摘要
为了提升睡眠分期系统的准确率和易用性,采用了无线心电贴和桌上型心电处理设备的系统架构,并设计了一款低功耗心电芯片.睡眠分期算法基于单通道ECG信号的RRI和HRV的六个衍生特征训练HMM并作为分类器,采用了EEMD算法对RRI序列标准化.为了提升心电贴的续航时间,采用系统级和电路级的低功耗手段.测试表明,系统平均分类准确率达到93.2%.心电芯片在SMIC 0.18μm工艺下面积仅为1.6 mm^2,平均功耗1.3 mW,100 mAh的电池供电心电贴能够工作70小时以上.
To improve accuracy and convenience of sleep-staging system, a structure with desktop ECG harvest center and wireless ECG paste which integrates special ASIC is presented in this paper. The sleep-staging algorithm is based on six features which are derived from RRI and HRV of single channel ECG, and these features are fed to HMM as a classifier. In which, EEMD algorithm is used to standardize RRI sequence. To improve battery life of the ECG paste, low power design method on system level and circuit level are used. The test results show that the classification accuracy of sleep-staging system is 93.2% on an average. The ECG chip occupies only 1.6 mm^2 on SMIC 0.18 μm process and average power consumption is only 1.3 mW, which means 70 h continuously work under a 100 mAh battery for the ECG pastes.
作者
冯晓星
唐飞
李琰
俞航
葛彬杰
FENG Xiao-xing;TANG Fei;LI Yan;YU Hang;GE Bin-jie(College of Computer Science & Software Engineering,Shenzhen University,Shenzhen 518060,China;Shenzhen Institute of Information Technology,Shenzhen 518029,China)
出处
《微电子学与计算机》
北大核心
2019年第4期23-28,共6页
Microelectronics & Computer
基金
国家自然基金(61471245
U1201256)
广东省协同创新基金(2014B090901031)
深圳产业发展基金(JCYJ20160308095019383
JSGG20150529160945187)
