RX-0035.0147
`
`APL_MAS_ITC_00015764
`
`130
`
`Design of pulse oximeters
`
`Because the Acl terms in the numerator and denominator of the right side of the
`equation (9.19) cancel, as do the negative signs before each term, equation (9.19)
`when combined with equation (9.13) yields
`
`Ratio = Ros =
`
`- ]
`- R L
`~
`l n
`a A (XY) _ (RH J
`DA (AIR ) In <IRIL.~
`l IR H j
`
`(9.20)
`
`1
`
`Thus, by measuring the minimum and the maximum emergent light intensities of
`both the red and infrared wavelengths CRL, RH, IRL, IRH), a value for the term
`RoS can be computed. Empirically derived calibration curves are then used to
`determine the oxygen saturation based on ROS.
`
`Red transmittance
`
`Light
`intensity ~
`
`A
`
`Light
`intensity
`
`Infrared transmittance
`
`RH 1 RL
`
`IRH
`
`~ IRL
`
`Time
`
`Time
`
`Figure 9.2. A graphical plot of transmitted light intensity converted into voltage. High (H) and
`low (L) signals are shown as a function of time of the transmittancc of red (R) and i nfrared (IR)
`light through the finger.
`
`9.3.2 Derivative method: noise reduction software
`
`Yorkey (1996) derives the Ratio of Ratios by calculating using the separated AC
`and DC components of the measured signal. This mathematical derivation of the
`ratio of ratios is performed using the Beer-Lambert equation.
`
`/1 = loe
`
`(9.21)
`
`where /1 is the emerging light intensity, 4 is the incident light intensity, a is the
`relative extinction coefficient of the material and L is the path length. In this
`method, the Ratio of Ratios is determined using the derivatives. Assuming the
`change in path length is the same for both wavelengths during the same time
`interval between samples, the instantaneous change in path length (dL/dt) must
`also be the same for both wavelengths.
`We can extend the general case of taking the derivative of eu to our case
`
`deu =eu dE
`dt
`dt
`
`(9.22)
`
`147
`
`1
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0148
`
`APL_MAS_ITC_00015765
`
`Signal processing algorithms
`-01 ~-a -~dL
`dt
`
`dIi
`dt
`
`=/De
`
`Therefore,
`
`(dll/dr)
`
`dL
`= -Et-.
`dt
`
`131
`
`(9.23)
`
`(9.24)
`
`Here, Il is equal to the combined AC and DC component of the waveform and
`dll/dt is equal to the derivative of the AC component of the waveform. Using two
`wavelengths we have
`
`Rof R=
`
`(d/R /do//R _ -a (AR)
`(d/IR/dt)//IR -a(AIR )
`
`(9.25)
`
`Instead of using the previous method of calculating the Ratio of Ratios based
`on the natural logarithm of the peak and valley values of the red and infrared
`signals, the value of the R of R can be calculated based on the derivative value of
`the AC component of the waveform.
`
`1
`
`Light
`intensity
`
`1 Heart beat i I AC component
`
`'-11'
`
`/1\
`\C V l. DC component
`
`¥ Tr
`tl t3 t2
`
`~ DC offset
`
`Time
`
`Figure 9.3. A waveform of the transmitted light intensity through a finger showing the AC
`component, the DC component and the DC offset.
`
`Note in discrete time
`
`dIR (t)
`dt
`If we choose 4 and 4 to be the maximum and minimum of the waveform, we can
`refer to this difference as the AC value, and the denominator above evaluated at
`some point in time t3 in between t2 and ti as the DC value. So,
`
`- IR (12)- IR (4)
`
`(9.26)
`
`dIR (t) / dt IR (12) - IR (tl ) AC R
`IR (13)
`IR
`DCR = R
`d/IR (t) / dt Im (12 ) - IIR (tl ) ACIR
`IIR
`/IR (t:3)
`DC IR
`
`(9.27)
`
`148
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0149
`
`APL_MAS_ITC_00015766
`
`1
`
`J 1
`11
`
`1
`
`132
`
`Design of pulse oximeters
`
`Potratz (1994) implemented another improved method for noise reduction
`called the derivative method of calculating the Ratio of Ratios. To calculate the
`Ratio of Ratios based on the derivative formula, a large number of sampled
`points along the waveform are used instead of merely the peak and valley
`measurements. A series of sample points from the digitized AC and AC + DC
`values for the infrared and red signals are used to form each data point. A digital
`FIR filtering step essentially averages these samples to give a data point. A large
`number of data points are determined in each period. The period is determined
`after the fact by noting where the peak and valley occur (figure 9.3).
