`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`
`
`
`
`
`
`
`
`
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`APPLE INC.,
`Petitioner,
`
`v.
`
`ALIVECOR, INC.,
`Patent Owner.
`
`
`
`
`
`
`
`
`
`
`
`
`IPR2021-00970
`Patent 9,572,499
`
`
`
`
`
`
`
`
`
`
`
`PETITIONER’S REPLY TO
`PATENT OWNER’S RESPONSE
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`
`
`LIST OF EXHIBITS
`
`APPLE-1001
`
`U.S. Pat. No. 9,572,499 to Gopalakrishnan (“the ’499 patent”)
`
`APPLE-1002
`
`Excerpts from the Prosecution History of the ’499 patent (“the
`Prosecution History”)
`
`APPLE-1003
`
`Declaration of Dr. Bernard A. Chaitman
`
`APPLE-1004
`
` PCT Patent Publication WO2012/140559 (“Shmueli”)
`
`APPLE-1005
`
` U.S. Patent Publication 2014/0275840 (“Osorio”)
`
`APPLE-1006
`
` Li Q, Clifford GD, “Signal quality and data fusion for false
`alarm reduction in the intensive care unit,” J Electrocardiol.
`2012 Nov-Dec; 45(6):596-603 (“Li-2012”)
`
`APPLE-1007
`
` U.S. Patent Publication 2008/0004904 (“Tran”)
`
`APPLE-1008
`
` U.S. Patent Publication 2014/0107493 (“Yuen”)
`
`APPLE-1009
`
` U.S. Patent Publication 2015/0119725 (“Martin”)
`
`APPLE-1010
`
` U.S. Provisional Application No. 61/794,540 (“Osorio
`Provisional”)
`
`APPLE-1011
`
` Lee J, Reyes BA, McManus DD, Mathias O, Chon KH. Atrial
`fibrillation detection using a smart phone. International Journal
`of Bioelectromagnetism, Vol. 15, No. 1, pp. 26 - 29, 2013
`(“Lee 2013”)
`
`APPLE-1012
`
` Tsipouras MG, Fotiadis DI. Automatic arrhythmia detection
`based on time and time-frequency analysis of heart rate
`variability. Comput Methods Programs Biomed. 2004 May;
`74(2):95-108 (“Tsipouras 2004”)
`
`APPLE-1013
`
` Lu S, Zhao H, Ju K, Shin K, Lee M, Shelley K, Chon KH. Can
`
`i
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`photoplethysmography variability serve as an alternative
`approach to obtain heart rate variability information? J Clin
`Monit Comput. 2008 Feb; 22(1):23-9 (“Lu 2008”)
`
`APPLE-1014
`
` Selvaraj N, Jaryal A, Santhosh J, Deepak KK, Anand S.
`Assessment of heart rate variability derived from finger-tip
`photoplethysmography as compared to electrocardiography. J
`Med Eng Technol. 2008 Nov-Dec; 32(6):479-84 (“Selvaraj
`2008”)
`
`APPLE-1015
`
` Lu G, Yang F, Taylor JA, Stein JF. A comparison of
`photoplethysmography and ECG recording to analyse heart rate
`variability in healthy subjects. J Med Eng Technol. 2009;
`33(8):634-41 (“Lu 2009”)
`
`APPLE-1016
`
` Suzuki T, Kameyama K, Tamura T. Development of the
`irregular pulse detection method in daily life using wearable
`photoplethysmographic sensor. Annu Int Conf IEEE Eng Med
`Biol Soc. 2009; 2009:6080-3 (“Suzuki 2009”)
`
`APPLE-1017
`
` Reed MJ, Robertson CE, Addison PS. Heart rate variability
`measurements and the prediction of ventricular arrhythmias.
