Enrica Tricomi, Francesco Missiroli, Michele Xiloyannis, Nicola Lotti, Xiaohui Zhang, Marios Stefanakis, Maximilian Theisen, Jürgen Bauer, Clemens Becker, Lorenzo Masia
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引用次数: 0
Abstract
Peoples'' walking efficiency declines as they grow older, posing constraints on mobility, and affecting independence and quality of life. Although wearable assistive technologies are recognized as a potential solution for age-related movement challenges, few have proven effective for older adults, predominantly within controlled laboratory experiments. Here we present WalkON, a pair of soft robotic shorts designed to enhance walking efficiency for older individuals by assisting hip flexion. The system features a compact and lightweight tendon-driven design, using a controller based on natural leg movements to autonomously assist leg propagation. To assess WalkON''s impact on daily walking, we initially conducted a technology assessment with young adults on a demanding outdoor uphill 500 m hiking trail. We then validated our findings with a group of older adults walking on a flat outdoor 400 m track. WalkON considerably reduced the metabolic cost of transport by 17.79% for young adults during uphill walking. At the same time, participants reported high perceived control over their voluntary movements (a self-reported mean score of 6.20 out of 7 on a Likert scale). Similarly, older adults reduced their metabolic cost by 10.48% when using WalkON during level ground walking, while retaining a strong sense of movement control (mean score of 6.09 out of 7). These findings emphasize the potential of wearable assistive devices to improve efficiency in outdoor walking, suggesting promising implications for promoting physical well-being and advancing mobility, particularly during the later stages of life. Walking efficiency declines in older adults. To address this challenge, Tricomi and colleagues present a pair of lightweight, soft robotic shorts that enhance walking efficiency for older adults by assisting leg mobility. This method improves energy efficiency on outdoor tracks while maintaining the users’ natural movement control.
期刊介绍:
Nature Machine Intelligence is a distinguished publication that presents original research and reviews on various topics in machine learning, robotics, and AI. Our focus extends beyond these fields, exploring their profound impact on other scientific disciplines, as well as societal and industrial aspects. We recognize limitless possibilities wherein machine intelligence can augment human capabilities and knowledge in domains like scientific exploration, healthcare, medical diagnostics, and the creation of safe and sustainable cities, transportation, and agriculture. Simultaneously, we acknowledge the emergence of ethical, social, and legal concerns due to the rapid pace of advancements.
To foster interdisciplinary discussions on these far-reaching implications, Nature Machine Intelligence serves as a platform for dialogue facilitated through Comments, News Features, News & Views articles, and Correspondence. Our goal is to encourage a comprehensive examination of these subjects.
Similar to all Nature-branded journals, Nature Machine Intelligence operates under the guidance of a team of skilled editors. We adhere to a fair and rigorous peer-review process, ensuring high standards of copy-editing and production, swift publication, and editorial independence.