Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 1 of 19
`
`6:20-cv-1112
`
`Exhibit “2”
`
`

`

`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 2 of 19
`Case 612°‘CV'01112'ADA D°°“mfillflflillil"01111111111111llifilifllfllflilfililllllllll
`
`US010638941B2
`
`(12) United States Patent
`US 10,638,941 B2
`(10) Patent N0.:
`
` Albert et al. (45) Date of Patent: *May 5, 2020
`
`
`(72)
`
`(54) DISCORDANCE MONITORING
`.
`(71) Apphcam: AliveCor, Inc
`.
`_
`InVemors: DaV‘d E- Albert: Oklahoma Cltys OK
`(Us); 01?“ Df‘WOOds Sal} “311101500:
`CA (Us): Ra“ GOPalakmhnans San
`FranCISCOs CA (Us)
`.
`.
`.
`.
`.
`(73) ASSlgnee' Egan 1‘1“" Mount“ Vlewa CA
`
`( * ) Notice:
`
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U'S'C' 154(1)) by 0 days.
`This patent is subject to a terminal dis-
`claimer.
`
`.
`(21) Appl‘ No" 16/158412
`.
`Flledi
`
`(22)
`
`Oct- 11, 2018
`
`(65)
`
`Prior Publication Data
`
`US 2019/0104948 A1
`
`Apr. 11, 2019
`
`(2006.01)
`(2006.01)
`(2006.01)
`
`A613 5/046
`A613 5/0464
`A613 5/0408
`(52) us. Cl.
`CPC ............ A613 5/0205 (2013.01) A613 5/681
`(2013.01); A613 5/7267 (2013.01); A613
`5/02405 (2013.01); A613 5/02438 (2013.01);
`A613 5/046 (2013.01); A613 5/0464
`(2013.01); A613 5/04085 (2013.01); A613
`5/1118 (2013.01); A613 2562/0219 (2013.01)
`(58) Field of Classification Search
`.
`None
`.
`.
`See application file for complete search history.
`References Cited
`
`(56)
`
`U.S. PATENT DOCUMENTS
`
`12/2010 Andrews et a1.
`7,846,106 B2
`9,839,363 B2 * 12/2017 Albert .................. A61B 5/0205
`10,537,250 B2 *
`1/2020 Albert .................... A61B 5/681
`2007/0213624 A1
`9/2007 Reisfeld et al.
`2012/0109675 A1
`5/2012 Ziegler et a1.
`2012/0197148 A1
`8/2012 Levitan et al.
`2012/0289790 A1
`11/2012 Jain et 31.
`2014/0125619 A1
`5/2014 Panther et al.
`2014/0163393 A1
`6/2014 McCombie et 211.
`
`Related US. Application Data
`
`(Continued)
`
`(63) Continuation of application No. 15/656,745, filed on
`JUL 21, 2017, HOW Pat. NO- 10,537,250: WhiCh is a
`continuation of application No. 15/ 154,849, filed on
`May 13, 2016, now Pat. No. 9,839,363.
`
`(60) Provisional application No. 62/1 61,092, filed on May
`13, 2015.
`
`(51)
`
`Int. Cl-
`A613 5/02
`A613 5/0205
`A613 5/00
`A613 5/024
`A613 5/]]
`
`400\
`
`(2006.01)
`(2006.01)
`(2006.01)
`(2006.01)
`(2006.01)
`
`Primary Examiner 7 Ankit D Tejani
`(74) Attorney, Agent, or Firm 7 Womble Bond Dickinson
`(US) LLP; William D. Jacobs, Jr.
`
`ABSTRACT
`(57)
`Described herein are systems, devices, and methods for
`cardiac monitoring. In particular, the systems, devices, and
`methods described herein may be used to conveniently sense
`the presence of an intermittent arrhythmia in an individual.
`The systems, devices, and methods described herein may be
`further configured to sense an electrocardiogram.
`
`23 Claims, 7 Drawing Sheets
`
`
`
`
`1:2
`
`
` 1
`7:28PM, 23m ago 60 8PM i
`
`

