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.

A continuous statistical-geometric framework for normative and impaired gaits.

A quantitative analysis of human gait patterns in space-time provides an opportunity to observe variability within and across individuals of varying motor capabilities. Impaired gait significantly affects independence and quality of life, and thus a large part of clinical research is dedicated to improving gait through rehabilitative therapies. Evaluation of these paradigms relies on understanding the characteristic differences in the kinematics and underlying biomechanics of impaired and unimpaired locomotion, which has motivated quantitative measurement and analysis of the gait cycle. Previous analysis has largely been limited to a statistical comparison of manually selected pointwise metrics identified through expert knowledge. Here, we use a recent statistical-geometric framework, elastic functional data analysis (FDA), to decompose kinematic data into continuous 'amplitude' (spatial) and 'phase' (temporal) components, which can then be integrated with established dimensionality reduction techniques. We demonstrate the utility of elastic FDA through two unsupervised applications to post-stroke gait datasets. First, we distinguish between unimpaired, paretic and non-paretic gait presentations. Then, we use FDA to reveal robust, interpretable groups of differential response to exosuit assistance. The proposed methods aim to benefit clinical practice for post-stroke gait rehabilitation, and more broadly, to automate the quantitative analysis of motion.

Reducing the energy cost of walking with low assistance levels through optimized hip flexion assistance from a soft exosuit.

As we age, humans see natural decreases in muscle force and power which leads to a slower, less efficient gait. Improving mobility for both healthy individuals and those with muscle impairments/weakness has been a goal for exoskeleton designers for decades. In this work, we discover that significant reductions in the energy cost required for walking can be achieved with almost 50% less mechanical power compared to the state of the art. This was achieved by leveraging human-in-the-loop optimization to understand the importance of individualized assistance for hip flexion, a relatively unexplored joint motion. Specifically, we show that a tethered hip flexion exosuit can reduce the metabolic rate of walking by up to 15.2 ± 2.6%, compared to locomotion with assistance turned off (equivalent to 14.8% reduction compared to not wearing the exosuit). This large metabolic reduction was achieved with surprisingly low assistance magnitudes (average of 89 N, ~ 24% of normal hip flexion torque). Furthermore, the ratio of metabolic reduction to the positive exosuit power delivered was 1.8 times higher than ratios previously found for hip extension and ankle plantarflexion. These findings motivated the design of a lightweight (2.31 kg) and portable hip flexion assisting exosuit, that demonstrated a 7.2 ± 2.9% metabolic reduction compared to walking without the exosuit. The high ratio of metabolic reduction to exosuit power measured in this study supports previous simulation findings and provides compelling evidence that hip flexion may be an efficient joint motion to target when considering how to create practical and lightweight wearable robots to support improved mobility.

Estimation of Walking Speed and Its Spatiotemporal Determinants Using a Single Inertial Sensor Worn on the Thigh: From Healthy to Hemiparetic Walking.

We present the use of a single inertial measurement unit (IMU) worn on the thigh to produce stride-by-stride estimates of walking speed and its spatiotemporal determinants (i.e., stride time and stride length). Ten healthy and eight post-stroke individuals completed a 6-min walk test with an 18-camera motion capture system used for ground truth measurements. Subject-specific estimation models were trained to estimate walking speed using the polar radius extracted from phase portraits produced from the IMU-measured thigh angular position and velocity. Consecutive flexion peaks in the thigh angular position data were used to define each stride and compute stride times. Stride-by-stride estimates of walking speed and stride time were then used to compute stride length. In both the healthy and post-stroke cohorts, low error and high consistency were observed for the IMU estimates of walking speed (MAE < 0.035 m/s; ICC > 0.98), stride time (MAE < 30 ms; ICC > 0.97), and stride length (MAE < 0.037 m; ICC > 0.96). This study advances the use of a single wearable sensor to accurately estimate walking speed and its spatiotemporal determinants during both healthy and hemiparetic walking.

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.

Reducing the metabolic rate of walking and running with a versatile, portable exosuit.

Walking and running have fundamentally different biomechanics, which makes developing devices that assist both gaits challenging. We show that a portable exosuit that assists hip extension can reduce the metabolic rate of treadmill walking at 1.5 meters per second by 9.3% and that of running at 2.5 meters per second by 4.0% compared with locomotion without the exosuit. These reduction magnitudes are comparable to the effects of taking off 7.4 and 5.7 kilograms during walking and running, respectively, and are in a range that has shown meaningful athletic performance changes. The exosuit automatically switches between actuation profiles for both gaits, on the basis of estimated potential energy fluctuations of the wearer's center of mass. Single-participant experiments show that it is possible to reduce metabolic rates of different running speeds and uphill walking, further demonstrating the exosuit's versatility.