Impact of automated data flow and reminders on adherence and resource utilization for remotely monitoring physical activity in individuals with stroke or chronic obstructive pulmonary disease.

As rehabilitation advances into the era of digital health, remote monitoring of physical activity via wearable devices has the potential to change how we provide care. However, uncertainties about patient adherence and the significant resource requirements needed create challenges to adoption of remote monitoring into clinical care. Here we aim to determine the impact of a novel digital application to overcome these barriers. The Rehabilitation Remote Monitoring Application (RRMA) automatically extracts data about physical activity collected via a Fitbit device, screens the data for adherence, and contacts the participant if adherence is low. We compare adherence and estimate the resources required (i.e., time and financial) to perform remote monitoring of physical activity with and without the RRMA in two patient groups. Seventy-three individuals with stroke or chronic obstructive pulmonary disease completed 28 days of monitoring physical activity with the RRMA, while 62 individuals completed 28 days with the data flow processes being completed manually. Adherence (i.e., the average percentage of the day that the device was worn) was similar between groups (p=0.85). However, the RRMA saved an estimated 123.8 minutes or $50.24 per participant month when compared to manual processes. These results demonstrate that automated technologies like the RRMA can maintain patient adherence to remote monitoring of physical activity while reducing the time and financial resources needed. Applications like the RRMA can facilitate the adoption of remote monitoring in rehabilitation by reducing barriers related to adherence and resource requirements.

Acute pain impairs retention of locomotor learning.

Despite abundant evidence that pain alters movement performance, considerably less is known about the potential effects of pain on motor learning. Some of the brain regions involved in pain processing are also responsible for specific aspects of motor learning, indicating that the two functions have the potential to interact, yet it is unclear if they do. In experiment 1, we compared the acquisition and retention of a novel locomotor pattern in young, healthy individuals randomized to either experience pain via capsaicin and heat applied to the lower leg during learning or no stimulus. On day 1, participants learned a new asymmetric walking pattern using distorted visual feedback, a paradigm known to involve mostly explicit re-aiming processes. Retention was tested 24 h later. Although there were no differences in day 1 acquisition between groups, individuals who experienced pain on day 1 demonstrated reduced retention on day 2. Furthermore, the degree of forgetting between days correlated with pain ratings during learning. In experiment 2, we examined the effects of a heat stimulus alone, which served as a control for (nonpainful) cutaneous stimulation, and found no effects on either acquisition or retention of learning. Thus, pain experienced during explicit, strategic locomotor learning interferes with motor memory consolidation processes and does so most likely through a pain mechanism and not an effect of distraction. These findings have important implications for understanding basic motor learning processes and for clinical rehabilitation, in which painful conditions are often treated through motor learning-based interventions.NEW & NOTEWORTHY Pain is a highly prevalent and burdensome experience that rehabilitation practitioners often treat using motor learning-based interventions. Here, we showed that experimental acute pain, but not a heat stimulus, during locomotor learning impaired 24-h retention of the newly learned walking pattern. The degree of retention loss was related to the perceived pain level during learning. These findings suggest important links between pain and motor learning that have significant implications for clinical rehabilitation.

The effect of post-acute rehabilitation setting on 90-day mobility after stroke: A difference-in-difference analysis.

Background: After discharged from the hospital for acute stroke, individuals typically receive rehabilitation in one of three settings: inpatient rehabilitation facilities (IRFs), skilled nursing facilities (SNFs), or home with community services (i.e., home health or outpatient clinics). The initial setting of post-acute care (i.e., discharge location) is related to mortality and hospital readmission; however, the impact of this setting on the change in functional mobility at 90-days after discharge is still poorly understood. The purpose of this work was to examine the impact of discharge location on the change in functional mobility between hospital discharge and 90-days post-discharge. Methods: In this retrospective cohort study, we used the electronic health record to identify individuals admitted to Johns Hopkins Medicine with an acute stroke and who had measurements of mobility [Activity Measure for Post Acute Care Basic Mobility (AM-PAC BM)] at discharge from the acute hospital and 90-days post-discharge. Individuals were grouped by discharge location (IRF=190 [40%], SNF=103 [22%], Home with community services=182 [(38%]). We compared the change in mobility from time of discharge to 90-days post-discharge in each group using a difference-in-differences analysis and controlling for demographics, clinical characteristics, and social determinants of health. Results: We included 475 individuals (age 64.4 [14.8] years; female: 248 [52.2%]). After adjusting for covariates, individuals who were discharged to an IRF had a significantly greater improvement in AM-PAC BM from time of discharge to 90-days post-discharge compared to individuals discharged to a SNF or home with community services (ß=-3.5 (1.4), p=0.01 and ß=-8.2 (1.3), p=<0.001, respectively). Conclusions: These findings suggest that the initial post-acute rehabilitation setting impacts the magnitude of functional recovery at 90-days after discharge from the acute hospital. These findings support the need for high-intensity rehabilitation and for policies that facilitate the delivery of high-intensity rehabilitation after stroke.

