Electrical conductivity of skeletal muscle tissue: experimental results from different muscles in vivo

Multifunctional Conductive Hydrogel Interface for Bioelectronic Recording and Stimulation

The past few decades have witnessed the rapid advancement and broad applications of flexible bioelectronics, in wearable and implantable electronics, brain-computer interfaces, neural science and technology, clinical diagnosis, treatment, etc. It is noteworthy that soft and elastic conductive hydrogels, owing to their multiple similarities with biological tissues in terms of mechanics, electronics, water-rich, and biological functions, have successfully bridged the gap between rigid electronics and soft biology. Multifunctional hydrogel bioelectronics, emerging as a new generation of promising material candidates, have authentically established highly compatible and reliable, high-quality bioelectronic interfaces, particularly in bioelectronic recording and stimulation. This review summarizes the material basis and design principles involved in constructing hydrogel bioelectronic interfaces, and systematically discusses the fundamental mechanism and unique advantages in bioelectrical interfacing with the biological surface. Furthermore, an overview of the state-of-the-art manufacturing strategies for hydrogel bioelectronic interfaces with enhanced biocompatibility and integration with the biological system is presented. This review finally exemplifies the unprecedented advancement and impetus toward bioelectronic recording and stimulation, especially in implantable and integrated hydrogel bioelectronic systems, and concludes with a perspective expectation for hydrogel bioelectronics in clinical and biomedical applications.

Validated computational models predict vagus nerve stimulation thresholds in preclinical animals and humans

Objective.We demonstrated how automated simulations to characterize electrical nerve thresholds, a recently published open-source software for modeling stimulation of peripheral nerves, can be applied to simulate accurately nerve responses to electrical stimulation.Approach.We simulated vagus nerve stimulation (VNS) for humans, pigs, and rats. We informed our models using histology from sample-specific or representative nerves, device design features (i.e. cuff, waveform), published material and tissue conductivities, and realistic fiber models.Main results.Despite large differences in nerve size, cuff geometry, and stimulation waveform, the models predicted accurate activation thresholds across species and myelinated fiber types. However, our C fiber model thresholds overestimated thresholds across pulse widths, suggesting that improved models of unmyelinated nerve fibers are needed. Our models of human VNS yielded accurate thresholds to activate laryngeal motor fibers and captured the inter-individual variability for both acute and chronic implants. For B fibers, our small-diameter fiber model underestimated threshold and saturation for pulse widths >0.25 ms. Our models of pig VNS consistently captured the range ofin vivothresholds across all measured nerve and physiological responses (i.e. heart rate, Aδ/B fibers, Aγfibers, electromyography, and Aαfibers). In rats, our smallest diameter myelinated fibers accurately predicted fast fiber thresholds across short and intermediate pulse widths; slow unmyelinated fiber thresholds overestimated thresholds across shorter pulse widths, but there was overlap for pulse widths >0.3 ms.Significance.We elevated standards for models of peripheral nerve stimulation in populations of models across species, which enabled us to model accurately nerve responses, demonstrate that individual-specific differences in nerve morphology produce variability in neural and physiological responses, and predict mechanisms of VNS therapeutic and side effects.

Fibers in smaller fascicles have lower activation thresholds with cuff electrodes due to thinner perineurium and smaller cross-sectional area

Objective. In nerve stimulation therapies, fibers in larger fascicles generally have higher activation thresholds, but the mechanisms are not well understood. We implemented and analyzed computational models to uncover the effects of morphological parameters on activation thresholds.Approach. We implemented finite element models of human vagus nerve stimulation to quantify the effects of morphological parameters on thresholds in realistic nerves. We also implemented simplified models to isolate effects of perineurium thickness, endoneurium diameter, fiber diameter, and fascicle location on current density, potential distributions (Ve), and activation thresholds across cuff geometries and stimulation waveforms. UsingVefrom each finite element model, we simulated activation thresholds in biophysical cable models of mammalian axons.Main results. Perineurium thickness increases with fascicle diameter, and both thicker perineurium and larger endoneurial diameter contributed to higher activation thresholds via lower peak and broader longitudinal potentials. Thicker perineurium caused less current to enter the fascicle transversely, decreasing peakVe. Thicker perineurium also inhibited current from leaving the fascicle, causing more constant longitudinal current density, broadeningVe. With increasing endoneurial diameter, intrafascicular volume increased faster than surface area, thereby decreasing intrafascicular current density and peakVe. Additionally, larger fascicles have greater cross-sectional area, thereby facilitating longitudinal intrafascicular current flow and broadeningVe. A large neighboring fascicle could increase activation thresholds, and for a given fascicle, fiber diameter had the greatest effect on thresholds, followed by fascicle diameter, and lastly, fascicle location within the epineurium. The circumneural cuff elicited robust activation across the nerve, whereas a bipolar transverse cuff with small contacts delivering a pseudo-monophasic waveform enabled more selective activation across fiber diameters and locations.Significance. Our computational studies provide mechanistic understanding of neural responses across relevant morphological parameters of peripheral nerves, thereby informing rational design of effective therapies.

Interrater and Intrarater Reliability of Electrical Impedance Myography: A Comparison between Large and Small Handheld Electrode Arrays

The objective of this study was to evaluate the interrater and intrarater reliability of electrical impedance myography (EIM) using handheld sensors of different sizes. Electrical impedance myography of the biceps brachii muscle of twenty healthy individuals was performed by two raters using both large and small sensors. The procedures were also repeated 5 to 8 days after the first recording session. The repeatability of the resistance, reactance, and phase angle at two different current frequencies (50 and 100 kHz) was assessed by the intraclass correlation coefficient (ICC). The ICCs of the large sensor were higher than those of the small sensor for both the intrarater and interrater reliabilities. High-frequency current tended to improve the ICC for the small sensor. These results indicate reasonable repeatability of the handheld electrode arrays for EIM measurements. The findings suggest that electrode array should be selected appropriately according to the size of the tested muscle.

ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds): A pipeline for sample-specific computational modeling of electrical stimulation of peripheral nerves

Electrical stimulation and block of peripheral nerves hold great promise for treatment of a range of disease and disorders, but promising results from preclinical studies often fail to translate to successful clinical therapies. Differences in neural anatomy across species require different electrodes and stimulation parameters to achieve equivalent nerve responses, and accounting for the consequences of these factors is difficult. We describe the implementation, validation, and application of a standardized, modular, and scalable computational modeling pipeline for biophysical simulations of electrical activation and block of nerve fibers within peripheral nerves. The ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds) pipeline provides a suite of built-in capabilities for user control over the entire workflow, including libraries for parts to assemble electrodes, electrical properties of biological materials, previously published fiber models, and common stimulation waveforms. We validated the accuracy of ASCENT calculations, verified usability in beta release, and provide several compelling examples of ASCENT-implemented models. ASCENT will enable the reproducibility of simulation data, and it will be used as a component of integrated simulations with other models (e.g., organ system models), to interpret experimental results, and to design experimental and clinical interventions for the advancement of peripheral nerve stimulation therapies.

Despite promising results from preclinical studies, novel therapies using electrical stimulation of peripheral nerves often fail to produce successful clinical outcomes due to differences in neural anatomy across species. These differences often require different electrodes to interface with the nerves and/or different stimulation parameters to achieve equivalent nerve responses. Further, differences in nerve anatomy across a population contribute to differences in nerve responses to stimulation. These inter-species and inter-individual differences can be studied using computational modeling of individual-specific peripheral nerve morphology and biophysical properties. To accelerate the process of computational modeling of individual nerve anatomy, we developed ASCENT, a software platform for simulating the responses of sample-specific nerves to electrical stimulation with custom electrodes and stimulation parameters. ASCENT automates the complex, multi-step process required to build computational models of preclinical and clinical studies and to design novel stimulation protocols using biophysically realistic simulations. The ASCENT pipeline will be used to develop technologies that increase the selectivity and efficiency of stimulation and to accelerate the translation of novel peripheral nerve stimulation therapies to the clinic.

Detection of Muscle Activation during Resistance Training Using Infrared Thermal Imaging

Infrared thermal imaging has been widely used to show the correlation between thermal characteristics of the body and muscle activation. This study aims to investigate a method using thermal imaging to visualize and differentiate target muscles during resistance training. Thermal images were acquired to monitor three target muscles (i.e., biceps brachii, triceps brachii, and deltoid muscle) in the brachium while varying the training weight, duration, and order of training. The acquired thermal images were segmented and converted to heat maps. By generating difference heat maps from pairs of heat maps during training, the target muscles were clearly visualized, with an average temperature difference of 0.86 °C. It was observed that training order had no significant effect on skin surface temperature. The difference heat maps were also used to train a convolutional neural network (CNN) to show the feasibility of target muscle classification, with an accuracy of 92.3%. This study demonstrated that infrared thermal imaging could be effectively utilized to locate and differentiate target muscle activation during resistance training.

Non-monotonic kilohertz frequency neural block thresholds arise from amplitude- and frequency-dependent charge imbalance

Reversible block of nerve conduction using kilohertz frequency electrical signals has substantial potential for treatment of disease. However, the ability to block nerve fibers selectively is limited by poor understanding of the relationship between waveform parameters and the nerve fibers that are blocked. Previous in vivo studies reported non-monotonic relationships between block signal frequency and block threshold, suggesting the potential for fiber-selective block. However, the mechanisms of non-monotonic block thresholds were unclear, and these findings were not replicated in a subsequent in vivo study. We used high-fidelity computational models and in vivo experiments in anesthetized rats to show that non-monotonic threshold-frequency relationships do occur, that they result from amplitude- and frequency-dependent charge imbalances that cause a shift between kilohertz frequency and direct current block regimes, and that these relationships can differ across fiber diameters such that smaller fibers can be blocked at lower thresholds than larger fibers. These results reconcile previous contradictory studies, clarify the mechanisms of interaction between kilohertz frequency and direct current block, and demonstrate the potential for selective block of small fiber diameters.

Lean regional muscle volume estimates using explanatory bioelectrical models in healthy subjects and patients with muscle wasting

BACKGROUND

The availability of non-invasive, accessible, and reliable methods for estimating regional skeletal muscle volume is paramount in conditions involving primary and/or secondary muscle wasting. This work aimed at (i) optimizing serial bioelectrical impedance analysis (S_BIA ) by computing a conductivity constant based on quantitative magnetic resonance imaging (MRI) data and (ii) investigating the potential of S_BIA for estimating lean regional thigh muscle volume in patients with severe muscle disorders.

METHODS

Twenty healthy participants with variable body mass index and 20 patients with idiopathic inflammatory myopathies underwent quantitative MRI. Anatomical images and fat fraction maps were acquired in thighs. After manual muscle segmentation, lean thigh muscle volume (lV_MRI ) was computed. Subsequently, multifrequency (50 to 350 kHz) serial resistance profiles were acquired between current skin electrodes (i.e. ankle and hand) and voltage electrodes placed on the anterior thigh. In vivo values of the muscle electrical conductivity constant were computed using data from S_BIA and MRI gathered in the right thigh of 10 healthy participants. Lean muscle volume (lV_BIA ) was derived from S_BIA measurements using this newly computed constant. Between-day reproducibility of lV_BIA was studied in six healthy participants.

RESULTS

Electrical conductivity constant values ranged from 0.82 S/m at 50 kHz to 1.16 S/m at 350 kHz. The absolute percentage difference between lV_BIA and lV_MRI was greater at frequencies >270 kHz (P < 0.0001). The standard error of measurement and the intra-class correlation coefficient for lV_BIA computed from measurements performed at 155 kHz (i.e. frequency with minimal difference) against lV_MRI were 6.1% and 0.95 in healthy participants and 9.4% and 0.93 in patients, respectively. Between-day reproducibility of lV_BIA was as follows: standard error of measurement = 4.6% (95% confidence interval [3.2, 7.8] %), intra-class correlation coefficient = 0.98 (95% confidence interval [0.95, 0.99]).

CONCLUSIONS

These findings demonstrate a strong agreement of lean muscle volume estimated using S_BIA against quantitative MRI in humans, including in patients with severe muscle wasting and fatty degeneration. S_BIA shows promises for non-invasive, fast, and accessible estimation and follow-up of lean regional skeletal muscle volume for transversal and longitudinal studies.

