In earlier work, the Sponsor developed a computer image processing system for analysis of pain diagrams from patients with chronic pain. This system was then tested in a study in over 500 chronic pain patients seen by both primary care practitioners and pain specialists. The hypothesis was that pain location would correlate with the pain type and the underlying cause of the pain. In the study, the computer analysis demonstrated clear correlations between pain diagram data and diagnosis/pain type. The present study extends these observations in a web-based setting, with a focus on the value of computer analysis of pain diagrams as diagnostic predictors.
||Observational Model: Cohort
Time Perspective: Prospective
||Internet-based Study of 10,000 Subjects With Chronic Pain, Including Subject-drawn Pain Diagrams, and Computer-generated Composite Images of Pain Patterns
| Estimated Enrollment:
| Study Start Date:
Earlier work performed by the Sponsor (TMT) included development of a MatLab/ImageJ computer image processing system for generation of composite images from pain diagrams drawn by patients with pain, and for calculation of related quantitative variables. The system was tested in a pharmaceutical company-sponsored US study in over 500 chronic pain patients seen by primary care practitioners, and then seen by pain specialists. The hypothesis was that pain location would correlate with the pain type and the underlying cause of the pain. TMT's analysis established correlations between the pain diagram information and the underlying diagnosis and pain type (e.g., nociceptive or neuropathic) reported by the pain specialists. The present study extends these observations in a web-based setting, with particular emphasis on automated computer-generated visual pain patterns as diagnostic predictors.