UNITED STATES PATENT AND TRADEMARK OFFICE
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`APPLE INC.,
`Petitioner,
`
`v.
`
`MASIMO CORPORATION,
`Patent Owner.
`
`IPR2022-01299
`U.S. Patent 7,761,127
`
`DECLARATION OF MOHAMED DIAB
`
`
`
`REDACTED
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`MASIMO 2102
`Apple v. Masimo
`IPR2022-01299
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`
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`APPLE INC.,
`Petitioner,
`
`v.
`
`MASIMO CORPORATION,
`Patent Owner.
`
`IPR2022-01299
`U.S. Patent 7,761,127
`
`DECLARATION OF MOHAMED DIAB
`
`
`
`REDACTED
`
`MASIMO 2102
`Apple v. Masimo
`IPR2022-01299
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`
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`IPR2022-01299
`Apple Inc. v. Masimo Corp.
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`1.
`
`I, Mohamed Diab, am making this declaration at the request of Patent
`
`Owner Masimo Corporation (“Masimo”) in the matter of the Inter Partes Review
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`No. IPR2022-01299 of U.S. Patent No. 7,761,127 (“the ’127 patent”). I understand
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`that Apple submitted the ’127 patent as Exhibit 1001 in these proceedings. The ’127
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`patent describes and claims the invention that came out of our development of a
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`sensor capable of noninvasively measuring carboxyhemoglobin. I understand that
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`this declaration is being submitted in this proceeding as Exhibit 2102.
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`2.
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`I gave deposition and hearing testimony in an ITC Investigation in
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`which Masimo asserts the ’127 patent and other patents against Apple. My
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`testimony in this declaration is similar to my testimony in the ITC Investigation.
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`3.
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`I started as an engineer at Masimo. My current position at Masimo is
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`fellow scientist. I started working at Masimo in 1989 and have worked there ever
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`since.
`
`4.
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`In 1986, I graduated from Cal State Fullerton with a Bachelor of
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`Science degree in electrical engineering with an emphasis on computer engineering.
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`5.
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`In the 1990s, I and the other engineers at Masimo were working on our
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`first pulse oximeter. I was involved in the hardware design, the sensor design, and
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`the algorithm design. The algorithm takes the signal from the sensor and calculates
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`pulse rate, oxygen saturation, and other parameters.
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`6.
`A pulse oximeter is a device that noninvasively measures physiological
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`parameters in a patient’s blood by transmitting light into a tissue site (such as a
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`finger) and measuring the light after it has passed through the tissue. Figure 1 of the
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`’127 patent depicts a pulse oximeter with a sensor attached to a patient’s finger.
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`7.
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`In a typical pulse oximeter, the sensor that attaches to a patient’s finger
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`contains: (1) two light sources, generally light-emitting diodes (LEDs), and (2) a
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`light detector (generally a photodetector). Top and bottom views of a representative
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`
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`Masimo rainbow® sensor are shown below.
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`IPR2022-01299
`Apple Inc. v. Masimo Corp.
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`Top view
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`Bottom view
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`8.
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`Oxygen saturation (“SpO2”) is a parameter measured noninvasively by
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`pulse oximeters. For an oxygen-saturation measurement, the LEDs typically
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`transmit red and infrared light into the patient’s finger. Some of the transmitted light
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`is absorbed by the tissue and pulsating blood flow in the finger. Bright red
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`oxygenated blood absorbs light differently than blue-green tinted deoxygenated
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`blood. The light detector measures the intensity of the light (i.e., amplitude) from
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`both wavelengths after it passes through the tissue. The ratio of the amplitude of the
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`measured pulsating intensity of the light detected at the red wavelength compared to
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`light detected at the infrared wavelength indicates the level of oxygen saturation.
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`Pulse oximeters typically have a calibration curve or lookup table that correlates
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`ratios of red to infrared wavelengths to SpO2 values. This curve reflects empirical
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`data of ratios to invasively measured oxygen saturation values determined with a
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`blood draw. Accurate measurements of saturation require the calibration curve to
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`correspond to the actual LED wavelengths during operation of the sensor.
