Abstract:
A hypovolemia monitor comprises a plethysmograph input responsive to light intensity after absorption by fleshy tissue. A measurement of respiration-induced variation in the input is made. The measurement is normalized and converted into a hypovolemia parameter. An audible or visual indication of hypovolemia is provided, based upon the hypovolemia parameter.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application relates to and claims the benefit of U.S. Provisional Application No. 60/607,562 entitled Noninvasive Hypovolemia Monitor, filed Sep. 7, 2004 and incorporated by reference herein. 
    
    
     BACKGROUND OF THE INVENTION 
     Pulse oximetry, a widely accepted noninvasive procedure for measuring the oxygen saturation level of arterial, blood, is responsive to pulsatile blood flowing within a fleshy tissue site.  FIG. 1  illustrates the standard plethysmograph waveform  100 , which can be derived from a pulse oximeter and corresponding pulse oximetry sensor. The sensor attaches to and illuminates a peripheral tissue site, such as a finger tip. The plethysmograph waveform  100  illustrates light absorption at the tissue site, shown along the y-axis  101 , versus time, shown along the x-axis  102 . The total absorption includes static absorption  110  and variable absorption  120  components. Static absorption  110  is due to tissue, venous blood and a base volume of arterial blood. Variable absorption  120  is due to the pulse-added volume of arterial blood. That is, the plethysmograph waveform  100  is a visualization of the tissue site arterial blood volume change over time, and is a function of heart stroke volume, pressure gradient, arterial elasticity and peripheral resistance. The ideal waveform pulse  130  displays a broad peripheral flow curve, with a short, steep inflow phase  132  followed by a 3 to 4 times longer outflow phase  134 . The inflow phase  130  is the result of tissue distention by the rapid blood volume inflow during ventricular systole. During the outflow phase  130 , blood flow continues into the vascular bed during diastole. The plethysmograph baseline  140  indicates the minimum basal tissue perfusion. 
     As shown in  FIG. 1 , a pulse oximetry sensor does not directly detect absorption, and hence does not directly measure the standard plethysmograph waveform  100 . Rather, a pulse oximeter sensor generates a detected light intensity signal. However, the standard plethysmograph  100  can be derived from the detected intensity signal because detected intensity is merely an out of phase version of light absorption. That is, the peak detected intensity occurs at minimum absorption  136 , and minimum detected intensity occurs at maximum absorption  138 . Further, a rapid rise in absorption  132  during the inflow phase of the plethysmograph is reflected in a rapid decline in intensity, and the gradual decline  134  in absorption during the outflow phase of the plethysmograph is reflected in a gradual increase in detected intensity. A pulse oximetry sensor is described in U.S. Pat. No. 6,088,607 entitled Low Noise Optical Probe. A pulse oximetry monitor is described in U.S. Pat. No. 6,650,917 entitled Signal Processing Apparatus. Both of these patents are assigned to Masimo Corporation, Irvine, Calif. and incorporated by reference herein. 
     SUMMARY OF THE INVENTION 
       FIG. 2  illustrates a hypovolemic plethysmograph waveform  200 . Hypovolemia is an abnormal decrease in blood volume, often caused from blood loss during surgery or due to an injury. Under hypovolemic conditions, a respiration-induced cyclical variation occurs in a plethysmograph baseline  240 . This cyclical variation  240  is particularly evident in patients undergoing positive ventilation. The amount of cyclical variation correlates to patient blood volume, i.e. the less blood volume the greater the cyclical variation in the plethysmograph waveform. As such, gauging cyclical variation, as described in detail with respect to  FIGS. 3-5 , below, allows a hypovolemia monitor to advantageously generate a noninvasive hypovolemia indication or blood volume measure. 
     One aspect of a hypovolemia monitor comprises a plethysmograph input responsive to light intensity after absorption by fleshy tissue and a measurement of respiration-induced variation in the input. The measurement is normalized and converted into a hypovolemia parameter. The plethysmograph may be generated by a pulse oximeter, and an audible or visual indication of hypovolemia may be provided. In one embodiment, an envelope of the plethysmograph is detected and a magnitude of the envelope is determined in order to measure the respiration-induced variation. In an alternative embodiment, a curve-fit is made to a locus of points on the plethysmograph and the variation magnitude is determined from a characteristic of the resulting curve. In yet another embodiment, a frequency spectrum of the plethysmograph is determined and a frequency component of that spectrum proximate a respiration rate is identified. The variation magnitude is calculated from the magnitude of that frequency component. 
