Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 71555-313, Iran.
Research Center for Design and Fabrication of Advanced Electronic Devices, Shiraz University of Technology, Shiraz 71555-313, Iran.
ACS Appl Mater Interfaces. 2024 Sep 11;16(36):47973-47987. doi: 10.1021/acsami.4c06855. Epub 2024 Sep 3.
Owing to the correlation between acetone in human's exhaled breath (EB) and blood glucose, the development of EB acetone gas-sensing devices is important for early diagnosis of diabetes diseases. In this article, a noninvasive blood glucose detection device through acetone sensing in EB, based on an α-FeO-multiwalled carbon nanotube (MWCNT) nanocomposite, was successfully developed. Different amounts of α-FeO were added to the MWCNTs by a simple solution method. The optimized acetone gas sensor showed a response of 5.15 to 10 ppm acetone gas at 200 °C. Also, the fabricated sensor showed very good sensing properties even in an atmosphere with high relative humidity. Since the EB has high humidity, the proposed sensor is a promising device to exactly detect the amount of acetone in EB with high humidity. The sensor was powered by a 3200 mAh battery with the possibility of charging using mains electricity. To increase the reliability and calibration of the sensing device, a practical test was taken to detect acetone EB from 50 volunteers, and a deep learning algorithm (DLA) was used to detect the effect of various factors on the amount of acetone in each person's acetone EB. The proposed device with ±15 errors had almost 85% correct responses. Also, the proposed device had excellent response, short response time, good selectivity, and good repeatability, leading it to be a suitable candidate for noninvasive blood glucose sensing.
由于人体呼出的丙酮（EB）与血糖之间存在相关性，因此开发 EB 丙酮气体传感装置对于糖尿病疾病的早期诊断非常重要。本文成功开发了一种基于α-FeO-多壁碳纳米管（MWCNT）纳米复合材料的非侵入式通过 EB 中的丙酮感应来检测血糖的装置。通过简单的溶液法向 MWCNTs 中添加了不同量的α-FeO。优化后的丙酮气体传感器在 200°C 时对 5ppm 至 10ppm 丙酮气体的响应为 5.15。此外，即使在相对湿度较高的环境中，所制备的传感器也表现出非常好的传感性能。由于 EB 具有高湿度，因此所提出的传感器是一种很有前途的设备，可以精确检测高湿度 EB 中的丙酮含量。传感器由 3200mAh 电池供电，并且可以通过 mains 电力进行充电。为了提高传感设备的可靠性和校准，对 50 名志愿者的 EB 丙酮进行了实际测试，并使用深度学习算法（DLA）来检测各种因素对每个人的 EB 丙酮中丙酮含量的影响。该设备的误差在±15 以内，几乎有 85%的响应是正确的。此外，该设备具有出色的响应、短的响应时间、良好的选择性和良好的重复性，使其成为非侵入式血糖感测的合适候选者。
