Transforming modeling in neurorehabilitation: clinical insights for personalized rehabilitation.

Practicing clinicians in neurorehabilitation continue to lack a systematic evidence base to personalize rehabilitation therapies to individual patients and thereby maximize outcomes. Computational modeling- collecting, analyzing, and modeling neurorehabilitation data- holds great promise. A key question is how can computational modeling contribute to the evidence base for personalized rehabilitation? As representatives of the clinicians and clinician-scientists who attended the 2023 NSF DARE conference at USC, here we offer our perspectives and discussion on this topic. Our overarching thesis is that clinical insight should inform all steps of modeling, from construction to output, in neurorehabilitation and that this process requires close collaboration between researchers and the clinical community. We start with two clinical case examples focused on motor rehabilitation after stroke which provide context to the heterogeneity of neurologic injury, the complexity of post-acute neurologic care, the neuroscience of recovery, and the current state of outcome assessment in rehabilitation clinical care. Do we provide different therapies to these two different patients to maximize outcomes? Asking this question leads to a corollary: how do we build the evidence base to support the use of different therapies for individual patients? We discuss seven points critical to clinical translation of computational modeling research in neurorehabilitation- (i) clinical endpoints, (ii) hypothesis- versus data-driven models, (iii) biological processes, (iv) contextualizing outcome measures, (v) clinical collaboration for device translation, (vi) modeling in the real world and (vii) clinical touchpoints across all stages of research. We conclude with our views on key avenues for future investment (clinical-research collaboration, new educational pathways, interdisciplinary engagement) to enable maximal translational value of computational modeling research in neurorehabilitation.

Variation of body weight supported treadmill training parameters during a single session can modulate muscle activity patterns in post-stroke gait.

Evidence supporting the benefits of locomotor training (LT) to improve walking ability following stroke are inconclusive and could likely be improved with a better understanding of the effects of individual parameters i.e., body weight support (BWS), speed, and therapist assistance and their interactions with walking ability and specific impairments. We evaluated changes in muscle activity of thirty-seven individuals with chronic stroke (> 6 months), in response to a single session of LT at their self-selected or fastest-comfortable speed (FS) with three levels of BWS (0%, 15%, and 30%), and at FS with 30% BWS and seven different combinations of therapist assistance at the paretic foot, non-paretic foot, and trunk. Altered Muscle Activation Pattern (AMAP), a previously developed tool in our lab was used to evaluate the effects of LT parameter variation on eight lower-extremity muscle patterns in individuals with stroke. Repeated-measures mixed-model ANOVA was used to determine the effects of speed, BWS, and their interaction on AMAP scores. The Wilcoxon-signed rank test was used to determine the effects of therapist-assisted conditions on AMAP scores. Increased BWS mostly improved lower-extremity muscle activity patterns, but increased speed resulted in worse plantar flexor activity. Abnormal early plantar flexor activity during stance decreased with assistance at trunk and both feet, exaggerated plantar flexor activity during late swing decreased with assistance to the non-paretic foot or trunk, and diminished gluteus medius activity during stance increased with assistance to paretic foot and/or trunk. Therefore, different sets of training parameters have different immediate effects on activation patterns of each muscle and gait subphases.

Slower than normal walking speeds involve a pattern shift in joint and temporal coordination contributions.

Kinematic and spatiotemporal gait parameters are known to scale with gait speed, though inter-joint coordination during swing remains consistent, at least across comfortable speeds. The purpose of this study was to determine whether coordination patterns serving limb clearance and shortening change across a range of gait speeds. We assessed 17 healthy adults walking overground at their self-selected speed and multiple, progressively slower speeds. We collected lower extremity kinematics with 3D motion analysis and quantified joint influence, or relative joint contributions, to limb clearance and shortening. We investigated changes in coordination using linear mixed models to determine magnitude and timing differences of joint influence across walking speeds. Joint influences serving limb clearance (hip, knee, and ankle) reduced considerably with slower walking speeds. Similarly, knee and ankle influences on limb shortening reduced with slower walking speeds. Temporally, joint influences on limb clearance varied across walking speeds. Notably, the temporal order of peak hip and knee influences reversed below typical self-selected walking speeds. For limb shortening, the timing of knee and ankle influences occurred later in the gait cycle as walking speed decreased. While relative joint contributions serve limb clearance and shortening scale with walking speeds, our results demonstrate that temporal coordination of limb clearance is altered in healthy individuals as walking speed falls below the range of typical self-selected walking speeds.

