Biology subjects

Roemmich, R. T.

Publications and source records attributed to Roemmich, R. T..

9 recordsLinked to original sources

bioRxiv2026

Energy Expenditure During Walking With a Novel Treadmill Controller That Induces Gait Asymmetry

Gait asymmetry is a common manifestation of walking impairment among clinical populations. We recently developed a novel treadmill walking approach called dynamic treadmill walking that can provide asymmetric gait training by changing the treadmill speed between fast and slow speeds within a single stride. Here, we studied the energy expenditure associated with a variety of dynamic treadmill walking conditions. We hypothesized that the metabolic power required for dynamic treadmill walking in all conditions would approximate the metabolic power associated with conventional walking at the mean of the fast and slow speeds employed in the task. Eleven young adults without gait impairment walked on an instrumented treadmill and breathed into a metabolic measurement system. During dynamic treadmill walking, the treadmill fluctuated between 0.75m/s and 1.50m/s, each for 50% of an individual's stride time. We used a metronome to synchronize participants' right heel-strikes with four different timing conditions. Net metabolic power during dynamic treadmill walking was significantly greater than normal walking at the mean speed of the task (1.125m/s) and generally lower than walking at the fast speed (1.5m/s). We did not observe any significant associations between net metabolic power and several measures of gait asymmetry during dynamic treadmill walking. These findings establish dynamic treadmill walking as a promising technique for improving gait symmetry in individuals who cannot tolerate fast treadmill walking, a common gait rehabilitation approach. Future work will assess the feasibility, metabolic demands, and clinical efficacy of using dynamic treadmill walking to improve gait symmetry in clinical populations.

physiology↗

bioRxiv2024

Changes in interlimb coordination induced by within-stride changes in treadmill speed

Human walking involves tightly coordinated movements of the right and left legs. We recently developed and tested a dynamic treadmill walking paradigm that changes the treadmill speed within a single step to provide asymmetric training for persons with gait dysfunction. We previously demonstrated that this approach could induce changes in human gait symmetry; however, if this approach is to be used in rehabilitation, we also need to understand how movements of the legs are coordinated to produce these asymmetric gait changes. The goal of this study was to examine the temporal (phase shift) and spatial (center of oscillation difference) aspects of interlimb coordination during dynamic treadmill walking in ten young adults without gait impairment. We found that dynamic treadmill walking drove significant changes in phase shift and center of oscillation difference that were dependent on the timing of the treadmill speed change within the gait cycle. For example, slowing the treadmill during the stance phase extended the double limb support period, and these changes were strongly correlated with a phase shift between the two legs. Accelerating the treadmill late in stance led to extensions in the trailing limb angle that were strongly correlated with changes in the center of oscillation difference. Overall, dynamic treadmill walking can be configured to drive changes in many spatiotemporal, kinematic, and interlimb coordination parameters, creating a variety of options for restoring gait symmetry and targeting aspects of spatial and temporal interlimb coordination in clinical populations with heterogenous patterns of gait asymmetry. NEW & NOTEWORTHYDynamic treadmill walking has been previously shown to drive asymmetric gait changes, but little is known about its effect on interlimb coordination. Here, we find that this approach induces significant changes in interlimb coordination (relative to normal walking) in both spatial and temporal domains. Altogether, dynamic treadmill walking offers a customizable gait rehabilitation strategy for asymmetric gait training that can induce changes in interlimb coordination using only a single-belt treadmill.

neuroscience↗

bioRxiv2023

Automatic learning mechanisms for flexible human locomotion.

Movement flexibility and automaticity are necessary to successfully navigate different environments. When encountering difficult terrains such as a muddy trail, we can change how we step almost immediately so that we can continue walking. This flexibility comes at a cost since we initially must pay deliberate attention to how we are moving. Gradually, after a few minutes on the trail, stepping becomes automatic so that we do not need to think about our movements. Canonical theory indicates that different adaptive motor learning mechanisms confer these essential properties to movement: explicit control confers rapid flexibility, while forward model recalibration confers automaticity. Here we uncover a distinct mechanism of treadmill walking adaptation - an automatic stimulus-response mapping - that confers both properties to movement. The mechanism is flexible as it learns stepping patterns that can be rapidly changed to suit a range of treadmill configurations. It is also automatic as it can operate without deliberate control or explicit awareness by the participants. Our findings reveal a tandem architecture of forward model recalibration and automatic stimulus-response mapping mechanisms for walking, reconciling different findings of motor adaptation and perceptual realignment.

