Abstract:
A method and device for detecting the presence of mixed venous and arterial blood pulsation in tissue, including receiving first and second electromagnetic radiation signals from a blood perfused tissue portion corresponding to infrared and red wavelengths of light, obtaining a measure of a phase difference between the first and second electromagnetic radiation signals, comparing the measure with a threshold value to form a comparison, and detecting the presence or absence of venous pulsation using the comparison.

Description:
BACKGROUND OF THE INVENTION  
       [0001]     The present invention relates in general to pulse oximetry, and in particular to the processing of signals generated by a pulse oximeter.  
         [0002]     A pulse oximeter is typically used to measure various blood characteristics including the blood oxygen saturation of hemoglobin in arterial blood and the pulse rate of the patient. Measurement of these characteristics has been accomplished by use of a non-invasive sensor that passes light through a portion of a patient&#39;s blood perfused tissue and photo-electrically senses the absorption and scattering of light in such tissue. The amount of light absorbed and scattered is then used to estimate the amount of blood constituent in the tissue using various algorithms known in the art. The “pulse” in pulse oximetry comes from the time varying amount of arterial blood in the tissue during a cardiac cycle. The signal processed from the sensed optical measurement is the familiar plethysmographic waveform, which corresponds with the cyclic attenuation of optical energy through a portion of a patient&#39;s blood perfused tissue.  
         [0003]     Various physiological and/or external factors can adversely impact the accuracy and/or the reliability of physiological parameters that are estimated by a pulse oximeter. These undesirable factors are sometimes referred to as artifacts. Venous pulsation is one undesired artifact in pulse oximetry, and may be caused by a patient&#39;s medical condition.  
         [0004]     It is therefore desirable that a pulse oximetry system be designed which effectively and accurately detects and/or notifies a clinician of the presence of venous pulsation.  
       BRIEF SUMMARY OF THE INVENTION  
       [0005]     The present invention provides a pulse oximeter that has the capability of detecting the presence of venous blood pulsation, or the presence of mixed venous and arterial blood pulsation in tissue.  
         [0006]     In one embodiment, the present invention provides a method of detecting the presence of mixed venous and arterial blood pulsation in tissue. The method includes receiving first and second electromagnetic radiation signals from a blood perfused tissue portion corresponding to infrared and red wavelengths of light; obtaining a measure of a phase difference between the first and second electromagnetic radiation signals; comparing the measure with a threshold value to form a comparison; and detecting the presence or absence of venous pulsation using the comparison.  
         [0007]     In one aspect, the measure of a phase difference between the first and second electromagnetic radiation signals is a measure of a persistent phase difference between the first and second electromagnetic radiation signals.  
         [0008]     In another aspect, the measure of a phase difference is a measure of the openness of an ellipse on a Lissajous plot formed by comparing the first electromagnetic radiation signal against the second electromagnetic radiation signal.  
         [0009]     In another embodiment, the present invention provides a device for detecting the presence of mixed venous and arterial blood pulsation in tissue. The device includes a module for receiving first and second electromagnetic radiation signals from a blood perfused tissue portion corresponding to infrared and red wavelengths of light; a module for obtaining a measure of a phase difference between the first and second electromagnetic radiation signals; a module for comparing the measure with a threshold value to form a comparison; and a module for detecting the presence or absence of venous pulsation using the comparison.  
         [0010]     For a fuiller understanding of the nature and advantages of the embodiments of the present invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0011]      FIG. 1  is a block diagram of an exemplary oximeter.  
         [0012]      FIG. 2  is a block diagram of the signal processing architecture of a pulse oximeter in accordance with one embodiment of the present invention.  
         [0013]     FIGS.  3 A-B are exemplary x-y, or Lissajous, plots of AC-coupled IR and Red pulse waveforms plotted against one another, showing in-phase ( FIG. 3A ) and out of phase ( FIG. 3B ) IR and Red pulse waveforms.  
         [0014]      FIG. 4  is a plot of % SpO 2  vs. Time (hr.:min.:sec.) showing periods of venous pulsation during normoxia in Trendelenburg position (i.e., a supine position on the operating table, which is inclined at varying angles so that the pelvis is higher than the head; used during and after operations in the pelvis or for shock).  