`From the AC signal, a derivative is then calculated for each pair of data
`points and used to determine the ratio of the derivatives for R and IR. A plot of
`these ratios over a period will ideally result in a straight line. Noise from the
`motion artifact and other sources will vary some values. But by doing the linear
`regression, a best line through a period can be determined, and used to calculate
`the Ratio of Ratios.
`A problem with other systems was DC drift. Therefore, a linear
`extrapolation was performed between two consecutive negative peaks of the
`waveform. This adjusts the negative peak of the waveform as if the shift due to
`the system noise did not occur. A similar correction can be calculated using the
`derivative form of the waveform. In performing the correction of the DC
`component of the waveform, it is assumed that the drift caused by noise in the
`system is much slower than the waveform pulses and the drift is linear. The
`linear change on top of the waveform can be described by the function
`
`&(t) =f(0 + mt + b
`
`(9.28)
`
`where m is equal to the slope of the waveform and b is equal to a constant.
`The linear change added to the waveform does not affect the instantaneous
`DC component of the waveform. However, the derivative of the linear change
`will have an offset due to the slope of the interfering signal:
`
`d(f(t) + mt + b)/dt = df(t)/dr + m.
`
`(9.29)
`
`if we assume that the offset is constant over the period of time interval, then the
`Ratio of Ratios may be calculated by subtracting the offsets and dividing:
`
`F Cy- m „)
`Rof R=-=
`X (x- nix)
`
`(9.30)
`
`where y and x are the original values and mx and my are the offsets.
`Since the Ratio of Ratios is constant over this short time interval the above
`formula can be written as
`(y- m.2 - R.
`(x - mx)
`
`(9.31)
`
`Therefore,
`
`y = Rx - Rmx + my.
`
`(9.32)
`
`Since it was assumed that mi, tn~, and R are constant over the time interval, we
`have an equation in the form of y = mx + b where in is the Ratio of Ratios. Thus,
`
`149
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0150
`
`APL_MAS_ITC_00015767
`
`Signal processing algorithms
`
`133
`
`we do a large number of calculations of the Ratio of Ratios for each period, and
`then do the best fit calculation to the line y = Rx + b to fit the optimum value of
`R for that period, taking into account the constant b which is caused by DC drift.
`To determine the Ratio of Ratios exclusive of the DC offset we do a linear
`regression. It is preferred to take points along the curve having a large
`differential component, for example, from peak to valley. This will cause the m r
`term to dominate the constant b:
`
`R= "I.r.j v.j -Ixj Iyj
`
`NX Xj- -(1 Xj)-
`
`(9.33)
`
`where n=#of samples, j = sample #,x= IRd/IR / dt, y= IIRdIR / dt.
`Prior sampling methods typically calculate the Ratio of Ratios by sampling
`the combined AC and DC components of the waveform at the peak and valley
`measurements of the waveform. Sampling a large number of points on the
`waveform, using the derivative and performing a linear regression increases the
`accuracy of the Ratio of Ratios, since noise is averaged out. The derivative form
`eliminates the need to calculate the logarithm. Furthermore doing a linear
`regression over the sample points not only eliminates the noise caused by patient
`movement of the oximeter, it also decreases waveform noise caused by other
`sources.
`
`9.4 GENERAL PROCESSING STEPS OF OXIMETRY SIGNALS
`
`The determination of the Ratio of Ratios (ROS) requires an accurate measure of
`both the baseline and pulsatile signal components (Frick et at 1989). The baseline
`component approximates the intensity of light received at the detector when only
`the fixed nonpulsatile absorptive component is present in the finger. This
`component of the signal is relatively constant over short intervals and does not
`vary with nonpulsatile physiological changes, such as movement of the probe.
`Over a relatively long time, this baseline component may vary significantly. The
`magnitude of the baseline component at a given point in time is approximately
`equal to the level identified as RH (figure 9.2). However, for convenience, the
`baseline component may be thought of as the level indicated by RL, with the
`pulsatile component varying between the values of RH and RL over a given pulse.
