An Approach to Using Electrical Impedance Myography Signal Sensors to Assess Morphofunctional Changes in Tissue during Muscle Contraction.

This present work is aimed at conducting fundamental and exploratory studies of the mechanisms of electrical impedance signal formation. This paper also considers morphofunctional changes in forearm tissues during the performance of basic hand actions. For this purpose, the existing research benches were modernized to conduct experiments of mapping forearm muscle activity by electrode systems on the basis of complexing the electrical impedance signals and electromyography signals and recording electrode systems' pressing force using force transducers. Studies were carried out with the involvement of healthy volunteers in the implementation of vertical movement of the electrode system and ultrasound transducer when the subject's upper limb was positioned in the bed of the stand while performing basic hand actions in order to identify the relationship between the morphofunctional activity of the upper limb muscles and the recorded parameters of the electro-impedance myography signal. On the basis of the results of the studies, including complex measurements of neuromuscular activity on healthy volunteers such as the signals of electro-impedance myography and pressing force, analyses of the morphofunctional changes in tissues during action performance on the basis of ultrasound and MRI studies and the factors influencing the recorded signals of electro-impedance myography are described. The results are of fundamental importance and will enable reproducible electro-impedance myography signals, which, in turn, allow improved anthropomorphic control.

A survey on the state of the art of force myography technique (FMG): analysis and assessment.

Precise feedback assures precise control commands especially for assistive or rehabilitation devices. Biofeedback systems integrated with assistive or rehabilitative robotic exoskeletons tend to increase its performance and effectiveness. Therefore, there has been plenty of research in the field of biofeedback covering different aspects such as signal acquisition, conditioning, feature extraction and integration with the control system. Among several types of biofeedback systems, Force myography (FMG) technique is a promising one in terms of affordability, high classification accuracies, ease to use, and low computational cost. Compared to traditional biofeedback systems such as electromyography (EMG) which offers some invasive techniques, FMG offers a completely non-invasive solution with much less effort for preprocessing with high accuracies. This work covers the whole aspects of FMG technique in terms of signal acquisition, feature extraction, signal processing, developing the machine learning model, evaluating tools for the performance of the model. Stating the difference between real-time and offline assessment, also highlighting the main uncovered points for further study, and thus enhancing the development of this technique.

AI-Enabled Soft Sensing Array for Simultaneous Detection of Muscle Deformation and Mechanomyography for Metaverse Somatosensory Interaction.

Motion recognition (MR)-based somatosensory interaction technology, which interprets user movements as input instructions, presents a natural approach for promoting human-computer interaction, a critical element for advancing metaverse applications. Herein, this work introduces a non-intrusive muscle-sensing wearable device, that in conjunction with machine learning, enables motion-control-based somatosensory interaction with metaverse avatars. To facilitate MR, the proposed device simultaneously detects muscle mechanical activities, including dynamic muscle shape changes and vibrational mechanomyogram signals, utilizing a flexible 16-channel pressure sensor array (weighing ≈0.38 g). Leveraging the rich information from multiple channels, a recognition accuracy of ≈96.06% is achieved by classifying ten lower-limb motions executed by ten human subjects. In addition, this work demonstrates the practical application of muscle-sensing-based somatosensory interaction, using the proposed wearable device, for enabling the real-time control of avatars in a virtual space. This study provides an alternative approach to traditional rigid inertial measurement units and electromyography-based methods for achieving accurate human motion capture, which can further broaden the applications of motion-interactive wearable devices for the coming metaverse age.

Muscle function assessment of the hindlimbs in healthy dogs using acoustic myography.

