Estimation of Gait Parameters in Huntington's Disease using Wearable Sensors in the Clinic and Free-living Conditions.

In Huntington's disease (HD), wearable inertial sensors could capture subtle changes in motor function. However, disease-specific validation of methods is necessary. This study presents an algorithm for walking bout and gait event detection in HD using a leg-worn accelerometer, validated only in the clinic and deployed in free-living conditions. Seventeen HD participants wore shank- and thigh-worn tri-axial accelerometers, and a wrist-worn device during two-minute walk tests in the clinic, with video reference data for validation. Thirteen participants wore one of the thigh-worn tri-axial accelerometers (AP: ActivPAL4) and the wrist-worn device for 7 days under free-living conditions, with proprietary AP data used as reference. Gait events were detected from shank and thigh acceleration using the Teager-Kaiser energy operator combined with unsupervised clustering. Estimated step count (SC) and temporal gait parameters were compared with reference data. In the clinic, low mean absolute percentage errors were observed for stride (shank/thigh: 0.6/0.9%) and stance (shank/thigh: 3.3/7.1%) times, and SC (shank/thigh: 3.1%). Similar errors were observed for proprietary AP SC (3.2%), with higher errors observed for the wrist-worn device (10.9%). At home, excellent agreement was observed between the proposed algorithm and AP software for SC and time spent walking (ICC2,1>0.975). The wrist-worn device overestimated SC by 34.2%. The presented algorithm additionally allowed stride and stance time estimation, whose variability correlated significantly with clinical motor scores. The results demonstrate a new method for accurate estimation of HD gait parameters in the clinic and free-living conditions, using a single accelerometer worn on either the thigh or shank.

Language-Independent Acoustic Biomarkers for Quantifying Speech Impairment in Huntington's Disease.

PURPOSE: Changes in voice and speech are characteristic symptoms of Huntington's disease (HD). Objective methods for quantifying speech impairment that can be used across languages could facilitate assessment of disease progression and intervention strategies. The aim of this study was to analyze acoustic features to identify language-independent features that could be used to quantify speech dysfunction in English-, Spanish-, and Polish-speaking participants with HD. METHOD: Ninety participants with HD and 83 control participants performed sustained vowel, syllable repetition, and reading passage tasks recorded with previously validated methods using mobile devices. Language-independent features that differed between HD and controls were identified. Principal component analysis (PCA) and unsupervised clustering were applied to the language-independent features of the HD data set to identify subgroups within the HD data. RESULTS: Forty-six language-independent acoustic features that were significantly different between control participants and participants with HD were identified. Following dimensionality reduction using PCA, four speech clusters were identified in the HD data set. Unified Huntington's Disease Rating Scale (UHDRS) total motor score, total functional capacity, and composite UHDRS were significantly different for pairwise comparisons of subgroups. The percentage of HD participants with higher dysarthria score and disease stage also increased across clusters. CONCLUSION: The results support the application of acoustic features to objectively quantify speech impairment and disease severity in HD in multilanguage studies. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25447171.

Consensus for experimental design in electromyography (CEDE) project: Checklist for reporting and critically appraising studies using EMG (CEDE-Check).

The diversity in electromyography (EMG) techniques and their reporting present significant challenges across multiple disciplines in research and clinical practice, where EMG is commonly used. To address these challenges and augment the reproducibility and interpretation of studies using EMG, the Consensus for Experimental Design in Electromyography (CEDE) project has developed a checklist (CEDE-Check) to assist researchers to thoroughly report their EMG methodologies. Development involved a multi-stage Delphi process with seventeen EMG experts from various disciplines. After two rounds, consensus was achieved. The final CEDE-Check consists of forty items that address four critical areas that demand precise reporting when EMG is employed: the task investigated, electrode placement, recording electrode characteristics, and acquisition and pre-processing of EMG signals. This checklist aims to guide researchers to accurately report and critically appraise EMG studies, thereby promoting a standardised critical evaluation, and greater scientific rigor in research that uses EMG signals. This approach not only aims to facilitate interpretation of study results and comparisons between studies, but it is also expected to contribute to advancing research quality and facilitate clinical and other practical applications of knowledge generated through the use of EMG.