`Typically, the pulsatile component may be relatively small in comparison to the
`baseline component and is shown out of proportion in figure 9.3. Because the
`pulsatile components are smaller, greater care must be exercised with respect to
`the measurement of these components. If the entire signal, including the baseline
`and the pulsatile components, were amplified and converted to a digital format
`for use by microcomputer, a great deal of the accuracy of the conversion would
`be wasted because a substantial portion of the resolution would be used to
`measure the baseline component (Cheung et at 1989)
`In this process, a substantial portion of the baseline component termed offset
`voltage Vos is subtracted off the input signal Vl · The remaining pulsatile
`component is amplified and digitized using an ADC. A digital reconstruction is
`then produced by reversing the process, wherein the digitally provided
`information allows the gain to be removed and the offset voltage added back.
`
`150
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0151
`
`APL_MAS_ITC_00015768
`
`1
`
`111
`
`134
`
`Design Of pulse oximeters
`
`This step is necessary because the entire signal, including the baseline and
`pulsatile components is used in the oxygen saturation measurement process.
`Feedback from the microcomputer is required to maintain the values for
`driver currents Io, Vos and gain A at levels appropriate to produce optimal ADC
`resolution (figure 9.4). Threshold levels Ll and L2 slightly below and above the
`maximum positive and negative excursions L3 and L4 allowable for the ADC
`input are established and monitored by the microcomputer (figure 9.5). When the
`magnitude of the input to and output from the ADC exceeds either of the
`thresholds Ll or L2, the drive currents ID are adjusted to increase or decrease
`the intensity of light impinging on the detector. This way, the ADC is not
`overdriven and the margin between L1 and L3 and between L2 and L4 helps
`assure this even for rapidly varying signals. An operable voltage margin for the
`ADC exists outside of the thresholds, allowing the AIX] to continue operating
`while the appropriate feedback adjustments to A and Vos are made. When the
`output from the ADC exceeds the positive and negative thresholds L5 or L6, the
`microcomputer responds by signaling the programmable subtractor to increase or
`decrease the voltage Vos being subtracted. This is accomplished based on the level
`of the signal received from the ADC. Gain control is also established by the
`microcomputer in response to the output of the ADC (Cheung et al 1989).
`
`A(Vl - Vos)
`VOS
`A
`
`1 9
`
`Microcomputer
`
`~ ADC ~- Vo/A + Vos = Vl
`A
`VOS
`
`t ad] i artifacl i detect
`
`1 calc ~
`
`Analysis,
`features
`display
`
`Figure 9.4. A functional block diagram of the miciocomputer feedback illustrating the basic
`operation of the feedback control system. The DC value of the signal is subtracted before digitizing
`the waveform to increase the dynamic range of conversion, The removed DC value is later added to
`the digitized values for further signal processing (Cheunget at 1989)
`
`A program of instructions executed by the Central Processing Unit of the
`microcomputer defines the manner in which the microcomputer provides
`servosensor control as well as produces measurements for display. The first
`segment of the software is the interrupt level routine.
`
`9.4.1 Start up software.
`
`The interrupt level routine employs a number of subroutines controlling various
`portions of the oximeter. At the start up, calibration of the oximeter is
`
`151
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0152
`
`APL_MAS_ITC_00015769
`
`.
`
`Signal processing algorithms
`
`135
`
`performed. After calibration, period zero subroutine is executed which includes
`five states, zero through four (figure 9.6).
`Period zero subroutine is responsible for normal sampling
`
`State 0: Initialize parameters
`State 1: Set drive current
`State 2: Set offsets
`State 3: Set gains
`State 4: Normal data acquisition state.
`
`Probe set-zip operations are performed during the states zero to three of this
`subroutine. During diese states probe parameters including the amplifier gain A
`and offset voltage Vos are initialized, provided thal a finger is present in the
`probe. State 4 of the interrupt period zero subroutine is the normal data
`acquisition state. The signals produced in response to light at each wavelength are
`then compared with the desired operating ranges to detennine whether
`modifications of the driver currents and voltage offsets are required. Finally state
`4 of the period zero subroutine updates the displays of the oximeter. Sequential
`processing returns to state 0 whenever the conditions required for a particular
`state are violated (Cheung et W 1989),
`
`L3
`
`High rai' X\X«
`¥Aeset c'7404*44Rk
`:t, p:,m/t~#blil#jm#,/4/4:i.-
`-#.21{!:i!#21' •' * ~11 -*f ;fl:il, 12 -,
`*.<42* eset oftfets*@*,9*U
`' *04 5/4,-11'4" 4' 7:Wi'/t!:flts?:.