`

`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 3 of 19
`Case 6:20-cv-01112-ADA Document 1—2 Filed 12/07/20 Page 3 of 19
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`US 10,638,941 B2
` Page 2
`
`(56)
`
`References Cited
`U.S. PATENT DOCUMENTS
`
`2014/0276154 A1*
`
`2015/0057512 A1
`2015/0122018 A1*
`
`2015/0305684 A1
`
`9/2014 Katra ................. A61B 5/04012
`600/509
`
`2/2015 Kapoor
`5/2015 Yuen ...................... G01B 21/16
`73/384
`
`10/2015 Gross
`
`* cited by examiner
`
`

`

`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 4 of 19
`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 4 of 19
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`US. Patent
`
`May 5, 2020
`
`Sheet 1 of 7
`
`US 10,638,941 B2
`
`FIG.1
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`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 5 of 19
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`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 6 of 19
`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 6 of 19
`
`US. Patent
`
`May 5, 2020
`
`Sheet 3 of 7
`
`US 10,638,941 B2
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`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 7 of 19
`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 7 of 19
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`US. Patent
`
`May 5, 2020
`
`Sheet 4 of 7
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`US 10,638,941 B2
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`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 8 of 19
`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 8 of 19
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`US. Patent
`
`May 5, 2020
`
`Sheet 5 of 7
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`US 10,638,941 B2
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`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 9 of 19
`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 9 of 19
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`US. Patent
`
`May 5, 2020
`
`Sheet 6 of 7
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`US 10,638,941 B2
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`

`

`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 10 of 19
`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 10 of 19
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`U.S. Patent
`
`May 5, 2020
`
`Sheet 7 of 7
`
`US 10,638,941 B2
`
`
`
`2.99
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`
`activity level
`
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`
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`
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`
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`
`FIG. 7
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`2.9.3.
`if heart
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`
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`
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`
`exercise, no
`
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`
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`fibrillation
`
`

