基于自适应滤波的可穿戴式心电信号检测系统
|
摘要
为了检测公安、消防官兵等高危职业人群的心电信号,以胸带作为穿戴载体,设计一款可穿戴式无线心电检测系统,在智能手机上实现心电、心率的实时传输与显示。考虑到警员日常的活动,基于自适应滤波器原理,将三轴加速度传感器作为参考信号,对比两种自适应滤波算法滤出运动伪迹(Motion Artifact,MA)后的输出波形。结果表明,采用归一化的最小均方算法(Normalized Least Mean Square,NLMS)的自适应滤波器输出心电信号基线平稳且R波定位准确性达99%以上。在正常的人体活动中实时测量的心率值误差在4%以内,心率测量精度较高。
In this paper, the researchers aim to monitor electrocardiogram( ECG) signal of the high-risk occupational people such as police, fire fighters and so on. By using chest strap, a wearable wireless system of real-time ECG monitoring was designed. The real-time transmission and display of ECG and heart rate is implemented on the smart phone. Considering of the routine activities of the policemen and basing on the theory of adaptive filter, the reference signal is obtained by 3D accelerometer and waveforms after filtering motion artifact( MA) by using two kinds of adaptive algorithms are compared in this paper. The result shows that the baseline of ECG waveforms from adaptive filter using normalized least mean square( NLMS) is more stable and the accuracy of location of ECG ' R wave can reach above 99 % in most case. The error of heat rate is within 4 % in daily routine of people. The measurement accuracy of the system is high.
In this paper, the researchers aim to monitor electrocardiogram( ECG) signal of the high-risk occupational people such as police, fire fighters and so on. By using chest strap, a wearable wireless system of real-time ECG monitoring was designed. The real-time transmission and display of ECG and heart rate is implemented on the smart phone. Considering of the routine activities of the policemen and basing on the theory of adaptive filter, the reference signal is obtained by 3D accelerometer and waveforms after filtering motion artifact( MA) by using two kinds of adaptive algorithms are compared in this paper. The result shows that the baseline of ECG waveforms from adaptive filter using normalized least mean square( NLMS) is more stable and the accuracy of location of ECG ' R wave can reach above 99 % in most case. The error of heat rate is within 4 % in daily routine of people. The measurement accuracy of the system is high.
引文
[1]袁国礼.5年来公安民警因公牺牲2129人[N].京华时报,2015-04-06(006).
[2]陈颖昭,高跃明,甘振华,等.基于STM32的便携式家用心电检测仪的设计[J].电子技术应用,2013,39(9):18-20.
[3]JAIN S K,BHAUMIK B.An ultra low power ECG signal processor design for cardiovascular disease detection[C]//International Conference of the IEEE Engineering in Medicine&Biology Society.Conf Proc IEEE Eng Med Biol Soc,2015:857.
[4]CHI Y M,JUNG T P,CAUWENBERGHS G.Dry-Contact and noncontact biopotential electrodes:methodological review[J].IEEE Reviews in Biomedical Engineering,1937,3:106-119.
[5]THAKOR N V,ZHU Y S.Applications of adaptive filtering to ECG analysis:noise cancellation and arrhythmia detection[J].IEEE Transactions on Biomedical Engineering,1991,38(8):785.
[6]TOMPKINS W J.Biomedical digital signal processing[M].Prentice Hall,1993.
[7]汪家旺,吴玲燕,杨涛,等.几种去心电基线漂移算法的实现和比较[J].中国医疗器械信息,2008,14(6):30-33.
[8]刘晓庆,熊晓燕.自适应滤波在噪声抵消中的应用[J].科技情报开发与经济,2007,17(11):208-209.
[9]LEE W C,YANG Y S O,KE T C,et al.Adaptive reduction of motion artifact in a portable ECG system[C]//Sensors.IEEE,2010:704-707.
[10]ROMERO I,GENG D,BERSET T.Adaptive filtering in ECG denoising:A comparative study[J].2012,30(1):45-48.
[11]LAI D,ZHANG F,WANG C.A real-time QRS complex detection algorithm based on differential threshold method[C]//IEEE International Conference on Digital Signal Processing.IEEE,2015:129-133.
[2]陈颖昭,高跃明,甘振华,等.基于STM32的便携式家用心电检测仪的设计[J].电子技术应用,2013,39(9):18-20.
[3]JAIN S K,BHAUMIK B.An ultra low power ECG signal processor design for cardiovascular disease detection[C]//International Conference of the IEEE Engineering in Medicine&Biology Society.Conf Proc IEEE Eng Med Biol Soc,2015:857.
[4]CHI Y M,JUNG T P,CAUWENBERGHS G.Dry-Contact and noncontact biopotential electrodes:methodological review[J].IEEE Reviews in Biomedical Engineering,1937,3:106-119.
[5]THAKOR N V,ZHU Y S.Applications of adaptive filtering to ECG analysis:noise cancellation and arrhythmia detection[J].IEEE Transactions on Biomedical Engineering,1991,38(8):785.
[6]TOMPKINS W J.Biomedical digital signal processing[M].Prentice Hall,1993.
[7]汪家旺,吴玲燕,杨涛,等.几种去心电基线漂移算法的实现和比较[J].中国医疗器械信息,2008,14(6):30-33.
[8]刘晓庆,熊晓燕.自适应滤波在噪声抵消中的应用[J].科技情报开发与经济,2007,17(11):208-209.
[9]LEE W C,YANG Y S O,KE T C,et al.Adaptive reduction of motion artifact in a portable ECG system[C]//Sensors.IEEE,2010:704-707.
[10]ROMERO I,GENG D,BERSET T.Adaptive filtering in ECG denoising:A comparative study[J].2012,30(1):45-48.
[11]LAI D,ZHANG F,WANG C.A real-time QRS complex detection algorithm based on differential threshold method[C]//IEEE International Conference on Digital Signal Processing.IEEE,2015:129-133.