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Efficacy of a Soft Wearable Robot for Hip Assistance in Chronic Stroke Patients: A Randomized Crossover Trial

  • Seung Hyeon Han
  • , Sanguk Choi
  • , Chanyoung Ko
  • , Jong Weon Lee
  • , Kyoungchul Kong
  • , Dong Wook Rha
  • , Deog Young Kim
  • Yonsei University
  • Korea Advanced Institute of Science and Technology

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

This study evaluates the effectiveness of a cable-driven soft wearable robot (SWR) in assisting hip flexion and extension in chronic stroke patients to improve gait performance, energy efficiency, and kinematic parameters. A randomized crossover trial assessed under three scenarios: no SWR, SWR without power, and SWR with active assistance. Nineteen patients with chronic stroke participated, showing substantial enhancements in gait performance, energy efficiency, and joint kinematics following SWR activation. Notable outcomes include a 14.9% reduction in oxygen cost during SWR-assisted walking compared to unassisted walking, underscoring its metabolic benefits. Gait performance improved, evidenced by a 0.11 m/s increase in self-selected walking speed and a 20.7-meter gain in the 6-minute walk test (6MWT) distance, exceeding the minimal clinically important difference (MCID) thresholds. Kinematic analysis disclosed significant improvements in paretic-side hip flexion angles, with a 39.4% increase at initial contact and a 41.1% increase during the swing phase. Moreover, reductions in compensatory movements such as hip hiking were noted. Despite these gains, gait asymmetry remained, highlighting the necessity for further enhancements in SWR design and control mechanisms to mitigate entrenched compensatory patterns in chronic stroke patients. The lightweight, body-adaptive design of the SWR added to user comfort and energy conservation, showcasing its potential for clinical use. This research highlights the potential of SWR technology to enhance functional mobility and autonomy in stroke survivors. Future investigations should focus on long-term impacts and real-world efficacy to refine rehabilitation approaches.

Original languageEnglish
Pages (from-to)2251-2262
Number of pages12
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume33
DOIs
StatePublished - 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Chronic stroke
  • energy efficiency
  • gait performance
  • rehabilitation technology
  • soft wearable robots

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