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Image processing algorithms and automated measurements were validated by performing tests on digital hand models, rigid plastic hand models, and real human hands and feet to determine accuracy and reproducibility compared to conventional measurement tools such as calipers, rulers, and goniometers. The mobile application was able to provide finger joint width measurements with accuracy better than 0.34 (±0.25) millimeters. Joint angulation measurement accuracy was better than 0.50 (±0.45) degrees. The automatically calculated foot length accuracy was 1.20 (±1.27) millimeters and the foot width accuracy was 1.93 (±1.92) millimeters. Hallux valgus angle (used in assessing bunions) accuracy was 1.30 (±1.29) degrees. Arch height index (AHI) measurements had an accuracy of 0.02 (±0.01).
Combined with in-app documentation of symptoms, treatment, and lifestyle factors, the anatomical feature measurements can be used by both healthcare professionals and manufacturers. Applications include: diagnosing hand osteoarthritis; providing custom finger splint measurements; providing compression glove measurements for burn and lymphedema patients; determining foot dimensions for custom shoe sizing, insoles, orthotics, or foot splints; and assessing arch height index and bunion treatment effectiveness.
Automated facial acne assessment was validated by performing tests on images of 60 digital human models and 10 real human face images. The application was able to identify 92% of acne lesions within five facial ROIs. The classification accuracy for separating papules from pustules was 98%.
Combined with in-app documentation of treatment, lifestyle factors, and automated facial acne assessment, the app can be used in both cosmetic and clinical dermatology. It allows users to quantitatively self-measure acne severity and treatment efficacy on an ongoing basis to help them manage their chronic facial acne.
In vivo fluorescence spectroscopy of the gastrointestinal tract under multiple wavelength excitation
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