Accuracy of Video-Based Gait Analysis Using Pose Estimation During Treadmill Walking Versus Overground Walking in Persons After Stroke.

OBJECTIVE: Video-based pose estimation is an emerging technology that shows significant promise for improving clinical gait analysis by enabling quantitative movement analysis with little costs of money, time, or effort. The objective of this study is to determine the accuracy of pose estimation-based gait analysis when video recordings are constrained to 3 common clinical or in-home settings (ie, frontal and sagittal views of overground walking and sagittal views of treadmill walking). METHODS: Simultaneous video and motion capture recordings were collected from 30 persons after stroke during overground and treadmill walking. Spatiotemporal and kinematic gait parameters were calculated from videos using an open-source human pose estimation algorithm and from motion capture data using traditional gait analysis. Repeated-measures analyses of variance were then used to assess the accuracy of the pose estimation-based gait analysis across the different settings, and the authors examined Pearson and intraclass correlations with ground-truth motion capture data. RESULTS: Sagittal videos of overground and treadmill walking led to more accurate measurements of spatiotemporal gait parameters versus frontal videos of overground walking. Sagittal videos of overground walking resulted in the strongest correlations between video-based and motion capture measurements of lower extremity joint kinematics. Video-based measurements of hip and knee kinematics showed stronger correlations with motion capture versus ankle kinematics for both overground and treadmill walking. CONCLUSION: Video-based gait analysis using pose estimation provides accurate measurements of step length, step time, and hip and knee kinematics during overground and treadmill walking in persons after stroke. Generally, sagittal videos of overground gait provide the most accurate results. IMPACT: Many clinicians lack access to expensive gait analysis tools that can help identify patient-specific gait deviations and guide therapy decisions. These findings show that video-based methods that require only common household devices provide accurate measurements of a variety of gait parameters in persons after stroke and could make quantitative gait analysis significantly more accessible.

Identifying Unique Subgroups of Individuals With Stroke Using Heart Rate and Steps to Characterize Physical Activity.

Background Low physical activity (PA) is associated with poor health outcomes after stroke. Step counts are a common metric of PA; however, other physiologic signals (eg, heart rate) may help to identify subgroups of individuals poststroke at varying levels of risk of poor health outcomes. Here, we aimed to identify clinically relevant subgroups of individuals poststroke based on PA profiles that leverage multiple data sources, including step count and heart rate data, from wearable devices. Methods and Results Seventy individuals poststroke participated. Participants wore a Fitbit Inspire 2 for 1 year and completed clinical assessments. We defined a group-based steps-per-minute threshold and an individual heart rate threshold to categorize each minute of PA into 1 of 4 states: high steps/high heart rate, low steps/low heart rate, high steps/low heart rate, and low steps/high heart rate. We used the proportion of time spent in each state along with steps per day, sedentary time, mean steps among minutes with high steps and high heart rate, and resting heart rate in a k-means clustering algorithm to identify subgroups and compared Activity Measure for Post-Acute Care Mobility T Score, Stroke Impact Scale, and gait speed among subgroups. We identified 3 subgroups, Active (n=8), Sedentary (n=29), and Deconditioned (n=33), which differed significantly on all clustering variables except resting heart rate. We observed significant differences in Activity Measure for Post-Acute Care Mobility T scores between subgroups, with the Deconditioned subgroup exhibiting the lowest score. Conclusions Quantifying PA with heart rate and step count using readily available wearable devices can identify clinically meaningful subgroups of individuals poststroke.