`2/-'*..fl:, 41/p./<;'- na""u".:" - L5
`Desired operating
`range
`*71!/imi#47/3/144'14.1 0.:it,.1146
`f,tfu '11 -t'*t:qw,ija?**b!,1,;,
`.'ifl,i4,91*ilf.ju.i.*ti.t44;"".fe.,'t L
`Low ra I *~Aeset driv~~~41%~
`L4
`
`Mid scale
`=062;Tis
`
`./*534*
`
`P~44~ Reset 011 5 Gtsy
`
`...
`
`Figure 9.5 A graphical representation of the possible ranges of digitized signal, showing the
`desired response of the VO circuit and microcomputer at each of the various possi ble ranges
`(Cheung et al 1989).
`
`9.5 TRANSIENT CONDITIONS
`
`The relative oxygen content of a patient's arterial pulses and the average
`background absorbance remain about the same from pulse to pulse. Therefore,
`the red and infrared light that is transmitted through the pulsatile flow produces a
`regularly modulated waveform with periodic pulses of comparable shape and
`amplitude and a steady state background transmittance. This regularity in shape
`helps in accurate determination of the oxygen saturation of the blood based on the
`maximum and minimum transmittance of the red and infrared light
`Changes in a patient's local blood volume at the probe site due to motion
`artifact or ventilatory artifact affect the absorbance of light. These localized
`
`152
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0153
`
`APL_MAS_ITC_00015770
`
`136
`
`Design Of pulse oxi.meters
`
`changes often introduce artificial pulses into the blood flow causing the pei·iodic
`pulses ride on a background intensity component of transmittance that varies 1
`blood volume changes. This background intensity component variation, which is
`not necessarily related to changes in saturation, affects the pulse to pulse
`uniformity of shape, amplitude and expected ratio of the maximum to minimum
`transmittance, and can affect the reliability and accuracy of oxygen saturation
`determination (Stone and Briggs 1992).
`
`Calibration
`at start up
`
`Start up
`
`Other interrupt
`periods
`
`Period 0
`Normal
`samples
`States 0 to 3 L -
`to setup probe ,
`
`1 State 4 1
`
`Drive LEDs &
`input samples
`
`Check offsets
`
`Update display
`
`Figure 9.6. Flow chart of a portion of an interrupt level software routine included in the
`microcomputer (Cheung a a/ 1989)
`
`In addition, there are times when the patient's background level of oxygen
`saturation undergoes transient changes, for example, when the patient loses or
`requires oxygen exchange in the lungs while under gaseous anesthesia. The
`transient waveform distorts the pulse shape, amplitude, and the expected ratio of
`the pulses, which in turn affects the reliability and accuracy of the oxygen
`saturation determination.
`With changes in the background intensity absorbance component due to
`artifacts from changes in blood volume or transient saturation changes, the
`determined saturation' value is not accurate and it would not become accurate
`again until the average absorbance level stabilizes.
`The saturation calculations based upon transient signals provide an
`overestimation or underestimation of the actual saturation value, depending upon
`the trend. The transmittance of red light increases as oxygen saturation increases
`resulting in a signal value having a smaller pulse, and the transmittance of the
`infrared light decreases as saturation increases resulting in the infrared pulsatile
`amplitude increasing. For these wavelengths, the transmittance changes with
`saturation are linear in the range of clinical interest, i.e., oxygen saturation
`between 50% and 100%. The accuracy of the estimation is of particular concern
`during rapid desaturation. In such a case, the determined saturation based on the
`
`153
`
`1
`
`1
`
`r
`
`1I
`
`11
`
`IL
`
`4 r I
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0154
`
`APL_MAS_ITC_00015771
`
`...
`
`1
`
`Signal processing algorithms
`
`137
`
`detected signals indicates a greater drop than the actual value. This
`underestimation of oxygen saturation may actuate low limit saturation alarms that
`can result in inappropriate clinical decisions.
