Individualized Learning-Based Ground Reaction Force Estimation in People Post-Stroke Using Pressure Insoles.

Stroke is a leading cause of gait disability that leads to a loss of independence and overall quality of life. The field of clinical biomechanics aims to study how best to provide rehabilitation given an individual's impairments. However, there remains a disconnect between assessment tools used in biomechanical analysis and in clinics. In particular, 3-dimensional ground reaction forces (3D GRFs) are used to quantify key gait characteristics, but require lab-based equipment, such as force plates. Recent efforts have shown that wearable sensors, such as pressure insoles, can estimate GRFs in real-world environments. However, there is limited understanding of how these methods perform in people post-stroke, where gait is highly heterogeneous. Here, we evaluate three subject-specific machine learning approaches to estimate 3D GRFs with pressure insoles in people post-stroke across varying speeds. We find that a Convolutional Neural Network-based approach achieves the lowest estimation errors of 0.75 ± 0.24, 1.13 ± 0.54, and 4.79 ± 3.04 % bodyweight for the medio-lateral, antero-posterior, and vertical GRF components, respectively. Estimated force components were additionally strongly correlated with the ground truth measurements ( ). Finally, we show high estimation accuracy for three clinically relevant point metrics on the paretic limb. These results suggest the potential for an individualized machine learning approach to translate to real-world clinical applications.

Effects of high-intensity gait training with and without soft robotic exosuits in people post-stroke: a development-of-concept pilot crossover trial.

INTRODUCTION: High-intensity gait training is widely recognized as an effective rehabilitation approach after stroke. Soft robotic exosuits that enhance post-stroke gait mechanics have the potential to improve the rehabilitative outcomes achieved by high-intensity gait training. The objective of this development-of-concept pilot crossover study was to evaluate the outcomes achieved by high-intensity gait training with versus without soft robotic exosuits. METHODS: In this 2-arm pilot crossover study, four individuals post-stroke completed twelve visits of speed-based, high-intensity gait training: six consecutive visits of Robotic Exosuit Augmented Locomotion (REAL) gait training and six consecutive visits without the exosuit (CONTROL). The intervention arms were counterbalanced across study participants and separated by 6 + weeks of washout. Walking function was evaluated before and after each intervention using 6-minute walk test (6MWT) distance and 10-m walk test (10mWT) speed. Moreover, 10mWT speeds were evaluated before each training visit, with the time-course of change in walking speed computed for each intervention arm. For each participant, changes in each outcome were compared to minimal clinically-important difference (MCID) thresholds. Secondary analyses focused on changes in propulsion mechanics and associated biomechanical metrics. RESULTS: Large between-group effects were observed for 6MWT distance (d = 1.41) and 10mWT speed (d = 1.14). REAL gait training resulted in an average pre-post change of 68 ± 27 m (p = 0.015) in 6MWT distance, compared to a pre-post change of 30 ± 16 m (p = 0.035) after CONTROL gait training. Similarly, REAL training resulted in a pre-post change of 0.08 ± 0.03 m/s (p = 0.012) in 10mWT speed, compared to a pre-post change of 0.01 ± 06 m/s (p = 0.76) after CONTROL. For both outcomes, 3 of 4 (75%) study participants surpassed MCIDs after REAL training, whereas 1 of 4 (25%) surpassed MCIDs after CONTROL training. Across the training visits, REAL training resulted in a 1.67 faster rate of improvement in walking speed. Similar patterns of improvement were observed for the secondary gait biomechanical outcomes, with REAL training resulting in significantly improved paretic propulsion for 3 of 4 study participants (p < 0.05) compared to 1 of 4 after CONTROL. CONCLUSION: Soft robotic exosuits have the potential to enhance the rehabilitative outcomes produced by high-intensity gait training after stroke. Findings of this development-of-concept pilot crossover trial motivate continued development and study of the REAL gait training program.

Natural Walking Intensity in Persons With Parkinson Disease.

BACKGROUND AND PURPOSE: Few persons with Parkinson disease (PD) appear to engage in moderate-intensity walking associated with disease-modifying health benefits. How much time is spent walking at lower, yet still potentially beneficial, intensities is poorly understood. The purpose of this exploratory, observational study was to describe natural walking intensity in ambulatory persons with PD. METHODS: Accelerometer-derived real-world walking data were collected for more than 7 days at baseline from 82 participants enrolled in a PD clinical trial. Walking intensity was defined according to the number of steps in each active minute (1-19, 20-39, 40-59, 60-79, 80-99, or ≥100 steps). Daily minutes of walking and duration of the longest sustained walking bout were calculated at each intensity. Number of sustained 10 to 19, 20 to 29, and 30-minute bouts and greater at any intensity also were calculated. Values were analyzed in the context of physical activity guidelines. RESULTS: Most daily walking occurred at lower intensities (157.3 ± 58.1 min of 1-19 steps; 81.3 ± 32.6 min of 20-39 steps; 38.2 ± 21.3 min of 40-59 steps; 15.1 ± 11.5 min of 60-79 steps; 7.4 ± 7.0 min of 80-99 steps; 7.3 ± 9.6 min of ≥100 steps). The longest daily sustained walking bout occurred at the lowest intensity level (15.9 ± 5.2 min of 1-19 steps). Few bouts lasting 20 minutes and greater occurred at any intensity. DISCUSSION AND CONCLUSIONS: Despite relatively high daily step counts, participants tended to walk at remarkably low intensity, in bouts of generally short duration, with relatively few instances of sustained walking. The findings reinforced the need for health promotion interventions designed specifically to increase walking intensity.Video Abstract available for more insight from authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A426 ).

Targeting Paretic Propulsion and Walking Speed With a Soft Robotic Exosuit: A Consideration-of-Concept Trial.

Background: Soft robotic exosuits can facilitate immediate increases in short- and long-distance walking speeds in people with post-stroke hemiparesis. We sought to assess the feasibility and rehabilitative potential of applying propulsion-augmenting exosuits as part of an individualized and progressive training program to retrain faster walking and the underlying propulsive strategy. Methods: A 54-yr old male with chronic hemiparesis completed five daily sessions of Robotic Exosuit Augmented Locomotion (REAL) gait training. REAL training consists of high-intensity, task-specific, and progressively challenging walking practice augmented by a soft robotic exosuit and is designed to facilitate faster walking by way of increased paretic propulsion. Repeated baseline assessments of comfortable walking speed over a 2-year period provided a stable baseline from which the effects of REAL training could be elucidated. Additional outcomes included paretic propulsion, maximum walking speed, and 6-minute walk test distance. Results: Comfortable walking speed was stable at 0.96 m/s prior to training and increased by 0.30 m/s after training. Clinically meaningful increases in maximum walking speed (Δ: 0.30 m/s) and 6-minute walk test distance (Δ: 59 m) were similarly observed. Improvements in paretic peak propulsion (Δ: 2.80 %BW), propulsive power (Δ: 0.41 W/kg), and trailing limb angle (Δ: 6.2 degrees) were observed at comfortable walking speed (p's < 0.05). Likewise, improvements in paretic peak propulsion (Δ: 4.63 %BW) and trailing limb angle (Δ: 4.30 degrees) were observed at maximum walking speed (p's < 0.05). Conclusions: The REAL training program is feasible to implement after stroke and capable of facilitating rapid and meaningful improvements in paretic propulsion, walking speed, and walking distance.