`

`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 11 of 19
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`US 10,638,941 B2
`
`2
`
`1
`DISCORDANCE MONITORING
`
`CROSS-REFERENCE
`
`This application is a continuation of US. patent applica-
`tion Ser. No. 15/656,745, filed Jul. 21, 2017, entitled “DIS-
`CORDANCE MONITORING”, which is a continuation of
`US. patent application Ser. No. 15/154,849, filed May 13,
`2016, entitled “DISCORDANCE MONITORING”, now
`issued as US. Pat. No. 9,839,363 on Dec. 12, 2017, which
`claims the benefit of US. Provisional Application No.
`62/161,092, filed May 13, 2015, both of which are incor-
`porated herein by reference in its entirety.
`
`BACKGROUND
`
`Irregular heartbeats and arrhythmias are associated with
`significant morbidity and mortality in patients. Arrhythmias
`may occur continuously or may occur intermittently. Types
`of arrhythmia include atrial fibrillation and supraventricular
`tachycardia. Non-invasive cardiac monitoring is useful in
`diagnosing cardiac arrhythmia.
`
`SUMMARY
`
`Described herein are systems, devices, and methods for
`cardiac monitoring. The systems, devices, and methods
`described herein for cardiac monitoring may comprise por-
`table computing devices
`such as
`smartphones,
`smart-
`watches, laptops, and tablet computers. Cardiac monitoring
`using the systems, devices, and methods described herein
`may be used to predict or identify the occurrence of arrhyth-
`mias.
`
`Arrhythmias may occur continuously or may occur inter-
`mittently. Continuously occurring arrhythmias may be diag-
`nosed using a number of different techniques including, for
`example, palpating a radial pulse of an individual, auscul-
`tating heart sounds of an individual, recording a heart rate of
`an individual, and recording an electrocardiogram of an
`individual. Because a continuous or essentially continuous
`arrhythmia is always present or essentially always present in
`the patient, any of the aforementioned diagnosis techniques
`may be applied at any time in order to make a diagnosis. For
`intermittent arrhythmia diagnosis any of the aforementioned
`diagnosis techniques may also be used, however, because
`intermittent arrhythmias do not always present, the diagnos-
`tic technique cannot be applied at any time, but must be
`applied at the time when the individual is experiencing the
`arrhythmia. Thus, diagnosing, intermittent arrhythmias may
`be difficult, because, for example, it is not practical to be
`prepared to apply one of the aforementioned diagnostic
`modalities at the exact time that an individual experiences an
`intermittent arrhythmia. This particular difficulty may also
`be compounded when an individual is not aware that they
`are experiencing an intermittent arrhythmia so that they
`would not, for example, seek out a health care provider
`during the intermittent arrhythmia.
`However, certain parameter values may be conveniently
`sensed continuously such as, for example, heart rate and
`activity level, and analyzed to predict or determine the
`presence of an arrhythmia. One or more conveniently con-
`tinuously sensed parameter values such as, for example,
`heart rate and activity level may be analyzed to determine
`the future onset of or the presence of an arrhythmia by
`identifying discordance between these two parameter val-
`ues. For example, discordance between two sensed values
`may indicate the future onset of or the presence of an
`
`arrhythmia. In response to the identification of the future
`onset of or presence of an arrhythmia an electrocardiogram
`may be caused to be sensed.
`Additional sensed parameters may also be used in an
`analysis as part of the cardiac monitoring systems, devices,
`and methods described herein. For example, a determined
`heart rate variability may be compared to a sensed heart rate
`and activity level to determine the presence of, for example,
`atrial fibrillation or supraventricular tachycardia.
`Described herein is a method for cardiac monitoring,
`comprising: sensing an activity level value of an individual
`with a first sensor of a wearable device worn by said
`individual; sensing a heart rate value of said individual with
`a second sensor of said wearable device; determining a heart
`rate variability value with a processor of said wearable
`device; determining if a discordance is present between two
`or more of said activity level value, said heart rate value, and
`said heart rate variability value with said processor; and
`indicating to said individual with said wearable device to
`record an electrocardiogram when said discordance is deter-
`mined to be present. In some embodiments, said first sensor
`comprises an accelerometer. In some embodiments, said first
`sensor comprises a gyroscope. In some embodiments, said
`second sensor comprises a photosensor. In some embodi-
`ments, said discordance is determined to be present when