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`9. Masimo has become a leading innovator in pulse oximeters that
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`measure oxygen saturation. I and other engineers at Masimo are inventors on
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`hundreds of patents for oxygen-saturation measurement using pulse oximeters. For
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`example, we were the first to develop pulse oximeters that could accurately measure
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`oxygen saturation while a patient is moving.
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`10. Masimo’s pulse-oximetry algorithms were already extremely accurate
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`in measuring oxygen saturation before the ’127 patent invention.
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`11.
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`In about 2001, we started a project at Masimo to work on noninvasively
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`measuring carboxyhemoglobin and other parameters within the hemoglobin species.
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`The parameters within the hemoglobin species include oxyhemoglobin (blood
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`oxygen saturation), carboxyhemoglobin, methemoglobin, and total hemoglobin.
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`These parameters are much more difficult to measure noninvasively than the
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`parameters traditionally measured by pulse oximetry.
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`12. When carbon monoxide binds with hemoglobin, it displaces the oxygen
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`and will not let the oxygen bind with hemoglobin for many hours to come. Thus, it
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`turns the hemoglobin into a dysfunctional hemoglobin, causing carbon monoxide
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`poisoning.
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`13. Firefighters are exposed to carbon monoxide and, thus, can suffer from
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`carbon monoxide poisoning. People that are exposed to furnaces or similar
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`appliances lacking good combustion can also get carbon monoxide poisoning.
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`14. Carbon monoxide poisoning is very hard to diagnose because it looks
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`like a flu. When people with high carbon monoxide poisoning go to the hospital,
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`they look bright red and look like they have a flu.
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`15.
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`Thus, the noninvasive measurement of carboxyhemoglobin was a
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`sought-after measurement to allow for early detection and treatment of carbon
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`monoxide poisoning. Before our invention of the ’127 patent, no company had been
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`able to noninvasively measure carboxyhemoglobin. To this day, no other company
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`offers a competitive product.
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`16. When Masimo started researching noninvasive measurement of
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`carboxyhemoglobin, we looked into how carboxyhemoglobin interacts with light
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`propagating through the tissue. I spent quite a bit of time looking into the theory
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`behind it. Then, we conducted computer simulations trying to understand whether
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`we could build a device that could measure carboxyhemoglobin in the tissue
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`noninvasively, with reasonable accuracy that is relevant to the field. These
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`simulations took about a year.
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`17.
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`The simulation results indicated that we could noninvasively measure
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`carboxyhemoglobin. We also found that we could measure methemoglobin and total
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`hemoglobin as well.
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`18. After I had worked on carboxyhemoglobin measurement for about two
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`years, Marcelo Lamego and others joined me on the rainbow® team. The name
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`rainbow® came from the number of colors, or wavelengths, of light emitted by the
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`LEDs needed in the sensor. Typically, Masimo’s pulse oximeters that measure
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`oxygen saturation use two LEDs with two wavelengths of light. Because the
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`carboxyhemoglobin sensors used eight or more wavelengths, we called them
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`rainbow® sensors.
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`19.
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`Exhibit 2131 is a true and correct copy of one of my research folders
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`related to carboxyhemoglobin measurement. The tab on the first page includes
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`“HbCO” in the label. “Hb” stands for hemoglobin and “CO” is carbon monoxide.
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`20.
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`The first page is the title page of a progress report we wrote in July
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`2003. The report is titled, “RAINBOW PROJECT: Feasibility Study for
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`Noninvasive Level Detection of Carbon Monoxide in Blood.” Mr. Lamego and I
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`wrote the project report with input from Ammar Al-Ali, as shown in the footer of
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`each page after the title page.
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`21.
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`In the report, we described a study we had done on 22 heavy smokers.
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`The study shows that our measurements at that time had an error of about plus or
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`minus six percent compared to the referee. We used about four sensors in the study.
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`Each of the sensors had nine LEDs.
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`22.
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`The error of about plus or minus six percent was a step in the right
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`direction and showed promise. However, the measurement was not accurate enough
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`for a medical device.
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`23.
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`
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`
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`
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`24. While considering new sensor designs, I decided to look at the data
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`itself and take a deeper look at what was causing the error.
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`25.
