UNITED STATES PATENT AND TRADEMARK OFFICE
`_______________________
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`_______________________
`APPLE INC.,
`Petitioner
`v.
`UNILOC LUXEMBOURG S.A.
`Patent Owner
`_______________________
`Case No. IPR2018-387
`U.S. PATENT NO. 7,653,508
`
`
`DECLARATION OF WILLIAM C. EASTTOM II (CHUCK EASTTOM)
`
`
`
`
`
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`

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`
`
`I.
`
`II.
`
`TABLE OF CONTENTS
`
`INTRODUCTION ........................................................................................................3
`
`BACKGROUND AND QUALIFICATIONS .....................................................................3
`
`III.
`
`CLAIM CONSTRUCTION ............................................................................................4
`
`IV.
`
`THE ‘508 PATENT .....................................................................................................5
`
`V.
`
`ONE OF ORDINARY SKILL IN THE ART ......................................................................6
`
`VI.
`
`GENERAL ISSUES ......................................................................................................6
`
`A. Dominant Axis ....................................................................................................6
`
`B. Cadence Window ...............................................................................................9
`
`VII.
`
`SPECIFIC CLAIM ELEMENTS ................................................................................... 10
`
`A. continuously determining an orientation of the inertial sensor; ................... 10
`
`B. assigning a dominant axis; .............................................................................. 11
`
`C. updating the dominant axis as the orientation of the inertial sensor changes;
`and .................................................................................................................. 13
`
`D. Claim 11 a dominant axis logic to continuously determine an orientation of a
`device, to assign a dominant axis, and to update the dominant axis as the
`orientation of the device changes, ................................................................. 13
`
`E. Claim 6 A method of monitoring human activity using an inertial sensor,
`comprising: ...................................................................................................... 14
`
`F. Claim 6 switching the device from the non-active mode to an active mode,
`after identifying a number of periodic human motions within appropriate
`cadence windows;........................................................................................... 15
`
`VIII.
`
`CONCLUSIONS ....................................................................................................... 17
`
`IX.
`
`APPENDIX A – EASTTOM CV .................................................................................. 17
`
`A. Education ........................................................................................................ 17
`1. University Degrees ........................................................................ 17
`2.
`Industry Certifications ................................................................... 18
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`1
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`
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`3. Security and Forensics Related Certifications............................... 19
`4. Software Certifications ................................................................. 20
`5. Licenses ......................................................................................... 20
`
`B. Publications ..................................................................................................... 20
`1. Books 20
`2. Papers, presentations, & articles. ................................................. 22
`
`C. Patents ............................................................................................................ 24
`
`D. Standards and Certification Creation.............................................................. 25
`
`E. Professional Awards and Memberships ......................................................... 25
`
`F. Speaking Engagements ................................................................................... 26
`
`G. Litigation Support Experience ......................................................................... 29
`1. Testifying Experience .................................................................... 34
`
`H. Professional Experience .................................................................................. 36
`
`I. Continuing Professional Education ................................................................. 39
`
`J. References to my work ................................................................................... 40
`1. Media References ......................................................................... 40
`2. References to publications ........................................................... 41
`3. Universities using my books ......................................................... 46
`
`K. Training ........................................................................................................... 48
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`L. Technical Skills ................................................................................................ 49
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`
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`2
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`
`
`I.
`
`INTRODUCTION
`
`1.
`
`I have been retained by Uniloc to provide my expert opinions regarding
`
`validity of U.S. Patent No. 8,712,508 (“508 Patent”). Specifically, I have been asked to
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`provide expert opinions regarding Claims 1-3, 5-7, and 10-18.
`
`2.
`
`I am being compensated for my time at my standard consulting rate of
`
`$300 per hour. I am also being reimbursed for expenses that I incur during the course of
`
`this work. My compensation is not contingent upon the results of my study or the
`
`substance of my opinions.
`
`II.
`
`BACKGROUND AND QUALIFICATIONS
`
`3.
`
`I have 25+ years of experience in the computer science industry including
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`extensive experience with computer security, computer programming, and computer
`
`networking. I have authored 26 computer science books, including textbooks used at
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`universities around the world. I hold 42 different computer industry certifications,
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`including many in networking subjects. I am experienced with multiple programming
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`languages. I also have extensive experience in computer networking. I have extensive
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`experience with mobile devices, including all aspects of mobile devices (hardware and
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`software). I am a Distinguished Speaker for the Association of Computing Machinery
`
`(ACM), and a reviewer for the IEEE Security and Privacy journal, as well as a reviewer for
`
`the International Journal of Cyber Warfare and Terrorism (IJCWT). My CV is attached as
`
`appendix A.
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`
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`3
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`

