UNITED STATES PATENT AND TRADEMARK OFFICE
`________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`________________
`
`APPLE, INC.,
`Petitioner,
`
`v.
`
`ALIVECOR, INC.,
`Patent Owner
`________________
`
`IPR2021-00972
`U.S. Patent No. 10,638,941
`________________
`
`DECLARATION OF DR. IGOR EFIMOV
`IN SUPPORT OF PATENT OWNER’S RESPONSE
`
`AliveCor Exhibit 2016, Page 1
`
`

`

`
`
`I.
`
`TABLE OF CONTENTS
`
`
`
`Page
`
`BACKGROUND, QUALIFICATIONS, AND LEGAL
`UNDERSTANDING ....................................................................................... 1
`
`II.
`
`TECHNICAL BACKGROUND ..................................................................... 1
`
`A. Arrhythmias and Atrial Fibrillation ...................................................... 1
`
`B.
`
`C.
`
`D.
`
`Strokes ................................................................................................... 5
`
`Photoplethysmography (PPG) ............................................................... 7
`
`Electrocardiography (ECG) ................................................................. 12
`
`E. Myocardial Infarctions aka Heart Attacks .......................................... 15
`
`F.
`
`Epileptic Seizures ................................................................................ 17
`
`III. THE ’941 PATENT ....................................................................................... 19
`
`A. Overview ............................................................................................. 19
`
`B.
`
`Specification ........................................................................................ 19
`
`IV. CLAIM CONSTRUCTION .......................................................................... 20
`
`A. A POSITA’s Understanding of the Term “Arrythmia” ...................... 21
`
`V.
`
`LEVEL OF ORDINARY SKILL IN THE ART ........................................... 22
`
`VI. OVERVIEW OF THE PRIOR ART ............................................................. 24
`
`A.
`
`B.
`
`C.
`
`D.
`
`Shmueli ................................................................................................ 24
`
`Osorio .................................................................................................. 28
`
`Lee 2013 .............................................................................................. 31
`
`Chan ..................................................................................................... 32
`
`VII. THE CITED ART DOES NOT ESTABLISH THAT THE
`CHALLENGED CLAIMS ARE OBVIOUS ................................................ 32
`
`A. Neither Shmueli Nor Osorio Discloses Or Renders Obvious
`Arrhythmia Detection .......................................................................... 33
`
`1.
`
`Shmueli Does Not Render Obvious Arrhythmia
`Detection ................................................................................... 33
`
`2.
`
`Osorio Does Not Render Obvious Arrhythmia Detection ........ 36
`
`
`
`
`i
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`AliveCor Exhibit 2016, Page 2
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`
`
`B.
`
`C.
`
`Grounds 1-3 Fail Because Shmueli Does Not Render Obvious
`Using ECG Data To Confirm The Initial Detection Of An
`Irregular Heart Condition Using PPG Data ........................................ 39
`
`Grounds 1-3 Fail Because A POSITA Would Not Have Been
`Motivated To Combine Shmueli and Osorio ...................................... 44
`
`D. Ground 2 Fails Because The Combination Of Lee 2013 With
`Shmueli and Osorio, Were A POSITA Motivated To Make It,
`Would Not Render The Claims Obvious ............................................ 46
`
`
`
`ii
`
`
`
`
`
`
`
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`
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`AliveCor Exhibit 2016, Page 3
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`

`

`
`
`TABLE OF EXHIBITS
`
`DESCRIPTION
`U.S. Pat. No. 10,595,941 to Gopalakrishnan (“the ’941 Patent”)
`Excerpts from the Prosecution History of the ’941 Patent (“the
`Prosecution History”)
`Declaration of Dr. Bernard A. Chaitman
`PCT Patent Publication WO2012/140559 (“Shmueli”)
`U.S. Patent Publication 2014/0275840 (“Osorio”)
`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”)
`U.S. Patent Publication 2008/0004904 (“Tran”)
`U.S. Patent Publication 2014/0107493 (“Yuen”)
`U.S. Patent Publication 2015/0119725 (“Martin”)
`U.S. Provisional Application No. 61/794,540 (“OP”)
`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”)
`Tsipouras MG, Fotiadis DI. Automatic arrhythmia detection based
`on time and time-frequency analysis of heart rate variability.
`Computer Methods Programs Biomed. 2004 May; 74(2):95-108
`(“Tsipouras 2004”)
`Lu S, Zhao H, Ju K, Shin K, Lee M, Shelley K, Chon KH. Can
`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”)
`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”)
`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”)
`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”)
`
`iii
`
`EX. NO.
`1001
`1002
`
`1003
`1004
`1005
`1006
`
`1007
`1008
`1009
`1010
`1011
`
`1012
`
`1013
`
`1014
`
`1015
`
`1016
`
`
`
`
`
`
`AliveCor Exhibit 2016, Page 4
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`