Effects of an Acute High Intensity Exercise Bout on Retention of Explicit, Strategic Locomotor Learning in Individuals With Chronic Stroke.

BACKGROUND: Exercise priming, pairing high intensity exercise with a motor learning task, improves retention of upper extremity tasks in individuals after stroke, but has shown no benefit to locomotor learning. This difference may relate to the type of learning studied. Upper extremity studies used explicit, strategic tasks; locomotor studies used implicit sensorimotor adaptation (split-belt treadmill). Since walking is an important rehabilitation goal, it is crucial to understand under which circumstances exercise priming may improve retention of a newly learned walking pattern. OBJECTIVE: Determine the impact of exercise priming on explicit, strategic locomotor learning task retention in chronic stroke survivors. METHODS: Chronic stroke survivors (>6 months) performed 2 treadmill walking sessions. Visual feedback was used to train increased step length. Participants were assigned to control group (no exercise), continuous exercise (5 minutes high intensity), or long-interval exercise (15 minutes high/moderate intervals). After day 1 learning, participants either rested or performed exercise. On day 2, retention of the learned walking pattern was tested. RESULTS: All groups learned on day 1 (P < .001). The 2 priming groups showed significant changes in blood lactate and heart rate after exercise priming, the resting control group did not (P < .001). On day 2, there was no significant between-group difference in cued or un-cued task retention (P = .963 and .287, respectively). CONCLUSIONS: Exercise priming did not affect retention of an explicit locomotor task in chronic stroke survivors. Further work should explore subgroups of individuals for whom priming may have selective clinical benefit to locomotor learning.ClinicalTrials.gov Identifier: NCT03726047.

The feasibility of remotely monitoring physical, cognitive, and psychosocial function in individuals with stroke or chronic obstructive pulmonary disease.

Objective: Clinical implementation of remote monitoring of human function requires an understanding of its feasibility. We evaluated adherence and the resources required to monitor physical, cognitive, and psychosocial function in individuals with either chronic obstructive pulmonary disease or stroke during a three-month period. Methods: Seventy-three individuals agreed to wear a Fitbit to monitor physical function and to complete monthly online assessments of cognitive and psychosocial function. During a three-month period, we measured adherence to monitoring (1) physical function using average daily wear time, and (2) cognition and psychosocial function using the percentage of assessments completed. We measured the resources needed to promote adherence as (1) the number of participants requiring at least one reminder to synchronize their Fitbit, and (2) the number of reminders needed for each completed cognitive and psychosocial assessment. Results: After accounting for withdrawals, the average daily wear time was 77.5 ± 19.9% of the day and did not differ significantly between months 1, 2, and 3 (p = 0.30). To achieve this level of adherence, 64.9% of participants required at least one reminder to synchronize their device. Participants completed 61.0% of the cognitive and psychosocial assessments; the portion of assessments completed each month didnot significantly differ (p = 0.44). Participants required 1.13 ± 0.57 reminders for each completed assessment. Results did not differ by disease diagnosis. Conclusions: Remote monitoring of human function in individuals with either chronic obstructive pulmonary disease or stroke is feasible as demonstrated by high adherence. However, the number of reminders required indicates that careful consideration must be given to the resources available to obtain high adherence.

Development and Implementation of a Standard Assessment Battery Across the Continuum of Care for Patients After Stroke.

ABSTRACT: Stroke rehabilitation occurs across the continuum of care starting in the acute hospital and through the inpatient and outpatient settings. Rehabilitation aims to minimize impairments and maximize function in individuals after stroke. Because patients often undergo rehabilitation for extended periods, longitudinal assessment of impairment, activity, and participation can facilitate the evaluation of patients' progress toward recovery, as well as communication and decision making to guide clinical practice regarding the intervention(s) to be used and may also be leveraged for clinical research. However, the clinical implementation of a standard assessment battery that spans the continuum of care for patients after stroke is challenging because of operational and time constraints. Here, we describe the development and implementation of a standard assessment battery across the continuum of care by physical therapists, occupational therapists, and speech-language pathologists at the Sheikh Khalifa Stroke Institute. We specifically describe our experience in (1) identifying the core team to lead the process, (2) selecting the measures for the standard assessment battery, and the timeframe for administration, and (3) implementing the standard assessment battery in routine clinical practice.

