Human physiological(biological)systems function in such a way that their complexity requires mathematical analysis.The functioning of the brain,heart and other parts are so complex to be easily comprehended.Under cond...Human physiological(biological)systems function in such a way that their complexity requires mathematical analysis.The functioning of the brain,heart and other parts are so complex to be easily comprehended.Under conditions of rest or work,the temporal distances of successive heartbeats are subject to fluctuations,thereby forming the basis of Heart Rate Variability(HRV).In normal conditions,the human is persistently exposed to highly changing and dynamic situational demands.With these demands in mind,HRV can,therefore,be considered as the human organism’s ability to cope with and adapt to continuous situational requirements,both physiologically and emotionally.Fast Fourier Transform(FFT)is used in various physiological signal processing,such as heart rate variability.FFT allows a spectral analysis of HRV and is great help in HRV analysis and interpretation.展开更多
It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present...It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present a multi-ray propagation model for UWB signal,which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces,A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment.This model enables replication of time-varying multipath profiles due to the displacement of a human chest.Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate.The analytical framework can serve as a basis in the planning and evaluation of future rheasurement programs.We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.展开更多
Early detection of sudden cardiac death may be used for surviving the life of cardiac patients. In this paper we have investigated an algorithm to detect and predict sudden cardiac death, by processing of heart rate v...Early detection of sudden cardiac death may be used for surviving the life of cardiac patients. In this paper we have investigated an algorithm to detect and predict sudden cardiac death, by processing of heart rate variability signal through the classical and time-frequency methods. At first, one minute of ECG signals, just before the cardiac death event are extracted and used to compute heart rate variability (HRV) signal. Five features in time domain and four features in frequency domain are extracted from the HRV signal and used as classical linear features. Then the Wigner Ville transform is applied to the HRV signal, and 11 extra features in the time-frequency (TF) domain are obtained. In order to improve the performance of classification, the principal component analysis (PCA) is applied to the obtained features vector. Finally a neural network classifier is applied to the reduced features. The obtained results show that the TF method can classify normal and SCD subjects, more efficiently than the classical methods. A MIT-BIH ECG database was used to evaluate the proposed method. The proposed method was implemented using MLP classifier and had 74.36% and 99.16% correct detection rate (accuracy) for classical features and TF method, respectively. Also, the accuracy of the KNN classifier were 73.87% and 96.04%.展开更多
Wavelet forced de-noising algorithm is suitable for denoising of unsteady drilling fluid pulse signal, including baseline drift rectification and two-stage de-noising processing of frame synchronization signal and ins...Wavelet forced de-noising algorithm is suitable for denoising of unsteady drilling fluid pulse signal, including baseline drift rectification and two-stage de-noising processing of frame synchronization signal and instruction signal. Two-stage de-noising processing can reduce the impact of baseline drift and determine automatic peak detection threshold range for signal recognition by distinguishing different features of frame synchronization pulse and instruction pulse. Rising and falling edge relative protruding threshold is defined for peak detection in signal recognition, which can make full use of the degree of the signal peak change and detect peaks flexibly with rising and falling edge relative protruding threshold combination. A synchronous decoding method was designed to reduce position uncertainty of the frame synchronization pulse and eliminate the accumulative error of time base drift, which determines the first instruction pulse position according to position of the frame synchronization pulse and decodes subsequent instruction pulse by taking current instruction pulse as new bit synchronization pulse. Special tool software was developed to tune algorithm parameters, which has a decoding success rate of about 95% for the universal coded signals. For the special coded signals with check byte, decoding success rate using the automatic threshold adjustment algorithm is as high as 99%.展开更多
