Smartphone-based quantitative measurements on holographic sensors.

Abstract

The research reported herein integrates a generic holographic sensor platform and a smartphone-based colour quantification algorithm in order to standardise and improve the determination of the concentration of analytes of interest. The utility of this approach has been exemplified by analysing the replay colour of the captured image of a holographic pH sensor in near real-time. Personalised image encryption followed by a wavelet-based image compression method were applied to secure the image transfer across a bandwidth-limited network to the cloud. The decrypted and decompressed image was processed through four principal steps: Recognition of the hologram in the image with a complex background using a template-based approach, conversion of device-dependent RGB values to device-independent CIEXYZ values using a polynomial model of the camera and computation of the CIEL*a*b* values, use of the colour coordinates of the captured image to segment the image, select the appropriate colour descriptors and, ultimately, locate the region of interest (ROI), i.e. the hologram in this case, and finally, application of a machine learning-based algorithm to correlate the colour coordinates of the ROI to the analyte concentration. Integrating holographic sensors and the colour image processing algorithm potentially offers a cost-effective platform for the remote monitoring of analytes in real time in readily accessible body fluids by minimally trained individuals.