`QJM. 2005 Feb; 98(2):87-95 (“Reed 2005”)
`
`APPLE-1018
`
` Schäfer A, Vagedes J. How accurate is pulse rate variability as
`an estimate of heart rate variability? A review on studies
`comparing photoplethysmographic technology with an
`electrocardiogram. Int J Cardiol. 2013 Jun 5; 166(1):15-29
`(“Schafer 2013”)
`
`APPLE-1019
`
` K. Douglas Wilkinson, “The Clinical Use of the
`Sphygmomanometer,” The British Medical Journal, 1189-90
`(Dec. 27, 1924) (“Wilkinson”)
`
`APPLE-1020
`
` U.S. Pat. No. 6,095,984 (“Amano”)
`
`APPLE-1021
`
` B.K. Bootsma et. al, “Analysis of R-R intervals in patients with
`atrial fibrillation at rest and during exercise.” Circulation 1970;
`41:783-794
`
`ii
`
`
`
`APPLE-1022
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
` Frits L. Meijler and Fred H. M. Wittkampf, “Role of the
`Atrioventricular Node in Atrial Fibrillation” Atrial Fibrillation:
`Mechanisms and Management, 2nd ed. 1997 (“Meijler”)
`
`APPLE-1023
`
` Heart Diseases _ Definition of Heart Diseases by Merriam-
`Webster
`
`APPLE-1024
`
` Acharya UR, Joseph KP, Kannathal N, Lim CM, Suri JS. Heart
`rate variability: a review. Med Biol Eng Comput. 2006 Dec;
`44(12):1031-51 (“Acharya 2006”)
`
`APPLE-1025
`
` Saime Akdemir Akar, Sadık Kara, Fatma Latifoğlu, Vedat
`Bilgiç. Spectral analysis of photoplethysmographic signals: The
`importance of preprocessing. Biomedical Signal Processing and
`Control, 2013; 8(1):16-22 (Akar 2013)
`
`APPLE-1026
`
` U.S. Provisional Application No. 61/915,113
`
`APPLE-1027
`
` U.S. Provisional Application No. 61/953,616
`
`APPLE-1028
`
` U.S. Provisional Application No. 61/969,019
`
`APPLE-1029
`
` U.S. Provisional Application No. 61/970,551
`
`APPLE-1030
`
` U.S. Provisional Application No. 62/014516
`
`APPLE-1031
`
` U.S. Patent Publication No. 2012/0203491 (“Sun”)
`
`APPLE-1032
`
` U.S. Patent No. 9,808,206 (“Zhao”)
`
`APPLE-1033
`
` Kleiger RE, Stein PK, Bigger JT Jr. Heart rate variability:
`measurement and clinical utility. Ann Noninvasive
`Electrocardiol. 2005 Jan; 10(1):88-101 (“Kleiger 2005”)
`
`APPLE-1034
`
` Chen Z, Brown EN, Barbieri R. Characterizing nonlinear
`heartbeat dynamics within a point process framework. IEEE
`Trans Biomed Eng. 2010 Jun; 57(6):1335-47 (“Chen 2010”)
`
`iii
`
`
`
`APPLE-1035
`
`APPLE-1036
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
` Karvonen, J., Vuorimaa, T. Heart Rate and Exercise Intensity
`During Sports Activities. Sports Medicine 5, 303–311 (1988)
`(“Karvonen 1988”)
`
` Yu C, Liu Z, McKenna T, Reisner AT, Reifman J. A method
`for automatic identification of reliable heart rates calculated
`from ECG and PPG waveforms. J Am Med Inform Assoc. 2006
`May-Jun; 13(3):309-20 (“Yu 2006”)
`
`APPLE-1037
`
` AliveCor v Apple ITC Complaint Exhibit 11 (499 Infringement
`Chart)
`
`APPLE-1038
`
` Tavassoli, M, Ebadzadeh, MM, Malek H. (2012). Classification
`of cardiac arrhythmia with respect to ECG and HRV signal by
`genetic programming. Canadian Journal on Artificial
`Intelligence, Machine Learning and Pattern Recognition. 3. 1-
`13 (“TavassoLi-2012”)
`
`APPLE-1039
`
` Asl BM, Setarehdan SK, Mohebbi M. Support vector machine-
`based arrhythmia classification using reduced features of heart
`rate variability signal. Artif Intell Med. 2008 Sep; 44(1):51-64
`(“Asl 2008”)
`
`APPLE-1040
`
` Yaghouby F., Ayatollahi A. (2009) An Arrhythmia
`Classification Method Based on Selected Features of Heart
`Rate Variability Signal and Support Vector Machine-Based
`Classifier. In: Dössel O., Schlegel W.C. (eds) World Congress
`on Medical Physics and Biomedical Engineering, September 7 -
`12, 2009, Munich, Germany. IFMBE Proceedings, vol 25/4.
`Springer, Berlin, Heidelberg (“Yaghouby 2009”)
`
`APPLE-1041
`
` Dallali, A, Kachouri, A, Samet, M. (2011). Integration of HRV,
`WT and neural networks for ECG arrhythmias classification.
`ARPN Journal of Engineering and Applied Sciences. VOL. 6.