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`I noticed something peculiar about one of the four sensors we were
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`using. Specifically, one sensor stood out as having a bias. When a sensor has a bias,
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`that means the error is not random. Rather, the error is systematic. It is a hint that
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`the sensor has properties that sets it apart from the rest.
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`26.
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`Initially, I thought something was wrong with the sensor itself.
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`However, after careful examination of the sensor I found there was nothing wrong
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`with how the sensor was built.
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`27.
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`I dug deeper, spending a couple of weeks looking in detail into the data.
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`I found out that the sensor had a very sensitive LED whose wavelength was about
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`one and a half nanometers off of the other three LEDs. We had carefully picked the
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`LEDs to have about the same wavelength as each other, but this one LED was off
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`by one and a half nanometers. To put things into perspective, the sensitive
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`wavelength is 630 nm and this particular sensor had a wavelength of 631.5 nm.
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`-7-
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`28.
`I did a calculation and showed that, given the light absorption curve of
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`carboxyhemoglobin, the LED being off by one and a half nanometers explained the
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`bias in the sensor. We then started thinking about ways we could compensate for
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`the LED wavelength shift.
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`29. One cause of LED wavelength shift is the LED heating up. While the
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`eye may see an LED as having a single color or wavelength, such as red, the LED
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`wavelength has an emission spectrum that looks like a bell curve when measured
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`using a device called a spectrophotometer. The emission spectrum has a peak and
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`can be characterized by a weighted average called a centroid.
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`30.
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`If an LED heats up, which typically happens when an LED turns on,
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`the peak, as well as the centroid, shifts to longer wavelengths. A mere increase of
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`10 degrees Celsius in the LED temperature, which happens regularly when an LED
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`is turned on, can cause a 2 nm shift in the wavelength. If this shift is not corrected
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`it will render a carboxyhemoglobin measurement useless. We needed a technique
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`that can calculate or adjust for that wavelength shift. We considered many
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`techniques.
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`31. We had previously designed a wavelength detector. Exhibit 2026 is a
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`true and correct copy of an earlier Masimo patent (U.S. Patent No. 5,758,644)
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`describing measuring LED wavelengths in real time without using a temperature
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`sensor for the measurement, as shown in the patent figures below:
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`-8-
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`EX2026, Figs. 7, 9B. One embodiment described in that patent uses two
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`photodiodes, a beam splitter, and an integrating optical sphere to determine the
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`operating wavelengths of LEDs. Id., 20:9-28. However, this system was too
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`unwieldy to implement in a small device such as the rainbow® sensors.
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`32. We also thought we needed to know the junction temperature of the
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`LED to calculate the wavelength. The junction temperature of the LED is the
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`temperature at a location in the middle of the LED called the p-n junction. The LED
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`has two different materials called p and n, and the junction between them is the p-n
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`junction. If the junction temperature of an LED can be measured, the LED’s
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`operating wavelength can be calculated. We initially thought that measuring the
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`LED junction temperature to calculate the LED operating wavelength was
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`conceptually the simplest and most straightforward solution to wavelength shift.
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`Because each LED’s temperature changes based on complex interactions and is
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`different from the temperatures of the other LEDs, we also thought we would need
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`a separate thermistor for each LED to measure each LED’s junction temperature.
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`33. Many factors contribute to these complex interactions. Typically,
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`about 90% of an LED’s energy is converted into heat. Accordingly, placing multiple
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`LEDs in a typical finger-based sensor with a very small footprint can raise each
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`LED’s junction temperature and the temperature at the base of the LED by tens of
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`degrees Celsius. By contrast, a typical electronic chip has a large body area and
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`many legs connected to the circuit board, which helps dissipate the heat generated
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`inside the chip. By way of example, a small 8-pin electronic chip has a footprint of
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`approximately 6 x 10 millimeters, which is 1,500 times larger than the footprint of
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`an LED used in a rainbow® sensor. In addition, LEDs typically have different drive
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`currents that may change based on differences in light absorption in the patient’s
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`finger being measured. Accordingly, the amount of heat generated inside each LED
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`is not constant but changes from patient to patient. Further, the LEDs need to be
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`located near each other to minimize errors induced by varying photon mean path
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`length, which adds complexity because heat interactions between the LEDs affect
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`each of the LED’s temperatures. In addition, the LEDs need to be encapsulated to
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`isolate them from contact with the human body, and the encapsulation layer’s poor
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`heat conductivity limits heat dissipation. The rapid pulsing on and off of the LEDs
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`also causes rapid fluctuation in LED temperatures. Finally, ambient temperature and
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`skin temperature, which are not constant, affect the LED temperatures. Further, the
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`appropriate design of a substrate to have a thermal mass capable of stabilizing and
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`normalizing a bulk temperature will differ depending on the amount of heat injected
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`into the substrate by the LEDs and the arrangement of the LEDs, which may differ
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`significantly based on how many LEDs are needed and how much heat each LED
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`generates.