Assessment of Fitbit Charge 4 for sleep stage and heart rate monitoring against polysomnography and during home monitoring in Huntington's disease.

STUDY OBJECTIVES: Wearable devices, monitoring sleep stages and heart rate (HR), bring the potential for longitudinal sleep monitoring in patients with neurodegenerative diseases. Sleep quality reduces with disease progression in Huntington's disease (HD). However, the involuntary movements characteristic of HD may affect the accuracy of wrist-worn devices. This study compares sleep stage and heart rate data from the Fitbit Charge 4 (FB) against polysomnography (PSG) in participants with HD. METHODS: Ten participants with manifest HD wore a FB during overnight hospital-based PSG, and for nine of these participants continued to wear the FB for seven nights at home. Sleep stages (30s epochs) and minute-by-minute HR were extracted and compared against PSG data. RESULTS: FB-estimated total sleep and wake times, and sleep stage times were in good agreement with PSG, with intra-class correlations 0.79-0.96. However, poor agreement was observed for Wake After Sleep Onset, and the number of awakenings. FB detected wake with 68.6±15.5% sensitivity and 93.7±2.5% specificity, rapid eye movement (REM) sleep with high sensitivity and specificity (78.7±31.9%, 95.6±2.3%), and deep sleep with lower sensitivity but high specificity (56.4±28.8%, 95.0±4.8%). FB HR was strongly correlated with PSG, and the mean absolute error between FB and PSG HR data was 1.16 ± 0.42 bpm. At home, longer sleep and shorter wake times were observed compared to hospital data, while percentage sleep stage times were consistent with hospital data. CONCLUSIONS: Results suggest the potential for long-term monitoring of sleep patterns using wrist-worn wearable devices as part of symptom management in HD.

Electroencephalographic ß-band oscillations in the sensorimotor network reflect motor symptom severity in amyotrophic lateral sclerosis.

BACKGROUND AND PURPOSE: Resting-state electroencephalography (EEG) holds promise for assessing brain networks in amyotrophic lateral sclerosis (ALS). We investigated whether neural ß-band oscillations in the sensorimotor network could serve as an objective quantitative measure of progressive motor impairment and functional disability in ALS patients. METHODS: Resting-state EEG was recorded in 18 people with ALS and 38 age- and gender-matched healthy controls. We estimated source-localized ß-band spectral power in the sensorimotor cortex. Clinical evaluation included lower (LMN) and upper motor neuron scores, Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised score, fine motor function (FMF) subscore, and progression rate. Correlations between clinical scores and ß-band power were analysed and corrected using a false discovery rate of q = 0.05. RESULTS: ß-Band power was significantly lower in people with ALS than controls (p = 0.004), and correlated with LMN score (R = -0.65, p = 0.013), FMF subscore (R = -0.53, p = 0.036), and FMF progression rate (R = 0.52, p = 0.036). CONCLUSIONS: ß-Band spectral power in the sensorimotor cortex reflects clinically evaluated motor impairment in ALS. This technology merits further investigation as a biomarker of progressive functional disability.

On-Off and Proportional Closed-Loop Adaptive Deep Brain Stimulation Reduces Motor Symptoms in Freely Moving Hemiparkinsonian Rats.

