Manifesting Nominal Assistance in Hemiplegia Gait Training Through an Assistive Normality Framework

Rehabilitation exoskeletons have been demonstrated to benefit mobility-limited patients; however, accessibility is hindered by several challenges, and interaction evaluation of coupled human–exoskeleton systems remains critically understudied. In this pioneering study“, assistive normality (AN)” is introduced to characterize the cross-stage spatiotemporal features of exoskeleton-assisted gait in hemiplegic patients, and a multidimensional, low-data-cost metric framework is developed to quantify AN. Three subdivided metrics, including gait restoration (GR), phase-deviation weighting (PDW) and multijoint coordination (MJC), are proposed to assess coupled system interaction behavior across different intervention stages during rehabilitation. A homologous difference evaluation paradigm (HDEP) is introduced to capture pathological differences between healthy and hemiplegic subjects on the basis of the reusability of experimental data, providing an approach for the nominal assistance calibration and assessment of specific exoskeleton devices. In a pilot study with eight healthy individuals and nine hemiplegic patients, between-group metric differences were analyzed to determine the calibrated AN of an exoskeleton. The results provide calibration references for quantitative metrics and demonstrate the ability of framework to characterize the temporal dynamics of human–exoskeleton interactions. The proposed AN framework offers a generalizable approach to assistive robotics, potentially enhancing evaluation of human-robot interaction and advancing clinical rehabilitation applications.

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Publication Details

Journal
IEEE Transactions on Systems Man and Cybernetics Systems
Published
2025-08-20
DOI
https://doi.org/10.1109/tsmc.2025.3595211
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
0.00

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article

Manifesting Nominal Assistance in Hemiplegia Gait Training Through an Assistive Normality Framework

Xingang Zhao, Lianqing Liu, Zhihai Li, Haibin Yu et al.
1 links
IEEE Transactions on Systems Man and Cybernetics Systems
Stroke Rehabilitation and Recovery
article

Manifesting Nominal Assistance in Hemiplegia Gait Training Through an Assistive Normality Framework

Xingang Zhao, Lianqing Liu, Zhihai Li, Haibin Yu, Wanxin Chen, Bi Zhang
article en

Abstract

Rehabilitation exoskeletons have been demonstrated to benefit mobility-limited patients; however, accessibility is hindered by several challenges, and interaction evaluation of coupled human–exoskeleton systems remains critically understudied. In this pioneering study“, assistive normality (AN)” is introduced to characterize the cross-stage spatiotemporal features of exoskeleton-assisted gait in hemiplegic patients, and a multidimensional, low-data-cost metric framework is developed to quantify AN. Three subdivided metrics, including gait restoration (GR), phase-deviation weighting (PDW) and multijoint coordination (MJC), are proposed to assess coupled system interaction behavior across different intervention stages during rehabilitation. A homologous difference evaluation paradigm (HDEP) is introduced to capture pathological differences between healthy and hemiplegic subjects on the basis of the reusability of experimental data, providing an approach for the nominal assistance calibration and assessment of specific exoskeleton devices. In a pilot study with eight healthy individuals and nine hemiplegic patients, between-group metric differences were analyzed to determine the calibrated AN of an exoskeleton. The results provide calibration references for quantitative metrics and demonstrate the ability of framework to characterize the temporal dynamics of human–exoskeleton interactions. The proposed AN framework offers a generalizable approach to assistive robotics, potentially enhancing evaluation of human-robot interaction and advancing clinical rehabilitation applications.

IEEE Transactions on Systems Man and Cybernetics SystemsVol. 55(10)
Shenyang Institute of Automation (CN)
National Natural Science Foundation of China, Natural Science Foundation of Liaoning Province
Openalex Percentile: Top 73%
Stroke Rehabilitation and Recovery
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