Electrical impedance myography: A critical review and outlook

Electrical impedance myography (EIM) technology is finding application in neuromuscular disease research as a tool to assess muscle health. Correlations between EIM outcomes, functional, imaging and histological data have been established in a variety of neuromuscular disorders; however, an analytical discussion of EIM is lacking. This review presents an explanation for clinicians and others who are applying EIM and interpreting impedance outcomes. The background of EIM is presented, including the relation between EIM, volume conduction properties, tissue structure, electrode configuration and conductor volume. Also discussed are technical considerations to guide the reader to critically evaluate EIM and understand its limitations and strengths.

Approaches for determining cardiac bidomain conductivity values: progress and challenges

Modelling the electrical activity of the heart is an important tool for understanding electrical function in various diseases and conduction disorders. Clearly, for model results to be useful, it is necessary to have accurate inputs for the models, in particular the commonly used bidomain model. However, there are only three sets of four experimentally determined conductivity values for cardiac ventricular tissue and these are inconsistent, were measured around 40 years ago, often produce different results in simulations and do not fully represent the three-dimensional anisotropic nature of cardiac tissue. Despite efforts in the intervening years, difficulties associated with making the measurements and also determining the conductivities from the experimental data have not yet been overcome. In this review, we summarise what is known about the conductivity values, as well as progress to date in meeting the challenges associated with both the mathematical modelling and the experimental techniques. Graphical abstract Epicardial potential distributions, arising from a subendocardial ischaemic region, modelled using conductivity data from the indicated studies.

Quantitative comparisons of block thresholds and onset responses for charge-balanced kilohertz frequency waveforms

OBJECTIVE

There is growing interest in delivering kilohertz frequency (KHF) electrical signals to block conduction in peripheral nerves for treatment of various diseases. Previous studies used different KHF waveforms to achieve block, and it remains unclear how waveform affects nerve block parameters.

APPROACH

We quantified the effects of waveform on KHF block of the rat tibial nerve in vivo and in computational models. We compared block thresholds and onset responses across current-controlled sinusoids and charge-balanced rectangular waveforms with different asymmetries and duty cycles.

MAIN RESULTS

Sine waves had higher block thresholds than square waves, but used less power at block threshold. Block threshold had an inverse relationship with duty cycle of rectangular waveforms irrespective of waveform asymmetry. Computational model results were consistent with relationships measured in vivo, although the models underestimated the effect of duty cycle on increasing thresholds. The axonal membrane substantially filtered waveforms, the filter transfer function was strikingly similar across waveforms, and filtering resulted in post-filtered rms block thresholds that were approximately constant across waveforms in silico and in vivo. Onset response was not consistently affected by waveform shape, but onset response was smaller at amplitudes well above block threshold. Therefore, waveforms with lower block thresholds (e.g. sine waves or square waves) could be more readily increased to higher amplitudes relative to block threshold to reduce onset response. We also observed a reduction in onset responses across consecutive trials after initial application of supra-block threshold amplitudes.

SIGNIFICANCE

Waveform had substantial effects on block thresholds, and the amplitude relative to block threshold had substantial effects on onset response. These data inform choice of waveform in subsequent studies and clinical applications, enhance effective use of block in therapeutic applications, and facilitate the design of parameters that achieve block with minimal onset responses.

A Novel Conductive and Micropatterned PEG-Based Hydrogel Enabling the Topographical and Electrical Stimulation of Myoblasts

In this study, we designed a cell-adhesive poly(ethylene glycol) (PEG)-based hydrogel that simultaneously provides topographical and electrical stimuli to C2C12 myoblasts. Specifically, PEG hydrogels with microgroove structures of 3 μm ridges and 3 μm grooves were prepared by micromolding; in situ polymerization of poly(3,4-ethylenedioxythiophene) (PEDOT) was then performed within the micropatterned PEG hydrogels to create a microgrooved conductive hydrogel (CH/P). The CH/P had clear replica patterns of the silicone mold and a conductivity of 2.49 × 10^-3 S/cm, with greater than 85% water content. In addition, the CH exhibited Young's modulus (45.84 ± 7.12 kPa) similar to that of a muscle tissue. The surface of the CH/P was further modified via covalent bonding with cell-adhesive peptides to facilitate cell adhesion without affecting conductivity. An in vitro cell assay revealed that the CH/P was cytocompatible and enhanced the cell alignment and elongation of C2C12 myoblasts. The microgrooves and conductivity of the CH/P had the greatest positive effect on the myogenesis of C2C12 myoblasts compared to the other PEG hydrogel samples without conductivity or/and microgrooves, even in the absence of electrical stimulation. Electrical stimulation studies indicated that the combination of topographical and electrical cues maximized the differentiation of C2C12 myoblasts into myotubes, confirming the synergetic effect of incorporating microgroove surface features and a conductive PEDOT component into hydrogels.

Micropatterned conductive hydrogels as multifunctional muscle-mimicking biomaterials: Graphene-incorporated hydrogels directly patterned with femtosecond laser ablation

Multifunctional biomaterials that can provide physical, electrical, and structural cues to cells and tissues are highly desirable to mimic the important characteristics of native tissues and efficiently modulate cellular behaviors. Especially, electrically conductive biomaterials can efficiently deliver electrical signals to living systems; however, the production of conductive biomaterials presenting multiple cell interactive cues is still a great challenge. In this study, we fabricafed an electrically conductive, mechanically soft, and topographically active hydrogel by micropatterning a graphene oxide (GO)-incorporated polyacrylamide hydrogel (GO/PAAm) with femtosecond laser ablation (FLA) and subsequent chemical reduction. FLA parameters were optimized to efficiently produce distinct line patterns on GO/PAAm hydrogels to induce myoblast alignment and maturation. The line patterns distances (PD) were varied to have different topographies (20-80 μm PD). In vitro studies with C2C12 myoblasts revealed that the micopatterned hydrogels are superior to the unpatterned substrates in inducing myogenesis and myotube alignment. Reduced GO/PAAm with 50 μm PD, i.e., PD50/r(GO/PAAm), showed the best results among the various features for differentiation and myotube alignment. Electrical stimulation of myoblasts on the micropatterned conductive hydrogels further promoted the differentiation of myoblasts. In vivo implantation studies indicated good tissue compatibility of PD50/r(GO/PAAm) samples. Altogether, we successfully demonstrated that the micropatterned r(GO/PAAm) may offer multiple properties capable of positively affecting myoblast responses. This hydrogel may serve as an effective multifunctional biomaterial, which possesses the topography for cell alignment/maturation, mechanical properties of the native skeletal muscle tissue, and desirable electrical conductivity for delivering electrical signals to cells, for various biomedical applications such as muscle tissue scaffolds. STATEMENT OF SIGNIFICANCE: Micropatterned conductive hydrogels were created by polymerization of a graphene oxide-incorporated polyacrylamide hydrogel, micropatterning with femtosecond laser ablation, and chemical reduction, which can mimic important characteristics of native skeletal muscle tissues. The micropatterned conductive hydro-gels promoted myogenesis/alignment, enabled electrical stimulation of myoblasts, and displayed good tissue compatibility, which can therefore serve as a multifunctional biomaterial that is topographically active, mechanically soft, and electrically conductive for delivering multiple cell stimulating signals for potential skeletal muscle tissue engineering applications.

