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Open-Source Anatomical Illustration for Digital Back Pain Documentation: Development and Feasibility Evaluation
Yanick Xavier Lukic1,2, Sonja Schläpfer3, Alessandro Holler4,5
1Institute of Computer Science, School of Engineering, Zurich University of Applied Sciences, Steinberggasse 13, Winterthur, 8400, Switzerland.
Background:
Accurate documentation of back pain is essential for effective diagnosis and treatment; however, conventional paper-based methods often lack precision and standardization, limiting their clinical utility. Digital pain drawings can improve consistency and integration; however, the literature continues to report variability in digital pain drawing methods, quantification approaches, body schemas, and implementation. Moreover, open access, anatomically labeled vector assets mapped to clinical terminology remain limited.
Objective:
This study aimed to develop an anatomically accurate, digitally segmented, open-source vector illustration of a sex-neutral human body (front and back views) for standardized back pain documentation and conduct a user-centered design validation and feasibility evaluation of its perceived usefulness, communication value, and visual acceptability.
Methods:
An interdisciplinary team used an iterative methodology informed by standard anatomical references to create the illustration, emphasizing anatomical precision, digital compatibility, and interoperability with medical coding systems. A survey-based design validation study (N=298) was conducted in the United Kingdom through the Prolific platform to evaluate perceived usefulness, confidence in identifying hypothetical pain regions (without an interactive drawing task or comparator), aesthetic appeal, and suggestions for improvement. Quantitative results were summarized descriptively with 95% CIs, and qualitative feedback guided final refinements. The finalized illustration was released under a CC BY 4.0 license.
Results:
Mean confidence ratings were 5.7 out of 7 (SD 1.2) for indicating pain regions using the illustration (95% CI 5.5-5.8) and 5.6 out of 7 (SD 1.2) for communicating pain with health care professionals (95% CI 5.5-5.8). Aesthetic ratings were more mixed (mean 4.3 out of 7, SD 1.5; 95% CI 4.1-4.5). User feedback highlighted the need for improved visual clarity, leading to adjustments in color contrast and anatomical proportions. Aesthetic concerns, including the removal of the areolae and changes to the facial features, were also addressed to enhance user comfort and neutrality.
Conclusions:
The resulting anatomically accurate vector illustration provides a feasible, open-source foundation for digital back pain documentation tools and may support patient-clinician communication and integration with electronic health records. The design validation study supports acceptability and perceived usefulness, but it does not establish superiority over existing body maps or objective accuracy of pain localization. By releasing it under a CC BY 4.0 license, we encourage broad adoption and community-driven improvements.