OBJECTIVES: Closed-loop adaptive deep brain stimulation (aDBS) continuously adjusts stimulation parameters, with the potential to improve efficacy and reduce side effects of deep brain stimulation (DBS) for Parkinson's disease (PD). Rodent models can provide an effective platform for testing aDBS algorithms and establishing efficacy before clinical investigation. In this study, we compare two aDBS algorithms, on-off and proportional modulation of DBS amplitude, with conventional DBS in hemiparkinsonian rats. MATERIALS AND METHODS: DBS of the subthalamic nucleus (STN) was delivered wirelessly in freely moving male and female hemiparkinsonian (N = 7) and sham (N = 3) Wistar rats. On-off and proportional aDBS, based on STN local field potential beta power, were compared with conventional DBS and three control stimulation algorithms. Behavior was assessed during cylinder tests (CT) and stepping tests (ST). Successful model creation was confirmed via apomorphine-induced rotation test and Tyrosine Hydroxylase-immunocytochemistry. Electrode location was histologically confirmed. Data were analyzed using linear mixed models. RESULTS: Contralateral paw use in parkinsonian rats was reduced to 20% and 25% in CT and ST, respectively. Conventional, on-off, and proportional aDBS significantly improved motor function, restoring contralateral paw use to approximately 45% in both tests. No improvement in motor behavior was observed with either randomly applied on-off or low-amplitude continuous stimulation. Relative STN beta power was suppressed during DBS. Relative power in the alpha and gamma bands decreased and increased, respectively. Therapeutically effective adaptive DBS used approximately 40% less energy than did conventional DBS. CONCLUSIONS: Adaptive DBS, using both on-off and proportional control schemes, is as effective as conventional DBS in reducing motor symptoms of PD in parkinsonian rats. Both aDBS algorithms yield substantial reductions in stimulation power. These findings support using hemiparkinsonian rats as a viable model for testing aDBS based on beta power and provide a path to investigate more complex closed-loop algorithms in freely behaving animals.

Impact of Network Topology on Neural Synchrony in a Model of the Subthalamic Nucleus-Globus Pallidus Circuit.

Synchronous neural oscillations within the beta frequency range are observed across the parkinsonian basal ganglia network, including within the subthalamic nucleus (STN) - globus pallidus (GPe) subcircuit. The emergence of pathological synchrony in Parkinson's disease is often attributed to changes in neural properties or connection strength, and less often to the network topology, i.e. the structural arrangement of connections between neurons. This study investigates the relationship between network structure and neural synchrony in a model of the STN-GPe circuit comprised of conductance-based spiking neurons. Changes in net synaptic input were controlled for through a synaptic scaling rule, which facilitated separation of the effects of network structure from net synaptic input. Five topologies were examined as structures for the STN-GPe circuit: Watts-Strogatz, preferential attachment, spatial, stochastic block, k-regular random. Beta band synchrony generally increased as the number of connections increased, however the exact relationship was topology specific. Varying the wiring pattern while maintaining a constant number of connections caused network synchrony to be enhanced or suppressed, demonstrating the ability of purely structural changes to alter synchrony. This relationship was well-captured by the algebraic connectivity of the network, the second smallest eigenvalue of the network's Laplacian matrix. The structure-synchrony relationship was further investigated in a network model designed to emulate the action selection role of the STN-GPe circuit. It was found that increasing the number of connections and/or the overlap of action selection channels could lead to a rapid transition to synchrony, which was also predicted by the algebraic connectivity.

Multivariable closed-loop control of deep brain stimulation for Parkinson's disease.

Objective. Closed-loop deep brain stimulation (DBS) methods for Parkinson's disease (PD) to-date modulate either stimulation amplitude or frequency to control a single biomarker. While good performance has been demonstrated for symptoms that are correlated with the chosen biomarker, suboptimal regulation can occur for uncorrelated symptoms or when the relationship between biomarker and symptom varies. Control of stimulation-induced side-effects is typically not considered.Approach.A multivariable control architecture is presented to selectively target suppression of either tremor or subthalamic nucleus beta band oscillations. DBS pulse amplitude and duration are modulated to maintain amplitude below a threshold and avoid stimulation of distal large diameter axons associated with stimulation-induced side effects. A supervisor selects between a bank of controllers which modulate DBS pulse amplitude to control rest tremor or beta activity depending on the level of muscle electromyographic (EMG) activity detected. A secondary controller limits pulse amplitude and modulates pulse duration to target smaller diameter axons lying close to the electrode. The control architecture was investigated in a computational model of the PD motor network which simulated the cortico-basal ganglia network, motoneuron pool, EMG and muscle force signals.Main results.Good control of both rest tremor and beta activity was observed with reduced power delivered when compared with conventional open loop stimulation, The supervisor avoided over- or under-stimulation which occurred when using a single controller tuned to one biomarker. When DBS amplitude was constrained, the secondary controller maintained the efficacy of stimulation by increasing pulse duration to compensate for reduced amplitude. Dual parameter control delivered effective control of the target biomarkers, with additional savings in the power delivered.Significance.Non-linear multivariable control can enable targeted suppression of motor symptoms for PD patients. Moreover, dual parameter control facilitates automatic regulation of the stimulation therapeutic dosage to prevent overstimulation, whilst providing additional power savings.

