Benchtop Performance of Novel Mixed Ionic-Electronic Conductive Electrode Form Factors for Biopotential Recordings.

Background: Traditional gel-based (wet) electrodes for biopotential recordings have several shortcomings that limit their practicality for real-world measurements. Dry electrodes may improve usability, but they often suffer from reduced signal quality. We sought to evaluate the biopotential recording properties of a novel mixed ionic-electronic conductive (MIEC) material for improved performance. Methods: We fabricated four MIEC electrode form factors and compared their signal recording properties to two control electrodes, which are electrodes commonly used for biopotential recordings (Ag-AgCl and stainless steel). We used an agar synthetic skin to characterize the impedance of each electrode form factor. An electrical phantom setup allowed us to compare the recording quality of simulated biopotentials with ground-truth sources. Results: All MIEC electrode form factors yielded impedances in a similar range to the control electrodes (all <80 kΩ at 100 Hz). Three of the four MIEC samples produced similar signal-to-noise ratios and interfacial charge transfers as the control electrodes. Conclusions: The MIEC electrodes demonstrated similar and, in some cases, better signal recording characteristics than current state-of-the-art electrodes. MIEC electrodes can also be fabricated into a myriad of form factors, underscoring the great potential this novel material has across a wide range of biopotential recording applications.

Either Autonomy Support or Enhanced Expectancies Delivered Via Virtual-Reality Benefits Frontal-Plane Single-Leg Squatting Kinematics.

Our purpose in this study was to determine the effects of a virtual reality intervention delivering specific motivational motor learning manipulations of either autonomy support (AS) or enhanced expectancies (EE) on frontal plane single-leg squatting kinematics. We allocated 45 participants (21 male, 24 female) demonstrating knee, hip, and trunk frontal plane mechanics associated with elevated anterior cruciate ligament injury risk to one of three groups (control, AS, or EE). Participants mimicked an avatar performing five sets of eight repetitions of exemplary single-leg squats. AS participants were given the added option of choosing the color of their avatar. EE participants received real-time biofeedback in the form of green highlights on the avatar that remained on as long as the participant maintained pre-determined 'safe' frontal plane mechanics. We measured peak frontal plane knee, hip, and trunk angles before (baseline) and immediately following (post) the intervention. The control group demonstrated greater increases in knee abduction angle (Δ = +2.3°) than did the AS (Δ = +0.1°) and EE groups (Δ = -0.4°) (p = .003; η2p = .28). All groups demonstrated increased peak hip adduction (p = .01, ηp2 = .18) (control Δ = +1.5°; AS Δ = +3.2°; EE Δ = +0.7°). Hip adduction worsened in all groups. AS and EE motivation strategies appeared to mitigate maladaptive frontal plane knee mechanics.

Decoding hand and wrist movement intention from chronic stroke survivors with hemiparesis using a user-friendly, wearable EMG-based neural interface.

OBJECTIVE: Seventy-five percent of stroke survivors, caregivers, and health care professionals (HCP) believe current therapy practices are insufficient, specifically calling out the upper extremity as an area where innovation is needed to develop highly usable prosthetics/orthotics for the stroke population. A promising method for controlling upper extremity technologies is to infer movement intention non-invasively from surface electromyography (EMG). However, existing technologies are often limited to research settings and struggle to meet user needs. APPROACH: To address these limitations, we have developed the NeuroLife® EMG System, an investigational device which consists of a wearable forearm sleeve with 150 embedded electrodes and associated hardware and software to record and decode surface EMG. Here, we demonstrate accurate decoding of 12 functional hand, wrist, and forearm movements in chronic stroke survivors, including multiple types of grasps from participants with varying levels of impairment. We also collected usability data to assess how the system meets user needs to inform future design considerations. MAIN RESULTS: Our decoding algorithm trained on historical- and within-session data produced an overall accuracy of 77.1 ± 5.6% across 12 movements and rest in stroke participants. For individuals with severe hand impairment, we demonstrate the ability to decode a subset of two fundamental movements and rest at 85.4 ± 6.4% accuracy. In online scenarios, two stroke survivors achieved 91.34 ± 1.53% across three movements and rest, highlighting the potential as a control mechanism for assistive technologies. Feedback from stroke survivors who tested the system indicates that the sleeve's design meets various user needs, including being comfortable, portable, and lightweight. The sleeve is in a form factor such that it can be used at home without an expert technician and can be worn for multiple hours without discomfort. SIGNIFICANCE: The NeuroLife EMG System represents a platform technology to record and decode high-resolution EMG for the real-time control of assistive devices in a form factor designed to meet user needs. The NeuroLife EMG System is currently limited by U.S. federal law to investigational use.

