光容积图
可穿戴计算机
持续监测
连续血糖监测
极限(数学)
计算机科学
信号(编程语言)
生物医学工程
心率变异性
检出限
灵敏度(控制系统)
实时计算
糖尿病
电子工程
嵌入式系统
医学
血糖性
无线
心率
数学
工程类
内科学
电信
数学分析
程序设计语言
运营管理
统计
血压
内分泌学
作者
Fariborz Mirlou,Taher Abbasiasl,Hakan Ürey,Emin Istif,Muhammad Junaid Akhtar,Cengiz Cakır,Levent Beker
标识
DOI:10.1002/admt.202301583
摘要
Abstract 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 µM −1 , a limit of detection (LOD) of 8.9 µM, and a limit of quantification (LOQ) of 27 µM. 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.
科研通智能强力驱动
Strongly Powered by AbleSci AI