Trials@uspto.gov
`571-272-7822
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`Paper No. 7
`Filed: August 2, 2018
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`UNITED STATES PATENT AND TRADEMARK OFFICE
`____________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`____________
`
`APPLE, INC.,
`Petitioner,
`
`v.
`
`UNILOC LUXEMBOURG S.A.
`Patent Owner.
`____________
`
`Case IPR2018-00424
`Patent 7,881,902 B1
`____________
`
`
`
`Before SALLY C. MEDLEY, JOHN F. HORVATH, and
`SEAN P. O’HANLON, Administrative Patent Judges.
`
`HORVATH, Administrative Patent Judge.
`
`
`
`DECISION
`Institution of Inter Partes Review
`35 U.S.C. § 314(a)
`
`
`
`
`
`
`
`
`571-272-7822
`
`
`
`
`
`Paper No. 7
`Filed: August 2, 2018
`
`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`____________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`____________
`
`APPLE, INC.,
`Petitioner,
`
`v.
`
`UNILOC LUXEMBOURG S.A.
`Patent Owner.
`____________
`
`Case IPR2018-00424
`Patent 7,881,902 B1
`____________
`
`
`
`Before SALLY C. MEDLEY, JOHN F. HORVATH, and
`SEAN P. O’HANLON, Administrative Patent Judges.
`
`HORVATH, Administrative Patent Judge.
`
`
`
`DECISION
`Institution of Inter Partes Review
`35 U.S.C. § 314(a)
`
`
`
`
`
`
`
`
`
`IPR2018-00424
`Patent 7,881,902 B1
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`
`A. Background
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`I. INTRODUCTION
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`Apple Inc. (“Petitioner”) filed a Petition requesting inter partes review
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`of claims 16, 9, and 10 (“the challenged claims”) of U.S. Patent No.
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`7,881,902 B1 (Ex. 1001, “the ’902 patent”). Paper 2 (“Pet.”). Uniloc
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`Luxembourg S.A. (“Patent Owner”)1, filed a Preliminary Response. Paper 6
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`(“Prelim. Resp.”). We have jurisdiction under 35 U.S.C. § 314. Upon
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`consideration of the Petition and Preliminary Response, we are persuaded
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`that Petitioner has demonstrated a reasonable likelihood that it would prevail
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`in showing the unpatentability of at least one challenged claim of the ’902
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`patent. Accordingly, we institute inter partes review of all challenged
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`claims.
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`B. Related Matters
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`Petitioner and Patent Owner identify the following as matters that
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`could affect, or be affected by, a decision in this proceeding: Uniloc USA,
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`Inc. v. Huawei Devices USA, Inc., 2-17-cv-00737 (E.D. Tx.); Uniloc USA,
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`Inc. v. HTC America, Inc., 2-17-cv-01629 (W.D. Wa); Uniloc USA, Inc. v.
`
`LG Electronics USA, Inc., 4-12-cv-00832 (N.D. Tx); Uniloc USA, Inc. v.
`
`Samsung Electronics America, Inc., 2-17-cv-00650 (E.D. Tx); and Uniloc
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`USA, Inc. v. Apple Inc., 2-17-cv-00522 (E.D. Tx). Pet. 1–2; Paper 3, (2).
`
`Neither party identifies the following matters before the Board, which also
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`involve the ’902 patent or patents that are related to the ’902 patent: Apple
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`Inc. v. Uniloc Luxembourg S.A., Case IPR2018-01028 (PTAB) (challenging
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`claim 8 of the ’902 patent); Apple Inc. v. Uniloc Luxembourg S.A., Case
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`1 Patent Owner identifies Uniloc USA, Inc. as a real party-in-interest.
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`2
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`
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`IPR2018-00424
`Patent 7,881,902 B1
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`IPR2018-00387 (PTAB) (challenging claims of related U.S. Patent No.