INTRODUCTION: Impaired muscle function is a frequent consequence of musculoskeletal disorders in dogs. Musculoskeletal disorders, especially stifle joint diseases, are common in dogs and assessment of muscle function in dogs is clinically relevant. Acoustic myography (AMG) is a non-invasive method to assess muscle activity. Quantifying muscle function in normal dogs could help identify clinically relevant changes in dogs with orthopaedic disease and allow targeted interventions to improve recovery in these. The objectives of the study were to characterize hindlimb muscle function in healthy dogs using AMG and to investigate the repeatability and reproducibility of AMG in dogs. METHODS: Healthy dogs (15-40 kg) without musculoskeletal disorders were recruited and screened for eligibility to participate in the study. The muscle activity in four hindlimb muscles related to the stifle was assessed using AMG. The degree of symmetry between the hindlimbs in these dogs was investigated and the reliability of AMG was evaluated. RESULTS AND CONCLUSIONS: The study population comprised 21 dogs. Reference intervals and symmetry indices for AMG scores of the hindlimb muscles were identified, with highest variability for the E-scores. For all AMG-scores, same-day variation was lower than between days variation, and both were lowest for S- and T-scores. Further investigation is needed to establish if AMG can enable discrimination between dogs with altered muscle function and healthy dogs.

Optimization of resting tension for wire myography in male rat pulmonary arteries.

Wire myography to test vasomotor functions of blood vessels ex-vivo are well-established for the systemic circulation, however, there is no consensus on protocols for pulmonary arteries. We created a standardized wire myography protocol for healthy rat PAs and validated this in a pulmonary hypertension (PH) model. Vessels stretched to higher initial tensions (5.0, 7.5 and 10.0 mN) exhibited a uniform response to phenylephrine, a larger dynamic range, and lower EC50 values. The endothelium-mediated relaxation showed that moderate tensions (7.5 and 10.0 mN) produced robust responses with higher maximum relaxation and lower EC50 values. For endothelium independent responses, the higher initial tension groups had lower and more consistent EC50 values than the lower initial tension groups. Pulmonary arteries from rats with PH were more responsive to vasoactive drugs when subjected to a higher initial tension. Notably, vessels in the PH group subjected to 15.0 mN exhibited high dynamic ranges in contractile and relaxation responses without tearing. Lastly, we observed attenuated cholinergic responses in these vessels-consistent with endothelial dysfunction in PH. Therefore, a moderate initial tension of 7.5-10.0 mN is optimal for healthy rat pulmonary arteries and a higher initial tension of 15.0 mN is optimal for pulmonary arteries from animals with PH.

Electrical impedance myography in healthy volunteers.

INTRODUCTION/AIMS: Electrical impedance myography (EIM) is a noninvasive technique being used in clinical studies to characterize muscle by phase, reactance, and resistance after application of a low-intensity current. The aim of this study was to obtain 50-kHz EIM data from healthy volunteers (HVs) for use in future clinical and research studies, perform reliability tests on EIM outcome measures, and compare findings with muscle ultrasound variables. METHODS: Four arm and four leg muscles of HVs were evaluated using an EIM device with two sensors, P/N 20-0045 and P/N 014-009. Muscles were evaluated individually and eight-muscle average (8MU), four-muscle upper extremity average, and four-muscle lower extremity average. An intraclass correlation coefficient (ICC) was applied to assess interrater, intrarater, and intersensor reliability using a subset of HVs. Ultrasound studies on muscle thickness and elastography were also performed on a subset of HVs. RESULTS: For the P/N 20-0045 sensor, the 8MU EIM mean and standard deviation (n = 41) was 14.54 ± 3.31 for phase, 7.04 ± 1.22 for reactance, and 28.91 ± 7.63 for resistance. Reliability for 8MU phase (n = 22) was good to excellent for both interrater (n = 22, ICC = 0.920, 95% CI 0.820 to 0.966) and intrarater (n = 22, ICC = 0.950, 95% CI 0.778 to 0.983). The P/N 014-009 sensor had similar reliability findings. Correlation analyses showed no association between EIM and muscle thickness. DISCUSSION: EIM is a reproducible measure of muscle physiology. Obtaining EIM values from HVs allows us to gain a better understanding how EIM may be altered in diseased muscle.

Hand Force Estimation from Acoustic Myography Using Deep Wavelet Scattering Transform and Long Short-Term Memory.

