Literature DB >> 33635650

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

Sujay K Biswas1, Subhamoy Chatterjee2, Soumya Bandyopadhyay3, Shantimoy Kar4,5, Nirmal K Som6, Satadal Saha1,7,8, Suman Chakraborty3,4.   

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) (>11 g/dL) (specificity: 97.2%), mildly anemic (n = 55) (<11 g/dL) (sensitivity: 87.5%, specificity: 100%), and severely anemic (n = 9) (<7 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.

Entities:  

Keywords:  POC device; colorimetric detection; hemoglobin detection; paper-based sensors; smartphone app

Mesh:

Substances:

Year:  2021        PMID: 33635650     DOI: 10.1021/acssensors.0c02361

Source DB:  PubMed          Journal:  ACS Sens        ISSN: 2379-3694            Impact factor:   7.711


  2 in total

Review 1.  Metabolomics for exposure assessment and toxicity effects of occupational pollutants: current status and future perspectives.

Authors:  Fatemeh Dehghani; Saeed Yousefinejad; Douglas I Walker; Fariborz Omidi
Journal:  Metabolomics       Date:  2022-09-09       Impact factor: 4.747

Review 2.  Smartphone-Based Biosensor Devices for Healthcare: Technologies, Trends, and Adoption by End-Users.

Authors:  Rossana E Madrid; Fernando Ashur Ramallo; Daniela E Barraza; Roberto E Chaile
Journal:  Bioengineering (Basel)       Date:  2022-03-01
  2 in total

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