`74-82 (“Dallali 2011”)
`
`APPLE-1042
`
` Sajda P. Machine learning for detection and diagnosis of
`disease. Annu Rev Biomed Eng. 2006; 8:537-65 (“Sajda 2006”)
`
`iv
`
`
`
`APPLE-1043
`
`APPLE-1044
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
` Aaron Smith. Smartphone Ownership – 2013 Update. Pew
`Research Center. June 5, 2013 (“Smith 2013”)
`
` C. Narayanaswami and M. T. Raghunath, “Application design
`for a smart watch with a high resolution display,” Digest of
`Papers. Fourth International Symposium on Wearable
`Computers, 2000, pp. 7-14 (“Narayanaswami 2000”)
`
`APPLE-1045
`
` Thong, YK, Woolfson, M, Crowe, JA, Hayes-Gill, B, Challis,
`R. (2002). Dependence of inertial measurements of distance on
`accelerometer noise, Meas. Measurement Science and
`Technology. 13. 1163 (“Thong 2002”)
`
`APPLE-1046
`
` AliveCor’s ITC Complaint filed on April 20, 2021 in “Certain
`Wearable Electronic Devices With ECG Capability and
`Components Thereof” ITC-337-3545-20210420 (“ITC
`Complaint”)
`
`
`APPLE-1047
`
` Excerpts from Marcovitch, Harvey. Black’s Medical
`Dictionary. London: A. & C. Black, 2005
`
`APPLE-1048
`
` U.S. Pat. No. 7,894,888 (“Chan”)
`
`APPLE-1049
`
` Hu YH, Palreddy S, Tompkins WJ. A patient-adaptable ECG
`beat classifier using a mixture of experts approach. IEEE
`Transactions on Bio-medical Engineering. 1997 Sep;
`44(9):891-900 (“Hu-1997”)
`
`APPLE-1050
`
` Strath SJ, Swartz AM, Bassett DR Jr, et al. Evaluation of heart
`rate as a method for assessing moderate intensity physical
`activity. Medicine and Science in Sports and Exercise. 2000
`Sep; 32(9 Suppl):S465-70 (“Strath 2000”)
`
`APPLE-1051
`
`Letter from Michael Amon re Conditional Stipulation dated
`June 4, 2021
`
`APPLE-1052
`
`Declaration of Mr. Jacob Munford
`
`
`
`v
`
`
`
`APPLE-1053
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
` Order Staying Case Pending Institution of And/Or Final
`Determination in Parallel ITC Matter (AliveCor Inc. v. Apple
`Inc., 6:20-cv-01112-26 (W.D.Tex. May 6, 2021)
`
`APPLE-1054
`
` U.S. Provisional Application No. 61/895,995 (“Martin
`Provisional”)
`
`APPLE-1055
`
` AliveCor’s District Court Complaint filed on May 25, 2021 in
`AliveCor, Inc. v. Apple Inc., 3:21-cv-03958 (N.D.Cal. May 25,
`2021) (“Antitrust Complaint”)
`
`APPLE-1056
`
` Apple’s Rebuttal Markman Brief of October 13, 2021
`
`APPLE-1057
`
` Email from Jeremy Monaldo re Prior Art Narrowing dated
`November 17, 2021
`
`APPLE-1058
`
` Declaration of Michael Amon
`
`APPLE-1059
`
` Declaration of Noah Graubart
`
`APPLE-1060
`
` U.S. Pat. No. 5,176,137 to Erickson et al. (“Erickson”)
`
`APPLE-1061
`
` U.S. Pat. No. 7,598,878 to Goldreich (“Goldreich”)
`
`APPLE-1062
`
` U.S. Pat. App. Pub. No. 2005/0177051 to Almen (“Almen”)
`
`APPLE-1063
`
` U.S. Pat. App. Pub. No. 2019/0376014 to Efimov (“Efimov”)
`
`APPLE-1064
`
`
`
`International App. Pub. No. WO 2005/110238 to Goldreich
`(“Goldreich-2”)
`
`
`
`APPLE-1065
`
` Yang et al., “Hardware-Mappable Cellular Neural Networks for
`Distributed Wavefront Detection in Next-Generation Cardiac
`Implant,” Adv. Intell. Syst. 2022, 2200032 (2022)
`
`APPLE-1066
`
`
`
`“Atrial fibrillation (part 1) – When the heart loses its rhythm,”
`https://www.hirslanden.com/en/international/private-hospital-
`
`vi
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`group/news/artikel-vorhofflimmern-i.html, accessed June 2,
`2022
`
`APPLE-1067
`
`
`
`“Holter heart monitor,”
`https://medlineplus.gov/ency/imagepages/8810.htm, accessed
`June 2, 2022
`
`APPLE-1068
`
`“Holter monitor (24h),” https://www.mountsinai.org/health-
`library/tests/holter-monitor-24h, accessed June 22, 2022
`
`APPLE-1069
`
`
`
`June 3, 2022 Deposition Transcript of Dr. Igor Efimov
`
`APPLE-1070
`
` AliveCor’s ITC Post-Hearing Brief (CBI Redacted), dated
`April 15, 2022
`
`APPLE-1071
`
`
`
`January 31, 2022 ITC Deposition Transcript of Dr. Igor Efimov
`
`APPLE-1072
`
`
`APPLE-1073
`
`
`APPLE-1074
`
`Excerpts from Transcript of Conference in Certain Wearable
`Electronic Devices with ECG Functionality and Components
`Thereof, 337-TA-1266, dated March 31, 2022 (pages 828-1101)
`
`Excerpts from Transcript of Conference in Certain Wearable
`Electronic Devices with ECG Functionality and Components
`Thereof, 337-TA-1266, dated April 1, 2022 (pages 1102-1375)
`
` Li, Qiao, and Gari D. Clifford. "Dynamic time warping and
`machine learning for signal quality assessment of pulsatile
`signals." Physiological measurement 33.9 (2012): 1491 (“Li
`and Clifford”).
