A User-Configurable Smartwatch as a Point-of-Care Testing Device for Electrochemical Biosensors

• Published in: IEEE sensors journal 2024-07, Vol.24 (13), p.20805-20812
• Main Authors: Raj, S Vineeth, Pradeep, Aarathi, Raveendran, Jeethu, Nair, Bipin G., Satheesh Babu, T. G., Suneesh, P. V.
• Format: Article
• Language: English
• Subjects: Amperometry; Analog to digital converters; Applications programs; Ascorbic acid; Biomarkers; Biomolecules; Biosensors; Electric potential; Electrical measurement; Electrodes; Glucose; High resolution; Mobile computing; Point of care testing; point-of-care testing (PoCT); Sensors; Smartphones; smartwatch; Smartwatches; Standard deviation; Testing; Uric acid; voltammetry; Wearable computers; wearable device; Wearable Health Monitoring Systems; Wristwatches
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2024.3397869

The article presents the development of a wristwatch as a configurable testing platform for personalized point-of-care testing (PoCT). The developed watch can perform voltammetry and amperometry in a wide operating range, thus making the system capable of detecting various bioanalytes. This overcomes a major limitation of the existing meters available in the market, where each sensor requires a dedicated meter. The user selects the desired biomolecule for quantification on the smartphone using the developed Android mobile application. The test parameters are transferred via Bluetooth, and the smartwatch is tuned to the chosen sensor. As a proof-of-concept, we have developed electrochemical biosensors for testing clinically significant biomolecules such as glucose, uric acid (UA), and ascorbic acid (AA), which was then interfaced with the smartwatch for the on-demand quantification. Using an analog-to-digital converter (ADC) with 12-bit resolution, the device demonstrated a high resolution of 0.732 mV. The smartwatch could overcome the limitation associated with the quantification of UA in the presence of AA by doing baseline subtraction, and the results show a low relative standard deviation of 4%. The glucose analysis was highly reproducible with a relative standard deviation of 4.95%, with a high resolution of 0.0217 mg dL-1, and the results could be obtained within 5 s. The results obtained using the smartwatch were in excellent conformity with those obtained from a laboratory electrochemical workstation. The key advantage of the device is that it can be easily configured to test any new biomarkers without any hardware change by over-the-air mobile application updates.