The ability to estimate user intention from surface electromyogram (sEMG) signals is a crucial aspect in the design of powered prosthetics. Recently, researchers have been using regression techniques to connect the user's intent, as expressed through sEMG signals, to the force applied at the fingertips in order to achieve a natural and accurate form of control. However, there are still challenges associated with processing sEMG signals that need to be overcome to allow for widespread and clinical implementation of upper limb prostheses. As a result, alternative modalities functioning as promising control signals have been proposed as source of control input rather than the sEMG, such as Acoustic Myography (AMG). In this study, six high sensitivity array microphones were used to acquire AMG signals, with custom-built 3D printed microphone housing. To tackle the challenge of extracting the relevant information from AMG signals, the Wavelet Scattering Transform (WST) was utilized. alongside a Long Short-Term Memory (LSTM) neural network model for predicting the force from the AMG. The subjects were asked to use a hand dynamometer to measure the changes in force and correlate that to the force predicted by using the AMG features. Seven subjects were recruited for data collection in this study, using hardware designed by the research team. the performance results showed that the WST-LSTM model can be robustly utilized across varying window sizes and testing schemes, to achieve average NRMSE results of approximately 8%. These pioneering results suggest that AMG signals can be utilized to reliably estimate the force levels that the muscles are applying.Clinical Relevance- This research presents a new method for controlling upper limb prostheses using Acoustic Myography (AMG) signals. A novel method mapping the AMG signals to force applied by the corresponding muscles is developed. The presented findings have the potential to lead to the development of more natural and accurate control of human-machine interfaces.

A Wearable Force Myography-Based Armband for Recognition of Upper Limb Gestures.

Force myography (FMG) represents a promising alternative to surface electromyography (EMG) in the context of controlling bio-robotic hands. In this study, we built upon our prior research by introducing a novel wearable armband based on FMG technology, which integrates force-sensitive resistor (FSR) sensors housed in newly designed casings. We evaluated the sensors' characteristics, including their load-voltage relationship and signal stability during the execution of gestures over time. Two sensor arrangements were evaluated: arrangement A, featuring sensors spaced at 4.5 cm intervals, and arrangement B, with sensors distributed evenly along the forearm. The data collection involved six participants, including three individuals with trans-radial amputations, who performed nine upper limb gestures. The prediction performance was assessed using support vector machines (SVMs) and k-nearest neighbor (KNN) algorithms for both sensor arrangments. The results revealed that the developed sensor exhibited non-linear behavior, and its sensitivity varied with the applied force. Notably, arrangement B outperformed arrangement A in classifying the nine gestures, with an average accuracy of 95.4 ± 2.1% compared to arrangement A's 91.3 ± 2.3%. The utilization of the arrangement B armband led to a substantial increase in the average prediction accuracy, demonstrating an improvement of up to 4.5%.

Electrical impedance myography for the early detection of muscle ischemia secondary to compartment syndrome: a study in a rat model.

Acute Compartment Syndrome (ACS) is one of the most devastating orthopedic conditions, affecting any of the body's many compartments, which, if sufficiently severe, may result in disability and amputation. Currently, intra-compartmental pressure measurements serve as the gold standard for diagnosing ACS. Diagnosing limbs at risk for ACS before irreversible damage to muscle and nerve is critical. Standard approaches for diagnosing impending compartment syndrome include clinical evaluation of the limb, such as assessment for "tightness" of the overlying skin, reduced pulses distally, and degree of pain, none of which are specific or sensitive. We have proposed a novel method to detect ACS via electrical impedance myography (EIM), where a weak, high-frequency alternating current is passed between one pair of electrodes through a region of tissue, and the resulting surface voltages are measured via a second pair. We evaluated the ability of EIM to detect early muscle ischemia in an established murine model of compression-induced muscle injury, where we collected resistance, reactance, and their dimensionless product, defined as Relative Injury Index (RII) during the study. Our model generated reproducible hypoxia, confirmed by Hypoxyprobe™ staining of endothelial regions within the muscle. Under conditions of ischemia, we demonstrated a reproducible, stable, and significant escalation in resistance, reactance, and RII values, compared to uninjured control limbs. These data make a reasonable argument for additional investigations into using EIM for the early recognition of muscle hypoperfusion and ischemia. However, these findings must be considered preliminary steps, requiring further pre-clinical and clinical validation.

In vivo noninvasive systemic myography of acute systemic vasoactivity in female pregnant mice.