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`34. The net result of these and other factors is that each LED temperature
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`is dynamic and has complex interactions with other LEDs based on their drive
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`currents. Those complex interactions and the LEDs having different temperatures
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`from each other led us to initially believe we would need a separate thermistor for
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`each LED to measure each LED’s junction temperature.
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`35. However, we found that it was impractical to measure the LED junction
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`temperature. It is very difficult to locate, at the p-n junction of an LED, a
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`temperature sensor that can measure the LED junction temperature while a sensor in
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`a very small device is in operation. Because each LED has a different junction
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`temperature depending on the p-n junction type and the amount of energy pumped
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`into the LED, it would have been even more complicated and impractical to use
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`multiple temperature sensors to measure each LED junction temperature of the
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`multiple LEDs of the rainbow® sensors. Furthermore, in a sensor, the LED junction
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`temperature is not fixed. Rather, the LED junction temperature is dynamic. Our
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`tests showed that the LED junction temperature is influenced by the ambient as well
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`as the patient body temperatures. This implies that each LED’s wavelength is also
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`dynamic and must be measured in real time in order to correct for errors in the final
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`physiologic parameter measurement.
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`36. Therefore, we explored many different techniques. Eventually, we
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`came up with a hypothesis that maybe a single thermistor could measure temperature
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`of a thermal mass to which the LEDs are thermally bonded, and that we could
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`calibrate to each LED the measured temperature could be used to estimate the
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`operating wavelengths of each of the LEDs. I am not aware of this hypothesis being
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`disclosed or suggested by anyone before we tried it. Also, this hypothesis was
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`contrary to the intuitive belief, which we initially held, that measuring the LED
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`junction temperature or an ambient temperature near the LEDs would provide the
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`most accurate estimate of LED junction temperature for correcting wavelength shift.
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`37. We could not just look up, in a technical data sheet or patent, a
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`previously designed circuit board with a thermal mass that would work for our
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`purpose. We also could not just buy an off-the-shelf circuit board with a thermal
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`mass that would work for our purpose. Circuit boards are specially designed for a
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`specific purpose within a specific product. I am not aware of any circuit boards
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`before the ones we developed for the rainbow® sensors that were designed to have
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`a thermal mass whose temperature could be used to reliably estimate the operating
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`wavelengths of multiple LEDs. Eventually, however, we were able to design a
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`thermal mass and measure the temperature of the thermal mass to reliably estimate
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`the operating wavelengths of the LEDs. We initially formed the thermal mass from
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`four internal copper layers of the substrate. The copper layers were thermally
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`connected to the LEDs and a temperature sensor. The temperature sensor measured
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`the temperature of the thermal mass. We used the measured temperature to estimate
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`the LED wavelengths. When we used this technique with a properly designed
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`thermal mass, the error dropped dramatically.
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`38.
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`I was initially skeptical that a thermal mass could be properly designed
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`so that the temperature of the thermal mass could be used to reliably estimate the
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`operating wavelengths of multiple dissimilar LEDs. This technique had not been
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`done before and had not been shown to work. Further, I knew that the measured
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`temperature of the thermal mass would not be the LED junction temperature and
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`would never match the LED junction temperature. I also knew that each LED would
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`have a different junction temperature and a different wavelength variation with
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`temperature. Therefore, a single temperature measurement could not possibly match
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`all of the junction temperatures. In view of these issues, I thought it would be
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`difficult, and maybe even impossible, to design a thermal mass that could produce a
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`single temperature measurement that would correlate with all LED junction
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`temperatures to allow estimating all LED operating wavelengths with sufficient
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`accuracy. However, by calibrating each LED wavelength against the temperature of
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`the thermal mass we were able to reliably estimate multiple LED wavelengths. I
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`was pleasantly surprised by how accurately we could predict the operating
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`wavelength of each LED of the rainbow® sensor.