     
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0015]     The methods and systems in accordance with the embodiments of the present invention are directed towards detecting the presence or absence of venous or mixed venous and arterial pulsation in a blood perfused tissue. The invention is particularly applicable to and will be explained by reference to measurements of oxygen saturation of hemoglobin in arterial blood and pulse or heart rate, as in pulse oximeter monitors and pulse oximetry sensors.  
         [0016]     A typical pulse oximeter measures two physiological parameters, percent oxygen saturation of arterial blood hemoglobin (SpO 2  or sat) and pulse rate. Oxygen saturation can be estimated using various techniques. In one common technique, the photocurrent generated by the photo-detector is conditioned and processed to determine the ratio of modulation ratios (ratio of ratios) of the red to infrared (IR) signals. This modulation ratio has been observed to correlate well to arterial oxygen saturation. Pulse oximeters and sensors may be empirically calibrated by measuring the modulation ratio over a range of in vivo measured arterial oxygen saturations (SaO 2 ) on a set of patients, healthy volunteers, or animals. The observed correlation is used in an inverse manner to estimate blood oxygen saturation (SpO 2 ) based on the measured value of modulation ratios of a patient. The estimation of oxygen saturation using modulation ratios is described in U.S. Pat. No. 5,853,364, entitled “METHOD AND APPARATUS FOR ESTIMATING PHYSIOLOGICAL PARAMETERS USING MODEL-BASED ADAPTIVE FILTERING,” issued Dec. 29, 1998, and U.S. Pat. No. 4,911,167, entitled “METHOD AND APPARATUS FOR DETECTING OPTICAL PULSES,” issued Mar. 27, 1990, which are both herein incorporated by reference in their entirety for all purposes. The relationship between oxygen saturation and modulation ratio is described, for example, in U.S. Pat. No. 5,645,059, entitled “MEDICAL SENSOR WITH MODULATED ENCODING SCHEME,” issued Jul. 8, 1997, which is herein incorporated by reference in its entirety for all purposes. Most pulse oximeters extract the plethysmographic signal having first determined saturation or pulse rate, both of which are susceptible to interference.  
         [0017]      FIG. 1  is a block diagram of one embodiment of a pulse oximeter that may be configured to implement the embodiments of the present invention. The venous pulsation detection embodiments of the present invention may be implemented as a data processing algorithm that is executed by the microprocessor  122 , described below. Light from light source  110  passes into a blood perfused tissue  112 , and is scattered and detected by photodetector  114 . A sensor  100  containing the light source and photodetector may also contain an encoder  116  which provides signals indicative of the wavelength of light source  110  to allow the oximeter to select appropriate calibration coefficients for calculating oxygen saturation. Encoder  116  may, for instance, be a resistor.  
         [0018]     Sensor  100  is connected to a pulse oximeter  120 . The oximeter includes a microprocessor  122  connected to an internal bus  124 . Also connected to the bus is a RAM memory  126  and a display  128 . A time processing unit (TPU)  130  provides timing control signals to light drive circuitry  132  which controls when light source  110  is illuminated, and if multiple light sources are used, the multiplexed timing for the different light sources. TPU  130  also controls the gating-in of signals from photodetector  114  through an amplifier  133  and a switching circuit  134 . These signals are sampled at the proper time, depending upon which of multiple light sources is illuminated, if multiple light sources are used. The received signal is passed through an amplifier  136 , a low pass filter  138 , and an analog-to-digital converter  140 . The digital data is then stored in a queued serial module (QSM)  142 , for later downloading to RAM  126  as QSM  142  fills up. In one embodiment, there may be multiple parallel paths of separate amplifier, filter and A/D converters for multiple light wavelengths or spectra received.  
         [0019]     Based on the value of the received signals corresponding to the light received by photodetector  114 , microprocessor  122  will calculate the oxygen saturation using various algorithms. These algorithms require coefficients, which may be empirically determined, corresponding to, for example, the wavelengths of light used. These are stored in a ROM  146 . In a two-wavelength system, the particular set of coefficients chosen for any pair of wavelength spectra is determined by the value indicated by encoder  116  corresponding to a particular light source in a particular sensor  100 . In one embodiment, multiple resistor values may be assigned to select different sets of coefficients. In another embodiment, the same resistors are used to select from among the coefficients appropriate for an infrared source paired with either a near red source or far red source. The selection between whether the near red or far red set will be chosen can be selected with a control input from control inputs  154 . Control inputs  154  may be, for instance, a switch on the pulse oximeter, a keyboard, or a port providing instructions from a remote host computer. Furthermore, any number of methods or algorithms may be used to determine a patient&#39;s pulse rate, oxygen saturation or any other desired physiological parameter.  