`The pulsatile amplitude is usually quite small, typically less than 5% o f the
`overall intensity change and any small change in overall or background
`transmittance, such as slight changes in average blood saturation, can have a
`relatively large effect on the difference in maximum and minimum intensity of
`the light levels. Because the change in transmittance with changing oxygen
`saturation is opposite in direction for the red and infrared, this can result in
`overestimation of the pulsatile ratio during periods when saturation is decreasing,
`and underestimation during periods when saturation is increasing. It is therefore
`essential to compensate for the effects of transient conditions and localized blood
`volume changes on the actual signal, thereby providing a more accurate
`estimation of the actual oxygen saturation value.
`This can be achieved by using a determined rate of change from pulse to
`pulse, using interpolation techniques and by using the low frequency
`characteristics of the detected signal values.
`The transient error is corrected by linear interpolation where the determined
`maxima and minima for a first and second optical pulses are obtained, the second
`pulse following the first. The respective rates of change in the transmittance due
`to the transient are determined from the maximum transmittance point of the first
`detected pulse to the second detected pulse (Stone and Briggs 1992). The
`determined rates of change are then used to compensate any distortion in the
`detected transmittance of the first detected pulse introduced by the transient in
`accordance with the following algorithm
`Vmax (n)~ = Vmax (n) + Dmax (n) - Vmax (n + 1)] >< max
`
`(9.34)
`
`[/max 1/1 +11 - imax (41
`
`where tmax(n) is the time of occurrence of the detected maximum transmittance at
`the n maximum, tmin(n) is the time of occurrence of the detected minimum
`transmittance of the wavelength at the n minimum, Vmax(n) is the detected optical
`signal maximum value at the maximum transmittance of the wavelength at the n
`maximum Vmax(n)* is the corrected value, for n being the first optical pulse, and
`n + 1 being the second optical pulse of that wavelength.
`By application of the foregoing linear interpolation routine, the detected
`maximum transmittance value at tmax(n) can be corrected, using the values
`tmax(n+1), detected at the next coming pulse, to correspond to the transmittance
`value that would be detected as if the pulse were at steady state conditions. The
`corrected maximum value and the detected (uncorrected) minimum value thus
`provide an adjusted optical pulse maximum and minimum that correspond more
`closely to the actual oxygen saturation in the patient's blood at that time, not
`withstanding the transient condition. Thus, using the adjusted pulse values in place
`of the detected pulse values in the modulation ratio for calculating oxygen
`saturation provides a more accurate measure of oxygen saturation than would
`otherwise be obtained during transient operation.
`Similarly, the respective rates of change in the transmittance are determined
`from the minimum transmittance point of the first detected pulse to the minimum
`of the second detected pulse. The determined rates of change are then used to
`compensate for any distortion in the detected minimum transmittance of the
`
`154
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0155
`
`APL_MAS_ITC_00015772
`
`, 1
`
`1
`
`1
`
`11
`
`III
`
`138
`
`Design of pulse oximeters
`
`second detected pulse introduced by the transient in accordance with the
`following algorithm
`
`1
`
`(9.35)
`
`Kn,n (n) = linln (n - 1) + [Vmln C
`
`n) - Itnin (n - 1)] X max
`[trnin l" ) - 'Init) C" - ' )1
`where tmax(n) is the time of occurrence of the detected maximum transmittance at
`the n maximum; tmin(n) is the time of occurrence of the detected minimum
`transmittance of the wavelength at the n minimum; Vmin(n) is the detected optical
`signal minimum value at the minimum transmittance of the wavelength at the n
`minimum; Knin(n)* is the corrected value, for n being the second optical pulse,
`and n-1 being the first optical pulse of that wavelength.
`By application of the foregoing linear interpolation routine, the detected
`minimum transmittance value at t = n can be compensated using the detected
`values at the preceding pulse t = n - 1, to correspond to the transmittance value
`that would be detected as if the pulse were detected at steady state conditions. The
`compensated minimum value and the detected (uncompensated) maximum value
`thus provide an adjusted optical pulse maximum and minimum that correspond
`more closely to the actual oxygen saturation in the patient's blood at that time,
`notwithstanding the transient condition. Thus, using the adjusted pulse values in
`place of the detected pulse values in the modulation ratio for calculating oxygen
`saturation provides a more accurate measure of oxygen saturation than would
`otherwise be obtained during transient operation.