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`
`III.
`
`CLAIM CONSTRUCTION
`
`4.
`
`Fort the purposes of an IPR, claim terms are given their broadest
`
`reasonable meaning.
`
`5.
`
`The petitioner has adopted the definitions of dominant axis as “the axis
`
`most influenced by gravity.”
`
`6.
`
`The petitioner has adopted the definition of cadence window as “a window
`
`of time since a last step was counted that is looked at to detect a new step.”
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`7.
`
`The petitioner has adopted the definition of a dominant axis logic to
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`determine an orientation of a device with respect to gravity, to assign a dominant axis,
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`and to update the dominant axis when the orientation of the device changes as
`
`“hardware, software, or both to determine an orientation of a device, to assign a
`
`dominant axis, and to update the dominant axis as the orientation of the device changes.”
`
`The petitioner seems to ignore the fact that software, by itself, cannot determine a
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`dominant axis. Hardware with software/firmware, can.
`
`8.
`
`The petitioner has adopted the definition of a counting logic to count
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`periodic human motions by monitoring accelerations relative to the dominant axis by
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`counting the periodic human motions when accelerations showing a motion cycle that
`
`meets motion criteria is detected within a cadence window as “hardware, software, or
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`both to count periodic human motions by monitoring accelerations relative to the
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`dominant axis by counting the periodic human motions when accelerations showing a
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`motion cycle that meets motion criteria is detected within a cadence window.” The
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`4
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`

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`
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`petitioner seems to ignore the fact that software, by itself, cannot determine motion.
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`Hardware with software/firmware, can.
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`9.
`
`The petitioner has adopted the definition of a cadence logic to update the
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`cadence window as actual cadence changes as “hardware, software, or both to update
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`the cadence window as actual cadence changes.”
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`10. While the petitioner has made some claims in claim construction that
`
`ignore the actual functionality of the hardware and software involved, for the purposes
`
`of this proceeding I will use the petitioners adopted definitions in performing my analysis
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`and forming my opinions.
`
`IV.
`
`THE ‘508 PATENT
`
`1.
`
`The ’508 patent is titled “Human activity monitoring device.” The ʼ508
`
`patent issued January 26, 2010, from U.S. Patent Application No. 11/644,455 filed
`
`December 22, 2006.
`
`2.
`
`The inventors of the ’508 patent observed that at the time, step counting
`
`devices that utilize an inertial sensor to measure motion to detect steps generally
`
`required the user to first position the device in a limited set of orientations. In some
`
`devices, the required orientations are dictated to the user by the device. In other devices,
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`the beginning orientation is not critical, so long as this orientation can be maintained.
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`Further, the inventors observed that devices at the time were often confused by motion
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`noise experienced by the device throughout a user's daily routine. The noise would cause
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`false steps to be measured and actual steps to be missed in conventional step counting
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`
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`5
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`
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`devices. Conventional step counting devices also failed to accurately measure steps for
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`individuals who walk at a slow pace.
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`3.
`
`According to the invention of the ’508 Patent, a device to monitor human
`
`activity using an inertial sensor assigns a dominant axis after determining the orientation
`
`of an inertial sensor. he orientation of the inertial sensor is continuously determined, and
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`the dominant axis is updated as the orientation of the inertial sensor changes.
`
`
`ONE OF ORDINARY SKILL IN THE ART
`
`V.
`
`4.
`
`Patent claims must be viewed from the perspective of one of ordinary skill
`
`in the art. A Person of Ordinary Skill in the Art (POSA) in November 1999 would have been
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`one with a bachelor’s degree in engineering, computer science, or related technical area
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`with 2 years of experience related to mobile devices, accelerometers or similar devices.
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`Additional experience can compensate for a lack of a degree.
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`5.
`
`I am aware that Dr. Paradiso has a somewhat different view of a POSA.
`
`While I disagree with a few of the nuances of Dr. Paradiso’s definition of a POSA, our
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`definitions are substantially similar. Even if one adopts his view of a POSA, it would not
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`alter my opinions.
`
`VI.
`
`GENERAL ISSUES
`
`A.
`
`6.
`
`Dominant Axis
`
`In general, the petitioner conflates the dominant axis in the ‘508 patent with
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`the Z axis in Fabio and Pasolini. This is incorrect for several reasons.
`
`7.
`
`In Pasolini, the only mention of orientation is
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`
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`6
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`