`

`
`
`DESCRIPTION
`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”)
`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”)
`K. Douglas Wilkinson, “The Clinical Use of the
`Sphygmomanometer,” The British Medical Journal, 1189-90 (Dec.
`27, 1924) (“Wilkinson”)
`U.S. Pat. No. 6,095,984 (“Amano”)
`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
`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”)
`Heart Diseases _ Definition of Heart Diseases by Merriam-Webster
`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”)
`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)
`U.S. Provisional Application No. 61/915,113
`U.S. Provisional Application No. 61/953,616
`U.S. Provisional Application No. 61/969,019
`U.S. Provisional Application No. 61/970,551
`U.S. Provisional Application No. 62/014516
`U.S. Patent Publication No. 2012/0203491 (“Sun”)
`U.S. Patent No. 9,808,206 (“Zhao”)
`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”)
`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”)
`
`iv
`
`
`
`EX. NO.
`1017
`
`1018
`
`1019
`
`1020
`1021
`
`1022
`
`1023
`1024
`
`1025
`
`1026
`1027
`1028
`1029
`1030
`1031
`1032
`1033
`
`1034
`
`
`
`
`AliveCor Exhibit 2016, Page 5
`
`

`

`
`
`DESCRIPTION
`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”)
`AliveCor v Apple ITC Complaint Exhibit 11 (941 Infringement
`Chart)
`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”)
`Asl BM, Setarehdan SK, Mohebbi M. Support vector machinebased
`arrhythmia classification using reduced features of heart rate
`variability signal. Artif Intell Med. 2008 Sep; 44(1):51-64 (“Asl
`2008”)
`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”)
`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”)
`Sajda P. Machine learning for detection and diagnosis of disease.
`Annu Rev Biomed Eng. 2006; 8:537-65 (“Sajda 2006”)
`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”)
`Thong, YK, Woolfson, M, Crowe, JA, Hayes-Gill, B, Challis, R.
`(2002). Dependence of inertial measurements of distance on
`
`v
`
`
`
`EX. NO.
`1035
`
`1036
`
`1037
`
`1038
`
`1039
`
`1040
`
`1041
`
`1042
`
`1043
`
`1044
`
`1045
`
`
`
`
`AliveCor Exhibit 2016, Page 6
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`

`

`DESCRIPTION
`accelerometer noise, Meas. Measurement Science and Technology.
`13. 1163 (“Thong 2002”)
`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”)
`Excerpts from Marcovitch, Harvey. Black’s Medical Dictionary.
`London: A. & C. Black, 2005
`U.S. Pat. No. 7,894,888 (“Chan”)
`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”)
`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”)
`Letter from Michael Amon re Conditional Stipulation dated June 4,
`2021
`Declaration of Mr. Jacob Munford
`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)
`U.S. Provisional Application No. 61/895,995 (“Martin Provisional”)
`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”)
`Declaration of Dr. Igor Efimov In Support of Patent Owner’s
`Preliminary Response
`B. S. Kim and S. K. Yoo, “Motion artifact reduction in
`photoplethysmography using independent component analysis,”
`IEEE Transactions on Biomedical Engineering, vol. 53, no. 3, pp.
`566-568, March 2006, doi: 10.1109/TBME.2005.869784
`Mao et al., Motion Artifact Reduction In Photoplethysmography
`For Reliable Signal Selection, arXiv, Sep 6, 2021;
`arXiv:2109.02755
`Apple’s September 10, 2021 Disclosure of Initial Invalidity
`Contentions in Response to Individual Interrogatory Nos. 19-21 of
`AliveCor’s First Set of Interrogatories to Apple, In the Matter of
`
`
`
`
`
`
`
`vi
`
`
`
`
`
`EX. NO.
`
`1046
`
`1047
`
`1048
`1049
`
`1050
`
`1051
`
`1052
`1053
`
`1054
`1055
`
`2001
`
`2002
`
`2003
`
`2004
`
`
`
`
`AliveCor Exhibit 2016, Page 7
`
`

