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Currently submitted to: Journal of Medical Internet Research

Date Submitted: Jun 27, 2026
Open Peer Review Period: Jun 29, 2026 - Aug 24, 2026
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Internet of exoneuromusculoskeleton (Io-ENMS)-assisted poststroke lower limb telerehabilitation: pilot clinical validation

  • Wanyi Qing; 
  • Hantao Song; 
  • Fuqiang Ye; 
  • Legeng Lin; 
  • Yixun Wang; 
  • Mingxin Jiang; 
  • Hon-Wah Wai; 
  • Danny Tat-Ming Chan; 
  • Wai-Sang Poon; 
  • Stephanie Chi-Ping Ng; 
  • Weiwei Ye; 
  • Yanhuan Huang; 
  • Xiaoling Hu

ABSTRACT

Background:

Persistent gait impairment after stroke limits independence and community participation. Telerehabilitation can extend rehabilitation access beyond clinical settings; however, home-based poststroke gait training remains limited by insufficient corrective assistance, limited remote supervision, and inadequate digital infrastructure for continuous monitoring and data-driven management.

Objective:

This study aimed to evaluate the feasibility, preliminary efficacy, and safety of an Internet of exoneuromusculoskeleton (Io-ENMS)-assisted telerehabilitation system that integrates Internet of Things (IoT) technology with a wearable ankle-foot ENMS to support self-help, home-based gait training under a hybrid remote therapist management model.

Methods:

A single-group, rater-blinded pilot validation trial was conducted in individuals with chronic stroke. Participants completed a 20-session ENMS-assisted gait training program combining guided preparation with remotely supervised home-based training and on-demand onsite support. Feasibility was assessed using training adherence, protocol compliance, remote management efficiency, participant experience, and satisfaction. Preliminary efficacy was evaluated using clinical outcomes, gait kinematics, plantar pressure distribution, and muscle activation before training, immediately after training, and at the 3-month follow-up. Safety was assessed based on adverse events, automated detection of protocol deviations, and therapist interventions during home-based training.

Results:

Sixteen participants completed the telerehabilitation program. The system demonstrated feasibility, supported by a high completion rate, consistent adherence during the program, positive usability and satisfaction ratings, and the effective operation of the hybrid remote management model that substantially reduced therapist involvement. Quantitative analysis of training logs and communication data provided detailed insights into user engagement patterns, training behaviors, and support needs throughout the program. Significant improvements were observed in lower-limb motor function, gait kinematics, plantar pressure distribution, and muscle activation profiles, with several gains maintained at the 3-month follow-up. Safety was supported through multilayered digital monitoring, automated detection of protocol deviations, and appropriate therapist intervention when needed, with no serious adverse events reported.

Conclusions:

The Io-ENMS-assisted telerehabilitation system demonstrated feasibility, preliminary efficacy, and acceptable safety for home-based gait rehabilitation in individuals with chronic stroke, supporting a data-driven and patient-centered model for delivering robot-assisted gait training in real-world home environments. Clinical Trial: ClinicalTrials.gov NCT04934787


 Citation

Please cite as:

Qing W, Song H, Ye F, Lin L, Wang Y, Jiang M, Wai HW, Chan DTM, Poon WS, Ng SCP, Ye W, Huang Y, Hu X

Internet of exoneuromusculoskeleton (Io-ENMS)-assisted poststroke lower limb telerehabilitation: pilot clinical validation

JMIR Preprints. 27/06/2026:105694

DOI: 10.2196/preprints.105694

URL: https://preprints.jmir.org/preprint/105694

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