`
`APPLE-1075
`
` Schlesinger, Daphne E., and Collin M. Stultz. "Deep learning
`for cardiovascular risk stratification." Current Treatment
`Options in Cardiovascular Medicine 22.8 (2020): 1-14.
`
`APPLE-1076
`
` D’Agostino Sr, Ralph B., et al. "General cardiovascular risk
`profile for use in primary care: the Framingham Heart Study."
`Circulation 117.6 (2008): 743-753.
`
`vii
`
`
`
`APPLE-1077
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
` Antman, Elliott M., et al. "The TIMI risk score for unstable
`angina/non–ST elevation MI: a method for prognostication and
`therapeutic decision making." Jama 284.7 (2000): 835-842.
`
`APPLE-1078
`
` Morrow, David A., et al. "Application of the TIMI risk score
`for ST-elevation MI in the National Registry of Myocardial
`Infarction 3." Jama 286.11 (2001): 1356-1359.
`
`APPLE-1079
`
` Pocock, Stuart J., et al. "Predicting survival in heart failure: a
`risk score based on 39 372 patients from 30 studies." European
`heart journal 34.19 (2013): 1404-1413.
`
`APPLE-1080
`
` Yu, Chenggang, et al. "A method for automatic identification of
`reliable heart rates calculated from ECG and PPG waveforms."
`Journal of the American Medical Informatics Association 13.3
`(2006): 309-320.
`
`APPLE-1081
`
` December 22, 2021 Collin Stultz ITC Invalidity Report
`(Redacted)
`
`APPLE-1082
`
` February 3, 2022 Deposition Transcript of Collin Stultz (ITC)
`
`APPLE-1083
`
` RDX-0003 Stultz Demonstratives (ITC)
`
`APPLE-1084
`
` APPLE’s ITC Post-Hearing Brief (CBI Redacted), dated April
`15, 2022
`
`APPLE-1085
`
` Bansal, Nikhil, Avrim Blum, and Shuchi Chawla. "Correlation
`clustering." Machine learning 56.1 (2004): 89-113.
`
`
`
`
`
`viii
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`
`
`
`TABLE OF CONTENTS
`
`I.
`II.
`
`1.
`2.
`3.
`
`INTRODUCTION ........................................................................................... 1
`THE PRIOR ART RENDERS ARRHYTHMIA DETECTION OBVIOUS .. 3
`A.
`Record Evidence Confirms Obvious ..................................................... 3
`Testimony From Both Experts Reinforce the Petition .................................... 3
`Shmueli And The ’499 Patent Both Reinforce The Petition ........................... 6
`Secondary Evidence Also Reinforces The Petition ......................................... 8
`B.
`AliveCor’s Response Arguments Fail ................................................... 9
`AliveCor’s Interpretation of Shmueli Deviates From its Disclosure .............. 9
`1.
`AliveCor Ignores Non-Limiting Language In Osorio ................................... 14
`2.
`III. A POSITA WOULD HAVE BEEN MOTIVATED TO COMBINE
`SHMUELI AND OSORIO ............................................................................ 16
`IV. SHMUELI-OSORIO-HU 1997 RENDERS OBVIOUS MACHINE
`LEARNING ................................................................................................... 18
`A. AliveCor Does Not Refute the Applicability of Machine Learning to
`Shmueli’s ECG Data ........................................................................... 20
`Hu 1997 Renders Obvious Applying Machine Learning to Shmueli’s
`SpO2/PPG Data .................................................................................... 22
`Shmueli’s Learning of New Detection Parameters Renders Obvious
`Machine Learning ................................................................................ 25
`V. ALIVECOR’S “POSITA” DEFINITION IS WRONG ................................ 27
`VI. CONCLUSION .............................................................................................. 29
`
`B.
`
`C.
`
`ix
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`
`I.
