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Pain Detection Through Automated Video Analysis
Sponsor: KK Women's and Children's Hospital
Summary
The study team has developed an algorithm for pain assessment based on automated video facial and body pose analysis. The investigators aim to assess the sensitivity of this algorithm in detecting pain in post-surgical patients and refine the algorithm to increase the sensitivity of pain detection in patients.
Key Details
Gender
All
Age Range
6 Years - 70 Years
Study Type
INTERVENTIONAL
Enrollment
370
Start Date
2019-08-01
Completion Date
2026-12-31
Last Updated
2024-11-19
Healthy Volunteers
No
Conditions
Interventions
Videotaping
Before the videotaping, patients will be asked on their baseline pain scores. Their face and body pose from a frontal view will be videotaped via a mobile phone with no internet access. The collected videos will be further processed to extract key points, which will be the primary input for modelling algorithms and will further ensure anonymity of the patients in the video sequences.
Questionnaires
Patients will be asked to fill in 1-2 questionnaires before surgery/procedure/consultation (Hospital Anxiety and Depression Scale (HADS) and/or EQ-5D-3L). After surgery/procedure/consultation, patients will be again asked to fill in HADS questionnaire (optional). For pediatrics patient, only Child Pain Anxiety Symptoms Scale (CPASS) will be administered before the surgery.
Empatica E4 wristband
A medical grade wearable device, Empatica E4 wristband, will be used in phase 3 for pediatrics patients to monitor real-time physiological data on heart rate and body temperature.
Locations (2)
KK Women's and Children's Hospital
Singapore, Singapore
Singapore General Hospital
Singapore, Singapore