Smartphone and wearable sensor rehab for lumbar spine degeneration

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

This project will test whether a smartphone app combined with wireless wearable sensors and AI can give real-time guidance to help older adults with degenerative lumbar spine disease do personalized home rehabilitation.

Quick facts

• Phase: NA
• Study type: Interventional
• Enrollment: 100 (estimated)
• Ages: 50 Years to 80 Years
• Sex: All
• Sponsor: National Taiwan University Hospital (other)
• Locations: 1 site (Taipei)
• Trial ID: NCT07133724 on ClinicalTrials.gov

What this trial studies

The trial will combine inertial measurement unit (IMU) wearables and smartphone camera imaging with multimodal artificial intelligence to monitor pelvic and lumbar movements in real time and create a digital twin of patient motion. Participants will complete functional assessments and then receive individualized pelvic-control exercise programs delivered through a smartphone app that provides instant feedback and corrective cues. Biomechanics and gait-analysis models will be developed to tailor training and track progress over time. Outcomes include changes in functional performance and quality of life, with remote monitoring to support continuity of care.

Who should consider this trial

Good fit: Ideal candidates are adults aged 50–80 with degenerative lumbar spine disease who can walk independently for more than 10 meters, have normal lumbar mobility, can follow instructions, and have not had disabling low back pain in the past year.

Not a fit: Patients with systemic joint disease, central nervous system or vestibular disorders, prior spinal or lower-limb surgery, inability to communicate or follow instructions, or significant mobility impairments are unlikely to benefit from this program.

Why it matters

Potential benefit: If successful, the system could enable precise, home-based rehabilitation with real-time feedback that improves function and quality of life while reducing the need for frequent clinic visits.

How similar studies have performed: Previous tele-rehabilitation and wearable-sensor programs have shown promising improvements in gait and function, but fully integrated IMU-plus-camera multimodal AI systems with digital-twin feedback remain relatively new and not widely validated.

Eligibility criteria

Inclusion Criteria:

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

Exclusion Criteria:

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

Where this trial is running

Taipei

• National Taiwan University Hospital — Taipei, Taiwan (RECRUITING)

Study contacts

• Study coordinator: Wei-Li Hsu, Ph.D.

Conditions: Degenerative Lumbar Spine Diseases, degenerative lumbar spine disease, real-time detection, artificial Intelligence