`said activity level value is normal and said heart rate value
`is elevated.
`In some embodiments, said discordance is
`determined to be present when said activity level value is
`normal, said heart rate value is elevated, and said heart rate
`variability value is increased. In some embodiments, said
`method comprises indicating a presence of atrial fibrillation.
`In some embodiments, said discordance is determined to be
`present when said activity level value is normal, said heart
`rate value is elevated, and said heart rate variability value is
`decreased. In some embodiments, said method comprises
`indicating a presence of a supraventricular tachycardia. In
`some embodiments, setting one or more threshold values
`based on said activity level value, said heart rate value, and
`said heart rate variability value. In some embodiments, said
`one or more threshold values is determined using a machine
`learning algorithm.
`Described herein is wearable device for cardiac monitor-
`
`ing, comprising: a processor; a first sensor configured to
`sense an activity level value of an individual, wherein said
`first sensor is coupled to said processor; a second sensor
`configured to sense a heart rate value of an individual,
`wherein said second sensor is coupled to said processor; a
`first electrode and a second electrode configured to sense an
`electrocardiogram; a non-transitory computer readable stor-
`age medium encoded with a computer program including
`instructions executable by said processor to cause said
`processor to: determine if a discordance is present between
`said activity level value of said individual and said heart rate
`value of said individual; and indicate that said electrocar-
`diogram be recorded when said discordance is determined to
`be present. In some embodiments, said first sensor com-
`prises an accelerometer. In some embodiments, said first
`sensor comprises a gyroscope. In some embodiments, said
`second sensor comprises a photosensor. In some embodi-
`ments, said discordance is determined to be present when
`said activity level value is normal and said heart rate value
`is elevated. In some embodiments, said computer program
`includes instructions that cause said processor to determine
`a heart rate variability value. In some embodiments, said
`discordance is determined to be present when said activity
`level value is normal, said heart rate value is elevated, and
`said heart rate variability value is increased.
`In some
`
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`US 10,638,941 B2
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`3
`embodiments, said computer program includes instructions
`that cause said processor to indicate a presence of atrial
`fibrillation. In some embodiments, said discordance is deter-
`mined to be present when said activity level value is normal,
`said heart rate value is elevated, and said heart rate vari-
`ability value is elevated. In some embodiments, said com-
`puter program includes instructions that cause said processor
`to indicate a presence of a supraventricular tachycardia. In
`some
`embodiments,
`said computer program includes
`instructions that cause said processor to set one or more
`threshold values based on said activity level value, and said
`heart rate value.
`
`In some embodiments, said one or more threshold values
`is determined using a machine learning algorithm.
`Described herein is a method for cardiac monitoring,
`comprising: sensing an activity level value of an individual
`with a first sensor of a wearable device worn by said
`individual; sensing a heart rate value of said individual with
`a second sensor of said wearable device; determining if a
`discordance is present between two or more of said activity
`level value and said heart rate value by using an activity
`level threshold and a heart rate threshold with a processor of
`said wearable device; and adjusting said activity level
`threshold and said heart rate level threshold using a machine
`learning algorithm executed by said processor.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`The novel features of the individual matter described
`
`herein are set forth with particularity in the appended claims.
`A better understanding of the features and advantages of the
`present individual matter described herein will be obtained
`by reference to the following detailed description that sets
`forth illustrative embodiments, in which the principles of the
`individual matter described herein are utilized, and the
`accompanying drawings of which:
`FIG. 1 shows a heart rate tracing with a corresponding
`electrocardiogram (ECG) tracing both sensed from the same
`individual over the same period.
`FIG. 2 shows a graphic showing both heart rate and
`rhythm analysis over a period of time in an individual who
`experienced different arrhythmias.
`FIG. 3 shows a close up of a heart rate tracing sensed over
`a period of paroxysmal atrial fibrillation.
