光容积图
可穿戴计算机
计算机科学
实时计算
小波变换
软件
信号处理
持续监测
远程病人监护
可穿戴技术
电子工程
计算机硬件
嵌入式系统
小波
人工智能
无线
数字信号处理
电信
工程类
医学
放射科
运营管理
程序设计语言
作者
Huirong Tao,Jindong Zhang
出处
期刊:AOPC 2020: Optical Sensing and Imaging Technology
日期:2021-11-24
卷期号:: 172-172
摘要
The development of photoelectric detection technology has promoted the development of the smart wearable market. Wristband heart rate monitoring equipment has become a familiar product to the public. However, according to related research tests, there is a large error between the heart rate monitoring data of the wristband device and the real data during exercise. This article proposes a dual-spectrum headband health monitoring system solution with ultra-small size, ultra-low power consumption, and high integration for the above problems, which converts the monitoring part from the common wrist to the forehead. The integrated monitoring system is as small as 11.8mm*5mm. Ultra-low power consumption design effectively improves the battery life of smart wearable devices. The dual-spectrum monitoring system adopts the reflected photoelectric pulse wave detection method, and integrates red light and infrared light to form a dual LED. The heart rate value is calculated through the collected photoplethysmography (PPG) signal. In the software algorithm processing, the Mallat algorithm of wavelet transform is first used for software filtering, and then the pulse wave signal characteristic points are identified. By comparing the system designed in this paper with the fluke blood oxygen simulator, the results show that the heart rate measurement error of the system reaches plus or minus 1% + 1 beat/min. In addition, the dual-spectrum health monitoring system can also use "cloud" big data analysis technology to provide more health information. It can also be used for the management of chronic cardiovascular diseases.
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