Modelling the electrical activity of skeletal muscle tissue using a multi-domain approach

Electromyography (EMG) can be used to study the behaviour of the motor neurons and thus provides insights into the physiology of the central nervous system. However, due to the high complexity of neuromuscular control, EMG signals are challenging to interpret. While the exact knowledge of the excitation patterns of a specific muscle within an in vivo experimental setting remains elusive, simulations allow to systematically investigate EMG signals in a controlled environment. Within this context, simulations can provide virtual EMG data, which, for example, can be used to validate and optimise signal analysis methods that aim to estimate the relationship between EMG signals and the output of motor neuron pools. However, since existing methods, which are employed to compute EMG signals, exhibit deficiencies with respect to the physical model itself as well as with respect to numerical aspects, we propose a novel homogenised continuum model that closely resolves the electro-physiological behaviour of skeletal muscle tissue. The proposed model is based on an extension of the well-established bidomain model and includes a biophysically detailed description of the electrical activity within the tissue, which is due to the depolarisation of the muscle fibre membranes. In contrast to all other published EMG models, which assume that the electrical potential field for each muscle fibre can be calculated independently, the proposed model assumes that the electrical potential in the muscle fibres is coupled to the electrical potential in the extracellular space. We show that the newly proposed model is able to simulate realistic EMG signals and demonstrate the potential to employ the predicted virtual EMG signal in order to evaluate the goodness of automated decomposition algorithms.

Anatomically accurate model of EMG during index finger flexion and abduction derived from diffusion tensor imaging

This study presents a modelling framework in which information on muscle fiber direction and orientation during contraction is derived from diffusion tensor imaging (DTI) and incorporated in a computational model of the surface electromyographic (EMG) signal. The proposed model makes use of the principle of reciprocity to simultaneously calculate the electric potentials produced at the recording electrode by charges distributed along an arbitrary number of muscle fibers within the muscle, allowing for a computationally efficient evaluation of extracellular motor unit action potentials. The approach is applied to the complex architecture of the first dorsal interosseous (FDI) muscle of the hand to simulate EMG during index finger flexion and abduction. Using diffusion tensor imaging methods, the results show how muscle fiber orientation and curvature in this intrinsic hand muscle change during flexion and abduction. Incorporation of anatomically accurate muscle architecture and other hand tissue morphologies enables the model to capture variations in extracellular action potential waveform shape across the motor unit population and to predict experimentally observed differences in EMG signal features when switching from index finger abduction to flexion. The simulation results illustrate how structural and electrical properties of the tissues comprising the volume conductor, in combination with fiber direction and curvature, shape the detected action potentials. Using the model, the relative contribution of motor units of different sizes located throughout the muscle under both conditions is examined, yielding a prediction of the detection profile of the surface EMG electrode array over the muscle cross-section.

Advances in diffusion tensor imaging are providing new information on muscle architecture and the orientation of muscle fibers in vivo. The arrangement of muscle fibers, in combination with geometrical and electrical properties of the surrounding biological tissues, shapes the electrical signal recorded at the skin surface during muscle contraction. As new recording and analysis methods enable muscle and motor unit activity to be examined during complex dynamic contractions, changes in muscle fiber orientation and surrounding tissue properties pose challenges for the interpretation of these data. Here we incorporate details of tissue geometry and muscle fiber architecture obtained using anatomical and diffusion MRI into an anatomically accurate model of electromyography (EMG) signal generation in the first dorsal interosseous muscle of the hand. The new modeling approach presented integrates interdependent electrical and geometrical properties in an anatomically accurate manner, leading to a realistic EMG model where tissue electrical properties are inherently related to bioelectric aspects of muscle activation. The results show how muscle fiber orientation and curvature change according to the direction of force generation, influencing the EMG signal, and provide new insights on how constitutive, anatomical and physiological properties contribute to shape motor unit action potentials detected at the skin surface.

New electrical impedance methods for the in situ measurement of the complex permittivity of anisotropic skeletal muscle using multipolar needles

This paper provides a rigorous analysis on the measurement of the permittivity of two-dimensional anisotropic biological tissues such as skeletal muscle using the four-electrode impedance technique. The state-of-the-art technique requires individual electrodes placed at the same depth in contact with the anisotropic material, e.g. using monopolar needles. In this case, the minimum of measurements in different directions needed to estimate the complex permittivity and its anisotropy direction is 3, which translates into 12 monopolar needle insertions (i.e. 3 directions × 4 electrodes in each direction). Here, we extend our previous work and equip the reader with 8 new methods for multipolar needles, where 2 or more electrodes are spaced along the needle's shaft in contact with the tissue at different depths. Using multipolar needles, the new methods presented reduce the number of needle insertions by a factor of 2 with respect to the available methods. We illustrate the methods with numerical simulations and new experiments on ex vivo ovine skeletal muscle (n = 3). Multi-frequency longitudinal and transverse permittivity data from 30 kHz to 1 MHz is made publicly available in the supplementary material. The methods presented here for multipolar needles bring closer the application of needle electrical impedance to patients with neuromuscular diseases.

