摘要
睡眠问题逐渐成为当今快节奏社会人们对生命健康的关注重点,由此本文提出了一套基于支持向量机的睡眠监测系统。该系统利用生物传感器,对心率和呼吸信号的实时监测,通过Wi-Fi的方式将数据传送入上位机,由设计好的机器学习算法,对睡眠呼吸暂停低通气综合征等进行判断,并搭配终端APP便于使用者跟踪病情。
Sleep problem has gradually become the focus of people’s life and health in today’s fast-paced society.Therefore,this paper proposes a sleep monitoring system based on Support Vector Machine.The system mainly uses biosensors to monitor heart rate and breathing signals in real time,and transmits data to the upper computer through Wi-Fi.The designed machine learning algorithm is used to judge sleep apnea-hypopnea syndrome.In order to facilitate the user to track the condition,it is also designed a terminal APP.
作者
钟佳良
易钢
ZHONG Jialiang;YI Gang(School of Informatics,Hunan University of Chinese Medicine,Changsha 410208,China)
出处
《智能计算机与应用》
2021年第8期56-60,共5页
Intelligent Computer and Applications
基金
湖南中医药大学电子科学与技术学科开放基金(2018DK05)。
关键词
支持向量机
睡眠监测
机器学习
support vector machine
sleep monitoring
machine learning