`FIG. 4 shows available technologies for continuously
`sensing a heart rate or an activity level.
`FIG. 5 shows a photosensor commonly used to measure
`heart rates integrated with a smartwatch.
`FIG. 6 exemplifies a computer system that is programmed
`or otherwise configured to sense one or more physiologic
`parameters of an individual.
`FIG. 7 shows a schematic of an algorithm for discordance
`monitoring.
`
`DETAILED DESCRIPTION
`
`Cardiac Monitoring
`Described herein are systems, devices, and methods for
`use in cardiac monitoring. Cardiac monitoring typically
`comprises monitoring of the heart function of an individual
`for changes in, for example, heart rate or heart rhythm.
`Heart rate may vary between, for example, bradycardia
`which typically is defined as a heart rate of less than 60 beats
`per minute, normal resting heart rate which typically is
`defined as a heart rate of between 60-100 beats per minute,
`and tachycardia which typically is defined as a heart rate of
`
`10
`
`15
`
`20
`
`25
`
`30
`
`35
`
`40
`
`45
`
`50
`
`55
`
`60
`
`65
`
`4
`
`greater than 100 beats per minute. Variance of heart rate over
`a period of time may be referred to as Heart Rate Variability
`(HRV).
`Heart function is also measured in terms of regularity of
`rhythm. A normal heart rhythm comprises of a systole
`(ejection phase) and diastole (filling phase). During the
`phases of systole and diastole, the ventricles of the heart act
`in concert in a regular manner that is repeated with every
`single heartbeat. When there is an abnormality of rhythm,
`the condition is typically referred to as an arrhythmia.
`Examples of arrhythmias include atrial fibrillation, WPW
`syndrome, prolonged QT syndrome, and premature ven-
`tricular contractions.
`
`Many arrhythmias occur intermittently and relatively
`infrequently. Thus,
`in order to monitor and capture an
`intermittent arrhythmia, continuous monitoring is typically
`required. ECGs can be measured continuously in the ambu-
`latory patient using holter monitoring, but
`this type of
`monitoring is cumbersome for the patient and is thus not
`widely used. A device or system configured to take an
`intermittent ECG is much more convenient for users. Such
`
`devices or systems comprise a mobile computing device that
`includes one or more electrodes that sense an ECG when
`
`contacted by a skin surface of the patient. Such devices are
`light and portable and don’t necessarily require the user to
`be in continuous physical contact with one or more elec-
`trodes as they would with a holter type monitor. Intermittent
`arrhythmias can be recorded with these devices and systems
`when a user is given an indication that an intermittent
`arrhythmia is occurring. HRV sensing is used in combina-
`tion with these devices or systems to indicate to a user when
`to contact one or more electrodes in order to sense an ECG.
`
`FIG. 1 shows a heart rate tracing 100 with a correspond-
`ing electrocardiogram (ECG) tracing 104 both sensed from
`the same individual over the same period. As is shown in the
`ECG tracing 104, the individual experienced a period of
`intermittent atrial fibrillation 106 during the time that the
`ECG was sensed. As is also shown in the heart rate tracing
`100, the heart rate of the individual rapidly increased 102
`during the period of intermittent atrial fibrillation. As such,
`the HRV of the individual increased during the period of
`intermittent atrial fibrillation as the heart rate of the indi-
`
`vidual increased from a resting heart rate to an increased
`heart rate 102. HRV changes are therefore associated with
`atrial fibrillation, wherein increased HRV is found during
`periods of intermittent atrial fibrillation.
`FIG. 2 shows a graphic showing both heart rate 202 and
`rhythm analysis 200 over a period of time in an individual
`who experienced different arrhythmias. As shown, the mea-
`sured heart rate 202 tended to increase above 100 beats per
`minute during the periods of sensed atrial fibrillation 200.
`Thus, elevated heart rate above resting heart rate occurred in
`this individual during the period of arrhythmia.
`FIG. 3 shows a close up of a heart rate tracing sensed over
`a period of paroxysmal atrial fibrillation. As shown, there
`was a substantial step increase from a normal heart of
`between 60-100 beats per minute to above 100 beats per
`minute 302 during the period of atrial fibrillation.
`FIG. 4 shows available technologies 400 for continuously
`sensing a heart rate or an activity level. Shown are smart-
`watches made available by manufactures such as,
`for
`example, Apple. A wearer of one of the shown smartwatch
`technologies 400 may conveniently and continuously wear
`one or more sensors that are either coupled to or integrated
`with the watch throughout the day, thus, effectively continu-
`ously monitoring one or more parameter values via the one
`or more sensors that are either coupled to or integrated with
`
`