         [0020]     The brief description of an exemplary pulse oximeter set forth above, serves as a basis for describing the methods for detecting the presence of venous pulsation, which are described below. The embodiments of the present invention, which are used to detect and/or indicate the presence of venous pulsation or mixed venous and arterial pulsation are described below in conjunction with the block diagram of  FIG. 2 .  
         [0021]     The embodiments of the present invention may be implemented as a part of a larger signal processing system used to process optical signals for the purposes of operating a pulse oximeter. Such a signal processing system is shown in  FIG. 2 , which is a block diagram  200  of a signal processing architecture of a pulse oximeter in accordance with one embodiment of the present invention. The signal processing architecture  200  in accordance with the embodiments of the present invention may be implemented as a software algorithm that is executed by a processor of a pulse oximeter. In addition to calculating oxygen saturation and pulse rate, the system  200  measures various signal metrics that are used to determine filter weighting coefficients. Signal metrics are things that indicate if a pulse is likely a plethysmograph or noise. Signal metrics may be related to, for example, frequency (is it in the range of a human heart rate), shape (is it shaped like a cardiac pulse), rise time, etc. The system shown in  FIG. 2  calculates both the oxygen saturation, and the pulse rate, as well as detecting venous pulsation and sensor off and lost pulse conditions, which are described separately below.  
         [0000]     I. Oxygen Saturation Calculation  
         [0022]     Block  202  represents the operation of the Signal Conditioning block. The digitized red and IR signals or waveforms are received and are conditioned in this block by: (1) taking the 1 st  derivative to get rid of baseline shift, (2) low pass filtering with fixed coefficients, and (3) dividing by a DC value to preserve the ratio. The function of the Signal Conditioning subsystem is to emphasize the higher frequencies that occur in the human plethysmograph and to attenuate low frequencies in which motion artifact is usually concentrated. The Signal Conditioning subsystem selects its filter coefficients (wide or narrow band) based on hardware characteristics identified during initialization. Inputs to block  202  are digitized red and IR signals, and its outputs are pre-processed red and IR signals.  
         [0023]     Block  204  represents the operation of the Pulse Identification and Qualification block. The low pass filtered digitized red and IR signals are provided to this block to identify pulses, and qualify them as likely arterial pulses. This is done using a pre-trained neural network, and is primarily done on the IR signal. The pulse is identified by examining its amplitude, shape and frequency. An input to this block is the average pulse period from block  208 . This function changes the upfront qualification using the pulse rate. The output of block  204  indicates the degree of arrhythmia and individual pulse quality. Inputs to block  204  are: (1) pre-processed red and IR signals, (2) Average pulse period, and (3) lowpass waveforms from the low pass filter. Outputs from block  204  include: (1) degree of arrhythmia, (2) pulse amplitude variations, (3) individual pulse quality, (4) pulse beep notification, and (5) qualified pulse periods and age.  
         [0024]     Block  206  is used to compute signal quality metrics. This block (block  206 ) determines the pulse shape (e.g., derivative skew), period variability, pulse amplitude and variability, Ratio of Ratios variability, and frequency content relative to pulse rate. Inputs to block  206  include: (1) raw digitized red and IR signals, (2) degree of arrhythmia, individual pulse quality, pulse amplitude variation, (3) pre-processed red and IR signals, and (4) average pulse period. Outputs from block  206  include: (1) lowpass and ensemble averaging filter weights, (2) metrics for sensor off detector, (3) normalized pre-processed waveforms, and (4) percent modulation.  
         [0025]     Block  208  computes average pulse periods. This block (block  208 ) calculates the average pulse period from the pulses received. Inputs to block  208  include: qualified pulse periods and age. An output from block  208  includes the average pulse period.  