Altered vasoactivity is a major characteristic of cardiovascular and oncological diseases, and many therapies are therefore targeted to the vasculature. Therapeutics which are selective for the diseased vasculature are ideal, but whole-body selectivity of a therapeutic is challenging to assess in practice. Vessel myography is used to determine the functional mechanisms and evaluate pharmacological responses of vascularly-targeted therapeutics. However, myography can only be performed on ex vivo sections of individual arteries. We have developed methods for implementation of spherical-view photoacoustic tomography for non-invasive and in vivo myography. Using photoacoustic tomography, we demonstrate the measurement of acute vascular reactivity in the systemic vasculature and the placenta of female pregnant mice in response to two vasodilators. Photoacoustic tomography simultaneously captures the significant acute vasodilation of major arteries and detects selective vasoactivity of the maternal-fetal vasculature. Photoacoustic tomography has the potential to provide invaluable preclinical information on vascular response that cannot be obtained by other established methods.

Electrical impedance myography detects age-related skeletal muscle atrophy in adult zebrafish.

Age-related deficits in skeletal muscle function, termed sarcopenia, are due to loss of muscle mass and changes in the intrinsic mechanisms underlying contraction. Sarcopenia is associated with falls, functional decline, and mortality. Electrical impedance myography (EIM)-a minimally invasive, rapid electrophysiological tool-can be applied to animals and humans to monitor muscle health, thereby serving as a biomarker in both preclinical and clinical studies. EIM has been successfully employed in several species; however, the application of EIM to the assessment of zebrafish-a model organism amenable to high-throughput experimentation-has not been reported. Here, we demonstrated differences in EIM measures between the skeletal muscles of young (6 months of age) and aged (33 months of age) zebrafish. For example, EIM phase angle and reactance at 2 kHz showed significantly decreased phase angle (5.3 ± 2.1 versus 10.7 ± 1.5°; p = 0.001) and reactance (89.0 ± 3.9 versus 172.2 ± 54.8 ohms; p = 0.007) in aged versus young animals. Total muscle area, in addition to other morphometric features, was also strongly correlated to EIM 2 kHz phase angle across both groups (r = 0.7133, p = 0.01). Moreover, there was a strong correlation between 2 kHz phase angle and established metrics of zebrafish swimming performance, including turn angle, angular velocity, and lateral motion (r = 0.7253, r = 0.7308, r = 0.7857, respectively, p < 0.01 for all). In addition, the technique was shown to have high reproducibility between repeated measurements with a mean percentage difference of 5.34 ± 1.17% for phase angle. These relationships were also confirmed in a separate replication cohort. Together, these findings establish EIM as a fast, sensitive method for quantifying zebrafish muscle function and quality. Moreover, identifying the abnormalities in the bioelectrical properties of sarcopenic zebrafish provides new opportunities to evaluate potential therapeutics for age-related neuromuscular disorders and to interrogate the disease mechanisms of muscle degeneration.

Comparison of a Modern Digital Mechanomyograph to a Mechanomyograph Utilizing an Archival Grass Force Transducer.

BACKGROUND: Mechanomyography is the traditional gold standard research technique for quantitative assessment of neuromuscular blockade. Mechanomyography directly measures the isometric force generated by the thumb in response to ulnar nerve stimulation. Researchers must construct their own mechanomyographs since commercial instruments are no longer available. A mechanomyograph was constructed, and its performance was compared against an archival mechanomyography system from the 1970s that utilized an FT-10 Grass force transducer, hypothesizing that train-of-four ratios recorded on each device would be equivalent. METHODS: A mechanomyograph was constructed using 3D-printed components and modern electronics. An archival mechanomyography system was assembled from original components, including an FT-10 Grass force transducer. Signal digitization for computerized data collection was utilized instead of the original paper strip chart recorder. Both devices were calibrated with standard weights to demonstrate linear voltage response curves. The mechanomyographs were affixed to opposite arms of patients undergoing surgery, and the train-of-four ratio was measured during the onset and recovery from rocuronium neuromuscular blockade. RESULTS: Calibration measurements exhibited a positive linear association between voltage output and calibration weights with a linear correlation coefficient of 1.00 for both mechanomyography devices. The new mechanomyograph had better precision and measurement sensitivity than the archival system: 5.3 mV versus 15.5 mV and 1.6 mV versus 5.7 mV, respectively (P < 0.001 for both). A total of 767 pairs of train-of-four ratio measurements obtained from eight patients had positive linear association (R 2 = 0.94; P < 0.001). Bland-Altman analysis resulted in bias of 3.8% and limits of agreement of -13% and 21%. CONCLUSIONS: The new mechanomyograph resulted in similar train-of-four ratio measurements compared to an archival mechanomyography system utilizing an FT-10 Grass force transducer. These results demonstrated continuity of gold standard measurement of neuromuscular blockade spanning nearly 50 yr, despite significant changes in the instrumentation technology.

