Methods and apparatus for estimating a physiological parameter using transforms

A method for use in a system for determining a physiological parameter is described. The system has a sensor for transmitting electromagnetic energy of first and second wavelengths toward a tissue sample and detecting the electromagnetic energy after scattering of the electromagnetic energy by the tissue sample, thereby generating a first signal corresponding to the first wavelength and a second signal corresponding to the second wavelength. The first and second signals are transformed into the frequency domain, thereby generating third and fourth signals. A ratio signal is generated using the third and fourth signals. For each of a plurality of ratio values an associated sum is generated corresponding to the number of times the ratio signal coincides with the ratio value associated with the sum. Contributions to each sum are weighted in accordance with the third signal. A best ratio value is selected from the plurality of ratio values based on the sums associated therewith.

BACKGROUND OF THE INVENTION 
The present invention relates to methods and apparatus for estimating a 
physiological parameter using Fourier transforms. More specifically, the 
invention relates to a pulse oximetry system for estimating the oxygen 
saturation of hemoglobin in arterial blood in which a saturation value is 
determined from representations of the oximeter sensor signals in a 
transformed space. 
Pulse oximeters measure and display various blood flow characteristics and 
blood constituents including but not limited to the oxygen saturation of 
hemoglobin in arterial blood. An oximeter sensor passes light through 
blood-perfused tissue and photoelectrically senses the absorption of the 
light by the tissue. The light passed through the tissue is selected to be 
of one or more wavelengths that are absorbed by the blood in an amount 
representative of the amount of the blood constituent being measured. The 
amount of light absorbed is then used to calculate the amount of the blood 
constituent present in the blood. 
The sensed light signals can be degraded by both noise and motion artifact. 
One source of noise is ambient light that reaches the sensor's light 
detector. Another source of noise is electromagnetic coupling from other 
electronic instruments. Motion of the patient also introduces noise and 
affects the detected light energy. For example, the contact between the 
sensor's detector and/or emitter and the tissue sample can be temporarily 
disrupted when motion causes either to move away from the tissue. In 
addition, because blood is fluid, it responds differently than the 
surrounding tissue to inertial effects, thus resulting in momentary 
changes in volume at the point to which the oximeter sensor is attached. 
The degradation of the detected light energy can, in turn, result in 
degradation of the pulse oximeter output and inaccurate reporting of the 
blood constituent concentration. It will be understood that such 
inaccuracies can have negative consequences. 
A variety of techniques have been developed to minimize the effects of 
noise and motion artifact in pulse oximetry systems. In a system described 
in U.S. Pat. No. 5,025,791, an accelerometer is used in the oximetry 
sensor to detect motion. When motion is detected, data taken during the 
motion are either eliminated or indicated as being corrupted. In U.S. Pat. 
No. 4,802,486, assigned to Nellcor Puritan Bennett, the assignee of the 
present invention, the entire disclosure of which is incorporated herein 
by reference, an EKG signal is monitored and correlated to the oximeter 
reading to provide synchronization to limit the effect of noise and motion 
artifact pulses on the oximeter readings. This reduces the chance of the 
oximeter locking onto a motion signal. In U.S. Pat. No. 5,078,136, 
assigned to Nellcor Puritan Bennett, the assignee of the present 
invention, the entire disclosure of which is incorporated herein by 
reference, signal processing techniques such as linear interpolation and 
rate of change analysis are employed to limit the effects of noise and 
motion artifact. 
In another oximetry system described in U.S. Pat. No. 5,490,505, an 
adaptive noise canceler is used on different additive combinations of the 
red and infrared signals from the oximeter sensor to identify a 
coefficient for which the output of the noise canceler best represents the 
oxygen saturation of hemoglobin in the patient's blood. Unfortunately, 
this technique is computationally intensive resulting in an expensive 
implementation with undesirably high power requirements. 
In yet another oximetry apparatus in U.S. Pat. No. 5,632,272, a technique 
using a Fourier transform is described. Data from the Fourier transform is 
analyzed to determine the arterial blood saturation, by considering all 
Fourier energies above a threshold with equal importance. However, the 
technique described in U.S. Pat. No. 5,632,272 is inadequate in the 
presence of significant random motion, where many anomalous signals exist 
above the noise threshold. 