`
`INTRODUCTION
`For the independent claims, AliveCor repeats the same two arguments that
`
`were raised pre-institution and that were rejected in the Institution Decision.
`
`AliveCor contends that the post-institution record warrants reconsideration of these
`
`preliminary findings. Not so. If anything, the record reinforces the obviousness
`
`arguments provisionally adopted in the Institution Decision. Testimony from
`
`AliveCor’s own expert, Igor Efimov, includes several admissions that contradict
`
`each of AliveCor’s primary arguments. The record evidence therefore confirms
`
`that the asserted prior art demonstrates unpatentability.
`
`AliveCor’s first argument is premised on a superficial distinction between
`
`Shmueli’s “irregular heart condition” and the claim term “arrhythmia.” AliveCor
`
`criticizes Shmueli for not literally using the claim term within its disclosure, but
`
`AliveCor’s analysis either overlooks or ignores several teachings that demonstrate
`
`obviousness. Indeed, AliveCor’s Dr. Efimov admitted that a POSITA would have
`
`understood that “irregular heart condition” included arrhythmia as a subcategory at
`
`the relevant time (and even today).
`
`Dr. Efimov also contradicted his opinions regarding Osorio. APPLE-1069,
`
`56:23-59:9. He recognized that Osorio detects arrhythmias, but failed to offer any
`
`justification for the position that Osorio’s detection of arrhythmias is somehow
`
`diminished as part of its process of detecting neurological conditions. APPLE-
`
`1
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`1069, 68:6-70:7. Osorio describes detecting “any pathological condition” and it is
`
`undisputed that “arrhythmia” is a pathological condition. Id., 50:17-22; 51:6-10.
`
`AliveCor’s second argument against the Shmueli-Osorio combination is
`
`similarly deficient. AliveCor does not dispute or rebut the Petition’s primary
`
`motivation for the combination—benefits of activity monitoring to detect
`
`pathological conditions, which would have included arrhythmias. Pet., 24-28.
`
`AliveCor instead argues that Shmueli and Osorio are non-analogous—an argument
`
`that relies on an unreasonably narrow view of Osorio and on AliveCor’s other
`
`argument that neither Shmueli nor Osorio disclose arrhythmia detection. Osorio is
`
`not so limited and the other argument is flawed.
`
`AliveCor’s last argument focuses on “machine learning” claims, which only
`
`apply generic machine learning algorithms to detect arrhythmia. As acknowledged
`
`by Dr. Efimov, the disclosed machine learning algorithms were well-known by
`
`December 2013. APPLE-1069, 169:10-170:14. Further, using machine learning
`
`to detect arrhythmias based on heart rate parameters (e.g., HR and HRV) derived
`
`from either PPG or ECG was well-known. APPLE-1069, 103:13-104:25, 115:7-21
`
`121:10-122:6; APPLE-1073, 1124:15-1125:7. The fact that Hu 1997 uses heart
`
`rate parameters derived from ECG does not change the obviousness of using
`
`machine learning to detect arrhythmia based on the data collected by Shmueli and
`
`Osorio.
`
`2
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`II. THE PRIOR ART RENDERS ARRHYTHMIA DETECTION
`OBVIOUS
`A. Record Evidence Confirms Obvious
`Shmueli “offers an expansive definition” of the term “irregular heart
`
`condition” and “[a] POSITA would have understood that the term ‘irregular heart
`
`condition’ refers to arrhythmia…” Pet., 10-11 (citing APPLE-1003, ¶49). Despite
`
`AliveCor’s contrary pre-institution argument, the Institution Decision recognized
`
`that irregular heart condition “at a minimum, encompass[es]—arrhythmia, and,
`
`thus, disclos[es] the detection of arrhythmia.” Dec., 44. The post-institution
`
`record reinforces this preliminary finding.
`
`Testimony From Both Experts Reinforce the Petition
`1.
`AliveCor’s position relies principally on declaration testimony from Dr.
`
`Efimov. Resp., 51-56 (citing Ex. 2016, ¶¶63-68). In deposition, however, Dr.
`
`Efimov admitted that an irregular heart condition is a “general category” and that
`
`arrhythmia is a “subcategory.” APPLE-1069, 28:3-24.1 He further confirmed that
`
`a POSITA by the Critical Date would have had the same understanding. Id.
`
`
`1 Dr. Efimov also made several factually incorrect statements. He testified that
`
`sinus tachycardia is “a symptom of a neurological system but not an arrhythmia per
`
`se[,]” which contradicts undisputed disclosures in the ’499 patent. Compare
`
`APPLE-1069, 58:1-2 and APPLE-1001, 1:31-42, Table 2.