Assessment of Low-Density Force Myography Armband for Classification of Upper Limb Gestures.

Using force myography (FMG) to monitor volumetric changes in limb muscles is a promising and effective alternative for controlling bio-robotic prosthetic devices. In recent years, there has been a focus on developing new methods to improve the performance of FMG technology in the control of bio-robotic devices. This study aimed to design and evaluate a novel low-density FMG (LD-FMG) armband for controlling upper limb prostheses. The study investigated the number of sensors and sampling rate for the newly developed LD-FMG band. The performance of the band was evaluated by detecting nine gestures of the hand, wrist, and forearm at varying elbow and shoulder positions. Six subjects, including both fit and amputated individuals, participated in this study and completed two experimental protocols: static and dynamic. The static protocol measured volumetric changes in forearm muscles at the fixed elbow and shoulder positions. In contrast, the dynamic protocol included continuous motion of the elbow and shoulder joints. The results showed that the number of sensors significantly impacts gesture prediction accuracy, with the best accuracy achieved on the 7-sensor FMG band arrangement. Compared to the number of sensors, the sampling rate had a lower influence on prediction accuracy. Additionally, variations in limb position greatly affect the classification accuracy of gestures. The static protocol shows an accuracy above 90% when considering nine gestures. Among dynamic results, shoulder movement shows the least classification error compared to elbow and elbow-shoulder (ES) movements.

Comparison between magnetic resonance imaging and electrical impedance myography for evaluating lumbar skeletal muscle composition.

BACKGROUND: To compare electrical impedance myography (EIM) and MRI in assessing lumbar skeletal muscle composition. METHODS: One hundred forty-one patients (78 females, mean age 57 ± 19 years) were prospectively enrolled and underwent lumbar spine MRI, EIM with Skulpt®, and clinical evaluation including the questionnaire SARC-F. MRIs were reviewed to assess the Goutallier score of paravertebral muscles at L3 level and to calculate the cross sectional area (CSA) of both psoas, quadratus lumborum, erector spinae, and multifidus muscles on a single axial slice at L3 level, in order to calculate the skeletal muscle index (SMI=CSA/height2). We tested the correlation between EIM-derived parameters [body fat percentage (BF%) and muscle quality] and body mass index (BMI), Goutallier score (1-4), SMI, and SARC-F scores (0-10) using the Pearson correlation coefficient. The strength of association was considered large (0.5 to 1.0), medium (0.3 to 0.5), small (0.1 to 0.3). RESULTS: Pearson's correlation coefficient showed small (0.26) but significant (p < 0.01) positive correlation between BF% obtained with EIM and Goutallier score. Small negative correlation (- 0.22, p < 0.01) was found between EIM muscle quality and Goutallier Score. Large negative correlation (- 0.56, p < 0.01) was found between SMI and Goutallier Score, while SMI showed small negative correlation with SARC-F (- 0.29, p < 0.01). Medium positive correlation was found between Goutallier Score and SARC-F (0.41, p < 0.01). BMI showed medium positive correlation with SMI (r = 0.369, p < 0.01) and small correlation with EIM muscle quality (r = - 0.291, p < 0.05) and BF% (r = 0.227, p < 0.05). We found a substantial increase of the strength of associations of BF% and muscle quality with Goutallier in the 18-40 years (r = 0.485 and r = - 0.401, respectively) and in the 41-70 years group (r = 0.448 and r = - 0.365, respectively). CONCLUSIONS: Muscle quality and BF% measured by EIM device showed only small strength of correlation with other quantitative parameters for assessing muscle mass and fat infiltration. Interesting results have been found in younger patients, but Skulpt Chisel™ should be applied cautiously to assess lumbar skeletal muscle composition. This point deserves further investigation and other studies are warranted. TRIAL REGISTRATION: The registration number of this study is 107/INT/2019.