Lower extremity long-latency reflexes differentiate walking function after stroke.

The neural mechanisms of walking impairment after stroke are not well characterized. Specifically, there is a need for understanding the mechanisms of impaired plantarflexor power generation in late stance. Here, we investigated the association between two neurophysiologic markers, the long-latency reflex (LLR) response and dynamic facilitation of antagonist motor-evoked responses, and walking function. Fourteen individuals with chronic post-stroke hemiparesis and thirteen healthy controls performed both isometric and dynamic plantarflexion. Transcranial magnetic stimulation (TMS) assessed supraspinal drive to the tibialis anterior. LLR activity was assessed during dynamic voluntary plantarflexion and individuals post-stroke were classified as either LLR present (LLR+) or absent (LLR-). All healthy controls and nine individuals post-stroke exhibited LLRs, while five did not. LLR+ individuals revealed higher clinical scores, walking speeds, and greater ankle plantarflexor power during walking compared to LLR- individuals. LLR- individuals exhibited exaggerated responses to TMS during dynamic plantarflexion relative to healthy controls. The LLR- subset revealed dysfunctional modulation of stretch responses and antagonist supraspinal drive relative to healthy controls and the higher functioning LLR+ individuals post-stroke. These abnormal physiologic responses allow for characterization of individuals post-stroke along a dimension that is clinically relevant and provides additional information beyond standard behavioral assessments. These findings provide an opportunity to distinguish among the heterogeneity of lower extremity motor impairments present following stroke by associating them with responses at the nervous system level.

Altered muscle activation patterns (AMAP): an analytical tool to compare muscle activity patterns of hemiparetic gait with a normative profile.

BACKGROUND: Stroke survivors often have lower extremity sensorimotor impairments, resulting in an inability to sufficiently recruit muscle activity at appropriate times in a gait cycle. Currently there is a lack of a standardized method that allows comparison of muscle activation in hemiparetic gait post-stroke to a normative profile. METHODS: We developed a new tool to quantify altered muscle activation patterns (AMAP). AMAP accounts for spatiotemporal asymmetries in stroke gait by evaluating the deviations of muscle activation specific to each gait sub-phase. It also recognizes the characteristic variability within the healthy population. The inter-individual variability of normal electromyography (EMG) patterns within some sub-phases of the gait cycle is larger compared to others, therefore AMAP penalizes more for deviations in a gait sub-phase with a constant profile (absolute active or inactive) vs variable profile. EMG data were collected during treadmill walking, from eight leg muscles of 34 stroke survivors at self-selected speeds and 20 healthy controls at four different speeds. Stroke survivors' AMAP scores, for timing and amplitude variations, were computed in comparison to healthy controls walking at speeds matched to the stroke survivors' self-selected speeds. RESULTS: Altered EMG patterns in the stroke population quantified using AMAP agree with the previously reported EMG alterations in stroke gait that were identified using qualitative methods. We defined scores ranging between ±2.57 as "normal". Only 9% of healthy controls were outside "normal" window for timing and amplitude. Percentages of stroke subjects outside the "normal" window for each muscle were, Soleus = 79%; 73%, Medial Gastrocnemius = 62%; 79%, Tibialis Anterior = 62%; 59%, and Gluteus Medius = 48%; 51% for amplitude and timing component respectively, alterations were relatively smaller for the other four muscles. Paretic-propulsion was negatively correlated to AMAP scores for the timing component of Soleus. Stroke survivors' self-selected walking speed was negatively correlated with AMAP scores for amplitude and timing of Soleus but only amplitude of Medial gastrocnemius (p < 0.05). CONCLUSIONS: Our results validate the ability of AMAP to identify alterations in the EMG patterns within the stroke population and its potential to be used to identify the gait phases that may require more attention when developing an optimal gait training paradigm. TRIAL REGISTRATION: ClinicalTrials.gov NCT00712179 , Registered July 3rd 2008.

Can Measured Synergy Excitations Accurately Construct Unmeasured Muscle Excitations?