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`
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`“For example, the main vertical axis can be identified at each acquisition
`of a new acceleration sample, block 30 of FIG. 4, so as to take into
`account variations in the orientation of the pedometer device 1, and
`consequently of the accelerometer 2 arranged inside it.”
`
`This depends entirely on the vertical axis but tries to account for “variations
`
`8.
`
`in the orientation of the pedometer device” It should be noted that Fabio, does not even
`
`mention orientation. It is clear that Pasolini is only concerned about a single axis and
`
`assumes that axis will be the main axis. This is made clear many places in Pasolini, a
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`sample of such data is provided here:
`
`“In use, the accelerometer 2 detects the component along the detection axis z of the
`vertical acceleration generated during the step, and produces a corresponding
`acceleration signal A.”
`
`“The accelerometer 2 could be equipped with a number of axes of
`measurement, for example three mutually orthogonal axes of measurement,
`and be built, for example, as described in “3-axis Digital Output Accelerometer
`For Future Automotive Applications”, B. Vigna et al., AMAA 2004. In this case,
`according to one embodiment of the present invention, the algorithm
`implemented by the processing unit 3 envisages identifying the main vertical axis
`to be used for step detection as the axis of detection that has the highest mean
`acceleration value Accm (on account of gravity). For example, the main vertical
`axis can be identified at each acquisition of a new acceleration sample, block 30
`of FIG. 4, so as to take into account variations in the orientation of the
`pedometer device 1, and consequently of the accelerometer 2 arranged inside
`it.”
`
`
`9.
`
`It is clear that Pasolini did not account for changing axis, and in fact it seems
`
`likely that was not even contemplated. That is in stark contrast to the ‘508 patent wherein
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`any direction might become dominant, and detecting the currently dominant axis is crucial
`
`(note the emphasis are added).
`
`“Embodiments of the present invention are designed to monitor human activity
`using an inertial sensor. In one embodiment, a dominant axis is assigned after
`determining an orientation of an inertial sensor”
`
`
`
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`7
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`