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`39. The thermal mass does two things that allow its bulk temperature, as
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`measured by the thermistor, to be meaningful for estimating LED wavelengths. It
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`stabilizes the bulk temperature so that it does not fluctuate too quickly to be useful
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`for estimating LED wavelengths. And it normalizes the temperatures at the base of
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`the LEDs so that the variation in base temperatures is small enough that the single
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`thermistor measurement can represent all of the LED temperatures and be used to
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`accurately estimate LED wavelengths. The stabilization and normalization do not
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`mean the measured bulk temperature does not change at all over time or that there is
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`no temperature variation across the thermal mass. However, the temporal and spatial
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`changes in temperature are small enough that the bulk temperature can be used to
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`accurately estimate all the LED wavelengths. Both stabilization and normalization
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`provide a bulk temperature that can be used to accurately estimate all the LED
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`wavelengths.
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`40. We did two things to confirm that we could reliably estimate the LED
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`operating wavelengths using this technique. I conducted hundreds of simulations
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`using a finite element partial differential equation solver software product called
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`Flex PDE. This software product allowed me to virtually build and simulate sensors
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`with specific properties and geometries, run a simulation on each sensor, and get
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`results that are meaningful and realistic without physically building the sensor itself
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`to optimize performance.
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`41. Exhibit 2103 is a true and correct copy of printed output from some of
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`the simulations that I ran.
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`.
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`42.
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` In conducting the simulations, I made a model of sensors with
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`specifically defined thermal and geometric properties, simulated applying heat to the
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`sensor, such as by turning on one or both of the LEDs, and watched the results. The
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`image above shows a steady-state temperature distribution for one of the simulated
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`sensors.
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`43.
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`44.
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`I recently created a model similar to the design of a representative early
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`rainbow® sensor using the same simulation software I used when developing the
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`invention. Below is an output plot from a simulation of that model, with the top
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`three curves showing the temperatures of three LEDs and the bottom curve labeled
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`“d” showing the thermal mass temperature at the location of the thermistor on the
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`other side of the substrate, both as a function of time.
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`EX2135
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`-17-
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`Exhibit 2135 is a true and correct copy of the above output plot. The three LEDs
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`have different temperatures because they have different drive currents. Exhibit 2136
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`is a true and correct copy of a temperature-distribution map showing a steady-state
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`temperature distribution of a cross-section of the simulated representative early
`
`rainbow® sensor.
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`45. As shown, the bottom right corner of Exhibit 2135 includes a schematic
`
`showing the placement of 8 LEDs (shown as small squares) on the substrate.
`
`Starting at the left corner of the output plot of Exhibit 2135 shown above, when the
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`LED is not turned on, the temperature of each of the LEDs and the thermal mass is
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`295 Kelvin (the ambient temperature), which is equivalent to 71.33 degrees
`
`Fahrenheit. This simulation assumed the sensor is in a roughly room-temperature
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`environment.
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`46. As shown, upon simulating the turning on of the LED, both the LED
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`temperatures and the thermal mass temperature begin to rise. The depicted
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`undulation in the LED temperatures occurs because the LEDs are sequentially turned
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`on and off, which is how pulse oximeters and other light-based physiological
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`measurement systems work.
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`47. As shown, the temperature of the thermal mass is stabilized and follows
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`along with the temperatures of the LEDs, while maintaining a delta (difference in
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`temperature) in between. The lack of undulation in the temperature of the thermal
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`mass indicates that the temperature is stabilized and does not experience rapid
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`temperature changes. The maintenance of the delta between the thermal mass and
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`the LEDs means that the thermal mass, as measured by the thermistor, does not
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`actually match the temperatures of the LEDs. However, the thermistor-measured
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`temperature of the thermal mass is correlated with the temperatures of the LEDs so
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`that the temperature of the thermal mass can be used to reliably estimate the
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`operating wavelengths of the LEDs. The thermal mass temperature provides a
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`baseline temperature shared by the base of the LEDs, and from which all the LED
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`junction temperatures can be estimated, so that the thermal mass temperature can be
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`used to accurately estimate all the LED operating wavelengths. The thermal mass
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`resists temperature change on a scale relevant to estimating the LED wavelengths.