         [0026]     Block  210  represents the functioning of the lowpass filter and ensemble averaging subsystem. Block  210  low pass filters and ensemble averages normalized and preprocessed waveforms processed by block  206 . The weights for the low pass filter are determined by the Signal Metrics block  206 . The signal is also ensemble averaged (this attenuates frequencies other than those of interest near the pulse rate and its harmonics), with the ensemble averaging filter weights also determined by Signal Metrics block  206 . Less weight is assigned if the signal is flagged as degraded. More weight is assigned if the signal is flagged as arrhythmic because ensemble-averaging is not appropriate during arrhythmia. Red and IR waveforms are processed separately, but with the same filtering weights. The filtering is delayed (e.g., approximately one second) to allow the signal metrics to be calculated first.  
         [0027]     The filters use continuously variable weights. If samples are not to be ensemble-averaged, then the weighting for the previous filtered samples is set to zero in the weighted average, and the new samples are still processed through the signal processing algorithm. This block tracks the age of the signal and/or the accumulated amount of filtering (e.g., sum of response times and delays in processing). Too old a result will be flagged, if good pulses haven&#39;t been detected for a while. The inputs to block  210  include: (1) normalized pre-processed red and IR signals, (2) average pulse period, (3) low pass filter weights and ensemble averaging filter weights, (4) ECG triggers, if available, and (5) IR fundamental, for zero-crossing triggers. Outputs from block  210  include: (1) filtered red and IR signals, and (2) age.  
         [0028]     Block  212  represents operations that estimate the ratio-of-ratios variance for the filtered waveforms and calculate averaging weights. The variable weighting for the filter is controlled by the ratio-of-ratios variance. The effect of this variable-weight filtering is that the ratio-of-ratios changes slowly as artifact increases and changes quickly as artifact decreases. The subsystem has two response modes, including fast and normal modes. For example, filtering in the fast mode targets an age metric of 3 seconds, and the target age may be 5 seconds in the normal mode. In the fast mode, the minimum weighting of the current value is clipped at a higher level. In other words, a low weight is assigned to the newest ratio-of-ratios calculation if there is noise present, and a high weight if no noise is present. The inputs to block  212  include: (1) filtered red and IR signals and age, (2) calibration coefficients, and (3) response mode (e.g., user speed settings). Outputs from block  212  include an averaging weight for ratio-of-ratios calculation. The averaging weight is used as an input to block  214  along with filtered IR and Red waveforms to calculate averaged ratio of ratios and age.  
         [0029]     Block  216  represents operations that calculate oxygen saturation. Saturation is calculated using an algorithm with the calibration coefficients and averaged ratio of ratios. Inputs to block  116  include: (1) Averaged Ratio-of-Ratios, and (2) calibration coefficients. An output from block  216  is the oxygen saturation value.  
         [0000]     II. Pulse Rate Calculation  
         [0030]     Block  218  low pass filters and ensemble averages the signal(s) conditioned by block  202 , for the pulse rate identification. The weights for the low pass filter are determined by the Signal Metrics block  206 . The signal is also ensemble averaged (this attenuates frequencies other than those of interest near the pulse rate and its harmonics), with the ensemble averaging filter weights also determined by Signal Metrics block  206 . Less weight is assigned if the signal is flagged as degraded. More weight is assigned if the signal is flagged as arrhythmic because ensemble-averaging is not appropriate during arrhythmia. Red and IR are processed separately, but with the same filtering weights. The filtering is delayed (e.g., approximately one second) to allow the signal metrics to be calculated first.  
         [0031]     The filters use continuously variable weights. If samples are not to be ensemble-averaged, then the weighting for the previous filtered samples is set to zero in the weighted average, and the new samples are still processed through the signal processing algorithm. This block (block  218 ) tracks the age of the signal and/or the accumulated amount of filtering (sum of response times and delays in processing). Too old a result will be flagged (if good pulses haven&#39;t been detected for awhile). Inputs to block  218  include: (1) pre-processed red and IR signals, (2) average pulse period, (3) lowpass filter weights and ensemble averaging filter weights, (4) ECG triggers, if available, and (5) IR fundamental, for zero-crossing triggers. Outputs from block  218  include: (1) filtered red and IR signals and (2) age.  
         [0032]     Block  220 , or the Filtered Pulse Identification and Qualification block, calculates the pulse periods from the filtered waveforms, and its results are used only when a pulse is disqualified by block  204 . Inputs to block  220  include: (1) filtered red and IR signals and age, (2) average pulse period, (3) front end ID or noise floor, (4) and the kind or type of sensor that is used to detect the IR and Red energies. Output from block  220  includes qualified pulse periods and age.  