`

`
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`“In one embodiment, the dominant axis setting logic 140 determines an
`orientation of the electronic device 100 and/or the inertial sensor(s) within the
`electronic device 100. The orientation may be determined based upon the
`rolling averages of accelerations created by the rolling average logic 135.”
`
`
`
`10.
`
`This is not a trivial difference. A POSA would immediately understand the
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`significant advantages that the ‘508 patent has over Fabio or Pasolini. And in fact the ‘508
`
`patent explicitly discussed the advantages this technology presents over the prior art. In the
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`background of the invention section, the ‘508 inventor point out the deficiencies of the
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`prior art stating:
`
`“Steps may be accurately counted regardless of the placement and/or orientation of
`the device on a user. Steps may be accurately counted whether the electronic device
`100 maintains a fixed orientation or changes orientation during operation. The
`electronic device 100 may be carried in a backpack, pocket, purse, hand, or
`elsewhere, and accurate steps may still be counted.”
`
`
`11.
`
`The petitioner completely ignores the fact that with the ‘508 patent, any
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`axis can be the dominant axis, and that this provides a significant advantage over the prior
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`art. The issue of the dominant axis is significant to the very claims the petitioner is
`
`challenging. Dominant axis is addressed three times in claim 1 alone, then again in claim
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`2. Claim 3 depends on claim 1. Then in claim 10 dominant axis is again discussed, in this
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`instance four times. Then again in claim 11. Claims 12 and 13 depend on claim 10.
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`12.
`
`Claim 14 returns to explicitly discussing the dominant axis three times, and
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`again in claim 15. Claims 16 and 17 depend on claim 14, and claim 18 depends on claim
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`17.
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`13.
`
`Once one understands that the dominant axis in the ‘508 patent is
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`substantially different than the simple vertical axis in Fabio and Pasolini, and further
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`
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`8
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`
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`conveys a significant advantage, then the challenged claims can be immediately seen as
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`not being obvious nor anticipated by Fabio or Pasolini alone or in combination.
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`B.
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`Cadence Window
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`14.
`
`Claim 3 and claim 6 describe a “cadence window”. Claim 11 describes “a
`
`cadence logic to continuously update a dynamic cadence window”.
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`15.
`
`The petitioner claims “Fabio discloses this limitation because it teaches
`
`switching the pedometer from the first counting procedure 110 (e.g., a non-active mode)
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`to a second counting procedure 130 (e.g., an active mode) after a condition of stepping
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`regularity has been met. Ex.1003, p.53. The condition of regularity is determined based
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`on the detected steps falling within a validation interval TV (i.e., a cadence window).
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`Ex.1003, p.53.;” However, what Fabio actually states is shown here (note that portion
`
`underlined in red is the portion the petitioner cited):
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`
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`9
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`16.
`
`. What is being describes is a test of the regularity of the individual step.
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`This is the first validation test. Even if one supposes that “regularity of the individual step”
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`to be synonymous with “cadence”, this excerpt is not describing updating the “regularity
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`of the individual step”. This in no way describes updating anything even analogous to the
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`cadence window. It must also be noted that Fabio only discusses updating with respect
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`to updating the number of steps, not anything even analogous to the cadence window.
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`VII.
`
`SPECIFIC CLAIM ELEMENTS
`
`17.
`
`Several claims discussed in the petitioner’s brief and Dr. Pasadino’s
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`declaration stand out as requiring specific commentary. Those claims are discussed in this
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`section
`
`A.
`
`continuously determining an orientation of the inertial sensor;
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`18.
`
`The petitioner claims that Pasolini renders this obvious and cites the
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`following:
`
`“The accelerometer 2 could be equipped with a number of axes of
`measurement, for example three mutually orthogonal axes of
`measurement …. In this case, according to one embodiment of the
`present invention, the algorithm implemented by the processing unit 3
`envisages identifying the main vertical axis to be used for step
`detection as the axis of detection that has the highest mean
`acceleration value Accm (on account of gravity). For example, the
`main vertical axis can be identified at each acquisition of a new
`acceleration sample, block 30 of FIG. 4, so as to take into account
`variations in the orientation of the pedometer device 1, and
`consequently of the accelerometer 2 arranged inside it.”
`
`19.
`
`Pasolini frequently discusses taking new samples from the accelerometer.
`
`However, Pasolini is only concerned with the orientation of the Z axis, and never mentions
`
`determining other axis. Thus, Pasolini is not determining the orientation of the inertial
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`
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`10
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`

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`
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`sensor, but only determining one of three dimensions. From examining Pasolini, it is
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`apparent that the inventor did not contemplate the orientation of the entire sensor.
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`20.
`
`It is also noteworthy that the petitioner does not point to any indication
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`that Pasolini’s determining of just the Z axis is constant. Every discussion of sampling
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`from the accelerometer in Pasolini is periodic.
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`21.
`
`These are significant differences. Moving from Pasolini which has
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`intermittent sampling and only determines the Z axis, to an invention that is
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`“continuously determining an orientation of the inertial sensor” is not an obvious or
`
`anticipated improvement. It is a significant improvement that would require significant
`
`engineering work. Therefore, Pasolini neither discloses this limitation, nor renders it
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`obvious.
`
`B.
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`assigning a dominant axis;
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`22.
`
`The petitioner claims that Pasolini discloses this limitation, and states the
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`following:
`
`“Pasolini discloses this limitation because it teaches identifying a main
`
`vertical axis (i.e., the dominant axis) of the accelerometer to be used in
`
`step detection: “the algorithm implemented by the processing unit 3
`
`envisages identifying the main vertical axis to be used for step detection
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`as the axis of detection that has the highest mean acceleration value Accm
`
`(on account of gravity).” Ex.1005, 8:11-24). A POSITA would understand
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`the main vertical axis to be a dominant axis because, in Pasolini, the main
`
`
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`11
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`

