NAILS: Normalized Artificial Intelligence Labeling Sensor for Self-Care Health.
Journal:
Sensors (Basel, Switzerland)
PMID:
39771732
Abstract
Visual examination of nails can reflect human health status. Diseases such as nutritive imbalances and skin diseases can be identified by looking at the colors around the plate part of the nails. We present the AI-based NAILS method to detect fingernails through segmentation and labeling. The NAILS leverages a pre-trained Convolutional Neural Network model to segment and label fingernail regions from fingernail images, normalizing RGB values to monitor tiny color changes via a GUI and the use of an HD webcam in real time. The use of normalized RGB values combined with AI-based segmentation for real-time health monitoring is novel and innovative. The NAILS algorithm could be used to self-extract and archive primary signs of diseases in humans, especially in rural areas or when other testing may be not available.