`As is apparent from the algorithms, during steady state conditions the
`compensated value is equal to the detected value. Therefore, the linear
`interpolation routine may be applied to the detected signal at all times, rather than
`only when transient conditions are detected. Also, the algorithm may be applied
`to compensate the detected minimum or maximum transmittance values by
`appropriate adjustment of the algorithm terms. The amount of oxygen saturation
`can then be determined from this adjusted optical pulse signal by determining the
`relative maxima and minima as compensated for the respective wavelengths and
`using that information in determining the modulation ratios of the known
`Lambert-Beer equation.
`The Nellcor® N-200 oximeter is designed to determine the oxygen saturation
`in one of the two modes. In the unintegrated mode the oxygen saturation
`determination is made on the basis of optical pulses in accordance with
`conventional pulse detection techniques. In the ECG synchronization mode the
`determination is based on enhanced periodic data obtained by processing the
`detected optical signal and the ECG waveform of the patient.
`The calculation of saturation is based on detecting maximum and minimum
`transmittance of two or more wavelengths whether the determination is made
`pulse by pulse (the unintegrated mode) or based on an averaged pulse that is
`updated with the occurrence of additional pulses to reflect the patient's actual
`condition (the ECG synchronized mode).
`Interrupt programs control the collection and digitization of incoming
`optical signal data. As particular events occur, various software flags are raised
`which transfer operation to various routines that are called from a main loop
`processing routine.
`The detected optical signal waveform is sampled at a rate of 57 samples per
`second. When the digitized red and infrared signals for a given portion of
`
`155
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0156
`
`APL_MAS_ITC_00015773
`
`i
`
`Signal processing algorithms
`
`139
`
`detected optical signals are obtained, they are stored in a buffer called DATBUF
`and a st,ftware flag indicating the presence of data is set. This set flag calls a
`routine called MUNCH, which processes each new digitized optical signal
`waveform sample to identify pairs of maximum and minimum amplitudes
`corresponding to a pulse. The MUNCH routine first queries whether or not there
`is ECG synchronization, then the MUNCH routine obtains the enhanced
`composite pulse data in the ECG synchronization mode. Otherwise, MUNCH
`obtains the red and infrared optical signal sample stored in DATBUF, in the
`unintegrated mode. The determined maximum and minimum pairs are then sent
`to a processing routine for processing the pairs. Preferably, conventional
`techniques are used for evaluating whether a detected pulse pair is acceptable for
`processing as an arterial pulse and performing the saturation calculation, whether
`the pulse pair is obtained from the DATBUF or from the enhanced composite
`pulse data.
`The MUNCH routine takes the first incoming pulse data and determines the
`maximum and minimum transmittance for each of the red and infrared detected
`optical signals, and then takes the second incoming pulse data, and determines the
`relative maximum and minimum transmittance. The routine for processing the
`pairs applies the aforementioned algorithm to the first and second pulse data of
`each wavelength. Then the oxygen saturation can be determined using the
`corrected minimum and detected maximum transmittance for the second pulses of
`the red and infrared optical signals. Some of the examples demonstrate the above
`application.
`
`Example 1
`
`Figure 9.7(a) shows the representative plethysmographic waveforms in a steady
`state condition for the red and infrared detected signals. VmaxR(1) equals 1.01 V,
`and VminR(1) equals 1.00 V, for n = 1,2 and 3 pulses. VminR(n) is the detected
`optical signal minimum value at the minimum transmittance at the n pulse
`minimum. The modulation ratio for the maxima and minima red signal is:
`
`VmaxR n) 1.Olv=-=1,01.
`VmtoR(n) 1.001,
`
`For the infrared wavelength, VmaxIR(n) equals 1.01 V and VminIR(n) equals
`1.00 V and the determined modulation ratio is 1.01.
`Using these determined modulation ratios in the formula for calculating the
`ratio R provides:
`
`R= ln[Vmax R(n) / Vmin R(n)] 0.01
`ln[VmaxIR(n)/ Vmin IR(n)] 0.01
`
`A calculated R= 1 corresponds to an actual saturation value of about 81% when
`incorporated into the saturation equation. A saturation of 81% corresponds to a
`healthy patient experiencing a degree of hypoxia for which some corrective
`action would be taken.