`
`3
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`Indeed, even Shmueli itself teaches “[p]rocedures for analyzing oximetry
`
`measurements to detect various irregular heart conditions…” APPLE-1004, 12:22-
`
`31.
`
`Dr. Chaitman’s testimony on Shmueli’s use of “irregular heart condition,” in
`
`contrast, is unrebutted; AliveCor failed to produce any evidence to the contrary. It
`
`instead concludes—without even citing to the record—that Dr. Chaitman
`
`“admitted during cross-examination that [Shmueli] only uses SpO2 measurements
`
`to detect ‘irregular heart conditions[.]’” Resp., 10. This mischaracterizes Dr.
`
`Chaitman’s testimony since AliveCor’s questions were limited to specific
`
`embodiments of Shmueli, not its entire disclosure. Ex. 2017, 71:31-90:12.
`
`With its narrow focus on SpO2 measurement, AliveCor appears to argue that
`
`Shmueli’s detection of irregular heart conditions is based exclusively on
`
`monitoring blood gas composition. Resp., 43 (citing Ex. 2016, ¶48); Ex. 2016,
`
`¶48. However, Shmueli’s title includes “pulse oximetry,” indicating that its
`
`disclosure is not limited only to oxygen saturation measurements. This is
`
`reinforced by Shmueli’s reference to “pulse oximetry,” “pulse oximeter” and
`
`“photoplethysmography,” which both have uses beyond just oxygen saturation
`
`measurements. APPLE-1004, Title, 8:24-30. Indeed, Dr. Efimov testified that a
`
`POSITA would have understood that a “pulse oximeter” includes both PPG and
`
`SpO2 sensors, and measures both pulse and blood gas. APPLE-1069, 83:11-25,
`
`4
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`84:16-85:2. This is consistent with Shmueli’s teaching that its device can derive
`
`“physiological parameters such as pulse rate, pulse amplitude, pulse shape, rate of
`
`blood flow etc.” and “scan the derived physiological parameters to detect various
`
`irregularities of the heart condition.” APPLE-1004, 13:14-22. To the extent that
`
`AliveCor’s position is that Shmueli’s detection of irregular heart conditions is
`
`based only on blood gas composition measurements, Shmueli’s disclosure and Dr.
`
`Efimov’s testimony refutes it. APPLE-1069, 120:6-13.
`
`AliveCor also is wrong that Shmueli’s “SpO2 measurements” necessarily
`
`precludes arrhythmia detection. Dr. Efimov admitted that pulse (and thus, heart
`
`rate) can be derived from pulse oximeters and SpO2 sensors. It is undisputed that
`
`heart rate data is used to detect arrhythmia. APPLE-1069, 84:4-12, 120:6-13,
`
`121:2-17. Dr. Chaitman similarly confirmed that physiological parameters used
`
`for arrhythmia detection (pulse rate, pulse amplitude, etc.) can be derived from
`
`Shmueli’s SpO2 measurements. Ex. 2017, 90:5-12, 120:6-13. Both parties’
`
`experts therefore agree that data used to detect arrhythmia is derived from
`
`Shmueli’s SpO2 measurements using a pulse oximeter sensor, which Dr. Efimov
`
`described as measuring both pulse and blood gas. APPLE-1069, 120:6-13.
`
`Thus, the expert testimony contradicts AliveCor’s incorrect view of
`
`Shmueli’s disclosure of SpO2 measurements, and also contradicts AliveCor’s
`
`conclusion that arrhythmia detection is necessarily precluded by Shmueli’s SpO2
`
`5
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`
`measurements.
`
`Beyond expert testimony, AliveCor’s position fails to rebut or even address
`
`other record evidence that reinforces the Petition: (1) disclosures in Shmueli and
`
`the ’499 patent specification, and (2) secondary evidence, including references
`
`cited within Shmueli.
`
`Shmueli And The ’499 Patent Both Reinforce The Petition
`2.
`AliveCor broadly alleges that “Shmueli does not give a POSITA any
`
`direction indicating to a POSITA that arrhythmias are included in the context of its
`
`discussion.” Resp., 54. This attempt to narrow Shmueli runs contrary to express
`
`descriptions within its disclosure. AliveCor tries to avoid this disclosure by
`
`denying that Shmueli provides an “expansive definition”; it “merely states that
`
`‘irregular heart condition’ is ‘intended to include all such new technologies a
`
`priori.’” Resp., 53 (fn 3) (citing APPLE-1004, 16:3-5). AliveCor’s analysis is
`
`incomplete—ignoring an earlier clause in Shmueli stating that “many relevant
`
`methods and systems will be developed and the scope of the terms herein,
`
`particularly of the term irregular heart condition are intended to include all such
`
`new technologies a priori.” APPLE-1004, 16:3-5. Through this reference to
`
`“irregular heart condition,” Shmueli makes clear that the term is not limited in the
`
`manner that AliveCor suggests (i.e., excluding arrhythmia). AliveCor’s position is
`
`at odds with Shmueli’s own disclosure.