     In other embodiments of the hypovolemia monitor, the normalized measurement is calculated by dividing the variation magnitude by an average value of the plethysmograph. Conversion is accomplished by constructing a calibration curve of hypovolemia parameter versus variation magnitude and using that calibration curve to determine the hypovolemia parameter from the normalized measurement. A percentage of normal total blood volume or a percentage of total blood volume loss may be displayed based upon the hypovolemia parameter. An audible alarm or a visual alarm indicating a hypovolemia condition may also be generated. 
     Another aspect of a hypovolemia monitor is a variation function having a sensor input and generating a variation parameter. The sensor input is responsive to light intensity after absorption by fleshy tissue and provides a measure of respiration-induced cyclical variation in the sensor input. A normalization function is applied to the variation parameter so as to generate a normalized variation parameter responsive to an average value of the sensor input. A conversion function is applied to the normalized variation parameter so as to generate a hypovolemia parameter responsive to blood volume of a living subject. In one embodiment, the variation function comprises an envelope detector adapted to determine an envelope of the sensor input and a magnitude processor configured to calculate a magnitude of the envelope. In another embodiment, the variation function comprises a curve-fit processor adapted to determine a locus of the sensor input representative of the cyclical variation. A magnitude processor is configured to calculate a magnitude of the cyclical variation from the locus. In yet another embodiment, the variation function comprises a frequency transform processor configured to generate a frequency spectrum of the sensor input. A frequency component processor is configured to determine the magnitude of a frequency component of the spectrum corresponding to a respiration rate of the living subject. 
     In other embodiments, the normalization function calculates the magnitude divided by the average value so as to generate a normalized magnitude. The conversion function comprises a look-up table containing a curve representing a hypovolemia parameter versus the normalized magnitude. In a particular embodiment, the hypovolemia parameter corresponds to a percentage blood volume loss of the living subject. 
     A further aspect of a hypovolemia monitor comprises a variation means, a normalization means and a conversion means. The variation means is for measuring a magnitude of respiration-induced cyclical variations in an input plethysmograph. The normalization means is for normalizing the magnitude relative to a DC value of the plethysmograph. The conversion means is for translating the normalized magnitude to a hypovolemia parameter responsive to blood volume loss in a living subject. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an absorption versus time graph of a standard pulse oximeter plethysmograph; 
         FIG. 2  is an absorption versus time graph of a plethysmograph exhibiting a respiration-induced, baseline cyclical variation; 
         FIG. 3  is an absorption versus time graph of a plethysmograph envelope magnitude measure of cyclical variation; 
         FIG. 4  is an absorption versus time graph of a plethysmograph envelope curve fit measure of cyclical variation; and 
         FIG. 5  is a block diagram of a noninvasive hypovolemia monitor. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       FIG. 3  illustrates a plethysmograph envelope magnitude measure for the cyclical variation of a plethysmograph  200 . In one embodiment, an upper envelope  301  of the plethysmograph  200  is determined. For example, the upper envelope  301  may be the locus of absorption maximums (peaks)  138  ( FIG. 1 ) of each pulse  130  ( FIG. 1 ). A variation parameter δ 1    310 , the magnitude of the upper envelope  301 , is determined, for example, from the delta between the highest peak and the lowest peak. The variation parameter  310  is normalized, e.g. by calculating the ratio of δ 1    310  over the DC  330  (direct current) value or average value of the plethysmograph  200 . A hypovolemia parameter  502  ( FIG. 5 ) responsive to the normalized variation parameter δ 1 /DC is then advantageously derived so as to noninvasively indicate a blood volume status, as described with respect to  FIG. 5 , below. 
     As shown in  FIG. 3 , in another embodiment, a lower envelope  302  of the plethysmograph  200  is determined. For example, the lower envelope  301  may be the locus of absorption minimums (valleys)  136  ( FIG. 1 ) of each pulse  130  ( FIG. 1 ). A variation parameter δ 2    320  of the lower envelope  302  is determined as, for example, the delta between the highest valley and the lowest valley. The variation parameter  320  is normalized as described above and a hypovolemia parameter  502  ( FIG. 5 ) responsive to the normalized variation parameter δ 2 /DC is then derived, as described with respect to  FIG. 5 , below. 
