Continuous Glycemic Monitoring Enabled by A Wi-Fi Energy-Harvesting Wearable Sweat-Sensing Patch
Creators
- 1. Koc Univ, Dept Biomed Sci & Engn, Rumelifeneri Yolu, TR-34450 Istanbul, Turkiye
- 2. Koc Univ, Dept Mech Engn, Rumelifeneri Yolu, TR-34450 Istanbul, Turkiye
- 3. Koc Univ, Dept Elect & Elect Engn, Rumelifeneri Yolu, TR-34450 Istanbul, Turkiye
- 4. Istanbul Tech Univ, Dept Elect & Commun Engn, 18 Maslak, TR-34469 Istanbul, Turkiye
Description
Continuous monitoring of multiple physiological parameters, such as glucose levels, temperature, and heart rate variability (HRV) is crucial for effective diabetes management and mitigating the risks associated with hypoglycemic events. These events often occur without apparent symptoms, posing a challenge for diabetic patients in managing their condition. Therefore, a non-invasive wearable device capable of continuously measuring multiple body signals to predict hypoglycemic events would be highly beneficial. In this study, a wearable patch that continuously measures glucose, temperature, and HRV is presented. The device uses a novel power harvesting system to convert radiofrequency (RF) signals with the frequency of 2.45 GHz to direct current (DC) signals to extend the battery life for further continuous monitoring. The patch is small and has a conformal structure that can easily fit onto different body parts. The screen-printed glucose sensor demonstrates a sensitivity of 10.3 nA cm-2 mu M-1, a limit of detection (LOD) of 8.9 mu M, and a limit of quantification (LOQ) of 27 mu M. The device employs a photoplethysmography (PPG) module with a peak-finding algorithm to calculate the HRV values. In vivo experiments demonstrate the validation of the device's proper operation in glucose, HRV, and temperature measurement.
This study introduces a wearable patch for diabetes management, employing a unique Wi-Fi energy harvesting system for extended battery life. The device's conformal structure enables effortless placement on the body, providing continuous monitoring of glucose, HRV, and temperature. The platform presents a non-invasive physiological monitoring approach that enhances diabetes care by offering real-time data in a compact and efficient design. image
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