Accurate prediction of muscle and joint contact forces during human movement could improve treatment planning for disorders such as osteoarthritis, stroke, Parkinson's disease, and cerebral palsy. Recent studies suggest that muscle synergies, a low-dimensional representation of a large set of muscle electromyographic (EMG) signals (henceforth called "muscle excitations"), may reduce the redundancy of muscle excitation solutions predicted by optimization methods. This study explores the feasibility of using muscle synergy information extracted from eight muscle EMG signals (henceforth called "included" muscle excitations) to accurately construct muscle excitations from up to 16 additional EMG signals (henceforth called "excluded" muscle excitations). Using treadmill walking data collected at multiple speeds from two subjects (one healthy, one poststroke), we performed muscle synergy analysis on all possible subsets of eight included muscle excitations and evaluated how well the calculated time-varying synergy excitations could construct the remaining excluded muscle excitations (henceforth called "synergy extrapolation"). We found that some, but not all, eight-muscle subsets yielded synergy excitations that achieved >90% extrapolation variance accounted for (VAF). Using the top 10% of subsets, we developed muscle selection heuristics to identify included muscle combinations whose synergy excitations achieved high extrapolation accuracy. For 3, 4, and 5 synergies, these heuristics yielded extrapolation VAF values approximately 5% lower than corresponding reconstruction VAF values for each associated eight-muscle subset. These results suggest that synergy excitations obtained from experimentally measured muscle excitations can accurately construct unmeasured muscle excitations, which could help limit muscle excitations predicted by muscle force optimizations.

Free-water and free-water corrected fractional anisotropy in primary and premotor corticospinal tracts in chronic stroke.

Measures from diffusion MRI have been used to characterize the corticospinal tract in chronic stroke. However, diffusivity can be influenced by partial volume effects from free-water, region of interest placement, and lesion masking. We collected diffusion MRI from a cohort of chronic stroke patients and controls and used a bitensor model to calculate free-water corrected fractional anisotropy (FAT ) and free water (FW) in the primary motor corticospinal tract (M1-CST) and the dorsal premotor corticospinal tract (PMd-CST). Region of interest analyses and whole-tract slice-by-slice analyses were used to assess between-group differences in FAT and FW in each tract. Correlations between FAT and FW and grip strength were also examined. Following lesion masking and correction for multiple comparisons, relative increases in FW were found for the stroke group in large portions of the M1-CST and PMd-CST in the lesioned hemisphere. FW in cortical regions was the strongest predictor of grip strength in the stroke group. Our findings also demonstrated that FAT is sensitive to the direct effects of the lesion itself, thus after controlling for the lesion, differences in FAT in nonlesioned tissue were small and generally similar between hemispheres and groups. Our observations suggest that FW may be a robust biological measurement that can be used to assess microstructure in residual white matter after stroke. Hum Brain Mapp 38:4546-4562, 2017. © 2017 Wiley Periodicals, Inc.

Microstructural properties of premotor pathways predict visuomotor performance in chronic stroke.

Microstructural properties of the corticospinal tract (CST) descending from the motor cortex predict strength and motor skill in the chronic phase after stroke. Much less is known about the relation between brain microstructure and visuomotor processing after stroke. In this study, individual's poststroke and age-matched controls performed a unimanual force task separately with each hand at three levels of visual gain. We collected diffusion MRI data and used probabilistic tractography algorithms to identify the primary and premotor CSTs. Fractional anisotropy (FA) within each tract was used to predict changes in force variability across different levels of visual gain. Our observations revealed that individuals poststroke reduced force variability with an increase in visual gain, performed the force task with greater variability as compared with controls across all gain levels, and had lower FA in the primary motor and premotor CSTs. Our results also demonstrated that the CST descending from the premotor cortex, rather than the primary motor cortex, best predicted force variability. Together, these findings demonstrate that the microstructural properties of the premotor CST predict visual gain-related changes in force variability in individuals poststroke. Hum Brain Mapp 37:2039-2054, 2016. © 2016 Wiley Periodicals, Inc.

Upper-extremity spinal reflex inhibition is reproducible and strongly related to grip force poststroke.