A Learning Health System Infrastructure for Precision Rehabilitation After Stroke.

ABSTRACT: Functional recovery and the response to rehabilitation interventions after stroke are highly variable. Understanding this variability will promote precision rehabilitation for stroke, allowing us to deliver targeted interventions to the right person at the right time. Capitalizing on large, heterogeneous data sets, such as those generated through clinical care and housed within the electronic health record, can lead to understanding of poststroke variability. However, accessing data from the electronic health record can be challenging because of data quality, privacy concerns, and the resources required for data extraction. Therefore, creating infrastructure that overcomes these challenges and contributes to a learning health system is needed to achieve precision rehabilitation after stroke. We describe the creation of a Precision Rehabilitation Data Repository that facilitates access to systematically collected data from the electronic health record as part of a learning health system to drive precision rehabilitation. Specifically, we describe the process of (1) standardizing the documentation of functional assessments, (2) obtaining regulatory approval, (3) defining the patient cohort, and (4) extracting data for the Precision Rehabilitation Data Repository. The development of similar infrastructures at other institutions can help generate large, heterogeneous data sets to drive poststroke care toward precision rehabilitation, thereby maximizing poststroke function within an efficient healthcare system.

Opportunities for Improving Motor Assessment and Rehabilitation After Stroke by Leveraging Video-Based Pose Estimation.

ABSTRACT: Stroke is a leading cause of long-term disability in adults in the United States. As the healthcare system moves further into an era of digital medicine and remote monitoring, technology continues to play an increasingly important role in post-stroke care. In this Analysis and Perspective article, opportunities for using human pose estimation-an emerging technology that uses artificial intelligence to track human movement kinematics from simple videos recorded using household devices (e.g., smartphones, tablets)-to improve motor assessment and rehabilitation after stroke are discussed. The focus is on the potential of two key applications: (1) improving access to quantitative, objective motor assessment and (2) advancing telerehabilitation for persons post-stroke.

Precision Rehabilitation: Optimizing Function, Adding Value to Health Care.

Precision medicine efforts are underway in many medical disciplines; however, the power of precision rehabilitation has not yet been explored. Precision medicine aims to deliver the right intervention, at the right time, in the right setting, for the right person, ultimately bolstering the value of the care that we provide. To date, precision medicine efforts have rarely focused on function at the level of a person, but precision rehabilitation is poised to change this and bring the focus on function to the broader precision medicine enterprise. To do this, subgroups of individuals must be identified based on their level of function via precise measurement of their abilities in the physical, cognitive, and psychosocial domains. Adoption of electronic health records, advances in data storage and analytics, and improved measurement technology make this shift possible. Here we detail critical components of the precision rehabilitation framework, including (1) the synergistic use of various study designs, (2) the need for standardized functional measurements, (3) the importance of precise and longitudinal measures of function, (4) the utility of comprehensive databases, (5) the importance of predictive analyses, and (6) the need for system and team science. Precision rehabilitation has the potential to revolutionize clinical care, optimize function for all individuals, and magnify the value of rehabilitation in health care; however, to reap the benefits of precision rehabilitation, the rehabilitation community must actively pursue this shift.

Fluid Cognition Relates to Locomotor Switching in Neurotypical Adults, Not Individuals After Stroke.