`
`156
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0157
`
`APL_MAS_ITC_00015774
`
`11
`
`111
`
`140
`
`Design of pulse oximeters
`
`Red
`
`1.OTOV A
`
`Steady state saturation
`
`1.010V A
`
`Infrared
`
`1.000V V V
`1s
`2s
`
`3s
`
`1 000V
`(a)
`
`1s
`
`2s
`
`3s
`
`Vmaxl(R)
`
`Vmax2(R)
`
`Decreasing saturation
`
`Vmax3(IR)
`Vma*2(im A
`
`~ ~ ~ Vmax*R)
`
`Vminl(R)
`
`Vmin2(R)
`
`Vmaxi<1111 /
`
`vmln3{IR)·
`
`1\\-3
`
`Vmir,1 (24)
`
`Vmin2(183
`
`Vmin3(R)
`
`(b)
`Increasing saturation
`
`Vmax3(R)
`
`Vmax2(R)
`
`Vmail(IR)
`
`Vmaxl(A) / ~
`
`Vmina (R)
`
`Vmin2(R)
`
`Vmin I (A)
`
`V
`
`Vmax2(IR)
`
`~ -/ ~ Vmax*IR]
`
`Vminl(IR)
`
`M
`
`Vmin2(IR)
`
`Vmin)(IR)
`
`Figure 9.7. Graphical representation of detected optical signals during the steady state and
`transient conditions (Stone and Briggs 1992).
`
`Example 2
`
`Figure 9.7(b) shows the representative plethysmographic waveforms for a patient
`during desaturation or decreasing saturation transient conditions for the red and
`infrared detected signals having optical pulses n = 1, 2, and 3. However, in this
`transient example, it is known at n = 1, that the actual saturation of the patient is
`very close to that during the steady state conditions in example 1. In this transient
`example, the detected values are as follows for both the red and infrared signals:
`
`157
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0158
`
`APL_MAS_ITC_00015775
`
`1
`
`Signal processing algorithms
`
`141
`
`tmax( 1)= LOS
`tmin C | ) = 1.2 s
`tmax (2) = 2.0 s
`tmin (2) = 2.2 s
`imax (3) = 3.0 s
`tmin (31 - 3.2 s
`
`VmaxRCI) = 1.012 V
`VminR(1) = 1.000 V
`VmaxR(2) = 1.002 V
`Vm nR(2) = 0.990 V
`VmaXR(3)= 0.992 V
`VminRO) = 0.980 V
`
`Vmax IR( 1)=1.008 V
`VminIRO)= 1.000 V
`KmaXIR(2) = 1.018 V
`VminlR(2)= 1.010 V
`VmaxIR(3) = 1.028 V
`VminIR(3) = 1.020 V
`
`Calculating the oxygen saturation ratio R at n = 1, using the detected optical
`signal provides the following
`
`R=
`
`ln[Vmax R(1) / Vmin Ron
`ln[Vmax IR(1) / Vmin IR(1)]
`= ln[ 1.012 / 1.000] / ln[1.008 /1.000]
`= ln[1.012] /ln[ 1.008]
`=0.012/0.008 =1.5.
`
`The calculated saturation ratio of 1.5 based on the detected transmittance
`corresponds to a calculated oxygen saturation of about 65 for the patient. which
`corresponds to severe hypoxia in an otherwise healthy patient. This contrasts with
`the known saturation of about 81% and demonstrates the magnitude of the
`underestimation of the oxygen saturation (overestimation of desaturation) due to
`the distortion in transmittance of the red and infrared light caused by transient
`conditions.
`Applying the correction algorithm to correct the distorted maximum
`transmittance point of the detected red signal during the transient condition:
`*
`VmaxR(1) = VmaxR(1) - [VmaxR(1) - VmaxR(2)] x
`
`[rmax ("- 'mir, ( 1)]
`[trnax (2) - tmax (1)]
`-1.012 -[1.012 -1.002] x [1.0 -1.2]/[1.0 - 2.0]
`=1.010.