         [0033]     Block  222 , or the Average Pulse Periods and Calculate Pulse Rate block, calculates the pulse rate and average pulse period. This block (block  222 ) receives qualified pulse periods and age as inputs and provides (1) average pulse period and (2) pulse rate as outputs.  
         [0000]     III. Venous Pulsation  
         [0034]     Block  224 , or the Detect Venous Pulsation block receives as inputs the pre-processed red and IR signals and age from Block  202 , and pulse rate and provides an indication of venous pulsation as an output. Block  224  also provides an IR fundamental waveform in the time domain using a single-tooth comb filter which is output to the Ensemble Averaging filters (e.g., block  210  and  218 ). Inputs to block  224  include: (1) filtered red and IR signals and age and (2) pulse rate. Outputs from block  124  include: an indication of venous pulsation and IR fundamental. In one embodiment, block  224  measures the “openness” of an IR-Red Lissajous plot to determine the whether a flag (e.g., Venous_Pulsation) should be set. The output flag (e.g., Venous_Pulsation) is updated periodically (e.g., every second). In addition, the IR fundamental waveform is output to the Ensemble Averaging filters.  
         [0000]     IV. Sensor Off  
         [0035]     Block  226 , or the Detect Sensor-Off and Loss of Pulse Amplitude block, uses a pre-trained neural net to determine whether the sensor is off the surface of the blood-perfused tissue, for example, of a patient. The inputs to the neural net are metrics that quantify several aspects of the behavior of the IR and Red values over the last several seconds. Samples are ignored by many of the system  200 &#39;s subsystems while the signal state is either not indicative of a pulse being present, or indicative that a sensor is not on a monitoring site (e.g., Pulse Present, Disconnect, Pulse Lost, Sensor May be Off, and Sensor Off). Inputs to block  226  include: (1) signal quality metrics, and (2) the oximeter&#39;s LED brightness, amplifier gain, and (3) an ID indicating the oximeter&#39;s hardware configuration. Outputs from block  226  include a signal state including sensor-off indication.  
         [0036]     In the architecture  200  described above, the function of block  226 , Pulse lost and Pulse Search indications, may be derived using information from several parts of the signal processing architecture. In addition, the signal processing architecture will not use the received IR and red waveforms to compute oxygen saturation or pulse rate if a valid sensor is not connected, or if the Sensor-Off or Loss of Pulse Amplitude are detected by the signal processing architecture.  
         [0037]     The brief description of an embodiment of a pulse oximeter signal processing architecture in accordance with the present invention, set forth above, serves as a basis for describing the methods and devices that are directed towards detecting the presence or absence of venous or mixed venous and arterial pulsation in a blood perfused tissue, as is generally indicated by block  224  above.  
         [0038]     Venous pulsation is an undesirable artifact in pulse oximetry. Venous pulsation is particularly common on the head or forehead, where the vascular anatomy lacks valves to prevent venous blood from backing up and pooling. Venous pulsation may be caused by the patient&#39;s medical condition, or during surgical interventions that interfere with venous return. The effects of venous pulsation may include: 1) oxygen saturation (e.g., SpO 2 ) readings reflecting a mix of venous and arterial blood, which would be substantially lower than the arterial oxygen saturation, thus resulting in incorrectly low oxygen saturation measurements, and 2) pulse rate readings that are double or even triple the patient&#39;s pulse rate, due to the prominent harmonics in the venous pressure wave. In addition, in extreme cases, it is possible that an oximeter would fail to acquire oxygen saturation and/or pulse rate measurements.  
         [0039]     Unlike motion artifacts that may not be present at all times, (e.g., they come and go), venous pulsation can continue uninterrupted for hours. While the side effects of venous pulsation are highly visible to the clinician, their cause may not be. Venous pulsation at the site of an oximetry sensor may be mitigated by applying pressure to the site, such as with a headband.  
         [0040]     The embodiments of the present invention provide methodologies, including software-based methods for detecting the venous pulsation artifact. The detection of the presence of venous pulsation enables an oximeter to display a troubleshooting message to a clinician, who could then address and/or correct the problem.  