neuroscience↗

bioRxiv2023

Multi-site identification and generalization of clusters of walking impairment in individuals with chronic stroke

BackgroundWalking patterns in stroke survivors are highly heterogeneous, which poses a challenge in systematizing treatment prescriptions for walking rehabilitation interventions. ObjectiveWe used bilateral spatiotemporal and force data during walking to create a multi-site research sample to: 1) identify clusters of walking behaviors in people post-stroke and neurotypical controls, and 2) determine the generalizability of these walking clusters across different research sites. We hypothesized that participants post-stroke will have different walking impairments resulting in different clusters of walking behaviors, which are also different from control participants. MethodsWe gathered data from 81 post-stroke participants across four research sites and collected data from 31 control participants. Using sparse K-means clustering, we identified walking clusters based on 17 spatiotemporal and force variables. We analyzed the biomechanical features within each cluster to characterize cluster-specific walking behaviors. We also assessed the generalizability of the clusters using a leave-one-out approach. ResultsWe identified four stroke clusters: a fast and asymmetric cluster, a moderate speed and asymmetric cluster, a slow cluster with frontal plane force asymmetries, and a slow and symmetric cluster. We also identified a moderate speed and symmetric gait cluster composed of controls and participants post-stroke. The moderate speed and asymmetric stroke cluster did not generalize across sites. ConclusionsAlthough post-stroke walking patterns are heterogenous, these patterns can be systematically classified into distinct clusters based on spatiotemporal and force data. Future interventions could target the key features that characterize each cluster to increase the efficacy of interventions to improve mobility in people post-stroke.

neuroscience↗

bioRxiv2022

Simple within-stride changes in treadmill speed can drive selective changes in human gait symmetry

BackgroundMillions of people worldwide are affected by clinical conditions that result in gait asymmetry (e.g., stroke, cerebral palsy, lower limb amputation). There is a need for customizable rehabilitation approaches that can flexibly target different aspects of gait asymmetry with minimal need for specialized equipment. Here, we studied how simple within-stride changes in treadmill speed could drive selective, predictable changes in human gait symmetry. MethodsIn Experiment 1, ten healthy young adults walked on an instrumented treadmill with and without a closed-loop controller engaged. The controller changed the treadmill speed to 1.50 m/s or 0.75 m/s depending on whether the right or left leg generated propulsive (i.e., forward-directed) ground reaction forces, respectively. In Experiment 2, a separate group of ten healthy young adults walked on the treadmill with and without an open-loop controller engaged. This controller changed the treadmill speed to 1.50 m/s or 0.75 at a prescribed time interval. We used a metronome to guide the participants to step at a series of different time points relative to the controller-driven speed change. We collected kinematic and kinetic data in Experiments 1 and 2. ResultsIn Experiment 1, participants walked with asymmetric kinematics and ground reaction forces when the closed-loop controller was engaged. The leg that accelerated during propulsion (right leg) showed a smaller leading limb angle and a larger trailing limb angle than the leg that decelerated during propulsion (left leg). The right leg also generated smaller propulsive forces than the left leg. In Experiment 2, the patterns of asymmetry in spatiotemporal gait parameters, kinematics, and ground reaction forces depended on the timing of the speed change within the gait cycle. Step times, leading limb angles, and peak propulsion became asymmetric when the treadmill speed changed early in stance. When the treadmill speed changed later in stance, step lengths, step times, and propulsion impulses became asymmetric. ConclusionsSimple manipulations of treadmill speed can drive predictable, selective changes in human gait symmetry. Future work will explore this customizable technique as a potential approach for restoring gait symmetry in clinical populations.

bioengineering↗

bioRxiv2021

Video-based quantification of human movement frequency using pose estimation

Assessment of repetitive movements (e.g., finger tapping) is a hallmark of motor examinations in several neurologic populations. These assessments are traditionally performed by a human rater via visual inspection; however, advances in computer vision offer potential for remote, quantitative assessment using simple video recordings. Here, we evaluated a pose estimation approach for measurement of human movement frequency from smartphone videos. Ten healthy young participants provided videos of themselves performing five repetitive movement tasks (finger tapping, hand open/close, hand pronation/supination, toe tapping, leg agility) at four target frequencies (1-4 Hz). We assessed the ability of a workflow that incorporated OpenPose (a freely available whole-body pose estimation algorithm) to estimate movement frequencies by comparing against manual frame-by-frame (i.e., ground-truth) measurements for all tasks and target frequencies using repeated measures ANOVA, Pearsons correlations, and intraclass correlations. Our workflow produced largely accurate estimates of movement frequencies; only the hand open/close task showed a significant difference in the frequencies estimated by pose estimation and manual measurement (while statistically significant, these differences were small in magnitude). All other tasks and frequencies showed no significant differences between pose estimation and manual measurement. Pose estimation-based detections of individual events (e.g., finger taps, hand closures) showed strong correlations with manual detections for all tasks and frequencies. In summary, our pose estimation-based workflow accurately tracked repetitive movements in healthy adults across a range of tasks and movement frequencies. Future work will test this approach as a fast, low-cost, accessible approach to quantitative assessment of repetitive movements in clinical populations.