Measurement of Endothelium-dependent Vasorelaxation in the Mouse Thoracic Aorta using Tensometric Small Volume Chamber Myography.

Small volume chamber tensometric myography is a commonly used technique to evaluate the vascular contractility of small and large blood vessels in laboratory animals and small arteries isolated from human tissue. The technique allows researchers to maintain isolated blood vessels in a tightly controlled and standardized (near-physiological) setting, with the option of adjusting to various environmental factors, while challenging the isolated vessels with different pharmacological agents that can induce vasoconstriction or vasodilation. The myograph chamber also provides a platform to measure vascular reactivity in response to various hormones, inhibitors, and agonists that may impact the function of smooth muscle and endothelial layers separately or simultaneously. The blood vessel wall is a complex structure consisting of three different layers: the intima (endothelial layer), media (smooth muscle and elastin fibers), and adventitia (collagen and other connective tissue). To gain a clear understanding of the functional properties of each layer, it is critical to have access to an experimental platform and system that would allow for a combinational approach to study all three layers simultaneously. Such an approach demands access to a semi-physiological condition that would mimic the in vivo environment in an ex vivo setting. Small volume chamber tensometric myography has provided an ideal environment to evaluate the impact of environmental cues, experimental variables, or pharmacological agonists and antagonists on vascular properties. For many years, scientists have used the tensometric myograph technique to measure endothelial function and smooth muscle contractility in response to different agents. In this report, a small volume chamber tensometric myograph system is used to measure endothelial function in the isolated mouse aorta. This report focuses on how small volume chamber tensometric myography can be used to evaluate the functional integrity of the endothelium in small segments of a large artery such as the thoracic aorta.

A Review of EMG-, FMG-, and EIT-Based Biosensors and Relevant Human-Machine Interactivities and Biomedical Applications.

Wearables developed for human body signal detection receive increasing attention in the current decade. Compared to implantable sensors, wearables are more focused on body motion detection, which can support human-machine interaction (HMI) and biomedical applications. In wearables, electromyography (EMG)-, force myography (FMG)-, and electrical impedance tomography (EIT)-based body information monitoring technologies are broadly presented. In the literature, all of them have been adopted for many similar application scenarios, which easily confuses researchers when they start to explore the area. Hence, in this article, we review the three technologies in detail, from basics including working principles, device architectures, interpretation algorithms, application examples, merits and drawbacks, to state-of-the-art works, challenges remaining to be solved and the outlook of the field. We believe the content in this paper could help readers create a whole image of designing and applying the three technologies in relevant scenarios.

Performing In Vivo and Ex Vivo Electrical Impedance Myography in Rodents.

Electrical impedance myography (EIM) is a convenient technique that can be used in preclinical and clinical studies to assess muscle tissue health and disease. EIM is obtained by applying a low-intensity, directionally focused, electrical current to a muscle of interest across a range of frequencies (i.e., from 1 kHz to 10 MHz) and recording the resulting voltages. From these, several standard impedance components, including the reactance, resistance, and phase, are obtained. When performing ex vivo measurements on excised muscle, the inherent passive electrical properties of the tissue, namely the conductivity and relative permittivity, can also be calculated. EIM has been used extensively in animals and humans to diagnose and track muscle alterations in a variety of diseases, in relation to simple disuse atrophy, or as a measure of therapeutic intervention. Clinically, EIM offers the potential to track disease progression over time and to assess the impact of therapeutic interventions, thus offering the opportunity to shorten the clinical trial duration and reduce sample size requirements. Because it can be performed noninvasively or minimally invasively in living animal models as well as humans, EIM offers the potential to serve as a novel translational tool enabling both preclinical and clinical development. This article provides step-by-step instructions on how to perform in vivo and ex vivo EIM measurements in mice and rats, including approaches to adapt the techniques to specific conditions, such as for use in pups or obese animals.