Because each of the above-described techniques has its own limitations and 
drawbacks, it is desirable to develop techniques for processing the 
signals from oximetry sensors to more accurately determine blood-oxygen 
levels in the presence of noise and motion artifact. 
SUMMARY OF THE INVENTION 
According to the present invention, a method and apparatus are provided by 
which noise from motion artifact and a variety of other sources is 
effectively removed from oximetry sensor signals for a reliable 
determination of the oxygen saturation of hemoglobin in a patient's 
arterial blood. Processed representations of the Red and IR signals from 
an oximetry sensor are combined in Fourier space and compared to a 
plurality of different values each of which corresponds to a different 
saturation value. A weighted count, also referred to herein as a sum, is 
maintained for each of the values which reflects the number of times the 
combined signal passes through the particular value. This information is 
used to generate a histogram or "saturation transform" of possible 
saturation values. The weights applied to contributions to each of the 
sums are selected in accordance with a representation of the IR signal in 
Fourier space. That is, individual contributions to each count are 
weighted according to the IR power level at the corresponding frequency. 
The histogram typically includes a number of local maxima, only one of 
which corresponds to the arterial blood saturation value. According to 
various embodiments, selection of the appropriate maximum may be 
accomplished using any of a variety of peak selection algorithms. For 
example, according to one embodiment, the local maximum corresponding to 
the highest weighted count is selected. According to another embodiment, 
the local maximum corresponding to the highest saturation value is 
selected. According to yet another embodiment, the local maximum 
corresponding to a saturation value that is closest to the most recent 
motion-free saturation value is selected. 
Thus, the present invention provides a method for use in a system for 
determining a physiological parameter. The system has a sensor for 
transmitting electromagnetic energy of first and second wavelengths toward 
a tissue sample and detecting the electromagnetic energy after scattering 
of the electromagnetic energy by the tissue sample, thereby generating a 
first signal corresponding to the first wavelength and a second signal 
corresponding to the second wavelength. The first and second signals are 
transformed into the frequency domain, thereby generating third and fourth 
signals. A ratio signal is generated using the third and fourth signals. 
For each of a plurality of ratio values an associated sum is generated 
corresponding to the number of times the ratio signal coincides with the 
ratio value associated with the sum. Contributions to each sum are 
weighted in accordance with the third signal. A best ratio value is 
selected from the plurality of ratio values based on the sums associated 
therewith.

DESCRIPTION OF SPECIFIC EMBODIMENTS 
FIG. 1 is a block diagram of an oximetry system 100 for use with the 
present invention. An oximetry sensor 102 is attached to a blood perfused 
tissue sample such as a patient's finger 104. Red and infrared (IR) LEDs 
106 and 108 alternately transmit Red and IR light toward finger 104. 
Detector 110 receives the Red and IR light transmitted through finger 104. 
Sensor 102 is connected to oximeter 112 which receives and processes the 
signal from detector 110, and which also provides the drive signal to LEDs 
106 and 108. The detector signal is received by front end signal 
processing circuitry 114 which demodulates the alternately transmitted Red 
and IR light received by detector 110, cancels ambient light, and includes 
fixed and variable hardware gain stages prior to digitization. 
The processed analog signal is converted to a digital signal by 
analog-to-digital conversion circuitry 116 and sent to central processing 
unit (CPU) 118 for computation of estimates of the oxygen saturation of 
hemoglobin in the patient's arterial blood according to a specific 
embodiment of the invention. The calculated saturation is then sent to 
display 120. CPU 118 also controls LED drive circuitry 122 which provides 
the drive signals for LEDs 106 and 108, and the demodulation of the 
collected light signals in front end circuitry 114. One example of an 
oximetry system for use with the present invention is described in 
commonly assigned, copending U.S. application Ser. No. 08/660,510 for 
METHOD AND APATUS FOR ESTIMATING PHYSIOLOGICAL AMETERS USING 
MODEL-BASED ADAPTIVE FILTERING filed on Jun. 7, 1996, which was based on 
Provisional Application Ser. No. 60/000,195 filed on Jun. 14, 1995, the 
entire specifications of which are incorporated herein by reference. 