Micromotion Derived Fluid Shear Stress Mediates Peri-Electrode Gliosis through Mechanosensitive Ion Channels.

The development of bioelectronic neural implant technologies has advanced significantly over the past 5 years, particularly in brain-machine interfaces and electronic medicine. However, neuroelectrode-based therapies require invasive neurosurgery and can subject neural tissues to micromotion-induced mechanical shear, leading to chronic inflammation, the formation of a peri-electrode void and the deposition of reactive glial scar tissue. These structures act as physical barriers, hindering electrical signal propagation and reducing neural implant functionality. Although well documented, the mechanisms behind the initiation and progression of these processes are poorly understood. Herein, in silico analysis of micromotion-induced peri-electrode void progression and gliosis is described. Subsequently, ventral mesencephalic cells exposed to milliscale fluid shear stress in vitro exhibited increased expression of gliosis-associated proteins and overexpression of mechanosensitive ion channels PIEZO1 (piezo-type mechanosensitive ion channel component 1) and TRPA1 (transient receptor potential ankyrin 1), effects further confirmed in vivo in a rat model of peri-electrode gliosis. Furthermore, in vitro analysis indicates that chemical inhibition/activation of PIEZO1 affects fluid shear stress mediated astrocyte reactivity in a mitochondrial-dependent manner. Together, the results suggest that mechanosensitive ion channels play a major role in the development of a peri-electrode void and micromotion-induced glial scarring at the peri-electrode region.

Cortico-muscular coherence in primary lateral sclerosis reveals abnormal cortical engagement during motor function beyond primary motor areas.

Primary lateral sclerosis (PLS) is a slowly progressing disorder, which is characterized primarily by the degeneration of upper motor neurons (UMNs) in the primary motor area (M1). It is not yet clear how the function of sensorimotor networks beyond M1 are affected by PLS. The aim of this study was to use cortico-muscular coherence (CMC) to characterize the oscillatory drives between cortical regions and muscles during a motor task in PLS and to examine the relationship between CMC and the level of clinical impairment. We recorded EEG and EMG from hand muscles in 16 participants with PLS and 18 controls during a pincer-grip task. In PLS, higher CMC was observed over contralateral-M1 (α- and γ-band) and ipsilateral-M1 (ß-band) compared with controls. Significant correlations between clinically assessed UMN scores and CMC measures showed that higher clinical impairment was associated with lower CMC over contralateral-M1/frontal areas, higher CMC over parietal area, and both higher and lower CMC (in different bands) over ipsilateral-M1. The results suggest an atypical engagement of both contralateral and ipsilateral M1 during motor activity in PLS, indicating the presence of pathogenic and/or adaptive/compensatory alterations in neural activity. The findings demonstrate the potential of CMC for identifying dysfunction within the sensorimotor networks in PLS.

Effects of Contralateral Deep Brain Stimulation and Levodopa on Subthalamic Nucleus Oscillatory Activity and Phase-Amplitude Coupling.