PURPOSE: Impaired reflex regulation is assumed to contribute to upper-extremity motor impairment poststroke; however, the relationship between reflex inhibition and motor function remains unclear. To address this question, it is first necessary to determine the reproducibility of reflex responses. The objective of this study was to establish the test-retest reliability of flexor carpi radialis H-reflex inhibition in healthy control and stroke participants and investigate the correlation between H-reflex inhibition and grip strength. MATERIALS AND METHODS: Eighteen persons poststroke (mean ± SD: age 63 ± 13 years; 6 ± 5 years poststroke; 13 males) and 16 healthy controls (age: 62 ± 12 years) participated. Reflex inhibition was tested on 2 separate days by conditioning the H-reflex with radial nerve stimulation at two different interstimulus intervals: 13 ms (presynaptic Ia inhibition-PSI) and 0 ms (disynaptic inhibition). Pearson's and intraclass correlation coefficients [two-way mixed model-ICC (1, 2)], and standard error of measurement (SEM) were calculated. RESULTS: Relative reliability (ICCs) ranged from good to excellent (0.61-0.78). SEM was low (range 10-19%, stroke; 15-20%, healthy controls). Paretic grip strength and paretic limb PSI revealed a positive correlation (r = 0.70; p < 0.0125). Disynaptic inhibition and paretic grip strength were not correlated. CONCLUSIONS: To our knowledge, this is the first study to demonstrate reproducibility of reflex inhibition in individuals poststroke. Furthermore, we quantify smallest real differences, which provide an estimate of the magnitude of effect required to determine a meaningful change, exceeding measurement error. The correlation between PSI and grip strength suggests the potential contribution of PSI to grip force production and upper-extremity motor function.

Longitudinal decline of lower extremity muscle power in healthy and mobility-limited older adults: influence of muscle mass, strength, composition, neuromuscular activation and single fiber contractile properties.

PURPOSE: This longitudinal study examined the major physiological mechanisms that determine the age-related loss of lower extremity muscle power in two distinct groups of older humans. We hypothesized that after ~3 years of follow-up, mobility-limited older adults (mean age: 77.2 ± 4, n = 22, 12 females) would have significantly greater reductions in leg extensor muscle power compared to healthy older adults (74.1 ± 4, n = 26, 12 females). METHODS: Mid-thigh muscle size and composition were assessed using computed tomography. Neuromuscular activation was quantified using surface electromyography and vastus lateralis single muscle fibers were studied to evaluate intrinsic muscle contractile properties. RESULTS: At follow-up, the overall magnitude of muscle power loss was similar between groups: mobility-limited: -8.5 % vs. healthy older: -8.8 %, P > 0.8. Mobility-limited elders had significant reductions in muscle size (-3.8 %, P < 0.01) and strength (-5.9 %, P < 0.02), however, these parameters were preserved in healthy older (P ≥ 0.7). Neuromuscular activation declined significantly within healthy older, but not in mobility-limited participants. Within both groups, the cross-sectional areas of type I and IIA muscle fibers were preserved while substantial increases in single fiber peak force (>30 %), peak power (>200 %) and unloaded shortening velocity (>50 %) were elicited at follow-up. CONCLUSION: Different physiological mechanisms contribute to the loss of lower extremity muscle power in healthy older and mobility-limited older adults. Neuromuscular changes may be the critical early determinant of muscle power deficits with aging. In response to major whole muscle decrements, major compensatory mechanisms occur within the contractile properties of surviving single muscle fibers in an attempt to restore overall muscle power and function with advancing age.

Concurrent neuromechanical and functional gains following upper-extremity power training post-stroke.

