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Automated Pain Spots Recognition Algorithm Provided by a Web Service-Based Platform: Instrument Validation Study
Corrado Cescon1, Giuseppe Landolfi2, Niko Bonomi2
1Rehabilitation Research Laboratory 2rLab, Department of Business Economics, Health and Social Care, University of Applied Sciences and Arts of Southern Switzerland, Via Violino 11, Manno, 6928, Switzerland, 41 586666442.
JMIR Mhealth and Uhealth
|August 27, 2024
Summary
Digital scanning of pain drawings (PDs) is accurate using affordable devices. A new web platform reliably analyzes PDs from various scanners, ensuring data quality for musculoskeletal pain research.
Area of Science:
- Musculoskeletal pain research
- Digital health technologies
- Medical imaging analysis
Background:
- Understanding musculoskeletal pain mechanisms is key for effective treatment.
- Pain drawings (PDs) are self-report measures of pain intensity and location.
- Digital PDs require validation for usability and reliability compared to traditional methods.
Purpose of the Study:
- To evaluate a web platform's accuracy in analyzing PDs scanned by various digital devices.
- To confirm that simple, affordable mobile devices can acquire PDs without data loss.
Main Methods:
- Generated PDs with colored circles and shapes on body charts.
- Printed PDs on A4 sheets with QR codes for alignment.
- Scanned PDs using flatbed scanners, smartphones, and virtual scanner apps.
Main Results:
- All devices accurately identified high-saturation colors.
- Percentage error for pain spots was below 20% across all devices.
- A negative correlation between error percentage and spot size was observed (R=-0.237; P=.04).
Conclusions:
- A web platform can accurately analyze PDs from diverse digital scanners.
- Cost-effective mobile devices are suitable for PD acquisition without compromising data quality.
- Standardizing scanning with this platform enhances PD analysis efficiency and consistency.