`
`and correspondingly for the maximum transmittance of the detected infrared
`signal
`
`VmaxIR(1)* = 1.008 - [1.008 - 1.018] x [1.0 - 1.2] /[1.0 - 2.0-1
`= 1.010
`
`Thus, by replacing VrrtaXR(n) With vmaxR(n)* and replacing VmaxIR(n) with
`VmaxIR(n)* in the calculations for determining the oxygen saturation ratio R, we
`have
`
`R=
`
`ln[VmaxR(1) / VminRO)]
`ln[VmaxIR(1)~ / Vmin IR(1)]
`= ln[ 1.010 / 1.00] /ln[ 1.010 / 1.00]
`= 0.01/ 0.01
`= 1.0.
`
`158
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0159
`
`APL_MAS_ITC_00015776
`
`1, 1
`1 1~
`
`1
`
`111£~
`
`I
`
`1
`
`11
`
`142
`
`Design of pulse oximeters
`
`Thus, basing the saturation calculations on the corrected maximum transmittance
`values and the detected minimum transmittance values, the corrected R value
`corresponds to the same R for the steady state conditions and the actual oxygen
`saturation of the patient.
`
`Exampl.e 3
`
`Figure 9.7(c) shows the representative plethysmographic waveforms for a patient
`during desaturation or decreasing saturation transient conditions for the red and
`infrared detected signals having optical pulses n = 1, 2 and 3. However, in this
`transient example, it is known that at n = 2, the actual saturation of the patient is
`very close to that during the steady state conditions in example 1. In this transient
`example, the detected values are as follows for both the red and infrared signals:
`KnaxiRC ')= 1.002 V
`~1)=0 992 V
`VmaxIR(2) = 1 012 V
`VminIRC) = 1.002 V
`4„·11[IR(3) = 1.022 V
`KninIR(3) = 1,012 V
`
`KnimR(1) = 1,022 V
`VminRO) = 1,008 V
`VmaXR(2) = 1,0 12 V
`An
`V + R(2) = 0.998 V
`KnaxRO) = 1,002 V
`VminRO) = 0,988 V
`
`tinax (1) = 1,0 s
`f · (U = 1 2 s
`Inin
`tinax (2) = 2.0 s
`tinin (2) =22s
`trnax (3) = 3.0 s
`fmin(3) = 3.2 s
`
`Calculating the oxygen saturation ratio R at n = 2, using the detected optical
`signal provides the following
`R= ln[VmaxR(2)/ VininR(2)]
`In[Vmax IR(2) / Vmin IR(2)]
`= ln[ 1.012 / 0.998-1/ ln[1.012 / 1.002]
`= 0.01393 / 0.0099 = 1.4.
`
`Thus, the calculated saturation ratio of 1.4 based on the detected transmittance
`corresponds to a calculated oxygen saturation of about 51% for the patient, which
`corresponds to severe hypoxia in an otherwise healthy patient. This contrasts with
`the known saturation of about 81% and demonstrates the magnitude of the
`underestimation of the oxygen saturation (overestimation of desaturation) due to
`the distortion in transmittance of the red and infrared light caused by transient
`conditions.
`Applying the correction algorithm to correct the distorted minimum
`transmittance point of the detected red signal during the transient condition, we
`find the following:
`
`Vmin R(2)* = VminR(2) - [VminR(2) - Vmin R(1)] x ['max (2) - 'Inin (' )]
`['min (2) - 'max (1)]
`= 1.008 - [0.998 - 1.008] x [2.0 - 1.21/[2.2 - 1,21
`= 1.0
`
`and correspondingly for the minimum transmittance of the detected infrared
`optical signal we have:
`
`159
`
`MASIMO 2053
`Apple v. Masimo
`IPR2022-01300
`
`

`

`RX-0035.0160
`
`APL_MAS_ITC_00015777
`
`Signal processing algorithms
` x 0 . 8
`[ 1 . 0 0 2 - 0 . 9 9 2 ]
`
`143
`
`V m i n I R ( 2 ) ~ = 0 . 9 9 2 -
`
`= 1.0.
`
`Thus, by replacing VminR(n) with VminR(n)* and replacing VminIR(n) with
`VminIR(n)* in the calculations for determining oxygen saturation ratio R we have:
`
`R= ln[Kmu R(2) / Vinja R(2)* ]
`ln[Vmax IR(2) / VminIR(2) ]
`= ln[1,012 /1.01/ln[1.012 / 1,01
`= 1.0.
`
`1
`
`Thus, basing the saturation calculat