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Be Right! Back: An Artificial Intelligence Enabled Mobile Application for Patients With Low Back Pain

NCT06973915 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 120

Last updated 2025-05-15

No results posted yet for this study

Summary

Low back pain (LBP) is a common problem with complex causes, of which some are modifiable. Physical factors like strength, movement, and pain play a big role, but measuring all these factors accurately is tricky. This is where Artificial Intelligence (AI) comes in.

This projects aims to develop an AI solution (in the form of a mobile application) that can measure four key components of the physical factor of LBP, such as how quickly you can stand up five times, your spine's flexibility, how you walk, and your pain levels while moving. The measurements taken by the mobile application will be compared against those of trained physiotherapists to ensure its accuracy.

If successful, this AI solution will be a game-changer. Physiotherapists will be able to remotely track the progress of their LBP patients. The data gained from the remote tracking will allow physiotherapists to have a better understanding of the individual profile of each LBP patient and adjust their treatment accordingly, hence allowing for better care and more effective LBP management.

In short, this project aims to harness the power of AI to make managing LBP easier for both patients and physiotherapists.

Conditions

  • Low Back Pain

Interventions

OTHER

AI model for movement and pain assessment in low back pain

This intervention involves developing an artificial intelligence (AI) model to objectively assess four physical parameters relevant to low back pain (LBP): 1) sit-to-stand performance, 2) trunk range of motion, 3) gait pattern, and 4) facial expression-based pain levels during movement. The AI model processes video recordings of participants performing these tasks to extract movement and facial data, providing standardized measurements. The tool is designed to assist physiotherapists in clinical decision-making by offering consistent and accurate assessments compared to traditional observational methods.

Sponsors & Collaborators

  • National Medical Research Council (NMRC), Singapore

    collaborator OTHER_GOV

  • KK Women's and Children's Hospital

    collaborator OTHER_GOV

  • Singapore General Hospital

    lead OTHER

Principal Investigators

  • Philip Cheong, DClinPhty · Singapore General Hospital

Eligibility

Min Age
21 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-06-01
Primary Completion
2026-09-30
Completion
2027-03-31

Countries

  • Singapore

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 NCT06973915 on ClinicalTrials.gov