![]() ![]() If human performance could instead be estimated quickly, using low-cost wearable sensors, optimization could be performed as people moved naturally through their daily lives. Individualizing consumer or medical devices in this way would require several long visits to a specialized clinic, which would be costly and impractical. Measuring important aspects of performance, including metabolic rate 16, has required expensive laboratory equipment and long periods of steady treadmill walking 18. ![]() The largest improvements in human walking performance have been achieved by individualizing assistance using human-in-the-loop optimization 1, 2, 3, 4, a process in which device control is systematically tuned to improve human performance while a person uses a device. ![]() Maximizing the benefits of exoskeleton assistance requires personalization to individual needs, which is challenging outside of a laboratory. In this study, we addressed each of these challenges to demonstrate effective exoskeleton assistance under naturalistic conditions. Providing beneficial assistance in the real world is difficult for several reasons: the specialized equipment used to personalize assistance is not available outside the laboratory unlike walking on a treadmill, everyday walking occurs in many bouts of varying speed and duration and devices must be self-contained and easy to use. In research laboratories, exoskeletons can increase walking speed 1, 8, 9 and reduce the energy required to walk 2, 3, 4, 10, 11, 12, 13, 14, 15, 16, but these benefits have not yet translated to real-world conditions 17. Millions of people have mobility impairments that make walking slower 5 and more fatiguing 6, while millions more people have occupations that require strenuous locomotion 7. Human movements encode information that can be used to personalize assistive devices and enhance performance.Įxoskeletons that assist leg movement show promise for enhancing personal mobility but have yet to provide real-world benefits. This assistance reduced metabolic energy consumption by 23 ± 8% when participants walked on a treadmill at a standard speed of 1.5 m s −1. Assistance optimized during one hour of naturalistic walking in a public setting increased self-selected speed by 9 ± 4% and reduced the energy used to travel a given distance by 17 ± 5% compared with normal shoes. We performed real-world optimization using data collected during many short bouts of walking at varying speeds. We developed a data-driven method for optimizing exoskeleton assistance outdoors using wearable sensors and found that it was equally effective as laboratory methods, but identified optimal parameters four times faster. We designed a portable ankle exoskeleton based on insights from tests with a versatile laboratory testbed. Here we show that exoskeleton optimization can be performed rapidly and under real-world conditions. Personalized exoskeleton assistance provides users with the largest improvements in walking speed 1 and energy economy 2, 3, 4 but requires lengthy tests under unnatural laboratory conditions. ![]()
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