`

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`US 10,638,941 B2
`
`5
`the smartwatch. Thus, one of the smartwatch technologies
`400 are an example of a type of device in the form of a
`wearable that conveniently provides continuous monitoring
`of one or more parameters of a user. Non-limiting examples
`of wearable devices that may have one or more sensors
`either coupled to them or integrated with them include
`watches (e.g. smartwatches), eyeglasses, wristbands, neck-
`laces, and clothing. The one or more continuously sensed
`parameters of the user of such a technology as, for example,
`shown in FIG. 4, are then used to indicate to the user to use
`a device or system to sense an ECG. For example, a user
`wearing a smartwatch having a heart rate sensor is alerted by
`the smartwatch to record an ECG when the HRV of the user
`increases.
`
`FIG. 5 shows a photosensor 500 commonly used to
`measure heart rates integrated with a smartwatch 502.
`Activity level
`is correlated with arrhythmia in many
`individuals who have a predisposition to develop arrhythmia
`wherein increased activity level is associated with onset of
`arrhythmia. In other individuals an increased activity level
`that
`is detected by one or more activity sensors in the
`presence of increased HRV is likely normal and is not
`associated with arrhythmia. Thus, as described herein, the
`addition of continuous heart rate monitoring along with
`continuous activity level monitoring may achieve the same
`results, in terms of arrhythmia monitoring, as continuous
`electrocardiogram monitoring. Using one or more sensors
`associated with the devices or systems described herein two
`parameter values of heart rate and activity level may be
`conveniently and accurately continuously and simultane-
`ously sensed.
`Devices and Systems
`FIG. 6 exemplifies a computer system 601 that is pro-
`grammed or otherwise configured to sense one or more
`physiologic parameters of an individual. Non-limiting
`examples of physiologic parameters include heart rate,
`blood pressure, temperature, oxygen saturation, ECG, HRV,
`and activity level. The computer system 601 comprises an
`electronic device of a user 635, or comprises a computer
`system that is remotely located with respect to the electronic
`device 635. Electronic devices suitable for use with the
`
`system 601 include mobile electronic devices such as smart-
`phones, smartwatches, tablets, and laptops. The electronic
`device 601 comprises one or more sensors configured to
`sense a physiologic parameter. Numerous sensors are known
`for measuring heart rate. Non-limiting examples of suitable
`sensors include light based sensors such as, for example,
`infrared sensor/emitter, ultrasound sensors, and tactile sen-
`sors. Sensors for measuring rhythm include electrodes for
`measuring electrocardiograms (ECG) and light based sen-
`sors for measuring photoplethysmograms.
`The computer system 601 includes a central processing
`unit
`(CPU, also “processor” and “computer processor”
`herein) 605, which can be a single core or multi core
`processor, or a plurality of processors for parallel process-
`ing. The computer system 601 also includes memory or
`memory location 610 (e.g., random-access memory, read-
`only memory, flash memory), electronic storage unit 615
`(e. g., hard disk), communication interface 602 (e. g., network
`adapter) for communicating with one or more other systems,
`and peripheral devices 625, such as cache, other memory,
`data storage and/or electronic display adapters. The memory
`610, storage unit 615, interface 602 and peripheral devices
`625 are in communication with the CPU 605 through a
`communication bus (solid lines), such as a motherboard. The
`storage unit 615 can be a data storage unit (or data reposi-
`tory) for storing data. The computer system 601 can be
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`6
`operatively coupled to a computer network (“network”) 603
`with the aid of the communication interface 602. The
`network 603 can be the Internet, an internet and/or extranet,
`or an intranet and/or extranet that is in communication with
`the Internet. The network 603 in some cases is a telecom-
`munication and/or data network. The network 603 can
`
`include one or more computer servers, which can enable
`distributed computing, such as cloud computing. The net-
`work 603, in some cases with the aid of the computer system
`601, can implement a peer-to-peer network, which may
`enable devices coupled to the computer system 601 to
`behave as a client or a server.
`
`The CPU 605 can execute a sequence of machine-read-
`able instructions, which can be embodied in a program or
`software. The instructions may be stored in a memory
`location, such as the memory 610. The instructions can be
`directed to the CPU 605, which can subsequently program
`or otherwise configure the CPU 605 to implement methods
`of the present disclosure. Examples of operations performed
`by the CPU 605 can include fetch, decode, execute, and
`writeback.
`
`The CPU 605 can be part of a circuit, such as an integrated
`circuit. One or more other components of the system 601 can
`be included in the circuit. In some cases, the circuit is an
`application specific integrated circuit (ASIC).
`The storage unit 615 can store files, such as drivers,
`libraries and saved programs. The storage unit 615 can store
`user data, e.g., user preferences and user programs. The
`computer system 601 in some cases can include one or more
`additional data storage units that are external to the com-
`puter system 601, such as located on a remote server that is
`in communication with the computer system 601 through an
`intranet or the Internet.
`
`The computer system 601 can communicate with one or
`more remote computer systems through the network 603.
`For instance, the computer system 601 can communicate
`with a remote computer system of a user (e.g., mobile
`device, server, etc.). Examples of remote computer systems
`include personal computers (e.g., portable PC), slate or
`tablet PC’s (e.g., Apple® iPad, Samsung® Galaxy Tab),
`telephones, Smart phones (e.g., Apple® iPhone, Android-
`enabled device, Blackberry®), or personal digital assistants.
`The user can access the computer system 601 via the
`network 603.
`
`Methods as described herein can be implemented by way
`of machine (e.g., computer processor) executable code
`stored on an electronic storage location of the computer
`system 601, such as, for example, on the memory 610 or
`electronic storage unit 615. The machine executable or
`machine readable code can be provided in the form of
`software. During use,
`the code can be executed by the
`processor 605. In some cases, the code can be retrieved from
`the storage unit 615 and stored on the memory 610 for ready
`access by the processor 605. In some situations, the elec-
`tronic storage unit 615 can be precluded, and machine-
`executable instructions are stored on memory 610.
`The code can be pre-compiled and configured for use with
`a machine have a processor adapted to execute the code, or
`can be compiled during runtime. The code can be supplied
`in a programming language that can be selected to enable the
`code to execute in a pre-compiled or as-compiled fashion.
`Aspects of the systems and methods provided herein, such
`as the computer system 601, can be embodied in program-
`ming. Various aspects of the technology may be thought of
`as “products” or “articles of manufacture” typically in the
`form of machine (or processor) executable code and/or
`associated data that is carried on or embodied in a type of
`
`

