BLIND SOURCE SEPARATION OF PULSE OXIMETRY SIGNALS

    公开(公告)号:WO2003039340A3

    公开(公告)日:2003-05-15

    申请号:PCT/US2002/035223

    申请日:2002-10-31

    Abstract: A method and apparatus for the application of Blind Source Separation (BSS), specifically Independent Component Analysis (ICA) to mixture signals obtained by a pulse oximeter sensor. In pulse oximetry, the signals measured at different wavelengths represent the mixture signals, while the plethysmographic signal, motion artifact, respiratory artifact and instrumental noise represent the source components. The BSS is carried out by a two-step method including an ICA. In the first step, the method uses Principal Component Analysis (PCA) as a preprocessing step, and the Principal Components are then used to derive sat and the Independent Components, where the Independent Components are determined in a second step. In one embodiment, the independent components are obtained by high-order decorrelation of the principal components, achieved by maximizing the sum of the squares of the higher-order cumulants of the plurality of mixture signals.

    SELECTION OF PRESET FILTER PARAMETERS BASED ON SIGNAL QUALITY
    2.
    发明申请
    SELECTION OF PRESET FILTER PARAMETERS BASED ON SIGNAL QUALITY 审中-公开
    基于信号质量选择预滤波器参数

    公开(公告)号:WO2004066161A1

    公开(公告)日:2004-08-05

    申请号:PCT/US2003/041467

    申请日:2003-12-29

    Abstract: Methods and devices for reducing noise effects in a system for measuring a physiological parameter, including receiving an input signal; obtaining an assessment of the signal quality of the input signal; selecting coefficients for a digital filter using the assessment of signal quality; and filtering the input signal using the digital filter, without comparing the filter's output signal with the input signal.

    Abstract translation: 用于减少用于测量生理参数的系统中的噪声影响的方法和装置,包括接收输入信号; 获得对输入信号的信号质量的评估; 使用信号质量评估来选择数字滤波器的系数; 并使用数字滤波器对输入信号进行滤波,而不将滤波器的输出信号与输入信号进行比较。

    BLIND SOURCE SEPARATION OF PULSE OXIMETRY SIGNALS
    3.
    发明授权
    BLIND SOURCE SEPARATION OF PULSE OXIMETRY SIGNALS 有权
    分离及盲脉搏血氧饱和度源中的

    公开(公告)号:EP1450676B1

    公开(公告)日:2008-02-13

    申请号:EP02802829.8

    申请日:2002-10-31

    CPC classification number: A61B5/14551 A61B5/02416 A61B5/7207 A61B5/7239

    Abstract: A method and apparatus for the application of Blind Source Separation (BSS), specifically Independent Component Analysis (ICA) to mixture signals obtained by a pulse oximeter sensor. In pulse oximetry, the signals measured at different wavelengths represent the mixture signals, while the plethysmographic signal, motion artifact, respiratory artifact and instrumental noise represent the source components. The BSS is carried out by a two-step method including an ICA. In the first step, the method uses Principal Component Analysis (PCA) as a preprocessing step, and the Principal Components are then used to derive sat and the Independent Components, where the Independent Components are determined in a second step. In one embodiment, the independent components are obtained by high-order decorrelation of the principal components, achieved by maximizing the sum of the squares of the higher-order cumulants of the plurality of mixture signals.

    BLIND SOURCE SEPARATION OF PULSE OXIMETRY SIGNALS
    5.
    发明公开
    BLIND SOURCE SEPARATION OF PULSE OXIMETRY SIGNALS 有权
    分离及盲脉搏血氧饱和度源中的

    公开(公告)号:EP1450676A2

    公开(公告)日:2004-09-01

    申请号:EP02802829.8

    申请日:2002-10-31

    CPC classification number: A61B5/14551 A61B5/02416 A61B5/7207 A61B5/7239

    Abstract: A method and apparatus for the application of Blind Source Separation (BSS), specifically Independent Component Analysis (ICA) to mixture signals obtained by a pulse oximeter sensor. In pulse oximetry, the signals measured at different wavelengths represent the mixture signals, while the plethysmographic signal, motion artifact, respiratory artifact and instrumental noise represent the source components. The BSS is carried out by a two-step method including an ICA. In the first step, the method uses Principal Component Analysis (PCA) as a preprocessing step, and the Principal Components are then used to derive sat and the Independent Components, where the Independent Components are determined in a second step. In one embodiment, the independent components are obtained by high-order decorrelation of the principal components, achieved by maximizing the sum of the squares of the higher-order cumulants of the plurality of mixture signals.

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