Exoskeletons can augment the performance of unimpaired users and restore movement in individuals with gait impairments. Knowledge of how users interact with wearable devices and of the physiology of locomotion have informed the design of rigid and soft exoskeletons that can specifically target a single joint or a single activity. In this Review, we highlight the main advances of the past two decades in exoskeleton technology and in the development of lower-extremity exoskeletons for locomotor assistance, discuss research needs for such wearable robots and the clinical requirements for exoskeleton-assisted gait rehabilitation, and outline the main clinical challenges and opportunities for exoskeleton technology.
Exosuits have the potential to assist locomotion in both healthy and pathological populations, but the effect of exosuit assistance on the underlying muscle-tendon tissue loading is not yet understood. In this study, we used shear wave tensiometers to characterize the modulation of Achilles tendon force with load carriage and exosuit assistance at the ankle. When walking (1.25 m/s) unassisted on a treadmill with load carriage weights of 15 and 30% of body weight, peak Achilles tendon force increased by 11 and 23%, respectively. Ankle exosuit assistance significantly reduced peak Achilles tendon force relative to unassisted, although the magnitude of change was variable across participants. Peak Achilles tendon force was significantly correlated with peak ankle torque for unassisted walking across load carriage conditions. However, when ankle plantarflexor assistance was applied, the relationship between peak tendon force and peak biological ankle torque was no longer significant. An outdoor pilot study was conducted in which a wearable shear wave tensiometer was used to measure Achilles tendon wave speed and compare across an array of assistance loading profiles. Reductions in tendon loading varied depending on the profile, highlighting the importance of in vivo measurements of muscle and tendon forces when studying and optimizing exoskeletons and exosuits.
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.
Background: Stroke is a leading cause of serious gait impairments and restoring walking ability is a major goal of physical therapy interventions. Soft robotic exosuits are portable, lightweight, and unobtrusive assistive devices designed to improve the mobility of post-stroke individuals through facilitation of more natural paretic limb function during walking training. However, it is unknown whether long-term gait training using soft robotic exosuits will clinically impact gait function and quality of movement post-stroke.
Objective: The objective of this pilot study was to examine the therapeutic efects of soft robotic exosuit-augmented gait training on clinical and biomechanical gait outcomes in chronic post-stroke individuals.
Methods: Five post-stroke individuals received high intensity gait training augmented with a soft robotic exosuit, delivered in 18 sessions over 6–8 weeks. Performance based clinical outcomes and biomechanical gait quality parameters were measured at baseline, midpoint, and completion.
Results: Clinically meaningful improvements were observed in walking speed (p < 0.05) and endurance (p < 0.01) together with other traditional gait related outcomes. The gait quality measures including hip (p < 0.01) and knee (p < 0.05) fexion/extension exhibited an increase in range of motion in a symmetric manner (p < 0.05). We also observed an increase in bilateral ankle angular velocities (p < 0.05), suggesting biomechanical improvements in walking function.
Conclusions: The results in this study ofer preliminary evidence that a soft robotic exosuit can be a useful tool to augment high intensity gait training in a clinical setting. This study justifes more expanded research on soft exosuit technology with a larger post-stroke population for more reliable generalization.
Trial registration This study is registered with ClinicalTrials.gov (ID: NCT04251091)
The force-generatingcapacity of skeletal muscle is an important metric in the evaluation and diagnosis of musculoskeletal health. Measuring changes in muscle force exertion is essential for tracking the progress of athletes during training, for evaluating patients’ recovery after muscle injury, and also for assisting the diagnosis of conditions such as muscular dystrophy, multiple sclerosis, or Parkinson’s disease. Traditional hardware for strength evaluation requires technical training for operation, generates discrete time points for muscle assessment, and is implemented in controlled settings. The ability to continuously monitor muscle force without restricting the range of motion or adapting the exercise protocol to suit specific hardware would allow for a richer dataset that can help unlock critical features of muscle health and strength evaluation. In this paper, we employ wearable, ultra-sensitive soft strain sensors for tracking changes in muscle deformation during contractions. We demonstrate the sensors’ sensitivity to isometric contractions, as well as the sensors’ capacity to track changes in peak torque over the course of an isokinetic fatiguing protocol for the knee extensors. The wearable soft system was able to efficiently estimate peak joint torque reduction caused by muscle fatigue (mean NRMSE = 0.15±0.03).
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.
The knee joint experiences significant torques in the frontal plane to keep the body upright during walking. Excessive loading over time can lead to knee osteoarthritis (OA), the progression of which is correlated with external knee adduction moment (KAM). In this paper, we present a wearable soft robotic exosuit that applies a hip abduction torque and evaluate its ability to reduce KAM. The exosuit uses a portable cable actuation system to generate torque when desired while remaining unrestrictive when unpowered. We explored five different force profiles on healthy participants (N=8) walking on an instrumented treadmill at 1.25 m/s. For each force profile, we tested two peak force levels: 15% and 20% of bodyweight. We observed KAM reductions with two of the five profiles. With Force Profile 2 (FP2), peak KAM was reduced by 9.61% and impulse KAM by 12.76%. With Force Profile 5 (FP5), we saw reductions of peak KAM by 6.14% and impulse KAM by 21.09%. These initial findings show that the device has the ability to change walking biomechanics in a consistent and potentially beneficial way.