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Automated Trainer-Based Gait Rehabilitation for Hemiplegic Stroke Patients

Gait Training for Hemiplegic Stroke Patients: Employing an Automated Trainer With Sensory Cues

Status
Enrolling by invitation
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07411703
Enrollment
60
Registered
2026-02-17
Start date
2025-03-26
Completion date
2029-03-26
Last updated
2026-02-17

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Stroke

Brief summary

This study aims to evaluate the effectiveness of an automated mobile gait training device developed based on neurodevelopmental treatment (NDT) principles for patients with hemiplegic stroke. Stroke is a major cause of long-term disability, and many survivors experience impaired walking ability that affects their independence and daily functioning. NDT is a commonly used rehabilitation approach that emphasizes therapist-guided facilitation of normal movement patterns during gait training. However, conventional NDT gait training is physically demanding and time-consuming for therapists, which may limit the amount of repetitive gait practice patients can receive. To address these limitations, this study introduces a power-assisted gait training device capable of reproducing key therapeutic interventions typically provided by therapists. The system uses synchronized dynamic assistance, auditory cues, and wearable inertial measurement units (IMUs) to support gait training on the ground and facilitate more natural and repetitive walking practice. The IMUs provide objective gait data that are used to evaluate changes in swing-phase symmetry, pelvic rotation amplitude, and walking speed. The primary goal of this study is to assess changes in these gait parameters following training with the proposed NDT-based assistive device. The study plans to enroll 60 adult stroke survivors (aged 20 and older) over a 3-year period starting from March 26, 2025.

Interventions

The intervention consists of an NDT gait training device that replicates therapist-applied techniques through mechanical assistance, combined with synchronized auditory feedback and real-time gait analysis using IMU sensors.

Sponsors

Cheng-Hsin General Hospital
Lead SponsorOTHER

Study design

Observational model
CASE_ONLY
Time perspective
CROSS_SECTIONAL

Eligibility

Sex/Gender
ALL
Age
20 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Age ≥ 20 years, first-ever stroke, with Brunnstrom stage III to IV of the affected lower limb motor recovery. * Functional Ambulation Category (FAC) level IV. * Ability to ambulate on level ground without assistive devices. * Ability to understand instructions and cooperate with assessments.

Exclusion criteria

* Presence of severe spinal cord injury or peripheral neuropathy. * Unstable gait requiring assistive devices, or participants at high risk of falling. * Severe impairment in vision, hearing, or cognition, making them unable to comply with assessments. * Lower limb fracture within the past 6 months.

Design outcomes

Primary

MeasureTime frameDescription
Swing phase asymmetryBaseline (pre-intervention) and post-intervention (immediately after completion of the NDT gait training program).Swing-phase asymmetry, defined as the difference in swing-phase proportion between the non-paretic and paretic limbs- will be calculated from toe-off to heel-strike timing within the gait cycle, using the wearable inertial measurement units (IMUs) before and after the NDT gait training intervention .
Pelvic rotation amplitudeBaseline (pre-intervention) and post-intervention (immediately after completion of the NDT gait training program).Gait data will be acquired via wearable IMUs before and after the NDT gait training intervention, and the amplitude of pelvic rotation will be derived from axial angular velocity data.
Walking speedBaseline (pre-intervention) and post-intervention (immediately after completion of the NDT gait training program).Walking speed will be quantified during gait using IMU-based measurements, and the average walking speed for each stage will be computed from recorded motor-driven motion data and reported in meters per second (m/s).

Countries

Taiwan

Contacts

PRINCIPAL_INVESTIGATORSzu-Fu Chen

MD, PhD

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 18, 2026