BACKGROUND: Repetitive task practice is argued to drive neural plasticity following stroke. However, current evidence reveals that hemiparetic weakness impairs the capacity to perform, and practice, movements appropriately. Here we investigated how power training (i.e., high-intensity, dynamic resistance training) affects recovery of upper-extremity motor function post-stroke. We hypothesized that power training, as a component of upper-extremity rehabilitation, would promote greater functional gains than functional task practice without deleterious consequences. METHOD: Nineteen chronic hemiparetic individuals were studied using a crossover design. All participants received both functional task practice (FTP) and HYBRID (combined FTP and power training) in random order. Blinded evaluations performed at baseline, following each intervention block and 6-months post-intervention included: Wolf Motor Function Test (WMFT-FAS, Primary Outcome), upper-extremity Fugl-Meyer Motor Assessment, Ashworth Scale, and Functional Independence Measure. Neuromechanical function was evaluated using isometric and dynamic joint torques and concurrent agonist EMG. Biceps stretch reflex responses were evaluated using passive elbow stretches ranging from 60 to 180º/s and determining: EMG onset position threshold, burst duration, burst intensity and passive torque at each speed. PRIMARY OUTCOME: Improvements in WMFT-FAS were significantly greater following HYBRID vs. FTP (p = .049), regardless of treatment order. These functional improvements were retained 6-months post-intervention (p = .03). SECONDARY OUTCOMES: A greater proportion of participants achieved minimally important differences (MID) following HYBRID vs. FTP (p = .03). MIDs were retained 6-months post-intervention. Ashworth scores were unchanged (p > .05). Increased maximal isometric joint torque, agonist EMG and peak power were significantly greater following HYBRID vs. FTP (p < .05) and effects were retained 6-months post-intervention (p's < .05). EMG position threshold and burst duration were significantly reduced at fast speeds (≥120º/s) (p's < 0.05) and passive torque was reduced post-washout (p < .05) following HYBRID. CONCLUSIONS: Functional and neuromechanical gains were greater following HYBRID vs. FPT. Improved stretch reflex modulation and increased neuromuscular activation indicate potent neural adaptations. Importantly, no deleterious consequences, including exacerbation of spasticity or musculoskeletal complaints, were associated with HYBRID. These results contribute to an evolving body of contemporary evidence regarding the efficacy of high-intensity training in neurorehabilitation and the physiological mechanisms that mediate neural recovery.

Development of an assessment of bilateral locomotor efficacy for individuals post-stroke.

BACKGROUND: A common framework is needed to assess walking impairments in older adults and individuals with stroke. This study develops an Assessment of Bilateral Locomotor Efficacy (ABLE) that is a straightforward indicator of walking function. RESEARCH QUESTION: Can we develop a clinically accessible index of walking function that summarizes gait dysfunction secondary to stroke? METHODS: The ABLE index was developed using a retrospective sample of 14 community-dwelling older adults. Data from 33 additional older adults and 105 individuals with chronic post-stroke hemiparesis were used to validate the index by factor analysis of the score components and correlation with multiple common assessments of lower extremity impairment and function. RESULTS: The ABLE consists of four components summed for a maximum possible score of 12. The components include self-selected walking speed (SSWS), speed change from SSWS to fastest speed, non-paretic leg step length change from SSWS to fastest speed, and peak paretic leg ankle power. The ABLE revealed good concurrent validity with all recorded functional assessments. Factor analysis suggested that the ABLE measures two factors: one for forward progression and another for speed adaptability. SIGNIFICANCE: The ABLE offers a straightforward, objective measure of walking function in adults, including individuals with chronic stroke. The index may also prove useful as a screening tool for subclinical pathology in community-dwelling older adults, but further testing is required. We encourage utilization of this index and reproduction of findings to adapt and refine the instrument for wider use and eventual clinical application.

EMG-Driven Musculoskeletal Model Calibration With Wrapping Surface Personalization.

Muscle forces and joint moments estimated by electromyography (EMG)-driven musculoskeletal models are sensitive to the wrapping surface geometry defining muscle-tendon lengths and moment arms. Despite this sensitivity, wrapping surface properties are typically not personalized to subject movement data. This study developed a novel method for personalizing OpenSim cylindrical wrapping surfaces during EMG-driven model calibration. To avoid the high computational cost of repeated OpenSim muscle analyses, the method uses two-level polynomial surrogate models. Outer-level models specify time-varying muscle-tendon lengths and moment arms as functions of joint angles, while inner-level models specify time-invariant outer-level polynomial coefficients as functions of wrapping surface parameters. To evaluate the method, we used walking data collected from two individuals post-stroke and performed four variations of EMG-driven lower extremity model calibration: 1) no calibration of scaled generic wrapping surfaces (NGA), 2) calibration of outer-level polynomial coefficients for all muscles (SGA), 3) calibration of outer-level polynomial coefficients only for muscles with wrapping surfaces (LSGA), and 4) calibration of cylindrical wrapping surface parameters for muscles with wrapping surfaces (PGA). On average compared to NGA, SGA reduced lower extremity joint moment matching errors by 31%, LSGA by 24%, and PGA by 12%, with the largest reductions occurring at the hip. Furthermore, PGA reduced peak hip joint contact force by 47% bodyweight, which was the most consistent with published in vivo measurements. The proposed method for EMG-driven model calibration with wrapping surface personalization produces physically realistic OpenSim models that reduce joint moment matching errors while improving prediction of hip joint contact force.

