OBJECTIVE: Traditional biochemical testing is limited by fixed sites, specialized equipment, and long turnaround times, severely reducing patient compliance with regular monitoring. To address the demands of routine lipid management, this study developed a simple, rapid and low-cost method for Total Cholesterol (TC) detection that enables high-throughput parallel processing of multiple samples. METHOD: This method synchronously identifies the RGB values of multiple pixels in an image through a mobile phone camera. All experiment procedures were strictly followed according to the guidelines of the National Committee for Clinical Laboratory Standards. Multiple performance indicators of the device were evaluated, and the results were compared for consistency with those from a fully automated clinical biochemical analyzer. RESULTS: The TC concentration showed the strongest quantitative correlation with the green channel intensity (G-value). This method was preliminarily validated on a prototype smartphone. Both its detection precision and accuracy met clinical standards. The method demonstrated satisfactory linearity over 1.19-8.49 mmoL/L, and its analytical results for the limited samples in this study were highly consistent with those obtained from the automatic biochemical analyzer. CONCLUSIONS: Integrating low cost and high efficiency, this novel method has great application potential in indoor settings within primary healthcare institutions and resource-limited remote areas.
Guo et al. (2026) studied this question.