Biomechanical Methods to Quantify Muscle Effort During Resistance Exercise

Chiu, LZF. Biomechanical methods to quantify muscle effort during resistance exercise. J Strength Cond Res 32(2): 502-513, 2018-Muscle hypertrophy and strength adaptations elicited by resistance training are dependent on the force exerted by active muscles. As an exercise may use many muscles, determining force for individual muscles or muscle groupings is important to understand the relation between an exercise and these adaptations. Muscle effort-the amount of force or a surrogate measure related to the amount of force exerted during a task-can be quantified using biomechanical methods. The purpose of this review was to summarize the biomechanical methods used to estimate muscle effort in movements, particularly resistance training exercises. These approaches include the following: (a) inverse dynamics with rigid body models, (b) forward dynamics and EMG-driven models, (c) normalized EMG, and (d) inverse dynamics with point-mass models. Rigid body models quantify muscle effort as net joint moments. Forward dynamics and EMG-driven models estimate muscle force as well as determine the effect of a muscle's action throughout the body. Nonlinear relations between EMG and muscle force and normalization reference action selection affect the usefulness of EMG as a measure of muscle effort. Point-mass models include kinetics calculated from barbell (or other implement) kinematics recorded using electromechanical transducers or measured using force platforms. Point-mass models only allow the net force exerted on the barbell or lifter-barbell system to be determined, so they cannot be used to estimate muscle effort. Data from studies using rigid body models, normalized EMG, and musculoskeletal modeling should be combined to develop hypotheses regarding muscle effort; these hypotheses should be verified by training interventions.

Modeling of sectionally continuous communication channel with inhomogeneously distributed tissues

BACKGROUND

This study aimed to investigate effects on the transmission channel caused by heterogeneous distribution in tissues and joint characteristics.

METHOD

Human arm section scans were taken using CT technology, and zoned, following which, a circumference measurement experiment was performed to analyze the effect of inhomogeneous distribution of tissues. In order to analyze the arm joint's effect on channel transmission, we proposed a piecewise modeling method in combination with connection conditions.

CONCLUSIONS

It can be seen from the experiment that, in the quasi-static mode, the communication channel error caused by the inhomogeneous distribution of tissues is small enough to be negligible. The error between calculated and experimental results is reduced by 3.93 dB in this experiment relative to models that did not include joint characteristics, and the average error is lowered by 0.73 dB. The variation curve fit to experimental data is also improved in this method. As such, it can be quantitatively determined that a channel model with joint characteristics is superior to models excluding joint characteristics.

Recording characteristics of electrical impedance myography needle electrodes

OBJECTIVE

Neurologists and physiatrists need improved tools for the evaluation of skeletal muscle condition. Here we evaluate needle electrical impedance myography (EIM), a new minimally invasive approach to determine muscle status that could ultimately become a bedside tool for the assessment of neuromuscular disorders.

APPROACH

We design and study the recording characteristics of tetrapolar EIM needle electrodes combining theory and finite-element model simulations. We then use these results to build and pilot in vivo an EIM needle electrode in the rat gastrocnemius muscle ([Formula: see text]). The dielectric properties of muscle are reported (mean  ±  standard deviation).

RESULTS

The numerical simulations show that the contribution of subcutaneous fat and muscle tissues to needle EIM data is <3% and >97%, respectively, and the sensed volume is [Formula: see text] cm³. Apparent resistivity [Formula: see text] [Formula: see text] cm and relative permittivity [Formula: see text] (dimensionless) measured at 10 kHz are in good agreement with in vivo dielectric properties reported in the literature.

SIGNIFICANCE

The results presented show the feasibility of measuring muscle impedivity in vivo using a needle electrode from 10 kHz to 1 MHz. The development of needle EIM technology can open up a new field of study in electrodiagnostic medicine, with potential applications to both disease diagnosis and biomarker assessment of therapy.

A Parametric Computational Analysis Into Galvanic Coupling Intrabody Communication

Intrabody Communication (IBC) uses the human body tissues as transmission media for electrical signals to interconnect personal health devices in wireless body area networks. The main goal of this work is to conduct a computational analysis covering some bioelectric issues that still have not been fully explained, such as the modeling of skin-electrode impedance, the differences associated with the use of constant voltage, or current excitation modes, or the influence on attenuation of the subject's anthropometrical and bioelectric properties. With this aim, a computational finite element model has been developed, allowing the IBC channel attenuation as well as the electric field and current density through arm tissues to be computed as a function of these parameters. As a conclusion, this parametric analysis has in turn permitted us to disclose some knowledge about the causes and effects of the above-mentioned issues, thus, explaining and complementing previous results reported in the literature.

The Use of Electrical Impedance to Identify Intraneural Needle Placement in Human Peripheral Nerves: A Study on Amputated Human Limbs

BACKGROUND

Even as the use of peripheral nerve blockade in the perioperative setting is increasing, neural injury secondary to accidental intraneural injection remains a significant patient safety concern. Current modalities, including electrical stimulation and ultrasound imaging, still lack consistency and absolute reliability in both the detection and prevention of this complication. The measurement of electrical impedance (EI) could be an easy and valuable additional tool to detect intraneural needle placement. Our objectives in this study were to measure the change in EI with intraneural needle advancement in recently amputated human limbs.

METHODS

The study was conducted within 45 minutes of amputation. The nerves that were studied were the sciatic nerve in the popliteal fossa in above-knee amputations or the tibial nerve below the calf in below-knee amputations. The amputated limb was placed on a tray and under ultrasound imaging guidance, an insulated peripheral block needle connected to a nerve stimulator was placed extraneurally and subsequently advanced intraneurally. The experiment was repeated on the same nerve after exposure by surgical dissection. The differences in impedance measurements between intraneural and extraneural needle placement were compared.

RESULTS

In the below-knee amputated extremity (tibial nerve, n = 6) specimens based on the ultrasound methods, mean ± SD for ultrasound-guided intraneural impedance was 10 ± 2 kΩ compared with an extraneural impedance of 6 ± 1.6 kΩ (P = 0.005). The difference between intraneural and extraneural impedance after open dissection was also significant when we repeated the analysis based on the same specimens (P = 0.005). Similarly, in the above-the-knee amputated extremity (sciatic nerve, n = 5) specimens, mean intraneural impedance was 35.2 ± 7.9 kΩ compared with an extraneural impedance of 25.2 ± 5.3 kΩ (P = 0.037). The difference between intraneural and extraneural impedance obtained after open dissection was also significant when we repeated the analysis based on the same specimens (P = 0.0002). The impedance values were consistent and similar to those obtained after open dissection.