Unexpected recovery after robotic locomotor training at physiologic stepping speed: a single-case design.

OBJECTIVES: To investigate the effect of walking speed on the emergence of locomotor electromyogram (EMG) patterns in an individual with chronic incomplete spinal cord injury (SCI), and to determine whether central pattern generator activity during robotic locomotor training (RLT) transfers to volitional EMG activity during overground walking. DESIGN: Single-case (B-A-B; experimental treatment-withdrawal-experimental treatment) design. SETTING: Freestanding rehabilitation research center. PARTICIPANT: A 50-year-old man who was nonambulatory for 16 months after incomplete SCI (sub-T11). INTERVENTIONS: The participant completed two 6-week blocks of RLT, training 4 times per week for 30 minutes per session at walking speeds up to 5km/h (1.4m/s) over continuous bouts lasting up to 17 minutes. MAIN OUTCOME MEASURES: Surface EMG was recorded weekly during RLT and overground walking. The Walking Index for Spinal Cord Injury (WISCI-II) was assessed daily during training blocks. RESULTS: During week 4, reciprocal, patterned EMG emerged during RLT. EMG amplitude modulation revealed a curvilinear relationship over the range of walking speeds from 1.5 to 5km/h (1.4m/s). Functionally, the participant improved from being nonambulatory (WISCI-II 1/20), to walking overground with reciprocal stepping using knee-ankle-foot orthoses and a walker (WISCI-II 9/20). EMG was also observed during overground walking. These functional gains were maintained greater than 4 years after locomotor training (LT). CONCLUSIONS: Here we report an unexpected course of locomotor recovery in an individual with chronic incomplete SCI. Through RLT at physiologic walking speeds, it was possible to activate the central pattern generator even 16 months postinjury. Further, to a certain degree, improvements from RLT transferred to overground walking. Our results suggest that LT-induced changes affect the central pattern generator and allow supraspinal inputs to engage residual spinal pathways.

Muscle power failure in mobility-limited older adults: preserved single fiber function despite lower whole muscle size, quality and rate of neuromuscular activation.

This study investigated the physiological and gender determinants of the age-related loss of muscle power in 31 healthy middle-aged adults (aged 40-55 years), 28 healthy older adults (70-85 years) and 34 mobility-limited older adults (70-85 years). We hypothesized that leg extensor muscle power would be significantly lower in mobility-limited elders relative to both healthy groups and sought to characterize the physiological mechanisms associated with the reduction of muscle power with aging. Computed tomography was utilized to assess mid-thigh body composition and calculate specific muscle power and strength. Surface electromyography was used to assess rate of neuromuscular activation and muscle biopsies were taken to evaluate single muscle fiber contractile properties. Peak muscle power, strength, muscle cross-sectional area, specific muscle power and rate of neuromuscular activation were significantly lower among mobility-limited elders compared to both healthy groups (P ≤ 0.05). Mobility-limited older participants had greater deposits of intermuscular adipose tissue (P < 0.001). Single fiber contractile properties of type I and type IIA muscle fibers were preserved in mobility-limited elders relative to both healthy groups. Male gender was associated with greater decrements in peak and specific muscle power among mobility-limited participants. Impairments in the rate of neuromuscular activation and concomitant reductions in muscle quality are important physiological mechanisms contributing to muscle power deficits and mobility limitations. The dissociation between age-related changes at the whole muscle and single fiber level suggest that, even among older adults with overt mobility problems, contractile properties of surviving muscle fibers are preserved in an attempt to maintain overall muscle function.

Evidence for shared neural information between muscle synergies and corticospinal efficacy.