心率和血氧饱和度是反映人体健康状况极其重要的生理指标.近年来,基于成像式光电容积描记技术(imaging photoplethysmography,IPPG)的非接触式心率和血氧饱和度检测方法因为其方便快捷且受约束较少等优点开始逐步成为研究热点.主要工作...心率和血氧饱和度是反映人体健康状况极其重要的生理指标.近年来,基于成像式光电容积描记技术(imaging photoplethysmography,IPPG)的非接触式心率和血氧饱和度检测方法因为其方便快捷且受约束较少等优点开始逐步成为研究热点.主要工作如下:首先,介绍了非接触式检测方法的背景和研究意义;其次,从目标区域检测和感兴趣区域(region of interest,ROI)选取两个方面总结并点明其研究现状以及未来改进方向;再次,从传统方法、信号处理结合深度学习方法以及端到端方法3个方面对心率和血氧饱和度检测方法进行了总结,并梳理了深度学习方法所使用的数据集以及在各个数据集中所展现的检测效果;最后,指出该领域所存在的亟待解决的问题以及未来的研究方向.展开更多
研究了水声图像高速传输信号处理方法,它包括两个方面,一方面是水声相干通信信号处理方法,其中:(1)多普勒频移补偿,在数据包的前后两端插入已知线性调频(Chirp)信号,拷贝相关后求互相关,估计相对多普勒平均频移。在自适应判决反馈均衡...研究了水声图像高速传输信号处理方法,它包括两个方面,一方面是水声相干通信信号处理方法,其中:(1)多普勒频移补偿,在数据包的前后两端插入已知线性调频(Chirp)信号,拷贝相关后求互相关,估计相对多普勒平均频移。在自适应判决反馈均衡器中加上自适应相位补偿器,采用快速自优化最小均方(LMS)算法,与其对应的速度容限优于常用的二阶锁相环相位补偿器的。两种补偿方法联合工作时,性能优良。(2)带有分集合并器的自适应判决反馈均衡器的算法是快速自优化的LMS算法,计算量小,性能优良。(3)自适应判决反馈均衡器与Turbo-网格编码调制(TCM)译码器级连、迭代算法。研究了基于软输出维特比(SOVA)方法的新型的比特-符号转换器,用它时误比特率(BER)比常规编码、映射方法的近似小2个数量级。另一方面是抗误码的图像压缩方法。本文基于数字小波变换和定长编码方法,研究了声图像的压缩。它包括:(1)选用CDF9/7小波进行小波变换。(2)对小波系数子带能量进行统计分析,三层小波分解是合适的。(3)对不同能量的子带采用不同的量化步长。(4)采用定长编码算法。结果表明声图像压缩比特率为0.85。当BER小于10^(-3)时,图像质量完好。当BER小于10^(-2)时,图像中出现少量小黑白点。在上述基础上研制了水声通信机,频带为(7.5～12.5)kHz,接收声呐阵为8基元等距线阵,信号为QPSK和8PSK。在中国千岛湖进行了湖试,采用SOVA硬迭代算法,达到了低BER。传输一幅256×256×8的声图需时约7s。传输距离与传输速率之积为55 km kbps。展开更多
文摘Human physiological(biological)systems function in such a way that their complexity requires mathematical analysis.The functioning of the brain,heart and other parts are so complex to be easily comprehended.Under conditions of rest or work,the temporal distances of successive heartbeats are subject to fluctuations,thereby forming the basis of Heart Rate Variability(HRV).In normal conditions,the human is persistently exposed to highly changing and dynamic situational demands.With these demands in mind,HRV can,therefore,be considered as the human organism’s ability to cope with and adapt to continuous situational requirements,both physiologically and emotionally.Fast Fourier Transform(FFT)is used in various physiological signal processing,such as heart rate variability.FFT allows a spectral analysis of HRV and is great help in HRV analysis and interpretation.
文摘It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present a multi-ray propagation model for UWB signal,which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces,A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment.This model enables replication of time-varying multipath profiles due to the displacement of a human chest.Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate.The analytical framework can serve as a basis in the planning and evaluation of future rheasurement programs.We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.
文摘Early detection of sudden cardiac death may be used for surviving the life of cardiac patients. In this paper we have investigated an algorithm to detect and predict sudden cardiac death, by processing of heart rate variability signal through the classical and time-frequency methods. At first, one minute of ECG signals, just before the cardiac death event are extracted and used to compute heart rate variability (HRV) signal. Five features in time domain and four features in frequency domain are extracted from the HRV signal and used as classical linear features. Then the Wigner Ville transform is applied to the HRV signal, and 11 extra features in the time-frequency (TF) domain are obtained. In order to improve the performance of classification, the principal component analysis (PCA) is applied to the obtained features vector. Finally a neural network classifier is applied to the reduced features. The obtained results show that the TF method can classify normal and SCD subjects, more efficiently than the classical methods. A MIT-BIH ECG database was used to evaluate the proposed method. The proposed method was implemented using MLP classifier and had 74.36% and 99.16% correct detection rate (accuracy) for classical features and TF method, respectively. Also, the accuracy of the KNN classifier were 73.87% and 96.04%.