CONCLUSIONS

There is no reliable "gold standard" to predict or prevent intraneural needle placement during peripheral nerve blockade. This small sample-sized study demonstrated that there is a change in EI with intraneural needle advancement. In clinical practice, measurement of the EI in conjunction with nerve stimulation may serve as another tool to use for identifying intraneural needle placement during peripheral nerve blockade.

Path Loss Measurement and Channel Modeling with Muscular Tissue Characteristics

BACKGROUND

The galvanic coupling intra-body communication has low radiation and strong anti-interference ability, so it has many advantages in the wireless communication.

METHOD

In order to analyze the effect of muscle tissue's characteristics upon the communication channel, we selected the muscle of pig buttock as the experimental sample, and used it to study the attenuation property with the galvanic coupling intra-body communication channel along the parallel direction and the transverse direction relative to the muscular fibre line as well as on the surface of destroyed muscular fibre; the study frequency ranges from 1kHz to 10MHz.In the isotropic experiment, in order to destroy muscle's fibre characteristics, we grinded the muscle four times, at least five minutes for each time. 0dbm sine-wave signal was input to measure the channel attenuation parameter S21 when the transmitter and the receiver were placed at different positions and different distances d1 and d2 (20mm, 40mm, 60mm), so as to analyze channel loss.

CONCLUSION

Within the same frequency range and at the same communication distance, the maximum error of channel attenuation was 10dB; within the same frequency, as the communication distance was increased, the channel attenuation rose gradually, with 4dB increased every 20mm. The conclusion provides the basis for building the theoretical model in the future.

Electrical Impedance Myography for Evaluating Paretic Muscle Changes After Stroke

Electrical impedance myography (EIM) was used to assess the paretic muscle intrinsic electrical properties post stroke. Twenty-seven subjects with chronic hemiparesis participated in this study. Muscle impedance was measured by applying high-frequency, low-intensity alternating current to biceps brachii muscles. Major EIM parameters, resistance ( ), reactance ( ), phase angle ( ), and electrical anisotropy ratios (AR) of the three parameters, were examined at 50 kHz. Statistical analysis demonstrated significant reduction of reactance, phase angle, AR of resistance, and AR of reactance in the paretic muscle compared with the contralateral side (Paretic X: , contralateral X: , and p < 0.001; Paretic : , contralateral : 14.5 ± 0.82°, and p < 0.001; Paretic AR of R: 0.969 ± 0.013, contralateral AR of R: 1.008 ± 0.011, and p < 0.02; and Paretic AR of X: 0.981 ± 0.066, contralateral AR of X: 1.114 ± 0.041, and p < 0.02). Correlation analysis, however, did not show any significant relationship between EIM parameters and clinical assessments. Findings of this paper indicated significant changes in the muscular intrinsic electrical properties after stroke, possibly related to structural modifications induced by loss of muscle fibers or fat infiltration as well as changes in the quality of cell membranes post stroke.

Optimization of Peripheral Vascular Sizing with Conductance Guidewire: Theory and Experiment

Although the clinical range of interventions for coronary arteries is about 2 to 5 mm, the range of diameters of peripheral vasculature is significantly larger (about 10 mm for human iliac artery). When the vessel diameter is increased, the spacing between excitation electrodes on a conductance sizing device must also increase to accommodate the greater range of vessel diameters. The increase in the excitation electrodes distance, however, causes higher parallel conductance or current losses outside of artery lumen. We have previously shown that the conductance catheter/guidewire excitation electrode distances affects the measurement accuracy for the peripheral artery lumen sizing. Here, we propose a simple solution that varies the detection electrode distances to compensate for parallel conductance losses. Computational models were constructed to simulate the conductance guidewire with various electrodes spacing combinations over a range of peripheral artery lumen diameters and surrounding tissue electrical conductivities. The results demonstrate that the measurement accuracy may be significantly improved by increased detection spacing. Specifically, an optimally configured detection/excitation spacing (i.e., 5-5-5 or an equidistant electrode interval with a detection-to-excitation spacing ratio of 0.3) was shown to accurately predict the lumen diameter (i.e., -10% < error < 10%) over a broad range of peripheral artery dimensions (4 mm < diameter < 10 mm). The computational results were substantiated with both ex-vivo and in-vivo measurements of peripheral arteries. The present results support the accuracy of the conductance technique for measurement of peripheral reference vessel diameter.

Communication channel modeling of human forearm with muscle fiber tissue characteristics

Human-Body Communication (HBC) is a wireless communication method using the human body tissue as a transmission medium for signals. This paper on the basis of human muscle fiber tissues' characteristics, it is first proposed to establish the analytical model of galvanic coupling human-body communication channel. In this model, the parallel and the transverse electrical characteristics of muscular tissue are fully considered, and the model accurately presents the transmission mechanism of galvanic coupling human-body communication signals in the channel. At last, through compare with the experimental results and calculation results, the maximum error of the model is 22.4% and the average error is 14.2% within the frequency range.

A Finite Element Model Approach to Determine the Influence of Electrode Design and Muscle Architecture on Myoelectric Signal Properties

Introduction

Surface electromyography (sEMG) is the measurement of the electrical activity of the skeletal muscle tissue detected at the skin’s surface. Typically, a bipolar electrode configuration is used. Most muscles have pennate and/or curved fibres, meaning it is not always feasible to align the bipolar electrodes along the fibres direction. Hence, there is a need to explore how different electrode designs can affect sEMG measurements.

Method

A three layer finite element (skin, fat, muscle) muscle model was used to explore different electrode designs. The implemented model used as source signal an experimentally recorded intramuscular EMG taken from the biceps brachii muscle of one healthy male. A wavelet based intensity analysis of the simulated sEMG signal was performed to analyze the power of the signal in the time and frequency domain.

Results

The model showed muscle tissue causing a bandwidth reduction (to 20-92- Hz). The inter-electrode distance (IED) and the electrode orientation relative to the fibres affected the total power but not the frequency filtering response. The effect of significant misalignment between the electrodes and the fibres (60°- 90°) could be reduced by increasing the IED (25–30 mm), which attenuates signal cancellation. When modelling pennated fibres, the muscle tissue started to act as a low pass filter. The effect of different IED seems to be enhanced in the pennated model, while the filtering response is changed considerably only when the electrodes are close to the signal termination within the model. For pennation angle greater than 20°, more than 50% of the source signal was attenuated, which can be compensated by increasing the IED to 25 mm.