FIG. 2 is a flowchart 200 illustrating the operation of the pulse oximetry 
system of FIG. 1. Data acquisition (step 202) may be achieved using a wide 
variety of available sensor and front-end analog signal processing such 
as, for example, sensor 102 and circuitry 114 of FIG. 1. The acquired data 
are digitized at an appropriate sample rate (step 204), and the natural 
logarithm of the digitized Red and IR waveforms is taken (step 206). The 
resulting data are then bandpass filtered (step 208) with an infinite 
impulse response filter (IIR) having a high pass cutoff at 0.5 Hz and a 
low pass roll off from 10 to 20 Hz. 
The signals are then employed for calculation of the pulse rate and 
saturation (steps 212 and 214). The values yielded by these process steps 
are both subjected to post processing (steps 216 and 218) which uses 
available metrics with regard to the calculated values to determine their 
reliability and whether and how they should be displayed. The respective 
values are then displayed (steps 220 and 222). A portion of saturation 
algorithm 214 will now be described in greater detail with reference to 
FIG. 3. 
FIG. 3 is a flowchart 300 illustrating the calculation of the oxygen 
saturation of hemoglobin in arterial blood according to a specific 
embodiment of the invention. FIGS. 4a-4c show representations of various 
signals used in the saturation calculation algorithm of the present 
invention. It will be understood that the described embodiment may be used 
in conjunction with a plurality of other methods for calculating 
saturation to thereby provide several independently calculated values from 
which the best value may then be selected. According to a specific 
embodiment, the processed and digitized Red and IR signals are transformed 
into Fourier Space (step 302). This Fourier transform results in frequency 
samples f.sub.i. The Fourier transformed signals are denoted by 
IR(f.sub.i) and Red(f.sub.i), which are both complex numbers. The relative 
magnitudes of some representative Fourier transformed signals are shown in 
FIG. 4a. 
Both the Red and IR waveforms (402 and 404 respectively) have components at 
the heart rate (approximately 1 Hz) and multiples thereof. The IR signal 
is then combined with the Red signal (step 304) generating a ratio signal 
406 (FIG. 4b) given by, 
##EQU1## 
Where * denotes a complex conjugate, and Re{x} connotes the real part of 
{x}. As will be understood and as shown in FIG. 4b, ratio signal 406 is 
relatively stable in the frequency ranges around each multiple of the 
heart rate and apparently random outside of these ranges. 
A weighted count or sum is then generated (step 306) for each of a 
plurality of ratio values, .omega..sub.i. The counts represent the 
strength of the IR amplitude at frequency indices (f.sub.i), where the 
ratio value .omega..sub.i equals the particular ratio value, .omega.. That 
is 
##EQU2## 
Where the sum is for all i such that .omega..sub.i =.omega.. 
The counts may be real numbers that correspond to the resolution of the 
measurement .vertline.IR(f.sub.i).vertline., or may be integerized or 
quantized approximations. In a specific embodiment, more than two possible 
values of the counts/weights are used. A histogram is generated (step 308) 
using the counts for each .omega..sub.i. An example of the histogram 
h(.omega.) is shown in FIG. 4c. According to a specific embodiment, the 
range of .omega..sub.i values is as follows: 
EQU 0.4&lt;.omega..sub.i &lt;2.5; .DELTA..omega..sub.i =0.05 
Each contribution to the count for a particular .omega..sub.i is weighted 
according to the strength of the IR signal at that Fourier index. That is, 
the weights accorded each transition of the ratio signal (FIG. 4b) through 
a particular ratio value .omega..sub.i are determined with reference to 
the amplitude of the IR signal as shown in FIG. 4a. Thus, the transitions 
that occur at or near the peaks (in Fourier space) of the IR waveform are 
weighted significantly more than those that occur where the IR amplitude 
is low. During motion, this typically results in a histogram having local 
maxima at two or more different values of .omega..sub.i, only one of which 
corresponds to the actual saturation value. 
