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Using Smart Devices and Artificial Intelligence to Prevent Back Pain in Office Workers in Delhi-NCR

Development of an AI-Based Predictive Model Using Wearable and Psychosocial Data for the Prevention of Non-Specific Low Back Pain among Corporate Workers in the NCR Region - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/12/099409
Enrollment
160
Registered
2025-12-18
Start date
Unknown
Completion date
Unknown
Last updated
2026-01-12

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

Conditions

None listed

Interventions

Intervention1: Nil: Nil Intervention2: Nil: Nil Intervention3: Nil: Nil Intervention4: Nil: Nil

Sponsors

Academic Study
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Sedentary Job for more than 6 months, Minimum 6 hours daily computer use, willingness to wear monitoring devices and complete psychosocial surveys.

Exclusion criteria

Exclusion criteria: Prior Diagnosis Spinal Conditions(Herniation, fracture) History of Spinal Surgery, Chronic Musculoskeletal or Neurological Disorders, Pregnancy, Non-Sedentary Job Profile

Design outcomes

Primary

MeasureTime frame
The Integration of wearable sensor data(posture, activity level and sitting duration) with psychosocial variables(stress, job satisfaction and work-life balance) through AI significantly improves the prediction and prevention of non-specific low back pain among corporate employees compared to using either data source alone.Timepoint: 16 weeks—

Secondary

MeasureTime frame
NILTimepoint: NIL—

Countries

India

Contacts

Public ContactRahul Tyagi

Galgotias University

Singh.nidhi@galgotiasuniversity.edu.in7042627025

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026