Reducing Personalization Time and Energy Cost While Walking Outdoors with a Portable Exosuit

Human‐in‐the‐loop optimization (HILO) has maximized the benefits of using wearable robots. Although all previous HILO studies have shown promising results, the majority have been validated in laboratory settings. The factor restricting HILO from real‐world applications is its optimization time. Therefore, this study focused on developing a swift HILO strategy targeting its outdoor applications. We validate the proposed HILO strategy in two phases during incline walking with a portable hip extension exosuit. The first phase was conducted on an instrumented treadmill, followed by an outdoor case study in community settings. During the first phase, the optimization converged in 7 min reducing the metabolic energy by 10.5 ± 1.3% compared to walking without assistance. After redesigning the HILO based on indoor results, we achieved a 16.2% metabolic reduction in 3 min 24 s of optimization while walking outdoors, making it the fastest HILO strategy to date.

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Publication Details

Journal
Advanced Robotics Research
Published
2025-06-29
DOI
https://doi.org/10.1002/adrr.202400027
Citations
2
Primary Topic
Prosthetics and Rehabilitation Robotics
Type
article
Field-Weighted Citation Impact
1.35
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Reducing Personalization Time and Energy Cost While Walking Outdoors with a Portable Exosuit

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article

Reducing Personalization Time and Energy Cost While Walking Outdoors with a Portable Exosuit

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article en
2 citations

Abstract

Human‐in‐the‐loop optimization (HILO) has maximized the benefits of using wearable robots. Although all previous HILO studies have shown promising results, the majority have been validated in laboratory settings. The factor restricting HILO from real‐world applications is its optimization time. Therefore, this study focused on developing a swift HILO strategy targeting its outdoor applications. We validate the proposed HILO strategy in two phases during incline walking with a portable hip extension exosuit. The first phase was conducted on an instrumented treadmill, followed by an outdoor case study in community settings. During the first phase, the optimization converged in 7 min reducing the metabolic energy by 10.5 ± 1.3% compared to walking without assistance. After redesigning the HILO based on indoor results, we achieved a 16.2% metabolic reduction in 3 min 24 s of optimization while walking outdoors, making it the fastest HILO strategy to date.

Advanced Robotics ResearchVol. 2(1)
Korea University Medical Center (KR), Indian Institute of Technology Bhilai (IN), Chung-Ang University (KR)
Openalex Percentile: Top 19%
Prosthetics and Rehabilitation Robotics
1.35
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