Smartphone-Enabled Paper-Based Hemoglobin Sensor for Extreme Point-of-Care Diagnostics

Abstract

We report a simple, affordable (∼0.02 US $/test), rapid (within 5 min), and quantitative paper-based sensor integrated with smartphone application for on-spot detection of hemoglobin (Hgb) concentration using approximately 10 μL of finger-pricked blood. Quantitative analytical colorimetry is achieved via an Android-based application (Sens-Hb), integrating key operational steps of image acquisition, real-time analysis, and result dissemination. Further, feedback from the machine learning algorithm for adaptation of calibration data offers consistent dynamic improvement for precise predictions of the test results. Our study reveals a successful deployment of the extreme point-of-care test in rural settings where no infrastructural facilities for diagnostics are available. The Hgb test device is validated both in the controlled laboratory environment (n = 200) and on the field experiments (n = 142) executed in four different Indian villages. Validation results are well correlated with the pathological gold standard results (r = 0.9583) with high sensitivity and specificity for the healthy (n = 136) (GT11 g/dL) (specificity: 97.2%), mildly anemic (n = 55) (LT11 g/dL) (sensitivity: 87.5%, specificity: 100%), and severely anemic (n = 9) (LT7 g/dL) (sensitivity: 100%, specificity: 100%) samples. Results from field trials reveal that only below 5% cases of the results are interpreted erroneously by classifying mildly anemic patients as healthy ones. On-field deployment has unveiled the test kit to be extremely user friendly that can be handled by minimally trained frontline workers for catering the needs of the underserved communities.