       FIG. 4  illustrates a plethysmograph curve-fit measure for the cyclical variation of a plethysmograph  200 . In one embodiment, an upper curve-fit  401  of the plethysmograph  200  is determined. For example, the upper curve fit  401  may be a best fit of the absorption maximums (peaks)  138  ( FIG. 1 ) of each pulse  130  ( FIG. 1 ). In a particular embodiment, the curve  401  is an ellipse having a first axis length that is dependent on the respiration rate RR  250  ( FIG. 2 ) and a variation parameter r 1    410  related to a second axis length is determined by a best fit to the plethysmograph pulse peaks  138  ( FIG. 1 ). The variation parameter r 1    410  is normalized, e.g. by calculating the ratio of r 1    410  over the DC  330  value. A hypovolemia parameter  502  ( FIG. 5 ) responsive to the normalized variation parameter r 1 /DC is then advantageously derived so as to noninvasively indicate a blood volume status, as described with respect to  FIG. 5 , below. 
     As shown in  FIG. 4 , in another embodiment, a lower curve-fit  402  of the plethysmograph  200  is determined. For example, the lower curve-fit  402  may be a best fit of the locus of absorption minimums (valleys)  136  ( FIG. 1 ) of each pulse  140  ( FIG. 1 ). In a particular embodiment, the curve  402  is an ellipse portion having a first axis length that is dependent on the respiration rate RR  250  ( FIG. 2 ) and a variation parameter r 2    420  related to a second axis length determined by a best fit to the plethysmograph pulse valleys  136  ( FIG. 1 ). In another embodiment, the curve  402  is a portion of a circle having radius r, the variation parameter. The variation parameter r 2    420  is normalized as described above. A hypovolemia parameter  502  ( FIG. 5 ) responsive to the normalized variation parameter r 2 /DC is then advantageously derived so as to noninvasively indicate a blood volume status, as described with respect to  FIG. 5 , below. 
       FIG. 5  illustrates a noninvasive hypovolemia monitor  500 , which is responsive to respiration-induced cyclical variations  240  ( FIG. 2 ) in a plethysmograph. The hypovolemia monitor receives a plethysmograph waveform  501  input and provides a hypovolemia parameter  502  output indicative of a patient&#39;s blood volume status. In one embodiment, the plethysmograph  501  is an IR plethysmograph generated by a pulse oximeter. In other embodiments, the plethysmograph  501  is a photoplethysmograph or a pulse oximetry red plethysmograph. The hypovolemia monitor  500  has variation measurement  510 , normalization  520  and conversion  530  functions. These functions can be performed with analog or digital circuitry or as processor-based algorithmic computations or a combination of the above. 
     As shown in  FIG. 5 , the variation measurement and normalization functions  510 ,  520  provide a relative measure of the degree of cyclical variation in the plethysmograph  200  ( FIG. 2 ). In one embodiment, the variation measurement function  510  comprises a peak detector that determines the local maxima of each pulse of the plethysmograph waveform. The magnitude  310 ,  320  ( FIG. 3 ), δ, of the resulting waveform envelope is then calculated. The result is normalized  520  relative to an average or DC value  330  ( FIG. 3 ) or similar value of the plethysmograph. The conversion function  530  converts the normalized variation measurement of the plethysmograph variation to a hypovolemia parameter  502 . In one embodiment, the conversion function  530  comprises a calibration curve of a hypovolemia measure versus the normalized magnitude of respiration-induced cyclical variations. The calibration curve may be derived from a patient population using a standard blood volume test, such as indocyanine green (ICG) dye injection and dissipation. In a particular embodiment, the conversion function  530  is a lookup table containing one or more of such calibration curves. The hypovolemia parameter  502  advantageously provides a numerical value relating to patient blood volume status. As one example, the hypovolemia parameter  502  is a percentage measure of blood loss. As another example, the hypovolemia parameter  502  is measure of total blood volume in liters. 
     Also shown in  FIG. 5 , input parameters  504  can be utilized by the conversion function  530 . In one embodiment, the input parameters  504  are patient type, such as adult, pediatric or neonate. In another embodiment, the input parameters include patient height and weight. In yet another embodiment, input parameters  504  are other physiological measurements, such as blood pressure. 
     Although the variation measurement and normalization functions are described above with respect to a time domain analysis, similar results can be achieved by a frequency domain analysis. For example, the variation measurement function  510  can be determined by performing a Fast Fourier Transform (FFT) or similar computation on the plethysmograph. In particular, the magnitude of the resulting spectral component at or near the respiration rate RR is determined. In one embodiment, respiration rate RR  503  is an input to the variation measurement function  510 , as provided by a ventilator, a respiration belt transducer or similar device. 
     A noninvasive hypovolemia monitor has been disclosed in detail in connection with various embodiments. These embodiments are disclosed by way of examples only and are not to limit the scope of the claims that follow. One of ordinary skill in the art will appreciate many variations and modifications.