         [0041]     Mixed venous and arterial pulses may be distinguished from arterial pulses due to the following properties, described below. First, venous blood has a lower saturation than arterial blood. Normoxic subjects (i.e., healthy subjects breathing air at sea level) who place their head significantly below their heart may readily create SpO 2  readings near 80% at the forehead if no pressure is applied to the sensor site. Second, the venous pulse occurs after the arterial pulse, and has a different shape.  
         [0042]     Due to these properties, the IR and red waveforms will have a significant and persistent phase difference if they include venous pulsation, as illustrated by the Lissajous plot of  FIG. 3B , which resembles a fairly open ellipse. Shown in FIGS.  3 A-B are IR and Red waveforms that are AC-coupled and plotted in an x-y plot, with the IR waveform on the x-axis, and the Red waveform on the y-axis. Note that the trace of  FIG. 3B  does not go through the origin. On the other hand, the IR and Red waveforms will be in-phase if they only include arterial pulses, as illustrated by the Lissajous plot of  FIG. 3A . Other artifacts, such as motion and noise may add out-of-phase components whose phase relationship and frequency content is unstable, and not as persistent as the venous pulsation induced phase difference.  
         [0043]     A waveform that is better suited for detecting phase differences between IR and Red waveforms is one that that contains just the waveform corresponding to the fundamental of the pulse rate, such as may be produced by an appropriate filter. Such a waveform is better suited for detecting phase differences between the IR and Red waveform that are of vascular origin.  
         [0044]     In one embodiment, the detection of the presence of venous pulsation involves detecting persistent phase differences between the IR and Red waveforms. As set forth above, preferably the detection of the phase difference, involves the detection of the phase difference between the IR and Red waveforms that have been filtered so as to contain just frequencies at or near the algorithm&#39;s pulse-rate or harmonics. Various techniques for detecting a persistent phase difference are described below. Using one or a combination of these techniques, one embodiment of the present invention for detecting the presence of venous pulsation includes an algorithm that will:  
         [0045]     1. AC-couple the IR and Red waveforms, and preferably filter them so as to pass only frequencies at or near the pulse rate.  
         [0046]     2. Over a time-window of at least one complete pulse, quantify the phase difference by quantifying the “openness of the ellipse” as (minimum distance from the origin)/(maximum distance from the x-axis). Alternatively the denominator of this ratio may be the maximum distance from the origin. A longer time-window will increase the likelihood that motion artifact or Gaussian noise would eventually produce samples near the origin, and reduce the likelihood of falsely reporting venous pulsation.  
         [0047]     3. Integrate the difference between this open-ellipse metric and a threshold. The threshold controls how open the ellipse must be to eventually notify the user of venous pulsation. The threshold preferably varies with the calculated SpO 2 , because venous pulsation is less likely to be occurring if high SpO 2  values are being calculated.  
         [0048]     4. If desired, to control how long venous pulsation must persist before notifying the user, clip the integral at pre-determined high and/or low limits, and report venous pulsation whenever a predetermined integral threshold in between the high and/or low limits is exceeded.  
         [0049]     The description below, discloses how the “how open is the ellipse” metric is quantified. The metric is quantified as follows:  
         Open_Lissajous   ⁢   _Axis   ⁢     _Ratio   t       =         min   ⁡     (       (       IR   t   2     +     Red   t   2       )     ,       (       IR     t   -   1     2     +     Red     t   -   1     2       )     ⁢   …   ⁢           ⁢     (       IR     t   -   N   +   1     2     +     Red     t   -   N   +   1     2       )         )         max   ⁡     (       IR   t   2     ,       IR     t   -   1     2     ⁢           ⁢   …   ⁢           ⁢     IR     t   -   N   +   1     2         )               
 
 Where IR and Red refer to waveforms that have been processed per step 1 above, and N denotes the number of samples in the time-window. 
 
         [0050]     In one embodiment, this metric is computed periodically (e.g., every second) from the most recent time window (e.g., four seconds) of data. It therefore covers a window of about several pulses. A preferred time window (e.g., four-second window) assures that the waveforms have multiple pulse periods in which to come close to the origin if the waveforms are actually in-phase. An alternate embodiment of this metric involves only using the Red data in the denominator. The inclusion of the Red data only in the numerator makes this metric more sensitive to out-of-phase waveforms at low saturations, where the Red modulation is larger, than at high saturations.  