基金Supported by the China National Science and Technology Major Project(2016ZX05020005-001)
文摘Wavelet forced de-noising algorithm is suitable for denoising of unsteady drilling fluid pulse signal, including baseline drift rectification and two-stage de-noising processing of frame synchronization signal and instruction signal. Two-stage de-noising processing can reduce the impact of baseline drift and determine automatic peak detection threshold range for signal recognition by distinguishing different features of frame synchronization pulse and instruction pulse. Rising and falling edge relative protruding threshold is defined for peak detection in signal recognition, which can make full use of the degree of the signal peak change and detect peaks flexibly with rising and falling edge relative protruding threshold combination. A synchronous decoding method was designed to reduce position uncertainty of the frame synchronization pulse and eliminate the accumulative error of time base drift, which determines the first instruction pulse position according to position of the frame synchronization pulse and decodes subsequent instruction pulse by taking current instruction pulse as new bit synchronization pulse. Special tool software was developed to tune algorithm parameters, which has a decoding success rate of about 95% for the universal coded signals. For the special coded signals with check byte, decoding success rate using the automatic threshold adjustment algorithm is as high as 99%.
文摘心率和血氧饱和度是反映人体健康状况极其重要的生理指标.近年来,基于成像式光电容积描记技术(imaging photoplethysmography,IPPG)的非接触式心率和血氧饱和度检测方法因为其方便快捷且受约束较少等优点开始逐步成为研究热点.主要工作如下:首先,介绍了非接触式检测方法的背景和研究意义;其次,从目标区域检测和感兴趣区域(region of interest,ROI)选取两个方面总结并点明其研究现状以及未来改进方向;再次,从传统方法、信号处理结合深度学习方法以及端到端方法3个方面对心率和血氧饱和度检测方法进行了总结,并梳理了深度学习方法所使用的数据集以及在各个数据集中所展现的检测效果;最后,指出该领域所存在的亟待解决的问题以及未来的研究方向.
文摘研究了水声图像高速传输信号处理方法,它包括两个方面,一方面是水声相干通信信号处理方法,其中:(1)多普勒频移补偿,在数据包的前后两端插入已知线性调频(Chirp)信号,拷贝相关后求互相关,估计相对多普勒平均频移。在自适应判决反馈均衡器中加上自适应相位补偿器,采用快速自优化最小均方(LMS)算法,与其对应的速度容限优于常用的二阶锁相环相位补偿器的。两种补偿方法联合工作时,性能优良。(2)带有分集合并器的自适应判决反馈均衡器的算法是快速自优化的LMS算法,计算量小,性能优良。(3)自适应判决反馈均衡器与Turbo-网格编码调制(TCM)译码器级连、迭代算法。研究了基于软输出维特比(SOVA)方法的新型的比特-符号转换器,用它时误比特率(BER)比常规编码、映射方法的近似小2个数量级。另一方面是抗误码的图像压缩方法。本文基于数字小波变换和定长编码方法,研究了声图像的压缩。它包括:(1)选用CDF9/7小波进行小波变换。(2)对小波系数子带能量进行统计分析,三层小波分解是合适的。(3)对不同能量的子带采用不同的量化步长。(4)采用定长编码算法。结果表明声图像压缩比特率为0.85。当BER小于10^(-3)时,图像质量完好。当BER小于10^(-2)时,图像中出现少量小黑白点。在上述基础上研制了水声通信机,频带为(7.5～12.5)kHz,接收声呐阵为8基元等距线阵,信号为QPSK和8PSK。在中国千岛湖进行了湖试,采用SOVA硬迭代算法,达到了低BER。传输一幅256×256×8的声图需时约7s。传输距离与传输速率之积为55 km kbps。