Conclusion

Differences in tissue filtering properties, shown in our model, indicates that different electrode designs should be considered for muscle with different geometric properties (i.e. pennated muscles).

A multiscale chemo-electro-mechanical skeletal muscle model to analyze muscle contraction and force generation for different muscle fiber arrangements

The presented chemo-electro-mechanical skeletal muscle model relies on a continuum-mechanical formulation describing the muscle's deformation and force generation on the macroscopic muscle level. Unlike other three-dimensional models, the description of the activation-induced behavior of the mechanical model is entirely based on chemo-electro-mechanical principles on the microscopic sarcomere level. Yet, the multiscale model reproduces key characteristics of skeletal muscles such as experimental force-length and force-velocity data on the macroscopic whole muscle level. The paper presents the methodological approaches required to obtain such a multiscale model, and demonstrates the feasibility of using such a model to analyze differences in the mechanical behavior of parallel-fibered muscles, in which the muscle fibers either span the entire length of the fascicles or terminate intrafascicularly. The presented results reveal that muscles, in which the fibers span the entire length of the fascicles, show lower peak forces, more dispersed twitches and fusion of twitches at lower stimulation frequencies. In detail, the model predicted twitch rise times of 38.2 and 17.2 ms for a 12 cm long muscle, in which the fibers span the entire length of the fascicles and with twelve fiber compartments in series, respectively. Further, the twelve-compartment model predicted peak twitch forces that were 19% higher than in the single-compartment model. The analysis of sarcomere lengths during fixed-end single twitch contractions at optimal length predicts rather small sarcomere length changes. The observed lengths range from 75 to 111% of the optimal sarcomere length, which corresponds to a region with maximum filament overlap. This result suggests that stability issues resulting from activation-induced stretches of non-activated sarcomeres are unlikely in muscles with passive forces appearing at short muscle length.

Evaluation of intradural stimulation efficiency and selectivity in a computational model of spinal cord stimulation

Spinal cord stimulation (SCS) is an alternative or adjunct therapy to treat chronic pain, a prevalent and clinically challenging condition. Although SCS has substantial clinical success, the therapy is still prone to failures, including lead breakage, lead migration, and poor pain relief. The goal of this study was to develop a computational model of SCS and use the model to compare activation of neural elements during intradural and extradural electrode placement. We constructed five patient-specific models of SCS. Stimulation thresholds predicted by the model were compared to stimulation thresholds measured intraoperatively, and we used these models to quantify the efficiency and selectivity of intradural and extradural SCS. Intradural placement dramatically increased stimulation efficiency and reduced the power required to stimulate the dorsal columns by more than 90%. Intradural placement also increased selectivity, allowing activation of a greater proportion of dorsal column fibers before spread of activation to dorsal root fibers, as well as more selective activation of individual dermatomes at different lateral deviations from the midline. Further, the results suggest that current electrode designs used for extradural SCS are not optimal for intradural SCS, and a novel azimuthal tripolar design increased stimulation selectivity, even beyond that achieved with an intradural paddle array. Increased stimulation efficiency is expected to increase the battery life of implantable pulse generators, increase the recharge interval of rechargeable implantable pulse generators, and potentially reduce stimulator volume. The greater selectivity of intradural stimulation may improve the success rate of SCS by mitigating the sensitivity of pain relief to malpositioning of the electrode. The outcome of this effort is a better quantitative understanding of how intradural electrode placement can potentially increase the selectivity and efficiency of SCS, which, in turn, provides predictions that can be tested in future clinical studies assessing the potential therapeutic benefits of intradural SCS.

Sensor spacing affects the tissue impedance spectra of rabbit ventricular epicardium

This study was designed to test the hypothesis that a complex composite impedance spectra develops when stimulation and recording of cardiac muscle with sufficiently fine spatial resolution in a four-electrode configuration is used. With traditional (millimeter scale) separations, the ratio between the recorded interstitial central potential difference and total supplied interstitial current is constant at all frequencies. This occurs because the fraction of supplied current that redistributes to the intracellular compartment depends on effective membrane resistance between electrodes, which is low, to a much greater extent than effective membrane capacitance. The spectra should therefore change with finer separations at which effective membrane resistance increases, as supplied current will remain primarily interstitial at lower frequencies and redistribute between compartments at higher frequencies. To test this hypothesis, we built arrays with sensors separated (d) by 804 μm, 452 μm, and 252 μm; positioned those arrays across myocyte axes on rabbit ventricular epicardium; and resolved spectra in terms of resistivity (ρt) and reactivity (χt) over the 10 Hz to 4,000 Hz range. With all separations, we measured comparable spectra with predictions from passive membrane simulations that used a three-dimensional structural framework in which intracellular, interstitial, and membrane properties were prescribed based on the limited data available from the literature. At the finest separation, we found mean ρt at 100 Hz and 4,000 Hz that lowered from 395 Ω-cm to 236 Ω-cm, respectively, with maximal mean χt of 160 Ω-cm. This experimental confirmation of spectra development in whole heart experiments is important because such development is central to achieve measurements of intracellular and interstitial passive electrical properties in cardiac electrophysiological experiments using only interstitial access.

Modeling the chemoelectromechanical behavior of skeletal muscle using the parallel open-source software library OpenCMISS

An extensible, flexible, multiscale, and multiphysics model for nonisometric skeletal muscle behavior is presented. The skeletal muscle chemoelectromechanical model is based on a bottom-up approach modeling the entire excitation-contraction pathway by strongly coupling a detailed biophysical model of a half-sarcomere to the propagation of action potentials along skeletal muscle fibers and linking cellular parameters to a transversely isotropic continuum-mechanical constitutive equation describing the overall mechanical behavior of skeletal muscle tissue. Since the multiscale model exhibits separable time scales, a special emphasis is placed on employing computationally efficient staggered solution schemes. Further, the implementation builds on the open-source software library OpenCMISS and uses state-of-the-art parallelization techniques taking advantage of the unique anatomical fiber architecture of skeletal muscles. OpenCMISS utilizes standardized data structures for geometrical aspects (FieldML) and cellular models (CellML). Both standards are designed to allow for a maximum flexibility, reproducibility, and extensibility. The results demonstrate the model's capability of simulating different aspects of nonisometric muscle contraction and efficiently simulating the chemoelectromechanical behavior in complex skeletal muscles such as the tibialis anterior muscle.