Quantification of Global Myoelectric Spatial Activations to Delineate Normal Hamstring Function at Progressive Running Speeds: A Technical Report.

ABSTRACT: Schlink, BR, Nordin, AD, Diekfuss, JA, and Myer, GD. Quantification of global myoelectric spatial activations to delineate normal hamstring function at progressive running speeds: A technical report. J Strength Cond Res 36(3): 867-870, 2022-Hamstring function is critical to maintain sport performance, and strain injuries to the biceps femoris muscle commonly force an athlete to withdraw from their sport while the muscle heals. Current mechanistic understanding of underlying injury and return-to-play (RTP) guidelines has limited prognostic value because of limitations in technology and nonfunctional assessment strategies to guide clinical care. Integrated structural and functional determinants and dynamic assessment methods are needed to guide advanced rehabilitation strategies for safe and rapid return to sport. A potential solution for assessment of hamstring function is high-density electromyography (EMG), which can noninvasively measure spatial muscle activity in dynamic environments. In this study, we demonstrated the utility of high-density EMG by measuring spatial myoelectric activity from the biceps femoris from a group of recreational athletes running at a range of speeds. The level of significance set for this study was p < 0.05. During the late swing phase of running, we observed increased EMG amplitudes in the central and distal portions of the muscle. There were no changes in this pattern of EMG activation across speed, suggesting that running speed does not affect the general neuromuscular recruitment in the biceps femoris. Applying these methods to athletes with hamstring strains may lead to a more complete understanding of muscle function during rehabilitation and adjunctively support current methods to enhance RTP decision-making.

Fatigue induces altered spatial myoelectric activation patterns in the medial gastrocnemius during locomotion.

This research investigates the effects of muscle fatigue on spatial myoelectric patterns in the lower limb during locomotion. Both spatial and frequency aspects of neuromuscular recruitment in the medial gastrocnemius change in response to fatigue, resulting in altered myoelectric patterns during walking and running. These data may help us better understand the adaptations that occur in lower limb muscles to avoid overuse injuries caused by fatigue.

Human myoelectric spatial patterns differ among lower limb muscles and locomotion speeds.

The spatial distribution of myoelectric activity within lower limb muscles is often nonuniform and can change during different stationary tasks. Recent studies using high-density electromyography (EMG) have suggested that spatial muscle activity may also differ among muscles during locomotion, but contrasting electrode array sizes and experimental designs have limited cross-study comparisons. Here, we sought to determine if spatial EMG patterns differ among lower limb muscles and locomotion speeds. We recorded high-density EMG from the vastus medialis, tibialis anterior, biceps femoris, medial gastrocnemius, and lateral gastrocnemius muscles of 11 healthy subjects while they walked (1.2 and 1.6 m/s) and ran (2.0, 3.0, 4.0, and 5.0 m/s) on a treadmill. To overcome the detrimental effects of cable, electrode, and soft tissue movements on high-density EMG signal quality during locomotion, we applied multivariate signal cleaning methods. From these data, we computed the spatial entropy and center of gravity from the total myoelectric activity within each recording array during the stance or swing phases of the gait cycle. We found heterogeneous spatial EMG patterns evidenced by contrasting spatial entropy among lower limb muscles. As locomotion speed increased, mean entropy values decreased in four of the five recorded muscles, indicating that EMG signal amplitudes were more spatially heterogeneous, or localized, at faster speeds. The EMG center of gravity location also shifted in multiple muscles as locomotion speed increased. Contrasting myoelectric spatial distributions among muscles likely reflect differences in muscle architecture, but increasingly localized activity and spatial shifts in the center of gravity location at faster locomotion speeds could be influenced by preferential recruitment of faster motor units under greater loads.

Comparison of Signal Processing Methods for Reducing Motion Artifacts in High-Density Electromyography During Human Locomotion.