bioengineering↗

bioRxiv2020

Two-dimensional video-based analysis of human gait using pose estimation

Walking is the primary mode of human locomotion. Accordingly, people have been interested in studying human gait since at least the fourth century BC. Human gait analysis is now common in many fields of clinical and basic research, but gold standard approaches - e.g., three-dimensional motion capture, instrumented mats or footwear, and wearables - are often expensive, immobile, data-limited, and/or require specialized equipment or expertise for operation. Recent advances in video-based pose estimation have suggested exciting potential for analyzing human gait using only two-dimensional video inputs collected from readily accessible devices (e.g., smartphones, tablets). However, we currently lack: 1) data about the accuracy of video-based pose estimation approaches for human gait analysis relative to gold standard measurement techniques and 2) an available workflow for performing human gait analysis via video-based pose estimation. In this study, we compared a large set of spatiotemporal and sagittal kinematic gait parameters as measured by OpenPose (a freely available algorithm for video-based human pose estimation) and three-dimensional motion capture from trials where healthy adults walked overground. We found that OpenPose performed well in estimating many gait parameters (e.g., step time, step length, sagittal hip and knee angles) while some (e.g., double support time, sagittal ankle angles) were less accurate. We observed that mean values for individual participants - as are often of primary interest in clinical settings - were more accurate than individual step-by-step measurements. We also provide a workflow for users to perform their own gait analyses and offer suggestions and considerations for future approaches.

bioengineering↗

bioRxiv2020

People can learn new walking patterns without walking

Humans can learn many new walking patterns. People have learned to snowshoe up mountains, racewalk marathons, and march in precise synchrony. But what is required to learn a new walking pattern? Here, we demonstrate that people can learn new walking patterns without actually walking. Through a series of experiments, we observe that stepping with only one leg can facilitate learning of an entirely new walking pattern (i.e., split-belt treadmill walking). We find that the nervous system learns from the relative motion between the legs - whether or not both legs are moving - and can transfer this learning to novel gaits. We also show that locomotor learning requires active movement: observing another person adapt their gait did not result in significantly faster learning. These findings reveal that people can learn new walking patterns without bilateral gait training, as stepping with one leg can facilitate adaptive learning that transfers to novel gait patterns.

neuroscience↗

bioRxiv2019

Persons post-stroke restore step length symmetry by walking asymmetrically

BackgroundRestoration of step length symmetry is a common rehabilitation goal after stroke. Persons post-stroke often retain the capacity to walk with symmetric step lengths (\"symmetric steps\"); however, the resulting walking pattern remains effortful. Two key questions with direct implications for rehabilitation have emerged: 1) how do persons post-stroke generate symmetric steps, and 2) why do symmetric steps remain so effortful?\n\nObjectiveTo understand how persons post-stroke generate symmetric steps and how the resulting gait pattern relates to the metabolic cost of transport.\n\nMethodsTen persons post-stroke walked on an instrumented treadmill under two conditions: preferred walking and symmetric stepping (using visual feedback). We recorded kinematic, kinetic, and metabolic data during both conditions.\n\nResultsPersons post-stroke restored step length symmetry using energetically expensive, asymmetric patterns. Impaired paretic propulsion and abnormal vertical movement of the center of mass were evident during both preferred walking and symmetric stepping. These deficits contributed to diminished positive work performed by the paretic limb on the center of mass in both conditions. Decreased positive paretic work correlated with increased metabolic cost of transport, decreased self-selected walking speed, and increased asymmetry in limb kinematics.\n\nConclusionsIt is important to consider the mechanics used to restore symmetric steps when designing interventions to improve walking after stroke. Facilitating symmetric steps via increased paretic propulsion or enabling paretic limb advancement without excessive vertical movement may enable persons post-stroke to walk with a less effortful, more symmetric gait pattern.

neuroscience↗