BACKGROUND: The modulatory effects of medication and deep brain stimulation (DBS) on subthalamic nucleus (STN) neural activity in Parkinson's disease have been widely studied. However, effects on the contralateral side to the stimulated STN, in particular, changes in local field potential (LFP) oscillatory activity and phase-amplitude coupling (PAC), have not yet been reported. OBJECTIVE: The aim of this study was to examine changes in STN LFP activity across a range of frequency bands and STN PAC for different combinations of DBS and medication on/off on the side contralateral to the applied stimulation. MATERIALS AND METHODS: We examined STN LFPs that were recorded using externalized leads from eight parkinsonian patients during unilateral DBS from the side contralateral to the stimulation. LFP spectral power in alpha (5 to ∼13 Hz), low beta (13 to ∼20 Hz), high beta (20-30 Hz), and high gamma plus high-frequency oscillation (high gamma+HFO) (100-400 Hz) bands were estimated for different combinations of medication and unilateral stimulation (off/on). PAC between beta and high gamma+HFO in the STN LFPs was also investigated. The effect of the condition was examined using linear mixed models. RESULTS: PAC in the STN LFP was reduced by DBS when compared to the baseline condition (no medication and stimulation). Medication had no significant effect on PAC. Alpha power decreased with DBS, both alone and when combined with medication. Beta power decreased with DBS, medication, and DBS and medication combined. High gamma+HFO power increased during the application of contralateral DBS and was unaltered by medication. CONCLUSIONS: The results provide new insights into the effects of DBS and levodopa on STN LFP PAC and oscillatory activity on the side contralateral to stimulation. These may have important implications in understanding mechanisms underlying motor improvements with DBS, including changes on both contralateral and ipsilateral sides, while suggesting a possible role for contralateral sensing during unilateral DBS.

Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix.

The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials generated by an alpha motor neuron and those received by the innervated muscle fibers. Such a powerful assessment has been conventionally performed with invasive electrodes (i.e., intramuscular electromyography (EMG)), however, recent advances in signal processing techniques have enabled the identification of single motor unit (SMU) activity in high-density surface electromyography (HDsEMG) recordings. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, provides recommendations for the recording and analysis of SMU activity with both invasive (needle and fine-wire EMG) and non-invasive (HDsEMG) SMU identification methods, summarizing their advantages and disadvantages when used during different testing conditions. Recommendations for the analysis and reporting of discharge rate and peripheral (i.e., muscle fiber conduction velocity) SMU properties are also provided. The results of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers to collect, report, and interpret SMU data in the context of both research and clinical applications.

Feasibility of pair-housing of rats after cranial implant surgery.

Rat models employing cranial implants are increasingly employed to facilitate neural stimulation and recording in freely moving animals. Due to possible damage to wound, implant or attached devices, rats with cranial implants are traditionally housed singly, and little information is available on group- or pair-housing. Here we describe a protocol for pair-housing rats following cranial implant surgery and describe our experience with pair-housing during post-surgical recovery and up to 16 weeks following surgery.Thirty-six adult Wistar rats of both sexes were implanted with deep brain stimulation electrodes. Ten rats were equipped with an additional wireless headstage. Rats were housed in stable pairs before surgery and re-introduced 0-18 h post-surgery. Rat grimace scores did not indicate pain after conclusion of the analgesia protocol, physiological parameters were in the normal range three days post-surgery and weight loss did not exceed 10%. Rats with a cement cap only were pair-housed continuously without damage to the headcap. Rats carrying an additional fragile headstage had to be separated during lights-off periods to prevent headstage damage but could be pair-housed during lights-on periods.Pair-housing is a feasible and effective method to facilitate the rats' need for social companionship following cranial implant surgery.

Prediction of low pulse oxygen saturation in COVID-19 using remote monitoring post hospital discharge.