Stroke survivors often exhibit gait dysfunction which compromises self-efficacy and quality of life. Muscle Synergy Analysis (MSA), derived from electromyography (EMG), has been argued as a method to quantify the complexity of descending motor commands and serve as a direct correlate of neural function. However, controversy remains regarding this interpretation, specifically attribution of MSA as a neuromarker. Here we sought to determine the relationship between MSA and accepted neurophysiological parameters of motor efficacy in healthy controls, high (HFH), and low (LFH) functioning stroke survivors. Surface EMG was collected from twenty-four participants while walking at their self-selected speed. Concurrently, transcranial magnetic stimulation (TMS) was administered, during walking, to elicit motor evoked potentials (MEPs) in the plantarflexor muscles during the pre-swing phase of gait. MSA was able to differentiate control and LFH individuals. Conversely, motor neurophysiological parameters, including soleus MEP area, revealed that MEP latency differentiated control and HFH individuals. Significant correlations were revealed between MSA and motor neurophysiological parameters adding evidence to our understanding of MSA as a correlate of neural function and highlighting the utility of combining MSA with other relevant outcomes to aid interpretation of this analysis technique.

Absolute Reliability of Gait Parameters Acquired With Markerless Motion Capture in Living Domains.

Purpose: To examine the between-day absolute reliability of gait parameters acquired with Theia3D markerless motion capture for use in biomechanical and clinical settings. Methods: Twenty-one (7 M,14 F) participants aged between 18 and 73 years were recruited in community locations to perform two walking tasks: self-selected and fastest-comfortable walking speed. Participants walked along a designated walkway on two separate days.Joint angle kinematics for the hip, knee, and ankle, for all planes of motion, and spatiotemporal parameters were extracted to determine absolute reliability between-days. For kinematics, absolute reliability was examined using: full curve analysis [root mean square difference (RMSD)] and discrete point analysis at defined gait events using standard error of measurement (SEM). The absolute reliability of spatiotemporal parameters was also examined using SEM and SEM%. Results: Markerless motion capture produced low measurement error for kinematic full curve analysis with RMSDs ranging between 0.96° and 3.71° across all joints and planes for both walking tasks. Similarly, discrete point analysis within the gait cycle produced SEM values ranging between 0.91° and 3.25° for both sagittal and frontal plane angles of the hip, knee, and ankle. The highest measurement errors were observed in the transverse plane, with SEM >5° for ankle and knee range of motion. For the majority of spatiotemporal parameters, markerless motion capture produced low SEM values and SEM% below 10%. Conclusion: Markerless motion capture using Theia3D offers reliable gait analysis suitable for biomechanical and clinical use.

Feasibility of Markerless Motion Capture for Three-Dimensional Gait Assessment in Community Settings.

Three-dimensional (3D) kinematic analysis of gait holds potential as a digital biomarker to identify neuropathologies, monitor disease progression, and provide a high-resolution outcome measure to monitor neurorehabilitation efficacy by characterizing the mechanisms underlying gait impairments. There is a need for 3D motion capture technologies accessible to community, clinical, and rehabilitation settings. Image-based markerless motion capture (MLMC) using neural network-based deep learning algorithms shows promise as an accessible technology in these settings. In this study, we assessed the feasibility of implementing 3D MLMC technology outside the traditional laboratory environment to evaluate its potential as a tool for outcomes assessment in neurorehabilitation. A sample population of 166 individuals aged 9-87 years (mean 43.7, S.D. 20.4) of varied health history were evaluated at six different locations in the community over a 3-month period. Participants walked overground at self-selected (SS) and fastest comfortable (FC) speeds. Feasibility measures considered the expansion, implementation, and practicality of this MLMC system. A subset of the sample population (46 individuals) walked over a pressure-sensitive walkway (PSW) concurrently with MLMC to assess agreement of the spatiotemporal gait parameters measured between the two systems. Twelve spatiotemporal parameters were compared using mean differences, Bland-Altman analysis, and intraclass correlation coefficients for agreement (ICC2,1) and consistency (ICC3,1). All measures showed good to excellent agreement between MLMC and the PSW system with cadence, speed, step length, step time, stride length, and stride time showing strong similarity. Furthermore, this information can inform the development of rehabilitation strategies targeting gait dysfunction. These first experiments provide evidence for feasibility of using MLMC in community and clinical practice environments to acquire robust 3D kinematic data from a diverse population. This foundational work enables future investigation with MLMC especially its use as a digital biomarker of disease progression and rehabilitation outcome.