A new approach for resolution of complex tissue impedance spectra in hearts

This study was designed to test the feasibility of using sinusoidal approximation in combination with a new instrumentation approach to resolve complex impedance (uCI) spectra from heart preparations. To assess that feasibility, we applied stimuli in the 10-4000 Hz range and recorded potential differences (uPDs) in a four-electrode configuration that allowed identification of probe constants (Kp) during calibration that were in turn used to measure total tissue resistivity ρt from rabbit ventricular epicardium. Simultaneous acquisition of a signal proportional to the supplied current (Vstim) with uPD allowed identification of the V- I ratio needed for ρt measurement, as well as the phase shift from Vstim to uPD needed for uCI spectra resolution. Performance with components integrated to reduce noise in cardiac electrophysiologic experiments, in particular, and provide accurate electrometer-based measurements, in general, was first characterized in tests using passive loads. Load tests showed accurate uCI recovery with mean uPD SNRs between 10 (1) and 10 (3) measured with supplied currents as low as 10 nA. Comparable performance characteristics were identified during calibration of nine arrays built with 250 μm Ag/AgCl electrodes, with uCIs that matched analytic predictions and no apparent effect of frequency ( F = 0.12, P = 0.99). The potential ability of parasitic capacitance in the presence of the electrode-electrolyte interface associated with the small sensors to influence the uCI spectra was therefore limited by the instrumentation. Resolution of uCI spectra in rabbit ventricle allowed measurement of ρt = 134 ± 53 Ω· cm. The rapid identification available with this strategy provides an opportunity for new interpretations of the uCI spectra to improve quantification of disease-, region-, tissue-, and species-dependent intercellular uncoupling in hearts.

Volume conductor models in surface electromyography: computational techniques

Models of surface electromyogram (EMG) are useful to assess the effect of geometrical or conductivity properties of the tissue on the recorded signal. This paper provides a review of structure based models describing specific volume conductors. The technique for the development of advanced analytical and numerical simulators is described. A new model is also introduced, simulating a layered volume conductor including a subcutaneous tissue with variable thicknesses, providing an approximate analytical solution in the Fourier transform domain. Note that volume conductors are described using Poisson equation, fundamental model of Mathematical Physics, which applies also to mechanics, diffusion, electrostatics problems.

Impact of surrounding tissue on conductance measurement of coronary and peripheral lumen area

Parallel conductance (electric current flow through surrounding tissue) is an important determinant of accurate measurements of arterial lumen diameter, using the conductance method. The present study is focused on the role of non-uniform geometrical/electrical configurations of surrounding tissue, which are a primary source of electric current leakage. Computational models were constructed to simulate the conductance catheter measurement with two different excitation electrodes spacings (i.e. 12 and 20 mm for coronary and peripheral sizing, respectively) for different vessel-tissue configurations: (i) blood vessel fully embedded in muscle tissue, (ii) blood vessel superficially embedded in muscle tissue, and (iii) blood vessel superficially embedded in muscle tissue with fat covering half of the arterial vessel (anterior portion). The simulations suggest that the parallel conductance and accuracy of measurement is dependent on the inhomogeneous/anisotropic configuration of surrounding tissue, including the asymmetric dimension and anisotropy in electrical conductivity of surrounding tissue. Specifically, the measurement was shown to be accurate as long as the vessel was superficial, regardless of the considerable total surrounding tissue dimension for coronary or peripheral arteries. Moreover, it was shown that the unfavourable impact of parallel conductance on the accuracy of conductance catheter measurement is decreased by the combination of a lower transverse electrical conductivity of surrounding muscle tissue, a smaller electrode spacing and a larger lumen diameter. The present findings confirm that the conductance catheter technique provides an accurate platform for sizing of clinically relevant (i.e. superficial and diseased) arteries.

Discriminating neurogenic from myopathic disease via measurement of muscle anisotropy

Skeletal muscle is electrically anisotropic, with a tendency for applied electrical current to flow more readily along muscle fibers than across them. In this study, we assessed a method for non-invasive measurement of anisotropy to determine its potential to serve as a new technique for distinguishing neurogenic from myopathic disease. Measurements were made on the biceps brachii and tibialis anterior muscles in 15 normal subjects and 12 patients with neuromuscular disease (6 with amyotrophic lateral sclerosis and 6 with various myopathies) using 50 kHZ applied current. Consistent multi-angle anisotropic patterns were found for reactance and phase in both muscles in normal subjects. Normalized anisotropy differences for each subject were defined, and group average values identified. The amyotrophic lateral sclerosis (ALS) patients demonstrated increased and distorted anisotropy patterns, whereas myopathic patients demonstrated normal or reduced anisotropy. These results suggest that non-invasive measurement of muscle anisotropy has potential for diagnosis of neuromuscular diseases.

Distribution of electrical stimulation current in a planar multilayer anisotropic tissue

This study analytically addresses the problem of neuromuscular electrical stimulation for a planar, multilayer, anisotropic model of a physiological tissue (referred to as volume conductor). Both conductivity and permittivity of the volume conductor are considered, including dispersive properties. The analytical solution is obtained in the 2-D Fourier transform domain, transforming in the planes parallel to the volume conductor surface. The model is efficient in terms of computational cost, as the solution is analytical (only numerical Fourier inversion is needed). It provides the current distribution in a physiological tissue induced by an electrical current delivered at the skin surface. Three representative examples of application of the model are considered. 1) The simulation of stimulation artefact during transcutaneous electrical stimulation and EMG detection. Only the effect of the volume conductor is considered, neglecting the other sources of artefact (such as the capacitive coupling between the stimulating and recording electrodes). 2) The simulation of the electrical current distribution within the muscle and the low-pass filter effect of the volume conductor on sinusoidal stimulation currents with different stimulation frequencies. 3) The estimation of the amplitude modulated current distribution within the muscle for interferential stimulation. The model is devoted to the simulation of neuromuscular stimulation, but the same method could be applied in other fields in which the estimation of the electrical current distribution in a medium induced by the injection of a current from the boundary of the medium is of interest.