BACKGROUND AND PURPOSE: The ability to switch between walking patterns (ie, locomotor switching) is vital for successful community navigation and may be impacted by poststroke impairments. Thus, the purpose of this work was to examine locomotor switching and the relationship between locomotor switching and fluid cognition in individuals after stroke compared with neurotypical adults. METHODS: Twenty-nine individuals more than 6 months after stroke and 18 neurotypical adults participated in a 2-day study. On day 1, participants were taught a new walking pattern on the treadmill and then locomotor switching was assessed by instructing participants to switch between the new walking pattern and their usual walking pattern. The change between these 2 patterns was calculated as the switching index. On day 2, the NIH Toolbox Cognition Battery was administered to obtain the Fluid Cognition Composite Score (FCCS), which reflected fluid cognition. The switching index was compared between groups using an analysis of covariance, and the relationship between locomotor switching and fluid cognition was assessed with regression. RESULTS: Individuals after stroke had significantly lower switching indexes compared with neurotypical adults (P = 0.03). The regression showed a significant interaction between group and FCCS (P = 0.002), with the FCCS predicting the switching index in neurotypical adults but not in individuals after stroke. DISCUSSION AND CONCLUSIONS: Individuals after stroke appear to have deficits in locomotor switching compared with neurotypical adults. The relationship between fluid cognition and locomotor switching was significant in neurotypical adults but not in individuals after stroke. Future work to understand the relationship between specific cognitive domains and locomotor switching is needed (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A361).

Depressive Symptoms Moderate the Relationship Among Physical Capacity, Balance Self-Efficacy, and Participation in People After Stroke.

OBJECTIVE: It was previously found that balance self-efficacy mediated the relationship between physical capacity and participation after stroke. The effect of other factors that influence participation, such as depression, on this relationship has not been explored. This study examined the effect of symptoms of depression on the mediated relationship between physical capacity and participation by balance self-efficacy in individuals after stroke. METHODS: In this cross-sectional study, 282 persons with chronic stroke (>6 months) were classified as having either low or high Geriatric Depression Scale scores. This study used a multiple group structural equation model to test moderated mediation by comparing a constrained model (indicating no effect of depression on the mediation) and an unconstrained model (indicating an effect of depression on the mediation). The models were compared using a chi-squared difference test. RESULTS: The chi-squared difference test suggested that the unconstrained model was a better fit, indicating that depressive symptoms moderated the mediated relationship between physical capacity and participation (χ2(3, N = 282) = 9.0). In the Low Depression group, a significant indirect effect indicated that balance self-efficacy did mediate the relationship between physical capacity and participation. There was no significant indirect effect in the High Depression group. CONCLUSION: The results suggest the relationship between physical capacity and participation appears to be mediated by balance self-efficacy in individuals after stroke with low reports of depressive symptoms, but in those with high reports of depressive symptoms, physical capacity and balance self-efficacy are unrelated to participation. IMPACT: Targeting balance self-efficacy to improve post-stroke participation may be beneficial only for individuals with low reports of depression. In individuals after stroke with high reports of depression, treatment should include and emphasize the treatment of those depressive symptoms. Additional work further examining these complex relationships is warranted.

Fluid Cognitive Abilities Are Important for Learning and Retention of a New, Explicitly Learned Walking Pattern in Individuals After Stroke.

BACKGROUND: There is significant variability in poststroke locomotor learning that is poorly understood and affects individual responses to rehabilitation interventions. Cognitive abilities relate to upper extremity motor learning in neurologically intact adults, but have not been studied in poststroke locomotor learning. OBJECTIVE: To understand the relationship between locomotor learning and retention and cognition after stroke. METHODS: Participants with chronic (>6 months) stroke participated in 3 testing sessions. During the first session, participants walked on a treadmill and learned a new walking pattern through visual feedback about their step length. During the second session, participants walked on a treadmill and 24-hour retention was assessed. Physical and cognitive tests, including the Fugl-Meyer-Lower Extremity (FM-LE), Fluid Cognition Composite Score (FCCS) from the NIH Toolbox -Cognition Battery, and Spatial Addition from the Wechsler Memory Scale-IV, were completed in the third session. Two sequential regression models were completed: one with learning and one with retention as the dependent variables. Age, physical impairment (ie, FM-LE), and cognitive measures (ie, FCCS and Spatial Addition) were the independent variables. RESULTS: Forty-nine and 34 participants were included in the learning and retention models, respectively. After accounting for age and FM-LE, cognitive measures explained a significant portion of variability in learning (R2 = 0.17, P = .008; overall model R2 = 0.31, P = .002) and retention (ΔR2 = 0.17, P = .023; overall model R2 = 0.44, P = .002). CONCLUSIONS: Cognitive abilities appear to be an important factor for understanding locomotor learning and retention after stroke. This has significant implications for incorporating locomotor learning principles into the development of personalized rehabilitation interventions after stroke.