`

`
`
`EX. NO.
`
`DESCRIPTION
`Certain Wearable Electronic Devices with ECG Functionality and
`Components Thereof, Inv. No. 337-TA-1266
`
`
`
`
`
`2005
`
`2006
`
`2007
`
`2008
`
`2009
`
`2010
`
`2011
`
`2012
`
`2013
`
`2014
`
`2015
`
`2016
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`Certain Automated Storage and Retrieval Systems, Robots, and
`Components Thereof, Inv. No. 337-TA-1228, Order No. 6 Denying
`Respondents’ Motion For A Stay (Mar. 9, 2021)
`Certain Wearable Electronic Devices with ECG Functionality and
`Components Thereof, Inv. No. 337-TA-1266, Order No. 6 Setting
`Procedural Schedule (June 25, 2021)
`Respondent Apple Inc.’s Response to the Amended Complaint of
`AliveCor, Inc. Under Section 337 of the Tariff Act of 1930, As
`Amended, and Notice of Investigation, In the Matter of Certain
`Wearable Electronic Devices with ECG Functionality and
`Components Thereof, Inv. No. 337-TA-1266 (June 28, 2021)
`(Public)
`Apple’s August 18, 2021 List of Claim Terms To Be Construed, In
`the Matter of Certain Wearable Electronic Devices with ECG
`Functionality and Components Thereof, Inv. No. 337-TA-1266
`Joint Disclosure Of Proposed Claim Constructions, In the Matter
`of Certain Wearable Electronic Devices with ECG Functionality
`and Components Thereof, Inv. No. 337-TA-1266 (Sept. 13, 2021)
`Certain Wearable Electronic Devices with ECG Functionality and
`Components Thereof, Inv. No. 337-TA-1266, Order No. 12
`Construing the Terms of the Asserted Claims of the Patents at Issue
`(June 25, 2021)
`Apple’s September 24, 2021 Notice of Prior Art, In the Matter of
`Certain Wearable Electronic Devices with ECG Functionality and
`Components Thereof, Inv. No. 337-TA-1266
`Complaint for Patent Infringement, AliveCor, Inc. v. Apple, Inc.,
`Case 6:20-cv-01112-ADA (W.D. Tex.) (Dec. 7, 2020)
`Complaint, iRobot Corp. v. SharkNinja Operating LLC et al., Case
`1:21-cv-10155-FDS (D. Del.) (Jan. 28, 2021)
`Oct. 12, 2021 Email authorizing Petitioner’s Reply to Patent Owner
`Preliminary Response
`Apple’s Sept. 22, 2021 Opening Claim Construction Brief, In the
`Matter of Certain Wearable Electronic Devices with ECG
`Functionality and Components Thereof, Inv. No. 337-TA-1266
`Declaration of Dr. Igor Efimov In Support of Patent Owner’s
`Response
`
`
`
`vii
`
`AliveCor Exhibit 2016, Page 8
`
`

`

`
`
`
`
`EX. NO.
`2017
`
`2018
`2019
`2020
`
`2021
`2022
`
`2023
`
`2024
`
`2025
`
`2026
`
`2027
`
`2028
`
`2029
`
`
`
`
`
`
`
`DESCRIPTION
`Transcript of March 24, 2022 Deposition of Dr. Bernard A.
`Chaitman
`Transcript of February 3, 2022 Deposition of Dr. Collin Stultz
`Heart Disease Facts, https://www.cdc.gov/heartdisease/facts.htm
`Changes in Heart Activity May Signal Epilepsy
`https://neurosciencenews.com/epilepsy-heart-rate-3827/ (Mar. 9,
`2016)
`Intentionally Omitted
`Nina Sviridova & Kenshi Sakai, Human photoplethysmogram: New
`insight into chaotic characteristics, Chaos Solitons & Fractals 77
`(Aug. 2015)
`Tania Pereira et al., Photoplethysmography based atrial fibrillation
`detection: a review, NPJ Digit Med. (Jan. 10, 2020),
`https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954115/
`IR Efimov, et al., Optical mapping of repolarization and
`refractoriness from intact hearts, American Heart Association (Nov.
`1994)
`Josep Masip et al., Pulse oximetry in the diagnosis of acute heart
`failure, Rev Esp Cardiol (Engl Ed). (Oct. 2012)
`Eric J. Topol, High-performance medicine; the convergence of
`human and artificial intelligence, Nature Medicine, Vol. 25, 44-56
`(Jan. 2019)
`Bernard S. Chang, M.D. & Daniel H. Lowenstein, M.D.,
`Mechanisms of Disease: Epilepsy, N. Engl. J. Med., 1257-66 (2003)
`Epilepsies: diagnosis and management, National Institute for Health
`and Care Guidance (Jan. 11, 2012)
`Carol Chen-Scarabelli et al, Device-Detected Atrial Fibrillation,
`Journal of the American College of Cardiology, Vol. 65, No. 3, 2015
`
`
`
`
`viii
`
`AliveCor Exhibit 2016, Page 9
`
`