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`Case 6:20-cv-01112-ADA Document 1-2 Filed 12/07/20 Page 14 of 19
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`US 10,638,941 B2
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`7
`machine readable medium. Machine-executable code can be
`
`8
`A device as described herein is in some embodiments
`
`stored on an electronic storage unit, such memory (e.g.,
`read-only memory, random-access memory, flash memory)
`or a hard disk. “Storage” type media can include any or all
`of the tangible memory of the computers, processors or the
`like, or associated modules thereof, such as various semi-
`conductor memories, tape drives, disk drives and the like,
`which may provide non-transitory storage at any time for the
`software programming. All or portions of the software may
`at times be communicated through the Internet or various
`other telecommunication networks. Such communications,
`for example, may enable loading of the software from one
`computer or processor into another, for example, from a
`management server or host computer into the computer
`platform of an application server. Thus, another type of
`media that may bear the software elements includes optical,
`electrical and electromagnetic waves, such as used across
`physical interfaces between local devices, through wired and
`optical landline networks and over various air-links. The
`physical elements that carry such waves, such as wired or
`wireless links, optical links or the like, also may be consid-
`ered as media bearing the software. As used herein, unless
`restricted to non-transitory, tangible “storage” media, terms
`such as computer or machine “readable medium” refer to
`any medium that participates in providing instructions to a
`processor for execution.
`Hence, a machine readable medium, such as computer-
`executable code, may take many forms, including but not
`limited to, a tangible storage medium, a carrier wave
`medium or physical
`transmission medium. Non-volatile
`storage media include, for example, optical or magnetic
`disks, such as any of the storage devices in any computer(s)
`or the like, such as may be used to implement the databases,
`etc. shown in the drawings. Volatile storage media include
`dynamic memory, such as main memory of such a computer
`platform. Tangible transmission media include coaxial
`cables; copper wire and fiber optics, including the wires that
`comprise a bus within a computer system. Carrier-wave
`transmission media may take the form of electric or elec-
`tromagnetic signals, or acoustic or light waves such as those
`generated during radio frequency (RF) and infrared (IR) data
`communications. Common forms of computer-readable
`media therefore include for example: a floppy disk, a flexible
`disk, hard disk, magnetic tape, any other magnetic medium,
`a CD-ROM, DVD or DVD-ROM, any other optical
`medium, punch cards paper tape, any other physical storage
`medium with patterns of holes, a RAM, a ROM, a PROM
`and EPROM, a FLASH-EPROM, any other memory chip or
`cartridge, a carrier wave transporting data or instructions,
`cables or links transporting such a carrier wave, or any other
`medium from which a computer may read programming
`code and/or data. Many of these forms of computer readable
`media may be involved in carrying one or more sequences
`of one or more instructions to a processor for execution
`The computer system 601 can include or be in commu-
`nication with an electronic display 535 that comprises a user
`interface (UI) 640 for providing, for example, distributions
`of magnetic fields, distributions of electrical currents, dis-
`tributions of local myocardial activities, etc. Examples of
`UI’s include, without limitation, a graphical user interface
`(GUI) and web-based user interface.
`Methods and systems of the present disclosure can be
`implemented by way of one or more algorithms. An algo-
`rithm can be implemented by way of software upon execu-
`tion by the central processing unit 605. The algorithm, for
`example, is used to analyze a sensed physiologic parameter.
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`configured to sense two or more physiologic parameters. For
`example, a device configured to measure the heart rate of an
`individual as described herein is also in some embodiments
`
`configured to sense the electrocardiogram of said individual.
`In these embodiments, a device as described herein includes
`one or more electrodes configured to sense an electrocar-
`diogram of an individual. In some embodiments, a device as
`described herein comprises two electrodes. In some embodi-
`m