Objective: High-density electromyography (EMG) is useful for studying changes in myoelectric activity within a muscle during human movement, but it is prone to motion artifacts during locomotion. We compared canonical correlation analysis and principal component analysis methods for signal decomposition and component filtering with a traditional EMG high-pass filtering approach to quantify their relative performance at removing motion artifacts from high-density EMG of the gastrocnemius and tibialis anterior muscles during human walking and running. Results: Canonical correlation analysis filtering provided a greater reduction in signal content at frequency bands associated with motion artifacts than either traditional high-pass filtering or principal component analysis filtering. Canonical correlation analysis filtering also minimized signal reduction at frequency bands expected to consist of true myoelectric signal. Conclusions: Canonical correlation analysis filtering appears to outperform a standard high-pass filter and principal component analysis filter in cleaning high-density EMG collected during fast walking or running.

A Lower Limb Phantom for Simulation and Assessment of Electromyography Technology.

Electromyography signal processing approaches have traditionally been validated through computer simulations. Electromyography electrodes and systems are often not validated or have been validated on human subjects where there is no clear ground truth signal for comparison. We sought to develop a physical limb phantom for validation of electromyography hardware and signal processing approaches. We embedded pairs of wires within a conductive gelatin surrounding an artificial bone such that the antennae could broadcast identified ground truth signals. The ground truth signals can be simple sinusoids or more complex representations of muscle activity. With the phantom and surface electromyography electrodes, we were able to show varying levels of crosstalk between nearby recording electrodes as we altered the amplitude of the antennae signals. We were also able to induce motion artifacts in our recordings by lightly dropping the phantom on a surface while antennae broadcast signals. High-density electromyography recordings of the trials showed that traditional filtering techniques fail to fully eliminate relatively small motion artifacts. The results suggest that the electrical limb phantom could be a valuable tool for testing potential effects of muscle crosstalk and motion artifacts on different electromyography systems and signal processing approaches.

Gait asymmetries in unilateral symptomatic hip osteoarthritis and their association with radiographic severity and pain.

INTRODUCTION:: Little is known about the loading patterns in unilateral hip osteoarthritis (OA) and their relationship to radiographic severity and pain. We aimed to examine the loading patterns at the hips of those with unilateral symptomatic hip OA and identify associations between radiographic severity and pain with loading alterations. METHODS:: 61 subjects with symptomatic unilateral hip OA underwent gait analyses and evaluation for radiographic severity (Kellgren-Lawrence [KL]-grade) and pain (visual analogue scale) at bilateral hips. RESULTS:: Hip OA subjects had greater range of motion and higher hip flexion, adduction, internal and external rotation moments at the contralateral, asymptomatic hip compared to the ipsilateral hip ( p < 0.05). Correlations were noted between increasing KL-grade and increasing asymmetry of contralateral to ipsilateral hip loading ( p < 0.05). There were no relationships with pain and loading asymmetry. DISCUSSION:: Unilateral symptomatic hip OA subjects demonstrate asymmetry in loading between the hips, with relatively greater loads at the contralateral hip. These loading asymmetries were directly related to the radiographic severity of symptomatic hip OA and not with pain. CONCLUSION:: Additional research is needed to determine the role of gait asymmetries in disease progression.

Independent Component Analysis and Source Localization on Mobile EEG Data Can Identify Increased Levels of Acute Stress.

Mobile electroencephalography (EEG) is a very useful tool to investigate the physiological basis of cognition under real-world conditions. However, as we move experimentation into less-constrained environments, the influence of state changes increases. The influence of stress on cortical activity and cognition is an important example. Monitoring of modulation of cortical activity by EEG measurements is a promising tool for assessing acute stress. In this study, we test this hypothesis and combine EEG with independent component analysis and source localization to identify cortical differences between a control condition and a stressful condition. Subjects performed a stationary shooting task using an airsoft rifle with and without the threat of an experimenter firing a different airsoft rifle in their direction. We observed significantly higher skin conductance responses and salivary cortisol levels (p < 0.05 for both) during the stressful conditions, indicating that we had successfully induced an adequate level of acute stress. We located independent components in five regions throughout the cortex, most notably in the dorsolateral prefrontal cortex, a region previously shown to be affected by increased levels of stress. This area showed a significant decrease in spectral power in the theta and alpha bands less than a second after the subjects pulled the trigger. Overall, our results suggest that EEG with independent component analysis and source localization has the potential of monitoring acute stress in real-world environments.