`

`
`
`1.
`
`I, Igor R. Efimov, Ph.D., have been retained by AliveCor, Inc.
`
`
`
`(“AliveCor” or “Patent Owner”) to provide certain expert opinions in connection
`
`with AliveCor’s Patent Owner response to the Petition for Inter Partes Review of
`
`U.S. Patent No. 10,638,941 (“the ’941 patent”), IPR2021-00971 (“the 971 Petition”)
`
`filed by Apple, Inc. (“Apple” or “Petitioner”).
`
`I.
`
`BACKGROUND, QUALIFICATIONS, AND LEGAL
`UNDERSTANDING
`
`2.
`
`I incorporate my Background and Qualifications section and Legal
`
`Understanding section from my declaration in support of Patent Owner’s
`
`Preliminary Response by reference. Ex. 2001.
`
`II. TECHNICAL BACKGROUND
`
`A. Arrhythmias and Atrial Fibrillation
`
`3.
`
`Normal heart rhythm is required to sustained life soon after conception
`
`and to death, because it assures normal pumping of blood which carries oxygen and
`
`nutrients throughout the body. Interruption of normal heart rhythm could result in
`
`death within 10 minutes. Irregular heartbeats and arrhythmias are associated with
`
`significant morbidity and mortality in patients. Ex. 1001, 1:17-18. Arrhythmias may
`
`occur continuously or intermittently. Ex. 1001, 1:18-19. Arrhythmias can be
`
`detected using non-invasive monitoring techniques. Ex. 1001, 1:21-22. Common
`
`arrhythmias include atrial fibrillation and supraventricular tachycardia. Ex. 1001,
`
`1:19-21.
`
`
`
`
`1
`
`AliveCor Exhibit 2016, Page 10
`
`

`

`
`
`4.
`
`An arrhythmia is an abnormal heart rhythm, which jeopardizes or stops
`
`
`
`necessary cardiac output leading to death. Normal heart rhythm is known as the sinus
`
`rhythm, because it originates in the small group of cardiac cells located in the Sino-
`
`Atrial Node, or simply sinus node. The sinus rhythm originates in the sinus node,
`
`but it also is controlled by the autonomic nervous system comprised of sympathetic
`
`and parasympathetic branches of the nervous system. Competition between the
`
`sympathetic and parasympathetic branches results in heart rate variability. In
`
`contrast, arrhythmias are distinguished by the anatomical site of their origin, with
`
`atrial and ventricular tachycardiac and fibrillation being major types that afflict
`
`millions of patients, and which are responsible for approximately 300,000 deaths per
`
`year in the USA.
`
`5.
`
`Continuously occurring arrhythmias may be diagnosed by palpating a
`
`radial pulse of an individual, auscultating heart sounds of an individual, recording a
`
`heart rate of an individual, or recording an electrocardiogram of an individual. Ex.
`
`1001, 1:35-40. Because continuously occurring arrhythmias are always present,
`
`these diagnosis techniques may be applied at any time. Ex. 1001, 1:40-43. For
`
`intermittent arrhythmias, however, the techniques must be applied when the
`
`arrhythmia is occurring in order to detect it. Ex. 1001, 43-49.
`
`6.
`
`Atrial fibrillation develops progressively, starting from infrequently
`
`occurring short episodes of “paroxysmal” AFib. At this early stage of AFib it is more
`
`
`
`
`2
`
`AliveCor Exhibit 2016, Page 11
`
`