BACKGROUND: Monitoring systems have been developed during the COVID-19 pandemic enabling clinicians to remotely monitor physiological measures including pulse oxygen saturation (SpO2), heart rate (HR), and breathlessness in patients after discharge from hospital. These data may be leveraged to understand how symptoms vary over time in COVID-19 patients. There is also potential to use remote monitoring systems to predict clinical deterioration allowing early identification of patients in need of intervention. METHODS: A remote monitoring system was used to monitor 209 patients diagnosed with COVID-19 in the period following hospital discharge. This system consisted of a patient-facing app paired with a Bluetooth-enabled pulse oximeter (measuring SpO2 and HR) linked to a secure portal where data were available for clinical review. Breathlessness score was entered manually to the app. Clinical teams were alerted automatically when SpO2 < 94 %. In this study, data recorded during the initial ten days of monitoring were retrospectively examined, and a random forest model was developed to predict SpO2 < 94 % on a given day using SpO2 and HR data from the two previous days and day of discharge. RESULTS: Over the 10-day monitoring period, mean SpO2 and HR increased significantly, while breathlessness decreased. The coefficient of variation in SpO2, HR and breathlessness also decreased over the monitoring period. The model predicted SpO2 alerts (SpO2 < 94 %) with a mean cross-validated. sensitivity of 66 ± 18.57 %, specificity of 88.31 ± 10.97 % and area under the receiver operating characteristic of 0.80 ± 0.11. Patient age and sex were not significantly associated with the occurrence of asymptomatic SpO2 alerts. CONCLUSION: Results indicate that SpO2 alerts (SpO2 < 94 %) on a given day can be predicted using SpO2 and heart rate data captured on the two preceding days via remote monitoring. The methods presented may help early identification of patients with COVID-19 at risk of clinical deterioration using remote monitoring.

Comparison of Acoustic Voice Features Derived From Mobile Devices and Studio Microphone Recordings.

OBJECTIVES/HYPOTHESIS: Improvements in mobile device technology offer new opportunities for remote monitoring of voice for home and clinical assessment. However, there is a need to establish equivalence between features derived from signals recorded from mobile devices and gold standard microphone-preamplifiers. In this study acoustic voice features from android smartphone, tablet, and microphone-preamplifier recordings were compared. METHODS: Data were recorded from 37 volunteers (20 female) with no history of speech disorder and six volunteers with Huntington's disease (HD) during sustained vowel (SV) phonation, reading passage (RP), and five syllable repetition (SR) tasks. The following features were estimated: fundamental frequency median and standard deviation (F0 and SD F0), harmonics-to-noise ratio (HNR), local jitter, relative average perturbation of jitter (RAP), five-point period perturbation quotient (PPQ5), difference of differences of amplitude and periods (DDA and DDP), shimmer, and amplitude perturbation quotients (APQ3, APQ5, and APQ11). RESULTS: Bland-Altman analysis revealed good agreement between microphone and mobile devices for fundamental frequency, jitter, RAP, PPQ5, and DDP during all tasks and a bias for HNR, shimmer and its variants (APQ3, APQ5, APQ11, and DDA). Significant differences were observed between devices for HNR, shimmer, and its variants for all tasks. High correlation was observed between devices for all features, except SD F0 for RP. Similar results were observed in the HD group for SV and SR task. Biological sex had a significant effect on F0 and HNR during all tests, and for jitter, RAP, PPQ5, DDP, and shimmer for RP and SR. No significant effect of age was observed. CONCLUSIONS: Mobile devices provided good agreement with state of the art, high-quality microphones during structured speech tasks for features derived from frequency components of the audio recordings. Caution should be taken when estimating HNR, shimmer and its variants from recordings made with mobile devices.

Deep-spindle: An automated sleep spindle detection system for analysis of infant sleep spindles.

BACKGROUND: Sleep spindles are an indicator of the development and integrity of the central nervous system in infants. Identifying sleep spindles manually in EEG is time-consuming and typically requires experienced experts. Automated detection of sleep spindles would greatly facilitate this analysis. Deep learning methods have been widely used recently in EEG analysis. METHOD: We have developed a deep learning-based automated sleep spindle detection system, Deep-spindle, which employs a convolutional neural network (CNN) combined with a bidirectional Long Short-Term Memory (LSTM) network, which could assist in the analysis of infant sleep spindles. Deep-spindle was trained on the EEGs of ex-term infants to estimate the number and duration of sleep spindles. The ex-term EEG on channel F4-C4 was split into training (N=81) and validation (N=30) sets. An additional 30 ex-term EEG and 54 ex-preterm infant EEGs (channel F4-C4 and F3-C3) were used as an independent test set. RESULT: Deep-spindle detected the number of sleep spindles with 91.9% to 96.5% sensitivity and 95.3% to 96.7% specificity, and estimated sleep spindle duration with a percent error of 13.1% to 19.1% in the independent test set. For each detected spindle event, the user is presented with amplitude, power spectral density and the spectrogram of the corresponding spindle EEG, and the probability of the event being a sleep spindle event, providing the user with insight into why the event is predicted as a sleep spindle to provide confidence in the predictions. CONCLUSION: The Deep-spindle system can reduce physicians' workload, demonstrating the potential to assist physicians in the automated analysis of sleep spindles in infants.

