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Recruiting NCT07133724

Digital Health for Lumbar Degeneration

No phase Interventional Degenerative Lumbar Spine Diseases

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: AI-Based Smart Assessment and Rehabilitation Training.
Who it may be relevant to
Registry conditions: Degenerative Lumbar Spine Diseases. Basic parameters: 50 years — 80 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Taiwan
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Digital Health for Aging: A Multimodal AI-Based Smart Assessment and Rehabilitation Training System for Lumbar Degeneration

Overview

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.

Detailed description

The multimodal AI-based smart assessment and rehabilitation training system developed in this study will provide patients with lumbar degeneration a convenient and precise home-based rehabilitation solution. 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. This design not only improves patients' self-awareness of posture and movement but also reduces the risk of improper compensatory strategies that often occur in traditional home exercise programs.

The system is particularly suitable for older adults with mobility limitations or those who have difficulties frequently visiting medical institutions. By enabling remote assessment, individualized training, and long-term monitoring, this platform ensures continuity of care and enhances patients' motivation to engage in rehabilitation. The outcomes of this project will establish a tele-rehabilitation system tailored to degenerative lumbar spine disease, support clinicians in delivering precise and effective treatment, and ultimately reduce the healthcare and economic burden on families and society.

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.

Primary outcome measures

  • Functional assessment: Walking speed [Time frame: 6 months]
  • Functional assessment: Walking distance [Time frame: 6 months]
  • Functional assessment: 5 Times Sit to Stand Test [Time frame: 6 months]
Secondary outcome measures (2)
  • Kinematic variables: Joint angles [Time frame: 6 months]
  • Kinetic variables [Time frame: 6 months]

Eligibility criteria

Inclusion criteria

  • Age between 50-80 years to capture the typical characteristics of lumbar degeneration in this age group.
  • No history of low back pain lasting more than one week or severe enough to interrupt work within the past year.
  • Normal lumbar functional mobility.
  • Ability to walk independently for more than 10 meters.

Exclusion criteria

  • Presence of systemic joint diseases such as ankylosing spondylitis, rheumatoid arthritis, or multiple sclerosis, which may significantly affect lumbar mobility and gait patterns.
  • Central nervous system disorders (e.g., spinal cord injury, stroke, or Parkinson's disease) that may influence gait and motor control.
  • Vestibular system disorders, to avoid balance abnormalities interfering with gait testing.
  • History of spinal or lower limb surgery, as postoperative changes may affect the accuracy of gait data.
  • Inability to communicate or follow instructions.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation
N/A
Model
Single group
Masking
Open label
Primary purpose
Treatment

Study locations

Taiwan · 1 center
  • National Taiwan University Hospital — Taipei

Identifiers

NCT: NCT07133724 · 202502072RIND

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