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Digital Health for Lumbar Degeneration

NCT07133724 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 100

Last updated 2025-08-21

No results posted yet for this study

Summary

This study will integrate wireless wearable sensors, smartphone imaging, and multimodal artificial intelligence (AI) to address the rehabilitation needs of patients with lumbar degeneration. Patients will undergo comprehensive functional assessments, and individualized exercise instruction with real-time feedback will be provided through a smartphone application. The goals of this research are to: (1) develop a multimodal AI-based digital health system combining IMU sensors and smartphone cameras for real-time assessment and interactive rehabilitation training, (2) construct biomechanics- and gait-analysis models to support personalized rehabilitation for patients with lumbar degeneration, and (3) investigate the mechanisms and clinical efficacy of pelvic control exercise training combined with real-time smartphone feedback in improving function and quality of life for aging patients.

Conditions

  • Degenerative Lumbar Spine Diseases

Interventions

OTHER

AI-Based Smart Assessment and Rehabilitation Training

Through the integration of wireless inertial sensors and smartphone imaging, the system can monitor pelvic and lumbar movements in real time, generate a digital twin model, and deliver instant feedback to guide patients in performing correct exercises.

Sponsors & Collaborators

  • National Taiwan University Hospital

    lead OTHER

Study Design

Allocation
NA
Purpose
TREATMENT
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
50 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-08-01
Primary Completion
2028-07-31
Completion
2028-07-31

Countries

  • Taiwan

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07133724 on ClinicalTrials.gov