Restricted vision increases sensorimotor cortex involvement in human walking.

This study aimed to determine whether there is electrocortical evidence of augmented participation of sensory brain areas in walking modulation during walking with eyes closed. Healthy subjects (n = 10) walked on a treadmill at 1 m/s while alternating 5 min of walking with the eyes open or closed while we recorded ground reaction forces (GRFs) and high-density scalp electroencephalography (EEG). We applied independent component analysis to parse EEG signals into maximally independent component (IC) processes and then computed equivalent current dipoles for each IC. We clustered cortical source ICs and analyzed event-related spectral perturbations synchronized to gait events. Our results indicated that walking with eyes closed reduced the first peak of the vertical GRFs and induced shorter stride duration. Regarding the EEG, we found that walking with eyes closed induced significantly increased relative theta desynchronization in the frontal and premotor cortex during stance, as well as greater desynchronization from theta to beta bands during transition to single support for both left and right somatosensory cortex. These results suggest a phase-specific increased participation of brain areas dedicated to sensory processing and integration when vision is not available for locomotor guidance. Furthermore, the lack of vision demands higher neural processing related to motor planning and execution. Our findings provide evidence supporting the use of eyes-closed tasks in clinical practice, such as gait rehabilitation and improvements in balance control, as there is higher demand for additional sensory integration for achieving postural control.NEW & NOTEWORTHY We measured electrocortical dynamics in sighted individuals while walking with eyes open and eyes closed to induce the participation of other sensory systems in postural control. Our findings show that walking with visual restriction increases the participation of brain areas dedicated to sensory processing, motor planning, and execution. These results confirm the essential participation of supraspinal inputs to postural control in human locomotion, supporting the use of eyes-closed tasks in clinical practice.

A Channel Rejection Method for Attenuating Motion-Related Artifacts in EEG Recordings during Walking.

Recording scalp electroencephalography (EEG) during human motion can introduce motion artifacts. Repetitive head movements can generate artifact patterns across scalp EEG sensors. There are many methods for identifying and rejecting bad channels and independent components from EEG datasets, but there is a lack of methods dedicated to evaluate specific intra-channel amplitude patterns for identifying motion-related artifacts. In this study, we proposed a template correlation rejection (TCR) as a novel method for identifying and rejecting EEG channels and independent components carrying motion-related artifacts. We recorded EEG data from 10 subjects during treadmill walking. The template correlation rejection method consists of creating templates of amplitude patterns and determining the fraction of total epochs presenting relevant correlation to the template. For EEG channels, the template correlation rejection removed channels presenting the majority of epochs (>75%) correlated to the template, and presenting pronounced amplitude in comparison to all recorded channels. For independent components, the template correlation rejection removed components presenting the majority of epochs correlated to the template. Evaluation of scalp maps and power spectra confirmed low neural content for the rejected components. We found that channels identified for rejection contained ~60% higher delta power, and had spectral properties locked to the gait phases. After rejecting the identified channels and running independent component analysis on the EEG datasets, the proposed method identified 4.3 ± 1.8 independent components (out of 198 ± 12) with substantive motion-related artifacts. These results indicate that template correlation rejection is an effective method for rejecting EEG channels contaminated with motion-related artifact during human locomotion.

Proposing Metrics for Benchmarking Novel EEG Technologies Towards Real-World Measurements.

