可穿戴血氧芯片的抗运动干扰算法与电路设计
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摘要
针对可穿戴血氧芯片因运动干扰而使准确度受限的问题,提出一种基于加速度传感器的自适应抗运动干扰算法并进行了电路设计.根据三轴加速度信号判断运动幅度,当运动较微弱时,采用自适应滤波(AF)算法消除运动干扰,提取特征参数,计算血氧饱和度;当运动较强烈时,采用改进型离散饱和度变换(IDST)算法,比较不同离散饱和度下参考信号与加速度信号的相关性,相关系数最大时的离散饱和度即为血氧饱和度.所设计的芯片采用SMIC 180 nm工艺实现,算法电路的测量误差在2%以内,整个抗运动干扰模块的电路面积为0.31 mm2,最高时钟频率可达到56.4 MHz,满足可穿戴应用的需求.
Aiming at the problem that the accuracy of wearable blood oxygen chip is limited by motion interference,an adaptive anti-motion interference algorithm based on the acceleration sensor was proposed and the circuit was designed.According to the triaxial acceleration signal,the motion amplitude was determined.When the motion was weak,the adaptive filtering algorithm was utilized to eliminate the motion interference,the characteristic parameters were extracted,and the oxygen saturation was calculated.When the motion was strong,the improved discrete saturation transformation algorithm was adopted to compare the correlation between the reference signal and the acceleration signal under different discrete saturations.When the correlation coefficient was the maximum,the discrete saturation was the blood oxygen saturation.The designed chip was implemented in the SMIC 180 nm process and the measurement error is within 2%.The anti-motion interference circuit occupies an area of 0.31 mm2 and the frequency can reach up to 56.4 MHz,which could meet the requirements of wearable applications.
Aiming at the problem that the accuracy of wearable blood oxygen chip is limited by motion interference,an adaptive anti-motion interference algorithm based on the acceleration sensor was proposed and the circuit was designed.According to the triaxial acceleration signal,the motion amplitude was determined.When the motion was weak,the adaptive filtering algorithm was utilized to eliminate the motion interference,the characteristic parameters were extracted,and the oxygen saturation was calculated.When the motion was strong,the improved discrete saturation transformation algorithm was adopted to compare the correlation between the reference signal and the acceleration signal under different discrete saturations.When the correlation coefficient was the maximum,the discrete saturation was the blood oxygen saturation.The designed chip was implemented in the SMIC 180 nm process and the measurement error is within 2%.The anti-motion interference circuit occupies an area of 0.31 mm2 and the frequency can reach up to 56.4 MHz,which could meet the requirements of wearable applications.
引文
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[14]黎圣峰,庞宇,高小鹏,等.便携式血氧信号检测装置设计[J].传感器与微系统,2017,36(3):110-112.
[2]刘杨.基于Cortex-M3的无线脉搏血氧饱和度监测系统研究[D].上海:上海交通大学图书馆,2013.
[3]YAN Y S,ZHANG Y T.An efficient motion-resistant method for wearable pulse oximeter[J].IEEE Transactions on Information Technology in Biomedicine,2008,12(3):399-405.
[4]RAM M R,MADHAV K V,KRISHNA E H,et al.ICA-based improved DTCWT technique for MAreduction in PPG signals with restored respiratory information[J].IEEE Transactions on Instrumentation&Measurement,2013,62(10):2639-2651.
[5]YE Y,CHENG Y,HE W,et al.Combining nonlinear adaptive filtering and signal decomposition for motion artifact removal in wearable photoplethysmography[J].IEEE Sensors Journal,2016,16(19):7133-7141.
[6]WIJSHOFF R W,MISCHI M,AARTS R M.Reduction of periodic motion artifacts in photoplethysmography[J].IEEE Transactions on Biomedical Engineering,2017,64(1):196-207.
[7]RAGHURAM M,SIVANI K,REDDY K A.Reduction of motion artifacts from Pulse oximeter's PPG signals using MSICA[C]//Proc of 2016 International Conference on Control,Instrumentation,Communication and Computational Technologies.Kumaracoil:IEEE,2016:491-494.
[8]龚渝顺.穿戴式抗运动干扰血氧饱和度监测技术研究[D].重庆:第三军医大学图书馆,2012.
[9]杜勇.数字滤波器的MATLAB与FPGA实现:Altera/Verilog版[M].北京:电子工业出版社,2015.
[10]PREEJITH S P,RAVINDRANA S,HAJARER,et al.Awrist worn SpO2 monitor with custom finger probe for motion artifact removal[C]//Proc of Conference on Engineering in Medicine and Biology Society.Orlando:IEEE,2016:5777-5780.
[11]KUNCHON S,DESUDCHIT T,CHINRUNGRUENGC.Comparative evaluation of adaptive filters in motion artifact cancellation for pulse oximetry[C]//Proc of 5th International Colloquium on Signal Processing&Its Applications,2009.Kuala Lumpur:IEEE,2009:307-311.
[12]ANDRUSCHENKO S,TIMM U,KRAITL J,et al.Motion-tolerant pulse oximetry based on the wavelet transformation and adaptive peak filtering[C]//Proc of2011 1st Middle East Conference on Biomedical Engineering.Sharjah:IEEE,2011:324-327.
[13]RAM M R,MADHAV K V,KRISHNA E H,et al.Anovel approach for motion artifact reduction in PPGsignals based on AS-LMS adaptive filter[J].IEEE Transactions on Instrumentation&Measurement,2012,61(5):1445-1457.
[14]黎圣峰,庞宇,高小鹏,等.便携式血氧信号检测装置设计[J].传感器与微系统,2017,36(3):110-112.