`

`
`
`
`
`easily treatable, but unfortunately it is often asymptomatic and is known as “silent”
`
`AFib. A patient with silent AFib is unaware of the disease and thus is not being
`
`treated while being at risk of stroke. More advanced stages of AFib are known as
`
`“persistent” AFib and “permanent” AFib, and they are more and more difficult or
`
`even impossible to treat. Thus early detection and diagnosis of paroxysmal AFib,
`
`when the disease can be treated and stroke can be prevented, is ideal but difficult.
`
`7.
`
`Patients with paroxysmal AFib are at risk of stroke, but they are
`
`unaware of it and thus cannot be treated with blood thinners to prevent stroke. Early
`
`diagnosis of silent AFib is needed for potentially millions of such patients. Ex.
`
`20291, 2. Clinically, AFib is diagnosed by cardiologists using gold standard tool –
`
`12 lead ECG, or Holter monitors and similar wearable or implantable devices. These
`
`methods cannot help diagnosing silent AFib, because such patients have no reason
`
`or motivation to see a cardiologist and be prescribed a Holter monitor or 12-lead
`
`ECG. Many ECG studies of patients at risk of AFib (with history of diabetes, heart
`
`failure, age, etc) demonstrated that a significant percent of them do indeed have
`
`AFib, which was not diagnosed previously. Ex. 2029, 2,3, Fig. 6.
`
`
`1 I am personally familiar with the Device-Detected Atrial Fibrillation article
`attached as Exhibit 2029. I retrieved a copy from the ScienceDirect website on
`March 24, 2021. Both the ScienceDirect website and the Journal of the American
`College of Cardiology in which the article was published are known and respected
`in the field. Exhibit 2029 is a true and correct copy of Device-Detected Atrial
`Fibrillation.
`
`
`
`
`3
`
`AliveCor Exhibit 2016, Page 12
`
`