`
`6
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`AliveCor’s myopic view of Shmueli also causes it to ignore key discussion
`
`of the other relevant terminology. Specifically, Shmueli teaches “intermittent”
`
`heart conditions as one example of “irregular heart conditions.” APPLE-1004,
`
`9:24-29, 3:4-9. Dr. Efimov also confirmed that intermittently-occurring heart
`
`conditions are types of arrhythmias. APPLE-1069, 23:25-24:14; 30:1-5.
`
`Moreover, Shmueli reinforces the Petition through disclosures of the
`
`challenges imposed by continuous cardiac monitoring when detecting
`
`intermittently-occurring heart conditions. APPLE-1004, 9:21-23. Shmueli
`
`describes that its invention “resolves this problem by providing a combined
`
`oximetry and electrocardiogram measuring device” in which “oximetry
`
`measurement is performed continuously and/or repeatedly…” APPLE-1004,
`
`9:24-29. Shmueli proposes using oximetry measurement to detect intermittent
`
`irregular heart-related events or irregular heart activity “without requiring the fixed
`
`wiring of the ECG device to the patient.” Id. Discussion of the problem of cardiac
`
`monitoring associated with detecting intermittent heart conditions—requiring
`
`continuous monitoring by ECG—confirms that Shmueli contemplates techniques
`
`for detecting cardiac arrhythmias. In fact, the ’499 patent specification describes
`
`devices “configured to continuously measure one or more physiological signals of
`
`a user” and that “continuously measurement may be made with a wrist or arm
`
`band…” APPLE-1001, 2:30-2:61. This is precisely the type of device disclosed in
`
`7
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`Shmueli, which “preferably performs measurements of intermittent irregular heart-
`
`related events without requiring the fixed wiring of the ECG device to the patient.”
`
`APPLE-1004, 9:24-29.
`
`Moreover, both Shmueli and the ’499 patent discuss the limitations of Holter
`
`devices in the context of cardiac monitoring, further suggesting a similar focus on
`
`arrhythmia detection. APPLE-1004, 2:21-3:3; APPLE-1001, 1:57-2:4. Both Dr.
`
`Efimov’s declaration and deposition testimony confirm that Holter devices are
`
`used to detect arrhythmia. APPLE-1069, 30:24-31:9; Ex. 2016, ¶7. Thus, there is
`
`no doubt that Shmueli is directed to arrhythmia detection.
`
`Secondary Evidence Also Reinforces The Petition
`3.
`The Petition noted that irregular heart condition “refers to arrhythmia, which
`
`is one of the most obvious (if not the most obvious) types of ‘irregular heart
`
`condition[s]’ that can be determined using PPG and ECG data.” Pet., 11 (citing
`
`APPLE-1003, ¶49). AliveCor concedes “an arrhythmia might be an irregular heart
`
`condition.” Resp., 53. But it still contends that arrhythmia “cannot be an
`
`‘irregular heart condition’ as that phrase is used in Shmueli.” Id. However,
`
`secondary evidence in this record contradicts AliveCor.
`
`APPLE-1066 references “irregular activity” in discussing “atrial
`
`fibrillation,” which Dr. Efimov identified in deposition as the most common type
`
`of diagnosed arrhythmia. APPLE-1066, 4; APPLE-1069, 23:5-9. Similarly,
`
`8
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`APPLE-1067 and APPLE-1068 use the term “irregular heart activity” in reference
`
`to Holter devices, which both experts agree are used for arrhythmia detection.
`
`APPLE-1067, 1; APPLE-1068, 1.
`
`Shmueli also cites several background references that relate to arrhythmia
`
`detection and describes them as “the most relevant prior art.” APPLE-1004, 3:10-
`
`13, 9:1-29. One example is U.S. 7,598,878 to Goldreich, which discloses a wrist-
`
`worn device with an SpO2 sensor. APPLE-1061, 13:23-29. Goldreich teaches that
`
`the SPO2 sensor can provide information regarding heart rate, such as a Pulse
`
`Wave Transit Time (PWTT). Id., 16:54-58. Further, claim 5 of Goldreich recites
`
`selection of “at least one physiological parameter” from a group that includes
`
`“arrhythmia of the heart.” Id., Claim 5.
`
`Another example is an international search report issued in Shmueli that also
`
`cites multiple references directed to arrhythmia detection. U.S. 2005/177051 to
`
`Almen discloses a wrist-watch with heart rate sensors, including an ECG and a
`
`pulse oximeter that is used to detect arrhythmia. APPLE-1062, [0014], [0051],
`
`[0055], [0062].