`
`48. The actual rainbow® sensors have multiple LEDs but a single
`
`thermistor that measures the temperature of a single thermal mass. The temperatures
`
`of the LEDs differ from each other and from the temperature of the thermal mass.
`
`However, the single thermistor-measured temperature of the thermal mass correlates
`
`with the LED temperatures, and, thus, can be used to reliably estimate the operating
`
`wavelengths of the multiple LEDs.
`
`49. The temperature of the thermal mass, or the temperatures of the LEDs,
`
`do not remain constant. As the graph above shows, the LED temperatures naturally
`
`rise after the LEDs are turned on. Further, the thermal mass temperature naturally
`
`-19-
`
`REDACTED
`
`MASIMO 2102
`Apple v. Masimo
`IPR2022-01299
`
`
`
`IPR2022-01299
`Apple Inc. v. Masimo Corp.
`follows all of the LED temperatures but is not equal to any of the LED temperatures
`
`as heat is distributed from the LEDs into the thermal mass. In addition, the thermal
`
`mass temperature is different from the LED temperatures and sits on top of the
`
`environment temperature, 295 Kelvin in the above simulation. And in the multi-
`
`LED rainbow® sensors, the temperatures of the LEDs are different from each other.
`
`Therefore, temperature stabilization in the ’127 patent is not about keeping the
`
`thermal mass and LED temperatures constant or equal to each other, but about
`
`maintaining a correlation between thermal mass and LED temperatures, so that the
`
`temperature of the thermal mass can be used to reliably estimate LED wavelengths.
`
`50. Exhibit 2137 is a true and correct copy of the temperature-distribution
`
`map below, which shows a steady-state temperature-distribution of the top surface
`
`of the simulated representative early rainbow® sensor substrate to which the base of
`
`the LEDs are bonded.
`
`-20-
`
`REDACTED
`
`MASIMO 2102
`Apple v. Masimo
`IPR2022-01299
`
`
`
`IPR2022-01299
`Apple Inc. v. Masimo Corp.
`
`EX2137
`
`
`
`While the temperature-distribution map shows a temperature gradient across the
`
`substrate, the differences in base temperature at the location of the LEDs are small
`
`enough that the single thermistor measurement can be used to accurately estimate
`
`all LED wavelengths.
`
`51.
`
`I also recently created a model similar to the design of the current
`
`rainbow® sensors using the same simulation software I used when developing the
`
`invention. Exhibit 2138 is a true and correct copy of an output plot from a simulation
`
`-21-
`
`REDACTED
`
`MASIMO 2102
`Apple v. Masimo
`IPR2022-01299
`
`
`
`IPR2022-01299
`Apple Inc. v. Masimo Corp.
`of that model, shown below with the top three curves showing the temperatures of
`
`three LEDs and the bottom curve labeled “d” showing the thermal mass temperature
`
`at the location of the thermistor, both as a function of time.
`
`EX2138
`
`
`
`As shown, the bottom right corner of Exhibit 2138 includes a schematic showing the
`
`placement of 8 LEDs (shown as small squares) on the substrate. The three LEDs
`
`have different temperatures because they have different drive currents or different
`
`locations on the substrate. Exhibit 2139 is a true and correct copy of a temperature-
`
`-22-
`
`REDACTED
`
`MASIMO 2102
`Apple v. Masimo
`IPR2022-01299
`
`
`
`IPR2022-01299
`Apple Inc. v. Masimo Corp.
`distribution map showing a steady-state temperature distribution of a cross-section
`
`of the simulated representative current rainbow® sensor.