`

`
`
`8.
`
`AFib, however, is not the only kind of cardiac arrhythmia. There are
`
`
`
`many types of dangerous atrial and ventricular arrhythmias. As recognized in the
`
`Suzuki paper cited by Petitioner, “[t]here are 8 kinds of arrhythmia” recognized by
`
`the widely used Minnesota Code Manual of Electrocardiographic Finding (June
`
`1982). Ex. 1016, 1. Of these, only “atrial or junctional premature beat;” “ventricular
`
`premature beat;” “atrial fibrillation / atrial flutter;” “supraventricular tachycardia
`
`intermittent;” “sick sinus syndrome;” “sinus tachycardia;” and “sinus bradycardia”
`
`are “detectable on the basis of RR intervals.” Ex. 1016, 1.
`
`9.
`
`There are other kinds of arrhythmia as well. For example, Osorio
`
`recognizes another kind of arrhythmia referred to as “respiratory sinus arrhythmia.”
`
`Ex. 1005, [0043]. Respiratory sinus arrhythmia is a “cardiac vagal reflex” where
`
`heart rate increases during inhalation (breathing in) and decreases during exhalation
`
`(breathing out). Ex. 20202; Ex. 20233. Unlike the arrhythmia defined in the patent,
`
`
`2 I am personally familiar with the Changes in Heart Activity May Signal Epilepsy
`article attached as Exhibit 2020. I retrieved a copy from the Neuro Science News
`website on March 20, 2021. The Neuro Science News website in which the article
`was published is known and respected in the field. Exhibit 2020 is a true and correct
`copy of Changes in Heart Activity May Signal Epilepsy.
`3 I am personally familiar with the Photoplethysmography based atrial fibrillation
`detection: a review article attached as Exhibit 2023. I retrieved a copy from the
`National Library of Medicine website on March 24, 2021. Both the National Library
`of Medicine website and the npj Digital Medicine journal in which the article was
`published are known and respected in the field. Exhibit 2023 is a true and correct
`copy of Photoplethysmography based atrial fibrillation detection: a review.
`
`
`
`
`
`4
`
`AliveCor Exhibit 2016, Page 13
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`respiratory sinus arrhythmia is not “a cardiac condition in which the electrical
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`activity of the heart is irregular or is faster (tachycardia) or slower (bradycardia) than
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`normal.”
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`B.
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`Strokes
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`10. While atrial arrhythmias themselves could be asymptomatic, they
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`increase the likelihood of palpitations, shortness of breath, fainting, chest pain or
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`congestive heart failure, but above all are a root cause of blood clots and stroke. One
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`in five strokes are associated with AFib and one-third of cardiac arrhythmias
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`hospitalizations are due to AFib-related complications. Ex. 2023,1. Because this
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`correlation between AFib and Stroke so strong and, as mentioned above, AFib can
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`be so hard to detect, patients with stroke of undetermined cause are often
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`recommended continuous ECG monitoring to detect intermittent, silent, AFib. Ex.
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`2023, 1.
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`11. Mechanically, the chaotic heart rhythm and lack of synchronized atrial
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`contraction caused by AFib results in stasis in the left atrium where blood lingers in
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`the upper chambers of the heart. Ex. 2029, 4. In turn, this damages the atrial and
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`vessel walls and promotes coagulants in the blood. Ex. 2029, 4. The damages to
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`atrial and vessel walls activates platelets themselves coagulate in the slow moving
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`blood and form a clot. Ex. 2029, 4. As shown in the figure below, this clot breaks
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`free from the vessel wall and travels the via the arteries to the small blood vessels in
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`the brain causing a stroke.
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`Ex. 2029, Fig. 1.
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`12. Because clots and strokes are the immediate concern associated with
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`AFib, they are sometimes treated before the underlying arrhythmia. Ex. 1001, 1:56-
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`58. This is particularly true because long-undetected arrhythmia such as persistent
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`AFib are so difficult to treat, in many cases untreatable, especially in advanced stages
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`of persistent and permanent AFib. However, if the early stage, paroxysmal AFib, is
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`diagnosed early, it can often be readily treated by medications and/or catheter
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`ablation.
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`C.
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`Photoplethysmography (PPG)
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`13. A photoplethysmography (PPG) sensor can measure “a pulse pressure
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`signal resulting from the propagation of blood pressure pulses along arterial blood
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`vessels.” Ex. 2023, 1. PPG is “a pulse pressure waveform that originates from the
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`heart contraction and propagates through the vascular tree.” Ex. 2023, 1. PPG
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`waveforms have typical morphological components corresponding to landmark
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`events in the cardiac cycle. Ex. 2023, 2.
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`During the contraction of the left ventricle, blood is
`ejected out of the heart and propagates along the arterial
`tree, this corresponds to the initial positive slope of a PPG
`pulse. The systolic peak marks the maximum of the
`waveform. A decrease in amplitude following the systolic
`peak is marked by a local minimum, or the dicrotic notch,
`which corresponds to the closing of aortic valves
`separating the systolic and diastolic phases.
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`Ex. 2023, 2. A PPG waveform for a healthy patient, including the diastolic notch
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`and systolic peak, can be seen in the below image:
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`Ex. 20224, 4. When a longer time period is used for measuring the signal, the peaks
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`are more compressed:
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`4 I am personally familiar with the Human photoplethysmogram: New insight into
`chaotic characteristics article attached as Exhibit 2022. I retrieved a copy from the
`ScienceDirect website on March 20, 2021. Both the ScienceDirect website and
`Chaos, Solitions & Fractals journal in which the article was published is known and
`respected in the field. Exhibit 2022 is a true and correct copy of Human
`photoplethysmogram: New insight into chaotic characteristics.
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`14. The “primary clinical application of PPG is arterial blood oxygen
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`saturation (SpO2) estimation through pulse oximetry,” where “SpO2 is defined as
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`the percentage of oxygen saturation in the arterial blood.” Ex. 2023, 2. It is only
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`recently—well after the priority dates of the AliveCor patents, that new applications
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`of PPG “emerged for the continuous estimation of valuable cardiovascular
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`parameters in ambulatory settings.” Ex. 2023, 2.