         [0051]     Because this ratio may be fairly noisy, it may be filtered, clipped and integrated before being used to announce the presence or absence of venous pulsation. The filtering, clipping and integration are described below, such that:  
       w   =     min   ⁡     [       0.005            Open_Lissajous   ⁢   _Axis   ⁢   _Ratio     -     Open_Lissajous   ⁢   _Axis   ⁢     _Ratio   ′                ,   1.0     ]           
 
Filt_Open_Lissajous_Axis_Ratio= w *Open_Lissajous_Axis_Ratio+(1− w )*Filt_Open_Lissajous_Axis_Ratio′
 
 where ′ denotes the value from one second ago. 
 
Filt_Open_Lissajous_Axis_Ratio=min(Filt_Open_Lissajous_Axis_Ratio t , 0.3) Open_Lissajous_Threshold=max(0.06, 0.06+0.5*(Saturation−90%)) Venous_Pulsation_Integral=Venous_Pulsation_Integral′+Filt_Open_Lissajous_Axis_Ratio−Open_Lissajous_Threshold Venous_Pulsation_Integral=min(2.0, max(0, Venous_Pulsation_Integral)), 
 
 where: 
        Saturation is the oxygen saturation value.     Open_Lissajous_Threshold is the threshold defined above in step 3 of the algorithm.        
 
         [0054]     In one embodiment, using the above approach, venous pulsation is reported if Venous_Pulsation_Integral is at least 1.0.  
         [0055]     The threshold and weights in the above equations are developed empirically, and may change depending on various conditions. It is preferred that this venous pulsation detection algorithm has a response time of tens of seconds, depending on how rapidly the integral changes. This response time is adequate for the clinician&#39;s needs, as the body positions and circulatory conditions that create venous pulsation at the sensor site are not likely to change much faster than this. However, the response time can be changed to accommodate likely changes in body positions and/or circulatory conditions that create venous pulsation at the sensor site.  
         [0056]     In addition to the technique described above for quantifying a phase difference, many alternative techniques of detecting a persistent phase difference in accordance with the present invention are also available. For instance, the phase difference may be quantified by analyzing the cross-correlation function of the two waveforms as a function of a delay interval between them. Or the phase difference may be quantified in the frequency domain by subtracting the phases of the waveforms at a given frequency. One way to subtract the phases of two complex numbers, without having to directly compute inverse trigonometric functions, is by taking their complex conjugate, and dividing by the product of their magnitudes. Or alternatively, a persistent phase-difference may be detected at a harmonic of the pulse rate, in place of, or in combination with its fundamental.  
         [0057]      FIG. 4 , which is s a plot  300  of % SpO 2  vs. Time (hr.:min.:sec.) showing periods of venous pulsation during normoxia in a Trendelenburg position (i.e., a supine position on the operating table, which is inclined at varying angles so that the pelvis is higher than the head; used during and after operations in the pelvis or for shock) shows that the method in accordance with the embodiments of the present invention detects all four episodes of venous pulsation created by deliberately placing a normoxic volunteer in a Trendelenburg position. The first three episodes  402 ,  404 , and  406  were created without a headband, and venous pulsation was detected in 15-25 seconds. The final episode  408  was created with a headband in place, so that venous pulsation developed more gradually and was announced in about one minute.  
         [0058]     A pulse oximeter having a venous pulsation detection and notification system in accordance with the embodiments of the present invention is able to identify and notify a clinician of a majority of the low (e.g., 80s-low 90s) SpO 2  readings as those possibly caused by venous pulsations, so that a clinician can take appropriate corrective measures, such as tightening a headband that holds an oximeter sensor against a patient&#39;s forehead. Likewise, a pulse oximeter having a venous pulsation detection and notification system in accordance with the embodiments of the present invention is able to, during a desaturation event (i.e. SpO 2  less than 50%), not provide an indication of a venous pulsation event, and thus help a clinician be certain that the desaturation is real event.  
         [0059]     Accordingly, as will be understood by those of skill in the art, the present invention which is related to detecting the presence of venous or mixed venous and arterial blood pulsation is tissue, may be embodied in other specific forms without departing from the essential characteristics thereof. For example, while the present embodiments have been described in the time-domain, frequency-based methods are equally relevant to the embodiments of the present invention. Accordingly, the foregoing disclosure is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.