Recent advances in electroencephalographic (EEG) acquisition allow for recordings using wet and dry sensors during whole-body motion. The large variety of commercially available EEG systems contrasts with the lack of established methods for objectively describing their performance during whole-body motion. Therefore, the aim of this study was to introduce methods for benchmarking the suitability of new EEG technologies for that context. Subjects performed an auditory oddball task using three different EEG systems (Biosemi wet-BSM, Cognionics Wet-Cwet, Conionics Dry-Cdry). Nine subjects performed the oddball task while seated and walking on a treadmill. We calculated EEG epoch rejection rate, pre-stimulus noise (PSN), signal-to-noise ratio (SNR) and EEG amplitude variance across the P300 event window (CVERP) from a subset of 12 channels common to all systems. We also calculated test-retest reliability and the subject's level of comfort while using each system. Our results showed that using the traditional 75 µV rejection threshold BSM and Cwet epoch rejection rates are ~25% and ~47% in the seated and walking conditions respectively. However, this threshold rejects ~63% of epochs for Cdry in the seated condition and excludes 100% of epochs for the majority of subjects during walking. BSM showed predominantly no statistical differences between seated and walking condition for all metrics, whereas Cwet showed increases in PSN and CVERP, as well as reduced SNR in the walking condition. Data quality from Cdry in seated conditions were predominantly inferior in comparison to the wet systems. Test-retest reliability was mostly moderate/good for these variables, especially in seated conditions. In addition, subjects felt less discomfort and were motivated for longer recording periods while using wet EEG systems in comparison to the dry system. The proposed method was successful in identifying differences across systems that are mostly caused by motion-related artifacts and usability issues. We conclude that the extraction of the selected metrics from an auditory oddball paradigm may be used as a benchmark method for testing the performance of different EEG systems in mobile conditions. Moreover dry EEG systems may need substantial improvements to meet the quality standards of wet electrodes.

Induction and separation of motion artifacts in EEG data using a mobile phantom head device.

OBJECTIVE: Electroencephalography (EEG) can assess brain activity during whole-body motion in humans but head motion can induce artifacts that obfuscate electrocortical signals. Definitive solutions for removing motion artifact from EEG have yet to be found, so creating methods to assess signal processing routines for removing motion artifact are needed. We present a novel method for investigating the influence of head motion on EEG recordings as well as for assessing the efficacy of signal processing approaches intended to remove motion artifact. APPROACH: We used a phantom head device to mimic electrical properties of the human head with three controlled dipolar sources of electrical activity embedded in the phantom. We induced sinusoidal vertical motions on the phantom head using a custom-built platform and recorded EEG signals with three different acquisition systems while the head was both stationary and in varied motion conditions. MAIN RESULTS: Recordings showed up to 80% reductions in signal-to-noise ratio (SNR) and up to 3600% increases in the power spectrum as a function of motion amplitude and frequency. Independent component analysis (ICA) successfully isolated the three dipolar sources across all conditions and systems. There was a high correlation (r > 0.85) and marginal increase in the independent components' (ICs) power spectrum (∼15%) when comparing stationary and motion parameters. The SNR of the IC activation was 400%-700% higher in comparison to the channel data SNR, attenuating the effects of motion on SNR. SIGNIFICANCE: Our results suggest that the phantom head and motion platform can be used to assess motion artifact removal algorithms and compare different EEG systems for motion artifact sensitivity. In addition, ICA is effective in isolating target electrocortical events and marginally improving SNR in relation to stationary recordings.

Sagittal plane hip motion reversals during walking are associated with disease severity and poorer function in subjects with hip osteoarthritis.

A midstance reversal of sagittal plane hip motion during walking, or motion discontinuity (MD), has previously been observed in subjects with endstage hip osteoarthritis (OA) and in patients with femoroacetabular impingement. The goal of the present study was to evaluate whether this gait pattern is a marker of OA presence or radiographic severity by analyzing a large IRB approved motion analysis data repository. We also hypothesized that subjects with the MD would show more substantial gait impairments than those with normal hip motion. We identified 150 subjects with symptomatic unilateral hip OA and Kellgren-Lawrence OA severity data on file, and a control group of 159 asymptomatic subjects whose ages fell within 2 standard deviations of the mean OA group age. From the gait data, the MD was defined as a reversal in the slope of the hip flexion angle curve during midstance. Logistic regressions and general linear models were used to test the association between the MD and OA presence, OA severity and, other gait variables. 53% of OA subjects compared to 7.5% of controls had the MD (p<0.001); occurrence of the MD was associated with OA severity (p=0.009). Within the OA subject group, subjects with the MD had reduced dynamic range of motion, peak, extension, and internal rotation moments compared to those who did not (MANCOVA p ≤ 0.042) after controlling for walking speed. We concluded that sagittal plane motion reversals are indeed associated with OA presence and severity, and with more severe gait abnormalities in subjects with hip OA.