`

`
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`vertical axis is the axis most aligned with gravity (i.e., has the highest mean
`
`acceleration value Accm on account of gravity). Ex.1003, p.34.”
`
`23.
`
`I agree with the petitioner on one element of this statement. In Pasolini
`
`the vertical axis is the dominant axis. However, that is not what the ‘508 patent teaches.
`
`The ‘508 patent teaches that the dominant axis must be determined. It is not fixed. This
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`is clear throughout the ‘508 patent, including the following exemplary citations:
`
`“assigning a dominant axis, updating the dominant axis as the orientation of the
`
`inertial sensor change”
`
`“In one embodiment, a dominant axis is assigned after determining an orientation
`
`of an inertial sensor. The orientation of the inertial sensor is continuously
`
`determined, and the dominant axis is updated as the orientation of the inertial
`
`sensor changes.”
`
`“Therefore, a new dominant axis may be assigned when the orientation of the
`
`electronic device 100 and/or the inertial sensor(s) attached to or embedded in the
`
`electronic device 100 changes.”
`
`24. What is taught in Pasolini is what was standard at the time of the invention,
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`a static system that always assumes that the Z axis is dominant. One of the innovations
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`of the ‘508 patent was the ability for any axis of the sensor to be dominant based on the
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`specific conditions at the time. Therefore, Pasolini neither discloses this limitation, nor
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`renders it obvious.
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`12
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`

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`
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`updating the dominant axis as the orientation of the inertial sensor
`C.
`changes; and
`
`25.
`
`As discussed in the preceding section, and as stated by the petitioner,
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`Pasolini assumes the Z axis will always be the dominant axis. The difference between
`
`Pasolini and the ‘508 patent is further clarified by looking to the names of each patent.
`
`Pasolini is entitled “Pedometer device and step detection method using an algorithm for
`
`self-adaptive computation of acceleration thresholds” A pedometer is used to measure
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`walking or jogging. A POSA would understand in such situations the person remains
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`vertical with no significant change in Z axis. And the persons acceleration is limited to the
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`limits of a humans running speed, which would always be less than the force of gravity.
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`The ‘508 patent is a far more flexible invention. It is entitled “Human activity monitoring
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`device”. It is in no way limited to walking or jogging, but can be used in any human activity.
`
`A POSA would understand that some human activities can have changes in Z axis and
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`acceleration beyond normal walking/running speed, for example skydiving or mountain
`
`climbing. Therefore, Pasolini neither discloses this limitation, nor renders it obvious.
`
`Claim 11 a dominant axis logic to continuously determine an orientation
`D.
`of a device, to assign a dominant axis, and to update the dominant axis as the
`orientation of the device changes,
`
`26.
`
`The petitioner claims:
`
` “Pasolini renders this limitation obvious because the
`combination of its embodiments teaches a processing unit that
`continuously determines which of three axes is the one most
`aligned with gravity. Ex.1003, p.40.”
`
`
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`13
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`

`
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`27.
`
`As previously discussed, Pasolini only contemplates the Z-axis being the
`
`dominant axis. It has not need for, nor mechanism to change or assign a dominant axis.
`
`Therefore, Pasolini neither discloses this limitation, nor renders it obvious.
`
`Claim 6 A method of monitoring human activity using an inertial sensor,
`E.
`comprising:
`
`28.
`
`The petitioner claims that this is met by Fabio and cites the following:
`
`“To the extent that the preamble is limiting, Fabio discloses it. Ex.1003,
`
`p.44. First, Fabio teaches “a method for controlling a pedometer” that
`
`includes “generating a signal correlated to movements of a user of the
`
`pedometer” and “detecting steps of the user based on the signal.”
`
`Ex.1006, 1:62-2:3. A POSITA would understand that a user’s steps are a
`
`form of “human activity.” Ex.1003, p.44. Fabio’s pedometer is shown in
`
`Figure 1 (below):”
`
`29. While it is true that steps are a form of human activity, what the petitioner
`
`misunderstands is that Fabio is limited to only detecting steps of a user. The ‘508 patent
`
`is far more flexible and can detect a range of human activities, far in excess of merely
`
`detecting steps. It would not be obvious to expand Fabio to include the broader topic of
`
`‘human activity’. Reading Fabio, it is apparent that Fabio never considered any
`
`applications beyond a pedometer. Therefore, Fabio neither discloses this limitation, nor
`
`renders it obvious.
`
`
`
`14
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`