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`15. A PPG signal has two main components: a DC component “which
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`represents light reflected/transmitted from static arterial blood, venous blood, skin
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`and tissues;” and an AC component “which arises from modulation in light
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`absorption due to changes in arterial blood volume.” Ex. 2023, 2. PPG measurement
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`can be carried out using two modes: transmission and reflectance. Ex. 2023, 2. In
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`transmission mode, “the light transmitted through the medium is detected by a
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`photodetector (PD), which is positioned in the opposite site of the light source.”
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`Transmission mode PPG measurements are “limited to the extremities of the body,
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`such as the fingertips,” and the location of the device “can interfere with daily routine
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`movements.” Ex. 2023, 2. In reflectance mode, “the PD detects light that is back
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`scattered or reflected from tissues, bone, and/or blood vessels, which means the light
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`source and PD are positioned on the same side.” Ex. 2023, 2. Reflectance mode PPG
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`can be measured at the wrist, such as on a smartwatch. Ex. 2023, 2.
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`16. PPG monitoring is reliable in measurements of oxygen saturation and
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`average heart rate, but historically has been found to be less reliable in detecting
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`arrhythmias, especially atrial arrhythmias, such as atrial fibrillation. Ex. 2023, 9
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`(noting in 2017 that while “PPG can be an alternative to ECG for AF detection, it
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`remains that in real-world applications, PPG-based AF detection could be limited by
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`a number of factors.”). Compared to an ECG, heart rate estimation is more
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`challenging when using a PPG signal. Ex. 2023, 2.
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`17.
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`In particular, motion artifacts, caused by the user’s physical activity
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`(e.g., arm movement), can create noisy signals resulting significantly reduced PPG-
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`signal quality. Ex. 2002. As a result, it is difficult to obtain a clean signal and extract
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`HR from contaminated PPG. Ex. 2002. Therefore, increasing the accuracy and
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`robustness of PPG-based heart rate estimation remains at the forefront of research in
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`this area even to this day. Ex. 2002; Ex. 2003.
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`Ex. 2002.
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`18. As Petitioner’s expert Dr. Stultz testified in the co-pending ITC
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`investigation, ECG—and not PPG—is the “gold standard” for arrhythmia detection.
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`Ex. 2018, 62:9-21; Ex. 1006 (“Gold standard data sets and subsets of critical ECG
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`arrhythmia alarms”); Ex. 2023, 3 (“ECG remains the gold standard for the
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`electrophysiological definition and recognition of arrhythmias, including AF
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`diagnosis.”). Dr. Stultz explained that “continuous PPG” is a “suboptimal
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`replacement” which “does not always result in a reliable signal and does not provide
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`any information about whether p-waves are present or absent in the underlying
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`ECG.” Ex. 2018, 62:9-21; Ex. 2023 (“Compared to ECG, PPG-based AF detection
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`is more challenging”). These p-waves are “needed to diagnose Afib.” Ex. 2018,
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`62:9-21.
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`D. Electrocardiography (ECG)
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`19.
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`“In conventional clinical practice, electrocardiography (ECG) at
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`hospital is used for diagnosis of arrhythmia.” Ex. 1016. An electrocardiogram, as its
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`name implies, is a measurement of the electrical activity of the heart. Typical ECGs,
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`including small Holter ECG devices, require connecting electrodes to the patient’s
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`chest to measure heart activity. Ex. 1016, 1.
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`20. The ECG waveform has several important features:
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`21. From the above, which I use when teaching ECG interpretation to
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`medical and engineering students, there are several important aspects to the ECG
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`waveform relevant to this proceeding. First is the P-wave, which reflects atrial
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`depolarization (activation). This wave indicates the start of a normal, healthy heart
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`beat. It is a smaller upward waveform reflecting excitation of the relatively smaller
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`muscle mass of the atria. Next is the QRS complex, which reflects the depolarization
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`(activation) of the ventricles. At the onset of the QRS complex the PR interval or PR
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`segment begins before the much larger R wave. The PR interval represents the time
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`it takes the initial signal to conduct through the atrio-ventricular node to cause the
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`ventricular excitation and contraction. The last important waveform, T-wave,
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`reflects repolarization of the ventricles, which completes cardiac cycle, and
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`corresponds to end of ventricular contraction. Duration and shape of all ECG
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`waveforms (P-wave, QRS-complex, T-wave) and intervals/segments (PR, QRS, ST,
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`QT) are important indicators of cardiac health or disease and are used in diagnosis
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`of heart disease.
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`22. By understanding each of these waves, a practitioner can see how each
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`chamber of the heart is contracting. Relevant here, a practitioner can see the order in
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`which the chambers contract and if each chamber contracts. Also important is the R-
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`R interval, which is the interval between the R waves of adjacent QRS complexes.
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`As Dr. Chaitman notes, when looking for an arrhythmia “[y]ou look for irregularities
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`. . . where you might drop a QRS complex . . . [or] if there are P waves present or
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`absent” this would indicate AFib. Ex. 2017, 13: 3-12; Ex. 2023. As such, the ECG
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`showing the otherwise difficult to detect P-wave is key for detecti