Use of explicit processes during a visually guided locomotor learning task predicts 24-h retention after stroke.

Implicit and explicit processes can occur within a single locomotor learning task. The combination of these learning processes may impact how individuals acquire/retain the task. Because these learning processes rely on distinct neural pathways, neurological conditions may selectively impact the processes that occur, thus, impacting learning and retention. Thus, our purpose was to examine the contribution of implicit and explicit processes during a visually guided walking task and characterize the relationship between explicit processes and performance/retention in stroke survivors and age-matched healthy adults. Twenty chronic stroke survivors and twenty healthy adults participated in a 2-day treadmill study. Day 1 included baseline, acquisition1, catch, acquisition2, and immediate retention phases, and day 2 included 24-h retention. During acquisition phases, subjects learned to take a longer step with one leg through distorted visual feedback. During catch and retention phases, visual feedback was removed and subjects were instructed to walk normally (catch) or how they walked during the acquisition phases (retention). Change in step length from baseline to catch represented implicit processes. Change in step length from catch to the end of acquisition2 represented explicit processes. A mixed ANOVA found no difference in the type of learning between groups (P = 0.74). There was a significant relationship between explicit processes and 24-h retention in stroke survivors (r = 0.47, P = 0.04) but not in healthy adults (r = 0.34, P = 0.15). These results suggest that stroke may not affect the underlying learning mechanisms used during locomotor learning, but that these mechanisms impact how well stroke survivors retain the new walking pattern.NEW & NOTEWORTHY This study found that stroke survivors used implicit and explicit processes similar to age-matched healthy adults during a visually guided locomotion learning task. The amount of explicit processes was related to how well stroke survivors retained the new walking pattern but not to how well they performed during the task. This work illustrates the importance of understanding the underlying learning mechanisms to maximize retention of a newly learned motor behavior.

Use-dependent plasticity explains aftereffects in visually guided locomotor learning of a novel step length asymmetry.

Studies of upper extremity reaching show that use-dependent plasticity, or learning from repetition, plays an important role in shaping motor behaviors. Yet the impact of repetition on locomotor learning is unclear, despite the fact that gait is developed and practiced over millions of repetitions. To test whether repetition alone can induce storage of a novel walking pattern, we instructed two groups of young healthy subjects to learn an asymmetric walking pattern through two distinct learning paradigms. The first group learned a new pattern through an established visual distortion paradigm, which provided both sensory prediction error and repetition of movement patterns to induce walking aftereffects, and the second received veridical feedback with a target change, which provided only repetition (use-dependent plasticity) to induce aftereffects. When feedback was removed, both groups demonstrated aftereffects in the primary outcome, step asymmetry index. Surprisingly, despite the different task demands, both groups produced similar aftereffect magnitudes, which also had similar rates of decay, suggesting that the addition of sensory prediction errors did not improve storage of learning beyond that induced by the use-dependent process alone. To further characterize the use-dependent process, we conducted a second experiment to quantify aftereffect size in a third group who practiced double the asymmetry magnitude. This new group showed a proportionately greater magnitude of the use-dependent aftereffect. Together, these findings show that the primary driver of storage of a new step length asymmetry during visually guided locomotor learning is repetition, not sensory prediction error, and this effect scales with the learning magnitude.NEW & NOTEWORTHY Use-dependent plasticity, or learning from repetition, is an important process for upper extremity reaching tasks, but its contribution to walking is not well established. Here, we demonstrate the existence of a dose-dependent, use-dependent process during visually guided treadmill walking. We also show that sensory prediction errors, previously thought to drive aftereffects in similar locomotor learning paradigms, do not appear to play a significant role in visually driven learning of a novel step asymmetry during treadmill walking.

Comparison of three kinematic gait event detection methods during overground and treadmill walking for individuals post stroke.