`

`
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`Claim 6 switching the device from the non-active mode to an active
`F.
`mode, after identifying a number of periodic human motions within
`appropriate cadence windows;
`
`30.
`
`Fabio does not disclose switching from a non-active mode to an active
`
`mode.
`
`31.
`
`The Petition claims that “Fabio discloses this limitation because it teaches
`
`switching the pedometer from the first counting procedure 110 (e.g., a non-active mode)
`
`to a second counting procedure 130 (e.g., an active mode) after a condition of stepping
`
`regularity has been met.” However, Fabio’s Figure 3, relied upon Petitioner, shows
`
`instead that Fabio’s “first counting procedure” is never switched away from, and in fact,
`
`by following the flow chart arrows in Figure 3, it is clear that the “first counting procedure”
`
`is always performed, and only then are other “counting procedures” performed:
`
`
`
`15
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`

`

`
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`32.
`
`Additionally, the Petition claims that Fabio’s “validation window” is the
`
`required “cadence window” from the claim language. However, a review of Fabio’s
`
`“validation window” shows Petitioner is incorrect.
`
`33.
`
`The ’508 Patent states that “[a] cadence window is a window of time since
`
`a last step was counted that is looked at to detect a new step.”
`
`34.
`
`However, Fabio’s “validation window” only looks to find “when the
`
`duration ΔTK of a current step K is substantially homogenous with respect to the duration
`
`of ΔTK-1 of an immediately preceding step K-1”. In other words, Fabio’s “validation
`
`window” is reactive, waiting for a step to be discovered and then looking backward to
`
`discover a duration. Whereas the ’508 Patent’s “cadence window” is proactive – first
`
`determining the appropriate window of time, and then actively seeking to detect a step
`
`while within that window of time.
`
`35.
`
`The Petition simply concludes, without support, that merely because
`
`Fabio’s “validation window” is based in part on the immediately preceding step, then the
`
`“validation window” meets the required “cadence window”. However, as the Petition
`
`agrees, the “cadence window” is “a window of time since a last step was counted that is
`
`looked at to detect a new step.” In other words, as discussed above, the “cadence
`
`window” is proactive and forward looking, whereas Fabio’s “validation window” is
`
`reactive and passive. Merely being partially based on the immediately preceding step
`
`does not change the fact that the “validation window” cannot be the required “cadence
`
`window”.
`
`
`
`
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`16
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`

`

`
`
`VIII.
`
`CONCLUSIONS
`
`36.
`
`For the reasons discussed in this declaration, it is my opinion that there are
`
`Pasolini neither renders obvious, nor anticipates the ‘508 patent.
`
`37.
`
`For the reasons discussed in this declaration, it is my opinion that there are
`
`Fabio neither renders obvious, nor anticipates the ‘508 patent.
`
`
`
`
`_______________________
`William C. Easttom II (Chuck Easttom) 19 April 2018
`
`
`
`
`
`IX.
`
`APPENDIX A – EASTTOM CV
`
`A.
`
`Education
`
`
`
`
`
`1.
`
`University Degrees
`
`• B.A. Southeastern Oklahoma State University. Major Communications with
`Minors in Chemistry and Psychology. Extensive coursework in science (chemistry,
`physics, and biology) as well as neuroscience (neurobiology of memory, cognitive
`science, etc.). Also, additional coursework in computer science including
`programming and database courses.
`• M.Ed. Southeastern Oklahoma State University. Coursework included technology
`related courses such as digital video editing, multimedia presentations, and
`computer graphics. A statistics course was also part of the coursework.
`• M.B.A. Northcentral University Emphasis in Applied Computer Science. Extensive
`course work in graduate computer science including graduate courses in: C++
`programming, C# programming, Computer Graphics, Web Programming,
`Network communication, Complex Database Management Systems, and
`Artificial Intelligence. Approximately 30 graduate hours of graduate computer
`science courses. Additionally, a doctoral level statistics course was included. A
`semester research project in medical software was also part of the curriculum. I
`also took several research courses beyond the requirements for the degree.
`
`17
`
`

