SURVEY ON SOCIALLY INTEGRATED WEARABLE GAIT ROBOTS IN 192 CHILDREN AND ADULTS WITH GAIT DYSFUNCTION: A NEW ROBOT STRATEGY AND DESIGN

Robot-assisted gait rehabilitation technology mitigates gait dysfunction caused by neurological conditions by focusing on functional impairments and activity limitations. However, it often neglects integrative robotic designs that address the international classification of functioning (ICF) domains, including impairments, activity limitations, and social community participation. To develop optimal social integration wearable gait-assisting robots for individuals with neurological gait dysfunction through a comprehensive robot design survey, a survey, including 192 participants with gait dysfunction across all age groups, was conducted to identify important demographic and clinical outcome variables and related robotic design features. Data were analyzed using qualitative, correlation, and [Formula: see text] analyses at [Formula: see text]. This survey data identified important relationships between functional ambulation classification and awareness of robot ([Formula: see text]), Timed Up and Go (TUG) and robot satisfaction [Formula: see text], gross motor function classification scale (GMFCS) levels and reason for using robots [Formula: see text] and social participation, considering personal and environmental contextual factors. The correlation between lower TUG scores and higher robot satisfaction suggests that users with mobility challenges benefit more from the wearable gait assisting robot (“MIRACLE”), leading us to refine the interface and control mechanisms to further optimize ease of use and stability for individuals with slower walking speeds or greater balance impairments. This, in turn, results in more tailored assistance and improved user interaction with the robotic device. The survey data can contribute to designing effective, socially integrated robotic systems that will enhance mobility, independence, and social integration for pediatric and adult populations with gait dysfunction. By highlighting these connections in the abstract, we aim to provide a clearer picture of how the study’s results contribute to meaningful improvements in the design and function of the MIRACLE robots, aligning with the ultimate goal of enhancing mobility and user satisfaction.

Authors

Institutions

Publication Details

Journal
Journal of Mechanics in Medicine and Biology
Published
2025-02-07
DOI
https://doi.org/10.1142/s021951942540007x
Primary Topic
Assistive Technology in Communication and Mobility
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SURVEY ON SOCIALLY INTEGRATED WEARABLE GAIT ROBOTS IN 192 CHILDREN AND ADULTS WITH GAIT DYSFUNCTION: A NEW ROBOT STRATEGY AND DESIGN

Seonmi Park, Suyong Lee, Yunhwan Kim, Jongeun Choi et al.
Journal of Mechanics in Medicine and Biology
Assistive Technology in Communication and Mobility
article

SURVEY ON SOCIALLY INTEGRATED WEARABLE GAIT ROBOTS IN 192 CHILDREN AND ADULTS WITH GAIT DYSFUNCTION: A NEW ROBOT STRATEGY AND DESIGN

Seonmi Park, Suyong Lee, Yunhwan Kim, Jongeun Choi, Joshua H. You, Jiwon Shin, Myung Sook Park, Yujin Na, Han Sung Kim, Byeong Jong Lee
article en

Abstract

Robot-assisted gait rehabilitation technology mitigates gait dysfunction caused by neurological conditions by focusing on functional impairments and activity limitations. However, it often neglects integrative robotic designs that address the international classification of functioning (ICF) domains, including impairments, activity limitations, and social community participation. To develop optimal social integration wearable gait-assisting robots for individuals with neurological gait dysfunction through a comprehensive robot design survey, a survey, including 192 participants with gait dysfunction across all age groups, was conducted to identify important demographic and clinical outcome variables and related robotic design features. Data were analyzed using qualitative, correlation, and [Formula: see text] analyses at [Formula: see text]. This survey data identified important relationships between functional ambulation classification and awareness of robot ([Formula: see text]), Timed Up and Go (TUG) and robot satisfaction [Formula: see text], gross motor function classification scale (GMFCS) levels and reason for using robots [Formula: see text] and social participation, considering personal and environmental contextual factors. The correlation between lower TUG scores and higher robot satisfaction suggests that users with mobility challenges benefit more from the wearable gait assisting robot (“MIRACLE”), leading us to refine the interface and control mechanisms to further optimize ease of use and stability for individuals with slower walking speeds or greater balance impairments. This, in turn, results in more tailored assistance and improved user interaction with the robotic device. The survey data can contribute to designing effective, socially integrated robotic systems that will enhance mobility, independence, and social integration for pediatric and adult populations with gait dysfunction. By highlighting these connections in the abstract, we aim to provide a clearer picture of how the study’s results contribute to meaningful improvements in the design and function of the MIRACLE robots, aligning with the ultimate goal of enhancing mobility and user satisfaction.

Journal of Mechanics in Medicine and BiologyVol. 25(02)
Yonsei University (KR), Soonchunhyang University (KR), Sangji University (KR)
Reduced inequalities
Openalex Percentile: Top 97%
Assistive Technology in Communication and Mobility
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.