`
`B. AliveCor’s Response Arguments Fail
`1.
`AliveCor’s Interpretation of Shmueli Deviates From its
`Disclosure
`AliveCor’s position is untenable as it requires every example of “irregular
`
`heart condition” to exclude arrhythmia. Otherwise, Shmueli renders the recited
`
`9
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`arrhythmia detection obvious since the term “at a minimum, encompass[es]”
`
`arrhythmia. Dec., 44.
`
`AliveCor advances three key arguments, each of which lacks evidentiary
`
`support and fails to rebut the Petition. Resp., 51-56.
`
`a)
`
`AliveCor’s First Argument Confirms The Breadth of
`“Irregular Heart Condition”
`AliveCor initially states that “there is no evidence a POSITA at the time of
`
`the invention of the ’499 Patent, reading Shmueli, would have understood
`
`Shmueli’s use of the phrase ‘irregular heart condition’ to include arrhythmias…”
`
`Resp., 53-54. As discussed in Section II.A, this is wrong based on the cited
`
`evidence. Beyond Shmueli, AliveCor further confirms the breadth of the term
`
`since it states “there are numerous other irregular heart conditions…” Resp., 53.
`
`If “irregular heart conditions” is understood to include “numerous” conditions and
`
`Shmueli discloses detecting “various irregular heart conditions,” then it would
`
`have been obvious that arrhythmia (which is the most common type of heart
`
`condition) is one example of an irregular heart condition detected by Shmueli.
`
`APPLE-1004, 12:29-31. AliveCor even states that irregular heart condition is a
`
`“genus” of arrhythmia. Resp., 54. Thus, AliveCor acquiesces that Shmueli’s
`
`disclosure of irregular heart condition renders arrhythmia detection obvious. Dec.,
`
`44.
`
`10
`
`
`
`b)
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`AliveCor’s Second Argument Contradicts Record
`Evidence Of Oximetry Measurements Used For
`Arrhythmia Detection
`AliveCor’s second argument is conclusory; it assumes no possible
`
`configuration for using SpO2 (PPG or oximetry) measurements for arrhythmia
`
`detection exists. AliveCor merely posits that “PPG was a ‘suboptimal’ tool for
`
`measuring arrhythmias,” but fails to provide meaningful evidence of
`
`incompatibility. Resp., 55. This is not surprising since several references teach the
`
`use of pulse oximetry for arrhythmia detection. Amano discloses an arrhythmia
`
`detecting apparatus with a “pulse wave detecting means” that “non-invasively
`
`detects the pulse wave form” and “an arrhythmia detecting means” that “detects
`
`arrhythmia by monitoring changes in the pulse waveform detected by the pulse
`
`wave detecting means.” APPLE-1020, Abstract. Amano’s Figure 3 depicts a
`
`wrist-worn device (similar to the device disclosed in Shmueli) that includes a band
`
`52. APPLE-1020, FIG. 3.
`
`11
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`
`APPLE-1020, FIG. 3
`
`
`
`Amano further teaches that pulse detection may be “designed so as to receive []
`
`light reflected when the detection site on the body is irradiated with light having a
`
`wavelength of 300 to 700 nm, and detect the received light signal as a pulse
`
`waveform.” APPLE-1020, 3:58-4:3. This references reflectance plethysmography
`
`(PPG), which is used to detect arrhythmias. Because Amano issued on 8/1/2000,
`
`before Shmueli’s 4/11/2011 priority date and the Critical Date, Amano illustrates
`
`the existence of wrist-worn devices configured to use SpO2/PPG data to detect
`
`arrhythmia before the relevant dates.
`
`AliveCor ignores Shmueli’s disclosure that element 38 is configured to
`
`12
`
`
`
`Case IPR2021-00970
`Attorney Docket No: 50095-0032IP1
`“derive from the SpO2 measurement physiological parameters such as pulse rate,
`
`pulse amplitude, pulse shape…” APPLE-1004, 13:14-22. Dr. Efimov confirmed
`
`that these parameters can be used to determine other parameters (heart rate, heart
`
`rate variability) used to detect arrhythmia. APPLE-1069, 120:17-122:8. AliveCor
`
`also fails to acknowledge or address that Shmueli is titled “Pulse Oximetry
`
`Measurement Triggering ECG Measurement,” and Dr. Efimov’s testimony that
`
`“pulse oximetry” includes both pulse and blood gas measurements. Id., 83:6-7
`
`(“So pulse oximetry measurements both pulse and oxygen”).
`
`AliveCor repeatedly alleges that Shmueli is focused on detecting oth