EMG-driven musculoskeletal model calibration with estimation of unmeasured muscle excitations via synergy extrapolation.

Subject-specific electromyography (EMG)-driven musculoskeletal models that predict muscle forces have the potential to enhance our knowledge of internal biomechanics and neural control of normal and pathological movements. However, technical gaps in experimental EMG measurement, such as inaccessibility of deep muscles using surface electrodes or an insufficient number of EMG channels, can cause difficulties in collecting EMG data from muscles that contribute substantially to joint moments, thereby hindering the ability of EMG-driven models to predict muscle forces and joint moments reliably. This study presents a novel computational approach to address the problem of a small number of missing EMG signals during EMG-driven model calibration. The approach (henceforth called "synergy extrapolation" or SynX) linearly combines time-varying synergy excitations extracted from measured muscle excitations to estimate 1) unmeasured muscle excitations and 2) residual muscle excitations added to measured muscle excitations. Time-invariant synergy vector weights defining the contribution of each measured synergy excitation to all unmeasured and residual muscle excitations were calibrated simultaneously with EMG-driven model parameters through a multi-objective optimization. The cost function was formulated as a trade-off between minimizing joint moment tracking errors and minimizing unmeasured and residual muscle activation magnitudes. We developed and evaluated the approach by treating a measured fine wire EMG signal (iliopsoas) as though it were "unmeasured" for walking datasets collected from two individuals post-stroke-one high functioning and one low functioning. How well unmeasured muscle excitations and activations could be predicted with SynX was assessed quantitatively for different combinations of SynX methodological choices, including the number of synergies and categories of variability in unmeasured and residual synergy vector weights across trials. The two best methodological combinations were identified, one for analyzing experimental walking trials used for calibration and another for analyzing experimental walking trials not used for calibration or for predicting new walking motions computationally. Both methodological combinations consistently provided reliable and efficient estimates of unmeasured muscle excitations and activations, muscle forces, and joint moments across both subjects. This approach broadens the possibilities for EMG-driven calibration of muscle-tendon properties in personalized neuromusculoskeletal models and may eventually contribute to the design of personalized treatments for mobility impairments.

Computational evaluation of psoas muscle influence on walking function following internal hemipelvectomy with reconstruction.

An emerging option for internal hemipelvectomy surgery is custom prosthesis reconstruction. This option typically recapitulates the resected pelvic bony anatomy with the goal of maximizing post-surgery walking function while minimizing recovery time. However, the current custom prosthesis design process does not account for the patient's post-surgery prosthesis and bone loading patterns, nor can it predict how different surgical or rehabilitation decisions (e.g., retention or removal of the psoas muscle, strengthening the psoas) will affect prosthesis durability and post-surgery walking function. These factors may contribute to the high observed failure rate for custom pelvic prostheses, discouraging orthopedic oncologists from pursuing this valuable treatment option. One possibility for addressing this problem is to simulate the complex interaction between surgical and rehabilitation decisions, post-surgery walking function, and custom pelvic prosthesis design using patient-specific neuromusculoskeletal models. As a first step toward developing this capability, this study used a personalized neuromusculoskeletal model and direct collocation optimal control to predict the impact of ipsilateral psoas muscle strength on walking function following internal hemipelvectomy with custom prosthesis reconstruction. The influence of the psoas muscle was targeted since retention of this important muscle can be surgically demanding for certain tumors, requiring additional time in the operating room. The post-surgery walking predictions emulated the most common surgical scenario encountered at MD Anderson Cancer Center in Houston. Simulated post-surgery psoas strengths included 0% (removed), 50% (weakened), 100% (maintained), and 150% (strengthened) of the pre-surgery value. However, only the 100% and 150% cases successfully converged to a complete gait cycle. When post-surgery psoas strength was maintained, clinical gait features were predicted, including increased stance width, decreased stride length, and increased lumbar bending towards the operated side. Furthermore, when post-surgery psoas strength was increased, stance width and stride length returned to pre-surgery values. These results suggest that retention and strengthening of the psoas muscle on the operated side may be important for maximizing post-surgery walking function. If future studies can validate this computational approach using post-surgery experimental walking data, the approach may eventually influence surgical, rehabilitation, and custom prosthesis design decisions to meet the unique clinical needs of pelvic sarcoma patients.