Computational Model of the Effect of Mitochondrial Dysfunction on Excitation-Contraction Coupling in Skeletal Muscle.

It has become well established that mitochondria not only regulate myoplasmic calcium in skeletal muscle, but also use that calcium to stimulate oxidative phosphorylation (OXPHOS). While experimental approaches have allowed for imaging of mitochondrial calcium and membrane potentials in isolated fibers, capturing the role of mitochondria and the impact of mitochondrial impairments on excitation-contraction coupling (ECC) remains difficult to explore in intact muscle. Computational models have been widely used to examine the structure and function of skeletal muscle contraction; however, models of ECC to date lack communication between the myoplasm and mitochondria for regulating calcium and ATP during sustained contractions. To address this, a mathematical model of mitochondrial calcium handling and OXPHOS was integrated into a physiological model of ECC incorporating action potential propagation, calcium handling between the sarcoplasmic reticulum (SR) and the myoplasm, and crossbridge cycling. The model was used to examine the protective role of mitochondria during repeated stimulation and the impact of mitochondrial dysfunction on ECC resulting from progressive OXPHOS inhibition. Pathological myoplasmic calcium accumulation occurred through distinct mechanisms in the model in the case of either electron transport chain, F1F0 ATP synthase, or adenine nucleotide transporter impairments. To investigate the effect of each impairment on force, a model of calcium-stimulated apoptosis was utilized to capture dysfunction-induced reductions in muscle mass, driving whole muscle force loss. The model presented in this study can be used to examine the role of mitochondria in the regulation of calcium, ATP, and force generation during voluntary contraction.

Consensus for experimental design in electromyography (CEDE) project: High-density surface electromyography matrix.

High-density surface electromyography (HDsEMG) can be used to measure the spatial distribution of electrical muscle activity over the skin. As this distribution is associated with the generation and propagation of muscle fiber action potentials, HDsEMG is processed to extract information on regional muscle activation, muscle fiber characteristics and behaviour of individual motor units. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, summarizes recommendations on the use of HDsEMG in experimental studies. For each application, recommendations are included regarding electrode montage, electrode type and configuration, electrode location and orientation, data analysis, and interpretation. Cautions and reporting standards are also included. The steps of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers when collecting, reporting, and interpreting HDsEMG data. It is hoped that this document will be used to generate new empirical evidence to improve how HDsEMG is used in research and in clinical applications.

Age-related fatigability in knee extensors and knee flexors during dynamic fatiguing contractions.

This study investigated the effects of dynamic knee extension and flexion fatiguing task on torque and neuromuscular responses in young and older individuals. Eighteen young (8 males; 25.1 ± 3.2 years) and 17 older (8 males; 69.7 ± 3.7 years) volunteered. Following a maximal voluntary isometric contraction test, participants performed a fatiguing task involving 22 maximal isokinetic (concentric) knee extension and flexion contractions at 60°/s, while surface EMG was recorded simultaneously from the knee extensors (KE) and flexors (KF). Fatigue-induced relative torque reductions were similar between age groups for KE (peak torque decrease: 25.15% vs 26.81%); however, KF torque was less affected in older individuals (young vs older peak torque decrease: 27.6% vs 11.5%; p < 0.001) and this was associated with greater increase in hamstring EMG amplitude (p < 0.001) and hamstrings/quadriceps peak torque ratio (p < 0.01). Furthermore, KE was more fatigable than KF only among older individuals (peak torque decrease: 26.8% vs 11.5%; p < 0.001). These findings showed that the age-related fatigue induced by a dynamic task was greater for the KE, with greater age-related decline in KE compared to KF.