Wearable robotic devices have been shown to substantially reduce the energy expenditure of human walking. However, response variance between participants for fixed control strategies can be high, leading to the hypothesis that individualized controllers could further improve walking economy. Recent studies on human-in-the-loop (HIL) control optimization have elucidated several practical challenges, such as long experimental protocols and low signal-to-noise ratios. Here, we used Bayesian optimization-an algorithm well suited to optimizing noisy performance signals with very limited data-to identify the peak and offset timing of hip extension assistance that minimizes the energy expenditure of walking with a textile-based wearable device. Optimal peak and offset timing were found over an average of 21.4 ± 1.0 min and reduced metabolic cost by 17.4 ± 3.2% compared with walking without the device (mean ± SEM), which represents an improvement of more than 60% on metabolic reduction compared with state-of-the-art devices that only assist hip extension. In addition, our results provide evidence for participant-specific metabolic distributions with respect to peak and offset timing and metabolic landscapes, lending support to the hypothesis that individualized control strategies can offer substantial benefits over fixed control strategies. These results also suggest that this method could have practical impact on improving the performance of wearable robotic devices.

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Many pneumatic energy sources are available for use in autonomous and wearable soft robotics, but it is often not obvious which options are most desirable or even how to compare them. To address this, we compare pneumatic energy sources and review their relative merits. We evaluate commercially available battery-based microcompressors (singly, in parallel, and in series) and cylinders of high-pressure fluid (air and carbon dioxide). We identify energy density (joules/gram) and flow capacity (liters/gram) normalized by the mass of the entire fuel system (versus net fuel mass) as key metrics for soft robotic power systems. We also review research projects using combustion (methane and butane) and monopropellant decomposition (hydrogen peroxide), citing theoretical and experimental values. Comparison factors including heat, effective energy density, and working pressure/flow rate are covered. We conclude by comparing the key metrics behind each technology. Battery-powered microcompressors provide relatively high capacity, but maximum pressure and flow rates are low. Cylinders of compressed fluid provide high pressures and flow rates, but their limited capacity leads to short operating times. While methane and butane possess the highest net fuel energy densities, they typically react at speeds and pressures too high for many soft robots and require extensive system-level development. Hydrogen peroxide decomposition requires not only few additional parts (no pump or ignition system) but also considerable system-level development. We anticipate that this study will provide a framework for configuring fuel systems in soft robotics.

To understand the effects of soft exosuits on human loaded walking, we developed a reconfigurable multi-joint actuation platform that can provide synchronized forces to the ankle and hip joints. Two different assistive strategies were evaluated on eight subjects walking on a treadmill at a speed of 1.25 m/s with a 23.8 kg backpack: 1) hip extension assistance and 2) multi-joint assistance (hip extension, ankle plantarflexion and hip flexion). Results show that the exosuit introduces minimum changes to kinematics and reduces biological joint moments. A reduction trend in muscular activity was observed for both conditions. On average, the exosuit reduced the metabolic cost of walking by 0.21 ±0.04 and 0.67 ±0.09 W/kg for hip extension assistance and multi-joint assistance respectively, which is equivalent to an average metabolic reduction of 4.6% and 14.6%, demonstrating that soft exosuits can effectively improve human walking efficiency during load carriage without affecting natural walking gait. Moreover, it indicates that actuating multiple joints with soft exosuits provides a significant benefit to muscular activity and metabolic cost compared to actuating single joint.

BackgroundRecent advances in wearable robotic devices have demonstrated the ability to reduce the metabolic cost of walking by assisting the ankle joint. To achieve greater gains in the future it will be important to determine optimal actuation parameters and explore the effect of assisting other joints. The aim of the present work is to investigate how the timing of hip extension assistance affects the positive mechanical power delivered by an exosuit and its effect on biological joint power and metabolic cost during loaded walking. In this study, we evaluated 4 different hip assistive profiles with different actuation timings: early-start-early-peak (ESEP), early-start-late-peak (ESLP), late-start-early-peak (LSEP), late-start-late-peak (LSLP).MethodsEight healthy participants walked on a treadmill at a constant speed of 1.5 m · s-1 while carrying a 23 kg backpack load. We tested five different conditions: four with the assistive profiles described above and one unpowered condition where no assistance was provided. We evaluated participants’ lower limb kinetics, kinematics, metabolic cost and muscle activation.ResultsThe variation of timing in the hip extension assistance resulted in a different amount of mechanical power delivered to the wearer across conditions; with the ESLP condition providing a significantly higher amount of positive mechanical power (0.219 ± 0.006 W · kg-1) with respect to the other powered conditions. Biological joint power was significantly reduced at the hip (ESEP and ESLP) and at the knee (ESEP, ESLP and LSEP) with respect to the unpowered condition. Further, all assistive profiles significantly reduced the metabolic cost of walking compared to the unpowered condition by 5.7 ± 1.5 %, 8.5 ± 0.9 %, 6.3 ± 1.4 % and 7.1 ± 1.9 % (mean ± SE for ESEP, ESLP, LSEP, LSLP, respectively).ConclusionsThe highest positive mechanical power delivered by the soft exosuit was reported in the ESLP condition, which showed also a significant reduction in both biological hip and knee joint power. Further, the ESLP condition had the highest average metabolic reduction among the powered conditions. Future work on autonomous hip exoskeletons may incorporate these considerations when designing effective control strategies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12984-016-0196-8) contains supplementary material, which is available to authorized users.