Tensor electrical impedance myography identifies bulbar disease progression in amyotrophic lateral sclerosis

OBJECTIVE: Electrical impedance myography (EIM) is a promising biomarker for amyotrophic lateral sclerosis (ALS). A key issue is how best to utilise the complex high dimensional, multi-frequency data output by EIM to fully characterise the progression of disease. METHODS: Muscle volume conduction properties were obtained from EIM recordings of the tongue across three electrode configurations and 14 input frequencies (76 Hz-625 kHz). Analyses of individual frequencies, averaged EIM spectra and non-negative tensor factorisation were undertaken. Longitudinal data were collected from 28 patients and 17 healthy volunteers at 3-monthly intervals for a maximum of 9 months. EIM was evaluated against the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) bulbar sub-score, tongue strength and an overall bulbar disease burden score. RESULTS: Longitudinal changes to individual patient EIM spectra demonstrated complex shifts in the spectral shape. At a group level, a clear pattern emerged over time, characterised by an increase in centre frequency and general shift to the right of the spectral shape. Tensor factorisation reduced the spectral data from a total of 168 data points per participant per recording to a single value which captured the complexity of the longitudinal data and which we call tensor EIM (T-EIM). The absolute change in tensor EIM significantly increased within 3 months and continued to do so over the 9-month study duration. In a hypothetical clinical trial scenario tensor EIM required fewer participants (n = 64 at 50% treatment effect), than single frequency measures (n range 87-802) or ALSFRS-R bulbar subscore (n = 298). CONCLUSIONS: Changes to tongue EIM spectra over time in ALS are complex. Tensor EIM captured and quantified disease progression and was more sensitive to changes than single frequency EIM measures and other biomarkers of bulbar disease. SIGNIFICANCE: Objective biomarkers for the assessment of bulbar disease in ALS are lacking. Tensor EIM enhances the biomarker potential of EIM data and can improve bulbar symptom monitoring in clinical trials.

Muscle Mass Measurement Using Machine Learning Algorithms with Electrical Impedance Myography.

Sarcopenia is a wild chronic disease among elderly people. Although it does not entail a life-threatening risk, it will increase the adverse risk due to the associated unsteady gait, fall, fractures, and functional disability. The import factors in diagnosing sarcopenia are muscle mass and strength. The examination of muscle mass must be carried in the clinic. However, the loss of muscle mass can be improved by rehabilitation that can be performed in non-medical environments. Electronic impedance myography (EIM) can measure some parameters of muscles that have the correlations with muscle mass and strength. The goal of this study is to use machine learning algorithms to estimate the total mass of thigh muscles (MoTM) with the parameters of EIM and body information. We explored the seven major muscles of lower limbs. The feature selection methods, including recursive feature elimination (RFE) and feature combination, were used to select the optimal features based on the ridge regression (RR) and support vector regression (SVR) models. The optimal features were the resistance of rectus femoris normalized by the thigh circumference, phase of tibialis anterior combined with the gender, and body information, height, and weight. There were 96 subjects involved in this study. The performances of estimating the MoTM used the regression coefficient (r2) and root-mean-square error (RMSE), which were 0.800 and 0.929, and 1.432 kg and 0.980 kg for RR and SVR models, respectively. Thus, the proposed method could have the potential to support people examining their muscle mass in non-medical environments.

Phonomyography on Perioperative Neuromuscular Monitoring: An Overview.

Complications related to neuromuscular blockade (NMB) could occur during anesthesia induction, maintenance, and emergency. It is recommended that neuromuscular monitoring techniques be utilized perioperatively to avoid adverse outcomes. However, current neuromuscular monitoring methods possess different shortcomings. They are cumbersome to use, susceptible to disturbances, and have limited alternative monitoring sites. Phonomyography (PMG) monitoring based on the acoustic signals yielded by skeletal muscle contraction is emerging as an interesting and innovative method. This technique is characterized by its convenience, stable signal quality, and multimuscle recording ability and shows great potential in the application field. This review summarizes the progression of PMG on perioperative neuromuscular monitoring chronologically and presents the merits, demerits, and challenges of PMG-based equipment, aiming at underscoring the potential of PMG-based apparatuses for neuromuscular monitoring.