Systems and Methods for Disease Detection Using Mobile Device

Point-of-care tests often rely on smartphone image methods for colorimetric analysis, however, the results of these methods are frequently difficult to reproduce or standardize. Unfortunately, the problem is aggravated by unpredictable image capture conditions, which pose a significant challenge when low limits of detection are needed. Application-specific smartphone attachments are utilized to standardize imaging conditions. However, there has recently been an interest in equipment-free point-of-care colorimetric analysis. Although improved output metrics and pre-processing methods have been developed, equipment-free imaging still has a high limit of detection and is, therefore, inappropriate for these quantitative tasks.

Researchers at FAU have developed a proprietary technology for video processing on smartphones. This novel technology includes a video processing method that synthesizes several images into a single output metric. Several image features are utilized to determine clarity and detail of the selected images. The resulting output values have a stronger correlation with laboratory methods and a lower standard error. Additionally, this technology only requires 20 seconds of video and can easily be integrated with related processing methods. This technology uses the saturation parameter of hue-saturation value colorpace to enable point-of-care diagnosis in the field. Through the analysis of over 10,000 images, the saturation method consistently outperforms current approaches under a wide range of operating field conditions. Performance improvement may be proven analytically via the mathematic relationship between the saturation method and existing techniques. Additionally, this technology does not require any light box or external equipment before imaging.