`

`
`
`
`
`
`• Doctor of Science (In progress) Capitol Technology University. Majoring in
`cybersecurity, dissertation topic is a study of post quantum computing
`asymmetric cryptographic algorithms.
`• MSSE Master of Science in Systems Engineering(In progress). University of Texas
`at El Paso. The coursework includes studies in software & system requirements;
`system integration, verification, and validation; system architecture and design;
`and systems modeling & simulation.
`
`2.
`
`Industry Certifications
`
`The following is a list of computer industry certifications I have earned.
`
`
`
`a.
`
`Hardware and Networking Related Certifications
`
`1. CompTIA (Computer Technology Industry Associations) A+ Certified
`
`2. CompTIA Network + Certified
`
`3. CompTIA Server+ Certified
`
`4. CompTIA I-Net+ Certified
`
`
`
`b.
`
`Operating System Related Certifications
`
`5. CompTIA Linux + Certified
`
`6. Microsoft Certified Professional (MCP) – Windows Server 2000 Professional
`Certification Number: A527-9546
`
`7. Microsoft Certified Systems Administrator (MCSA) Windows Server 2000
`Certification Number: A527-9556
`
`8. Microsoft Certified Systems Engineer (MCSE) Windows Server 2000 Certification
`Number: A527-9552
`
`9. Microsoft Certified Technology Specialist (MCTS) Windows Server 2008 Active
`Directory Microsoft Certification ID: 1483483
`
`10. Microsoft Certified Technology Specialist (MCTS) Windows 7 Microsoft Certification
`ID: 1483483
`
`11. Microsoft Certified IT Professional (MCITP) Windows 7 Microsoft Certification ID:
`1483483
`
`12. Microsoft Certified Solutions Associate Windows 7 Microsoft Certification ID:
`1483483
`
`13. National Computer Science Academy Windows 8 Certification Certificate #: 4787829
`
`
`
`
`
`18
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`

`

`
`
`Programming and Web Development Related
`c.
`Certifications
`
`14. Microsoft Certified Professional (MCP) – Visual Basic 6.0 Desktop Applications
`Microsoft Certification ID: 1483483
`
`15. Microsoft Certified Professional (MCP) – Visual Basic 6.0 Distributed Applications
`Microsoft Certification ID: 1483483
`
`16. Microsoft Certified Application Developer (MCAD) - C# Microsoft Certification ID:
`1483483
`
`17. Microsoft Certified Trainer (MCT 2005-2012) Microsoft Certification ID: 1483483
`
`18. Microsoft Certified Technology Specialist (MCTS) Visual Studio 2010 Windows
`Application Microsoft Certification ID: 1483483
`
`19. Microsoft Certified Technology Specialist (MCTS) Visual Studio 2010 Data Access
`Microsoft Certification ID: 1483483
`
`20. National Computer Science Academy HTML 5.0 Certification Certificate #: 4788000.
`
`21. National Computer Science Academy ASP.Net Certification Certificate #: 4788342
`
`22. Certified Internet Webmaster (CIW) Associate CIW0163791
`
`
`
`d.
`
`Database Related Certifications
`
`23. Microsoft Certified Database Administrator (MCDBA) SQL Server 2000 Microsoft
`Certification ID: 1483483
`
`24. Microsoft Certified Technology Specialist (MCTS) Implementing SQL Server 2008
`Microsoft Certification ID: 1483483
`
`25. Microsoft Certified IT Professional (MCITP) SQL Server Administration Microsoft
`Certification ID: 1483483
`
`
`
`3.
`
`Security and Forensics Related Certifications
`
`26. CIW Certified Security Analyst CIW0163791
`
`27. EC Council Certified Ethical Hacker v5 (CEH) ECC942445
`
`28. EC Council Certified Hacking Forensics Investigator v4 (CHFI) ECC945708
`
`29. EC Council Certified Security Administrator (ECSA) ECC947248
`
`30. EC Council Certified Encryption Specialist (ECES)
`
`31. EC Council Certified Instructor
`
`32. CISSP – Certified Information Systems Professional #387731
`
`33. ISSAP – Certified Information Systems Architect #387731
`
`34. CCFP – Certified Cyber Forensics Professional #387731
`
`
`
`19
`
`

`

`
`
`35. Certified Criminal Investigator (CCI)
`
`36. Forensic Examination of CCTV Digital VTR Surveillance Recording Equipment
`
`37. Oxygen Phone Forensics Certified
`
`38. Access Data Certified Examiner (ACE) 2014-2017
`
`39. OSForensics Certified Exa