If multiple peaks occur in the histogram, selection of the appropriate 
.omega..sub.i peak that corresponds to the arterial oxygen saturation for 
display (step 310) may be accomplished using a "peak selection" algorithm. 
Such an algorithm may be configured in a variety of ways including, but 
not limited to: 
1) The peak with the largest weighted count may be selected; 
2) The peak corresponding to the highest saturation value may be selected; 
3) The peak corresponding to a saturation value that is closest to the most 
recent saturation value calculated prior to the onset of motion may be 
selected. According to one embodiment, determination of the presence of 
motion is accomplished with a "motion detection" algorithm such as 
disclosed in U.S. Pat. No. 5,662,106 for OXIMETER WITH MOTION DETECTION 
FOR ALARM MODIFICATION issued on Sep. 2, 1997, the entire specification of 
which is incorporated herein by reference for all purposes. 
4) The peak corresponding to a saturation value closest to a predicted 
saturation value may be selected, where the predicted saturation value 
comes from following the trend of recently displayed saturations. 
According to various embodiments, this trend may, for example, incorporate 
the recently displayed saturation value, the time rate of change of 
recently displayed saturation values (i.e., saturation "velocity"), and 
the time rate of change of the change in recently displayed saturation 
values (i.e., saturation "acceleration") according to the following 
formula: 
EQU predicted saturation=last displayed saturation+C.sub.v 
.multidot.(dS/dt)+C.sub.a .multidot.(d.sup.2 S/dt.sup.2), 
where 
C.sub.v =velocity constant 
C.sub.a =acceleration constant 
dS/dt=time rate of change of recent previously displayed saturations 
d.sup.2 S/dt.sup.2 =time rate of change of recent values of dS/dt; 
5) The peak corresponding to the higher of two tracking saturations may be 
selected, where trending (as described above) of each of the peaks present 
in the histogram is conducted and those which track one another may be 
associated with the venous and arterial blood oxygen saturations. That is, 
a pure "motion" peak often is created and is unchanging near .omega..sub.i 
=1, while peaks that arise due to movement of venous and arterial blood 
will track one another, and in particular will track one another during a 
changing saturation condition. The .omega..sub.i peak corresponding to the 
higher saturation of the two "tracking" peaks is associated with the 
arterial oxygen saturation; 
6) An algorithm that arbitrates between a subset of the algorithms listed 
above may be used, where arbitration is accomplished by choosing the most 
appropriate method to use based on various signal factors. Such signal 
factors may include, but are not limited to, the number of local maxima in 
the histogram, the absence or presence of motion, or the degree of motion. 
For example, according to a specific embodiment, in the absence of motion, 
method #2 is used. According to another embodiment, method #3 is used in 
the presence of motion. In another specific embodiment, the arbitrating 
algorithm is configured such that in the absence of motion and/or when two 
.omega..sub.i peaks are present, method #2 is used. However, if three or 
more peaks are present, method #5 is used. 
Those skilled in the art will recognize that other schemes for selecting 
the .omega..sub.i peak corresponding to arterial saturation for display 
may be employed without departing from the scope of the invention. 
While the invention has been particularly shown and described with 
reference to specific embodiments thereof, it will be understood by those 
skilled in the art that changes in the form and details of the disclosed 
embodiments may be made without departing from the spirit or scope of the 
invention. For example, signal transforms other than the Fourier transform 
may be employed. Other such transforms include the Wavelet Transform, the 
Cosine Transform, and the Legendre Polynomial Transform. Furthermore, more 
than two wavelengths of light could be utilized, such as described in 
commonly assigned U.S. Pat. No. 5,645,060 entitled METHOD AND APATUS 
FOR REMOVING ARTIFACT AND NOISE FROM PULSE OXIMETRY issued on Jul. 8, 
1997, the entire specification of which is incorporated herein by 
reference for all purposes, or in the utilization of multivariate analysis 
in which many wavelengths are considered. Therefore, the scope of the 
invention should be determined with reference to the appended claims.