which had higher activations across all tasks (11.7 ± 2.7% MVIC, dominant arm). When averaged across participants, cocontraction was between 25 and 62% for all tests and muscle pairs. Tasks evaluated by speed of completion, rather than functional quality of movement demonstrated higher levels of muscle recruitment. These results provide baseline measurements that can be used to evaluate muscle-specific deficits after neurologic injury and track recovery using common clinical tests.

Altered viscoelastic properties of stroke-affected muscles estimated using ultrasound shear waves - Preliminary data

As a result of a brain injury such as stroke, the skeletal muscles may undergo numerous structural and functional alterations. These abnormal changes are linked to muscle weakness, joint contracture, and abnormal muscle tone and eventually, result in motor impairment. A subset of these alterations affects passive muscle stiffness, i.e., viscoelastic properties. However, in vivo estimation of changes in viscoelastic properties is a challenging task. Here, we used the shear wave velocity, estimated through ultrasound SuperSonic imaging (SSI), as a surrogate for viscoelastic properties. We estimated shear wave group and phase velocities (dispersion), and thus, quantified both elasticity and viscosity of the muscle tissue, respectively in muscles of hemiplegic stroke survivors. In these individuals, we found significantly higher group and phase velocities in the stroke-affected muscles (p<; 05) compared to those of the contralateral non-affected side. We hypothesize that in addition to changes in neural and contractile properties, there are also, changes in elastic and tissue dispersive properties through local mechanisms. An enhanced understanding of post-stroke changes in skeletal muscles will lead to better and targeted interventions for rehabilitation.