`
`52. As shown above in the plot of Exhibit 2138, starting at the left corner,
`
`when the LED is not turned on, the temperature of each of the LEDs and the thermal
`
`mass is 295 Kelvin (ambient temperature), which is equivalent to 71.33 degrees
`
`Fahrenheit. This simulation assumed the sensor is in a roughly room-temperature
`
`environment. This simulation shows that the thermal mass of the current rainbow®
`
`sensors achieves the same results as the thermal mass of the early rainbow® sensors,
`
`including that the thermal mass temperature is not equal to, but correlates with, all
`
`of the LED temperatures, so that the thermal mass temperature can be used to
`
`accurately estimate LED wavelengths. The thermal mass resists temperature change
`
`on a scale relevant to estimating LED wavelengths.
`
`53. Exhibit 2140 is a true and correct copy of the temperature-distribution
`
`map below, which shows a steady-state temperature-distribution of the top surface
`
`of the simulated representative current rainbow® sensor substrate to which the base
`
`of the LEDs are bonded.
`
`-23-
`
`REDACTED
`
`MASIMO 2102
`Apple v. Masimo
`IPR2022-01299
`
`
`
`IPR2022-01299
`Apple Inc. v. Masimo Corp.
`
`EX2140
`
`
`
`While the temperature-distribution map shows a temperature gradient across the
`
`substrate, the differences in base temperature at the location of the LEDs are small
`
`enough that the single thermistor measurement can be used to accurately estimate
`
`all LED wavelengths.
`
`54.
`
`In parallel to the simulations we did during development of the
`
`invention, we also ran experiments on actual rainbow® sensors by using a
`
`spectrophotometer to detect, very accurately, the wavelength of each LED. By
`
`testing actual rainbow® sensors, we showed that, if we measured the temperature of
`
`-24-
`
`REDACTED
`
`MASIMO 2102
`Apple v. Masimo
`IPR2022-01299
`
`
`
`IPR2022-01299
`Apple Inc. v. Masimo Corp.
`the thermal mass in the sensor and calibrated for each LED, we could estimate the
`
`LED operating wavelengths while the sensor was in operation typically within plus
`
`or minus 0.1 nanometer (one standard deviation).
`
`55. Specifically, we verified the accuracy of the wavelength-estimation
`
`algorithm in the rainbow® sensors by comparing actual wavelengths measured by a
`
`spectrophotometer with the wavelengths estimated by the algorithm, which relies on
`
`the thermal mass bulk temperature and LED drive current as inputs. For example,
`
`the spectrophotometer may detect an actual wavelength of 632.2 nm, while the
`
`wavelength-estimation algorithm calculates a wavelength of 632.1 nm, indicating an
`
`error of only 0.1 nm. Masimo created characterization stations, where it has tested
`
`and calibrated and continues to test and calibrate every single rainbow® sensor, both
`
`early and current, to ensure the accuracy of wavelength estimation in each sensor.
`
`These tests are done for each LED and particular drive current so the accuracy of
`
`wavelength estimation at different drive currents is verified for each LED. EX2128
`
`is a set of output plots from a characterization station. One such plot is shown below.
`
`-25-
`
`REDACTED
`
`MASIMO 2102
`Apple v. Masimo
`IPR2022-01299
`
`
`
`IPR2022-01299
`Apple Inc. v. Masimo Corp.
`
`EX2128
`
`
`
`The circles on the plot correspond to actual measured and estimated wavelength
`
`values. The x-axis indicates the actual operating wavelength (centroid) of an LED
`
`as measured by a referee (a spectrophotometer). The y-axis indicates the operating
`
`wavelength (centroid) of an LED as estimated by the wavelength-estimation
`
`algorithm that uses the thermistor measurement of bulk temperature as an input. The
`
`diagonal is the identity line where ideally all measurement points should lie in order
`
`to exactly match the referee. As shown, the circles are very close to the diagonal
`
`line. This close correlation confirms that the bulk temperature closely correlates
`
`with, and allows reliable estimation of, LED operating wavelengths. Note that there
`
`-26-
`
`REDACTED
`
`MASIMO 2102
`Apple v. Masimo
`IPR2022-01299
`
`
`
`IPR2022-01299
`Apple Inc. v. Masimo Corp.
`are two clusters of data points in the graph, each cluster belonging to a different bulk
`
`temperature which is intentionally induced while calibrating the sensor. The plot
`
`shown above
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