Detecting gait events using ground reaction forces (i.e. kinetic detection) is the gold standard, but it is not always possible. Kinematic methods exist; however, accuracy of these methods in stroke survivors during treadmill and overground walking is unknown. Thus, this study compared the accuracy of three kinematic methods during overground and treadmill walking in stroke survivors. Heel strike and toe off were calculated bilaterally using three kinematic methods (horizontal sacral-heel distance, horizontal ankle-heel distance, and horizontal velocity) and a kinetic method for ten stroke survivors. We calculated true and absolute error for each kinematic method relative to the kinetic method to evaluate accuracy. Repeated-measures ANOVAs compared the absolute error between the different methods for each condition. There was a significant effect of method for all conditions except heel strike during treadmill walking. Post hoc tests showed ankle-heel distance detected heel strike with significantly less error than the other methods during overground walking (p < 0.05). Ankle-heel distance identified 93.0% and 77.8% of gait events within 50 ms of the kinetic event for overground and treadmill walking, respectively. Sacral-heel distance detected toe-off with significantly less error than the other methods during overground and treadmill walking (p < 0.05) and identified 87.2% and 90.3% of gait events within 50 ms of the kinetic event for overground and treadmill walking, respectively. Results suggest that ankle-heel distance and sacral-heel distance accurately detect heel strike and toe-off, respectively, in stroke survivors.

A single high-intensity exercise bout during early consolidation does not influence retention or relearning of sensorimotor locomotor long-term memories.

A single exercise bout has been found to improve the retention of a skill-based upper extremity motor task up to a week post-practice. This effect is the greatest when exercise intensity is high and exercise is administered immediately after motor practice (i.e., early in consolidation). Whether exercise can affect other motor learning types (e.g., sensorimotor adaptation) and tasks (e.g., walking) is still unclear as previous studies have not optimally refined the exercise parameters and long-term retention testing. Therefore, we investigated whether a single high-intensity exercise bout during early consolidation would improve the long-term retention and relearning of sensorimotor adaptation during split-belt treadmill walking. Twenty-six neurologically intact adults attended three sessions; sessions 2 and 3 were 1 day and 7 days after session 1, respectively. Participants were allocated either to Rest (REST) or to Exercise (EXE) group. In session 1, all groups walked on a split-belt treadmill in a 2:1 speed ratio (1.5:0.75 m/s). Then, half of the participants exercised for 5 min (EXE), while the other half rested for 5 min (REST). A short exercise bout during early consolidation did not improve retention or relearning of locomotor memories one or seven days after session 1. This result reinforces previous findings that the effect of exercise on motor learning may differ between sensorimotor locomotor adaptation and skilled-based upper extremity tasks; thus, the utility of exercise as a behavioral booster of motor learning may depend on the type of motor learning and task.

A locomotor learning paradigm using distorted visual feedback elicits strategic learning.

Distorted visual feedback (DVF) during locomotion has been suggested to result in the development of a new walking pattern in healthy individuals through implicit learning processes. Recent work in upper extremity visuomotor rotation paradigms suggest that these paradigms involve implicit and explicit learning. Additionally, in upper extremity visuomotor paradigms, the verbal cues provided appear to impact how a behavior is learned and when this learned behavior is used. Here, in two experiments in neurologically intact individuals, we tested how verbal instruction impacts learning a new locomotor pattern on a treadmill through DVF, the transfer of that pattern to overground walking, and what types of learning occur (i.e., implicit vs. explicit learning). In experiment 1, we found that the instructions provided impacted the amount learned through DVF, but not the size of the aftereffects or the amount of the pattern transferred to overground walking. Additionally, the aftereffects observed were significantly different from the baseline walking pattern, but smaller than the behavior changes observed during learning, which is uncharacteristic of implicit sensorimotor adaptation. Thus, experiment 2 aimed to determine the cause of these discrepancies. In this experiment, when VF was not provided, individuals continued using the learned walking pattern when instructed to do so and returned toward their baseline pattern when instructed to do so. Based on these results, we conclude that DVF during locomotion results in a large portion of explicit learning and a small portion of implicit learning. NEW & NOTEWORTHY The results of this study suggest that distorted visual feedback during locomotor learning involves the development of an explicit strategy with only a small component of implicit learning. This is important because previous studies using distorted visual feedback have suggested that locomotor learning relies primarily on implicit learning. This paradigm, therefore, provides a new way to examine a different form of learning in locomotion.