@文章{信息:doi/10.2196/38664，作者="Valero, Maria和Pola, Priyanka和Falaiye, Oluwaseyi和Ingram, Katherine H和Zhao, Liang和Shahriar, Hossain和Ahamed, Sheikh Iqbal"，标题="开发一种无创血糖监测系统原型:初步研究"，期刊="JMIR Form Res"，年="2022"，月="Aug"，日="26"，卷="6"，号="8"，页="e38664"，关键词="糖尿病;深度学习;机器学习;葡萄糖浓度;非侵入性监测;光学传感器;背景:糖尿病是一种以高血糖水平为特征的严重疾病，其原因是胰岛素调节异常。糖尿病可以通过体育锻炼和饮食调整来控制，需要仔细监测血糖浓度。血糖浓度通常是全天通过分析从手指刺取的血液样本来监测的，使用的是市售的血糖计。然而，这个过程是侵入性的和痛苦的，并导致感染的风险。 Therefore, there is an urgent need for noninvasive, inexpensive, novel platforms for continuous blood sugar monitoring. Objective: Our study aimed to describe a pilot test to test the accuracy of a noninvasive glucose monitoring prototype that uses laser technology based on near-infrared spectroscopy. Methods: Our system is based on Raspberry Pi, a portable camera (Raspberry Pi camera), and a visible light laser. The Raspberry Pi camera captures a set of images when a visible light laser passes through skin tissue. The glucose concentration is estimated by an artificial neural network model using the absorption and scattering of light in the skin tissue. This prototype was developed using TensorFlow, Keras, and Python code. A pilot study was run with 8 volunteers that used the prototype on their fingers and ears. Blood glucose values obtained by the prototype were compared with commercially available glucometers to estimate accuracy. Results: When using images from the finger, the accuracy of the prototype is 79{\%}. Taken from the ear, the accuracy is attenuated to 62{\%}. Though the current data set is limited, these results are encouraging. However, three main limitations need to be addressed in future studies of the prototype: (1) increase the size of the database to improve the robustness of the artificial neural network model; (2) analyze the impact of external factors such as skin color, skin thickness, and ambient temperature in the current prototype; and (3) improve the prototype enclosure to make it suitable for easy finger and ear placement. Conclusions: Our pilot study demonstrates that blood glucose concentration can be estimated using a small hardware prototype that uses infrared images of human tissue. Although more studies need to be conducted to overcome limitations, this pilot study shows that an affordable device can be used to avoid the use of blood and multiple finger pricks for blood glucose monitoring in the diabetic population. ", issn="2561-326X", doi="10.2196/38664", url="https://formative.www.mybigtv.com/2022/8/e38664", url="https://doi.org/10.2196/38664", url="http://www.ncbi.nlm.nih.gov/pubmed/36018623" }