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`7,653,508 B1 (“the ’508 patent”)); Apple Inc. v. Uniloc Luxembourg S.A.,
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`Case IPR2018-01026 (PTAB) (challenging claims of the related ’508
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`patent); Apple Inc. v. Uniloc Luxembourg S.A., Case IPR2018-00389
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`(PTAB) (challenging claims of related U.S. Patent No. 8,712,723 B1 (“the
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`’723 patent”)); and Apple Inc. v. Uniloc Luxembourg S.A., Case IPR2018-
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`01027 (PTAB) (challenging claims of the related ’723 patent).
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`C. Evidence Relied Upon
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`References
`
`Effective Date2
`
`Exhibit
`
`Pasolini
`
`US 7,463,997 B2
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`Oct. 2, 2006
`
`Fabio
`
`US 7,698,097 B2
`
`Oct. 2, 2006
`
`1005
`
`1006
`
`Mitchnick
`
`US 2006/0084848 A1
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`Oct. 14, 2004
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`1007
`
`Tanenhaus
`
`US 6,469,639 B2
`
`Oct. 22, 2002
`
`1008
`
`Sheldon
`
`US 5,957,957
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`Sept. 28, 1999
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`1009
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`
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`Petitioner also relies upon the Declaration of Joseph A. Paradiso, Ph.D.
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`(Ex. 1003).
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`D. Asserted Grounds of Unpatentability
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`Petitioner asserts the following grounds of unpatentability:
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`Reference(s)
`
`Basis
`
`Claims Challenged
`
`Mitchnick
`
`§ 103(a)
`
`1 and 2
`
`Mitchnick and Sheldon
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`§ 103(a)
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`3
`
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`2 Petitioner relies on the filing dates of Pasolini, Fabio, and Mitchnick as the
`effective date for determining their availability as prior art.
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`3
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`IPR2018-00424
`Patent 7,881,902 B1
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`Reference(s)
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`Basis
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`Claims Challenged
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`Mitchnick, Sheldon, and
`Tanenhaus
`
`§ 103(a)
`
`4
`
`Fabio and Pasolini
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`§ 103(a)
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`5, 6, 9, 10
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`II. ANALYSIS
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`A. The ’902 Patent
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`The ’902 patent relates to “a method of . . . counting periodic human
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`motions such as steps.” Ex. 1001, 1:9–11. The method involves the use of a
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`“portable electronic device that includes one or more inertial sensors. . . .
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`[that] measure accelerations along a single axis or multiple axes.” Id. at
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`2:24–28. The measured accelerations may be linear or rotational. Id. at
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`2:28–29.
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`Figure 1 of the ’902 patent is reproduced below.
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`Patent 7,881,902 B1
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`Figure 1 of the ’902 patent is a block diagram illustrating electronic device
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`100. Id. at 1:47–48. Device 100 includes acceleration measuring logic 105
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`(e.g., inertial sensors), dominant axis logic 127, and step counting logic 130.
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`Id. at 2:19–24, 2:38–43, Fig. 1. Device 100 “may be used to count steps or
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`other periodic human motions.” Id. at 2:29–30. In the context of the ’902
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`patent, a “step” is “any user activity having a periodic set of repeated
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`movements.” Id. at 3:34–38. According to the ’902 patent, device 100
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`accurately counts steps “regardless of the placement and/or orientation of the
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`device on a user,” and regardless of whether the device “maintains a fixed
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`orientation or changes orientation during operation.” Id. at 2:31–35.
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`
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`Dominant axis logic 127 includes cadence logic 132 and rolling
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`average logic 135. Id. at 2:66–3:2, Fig. 1. Inertial sensors 105 measure
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`acceleration data, and cadence logic 132 analyzes this data to detect “a
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`period and/or cadence of a motion cycle” or step, which may be based on
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`user activity such as running or walking. Id. at 2:38–40, 3:14–18, 3:46–51.
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`Cadence logic 132 determines “a cadence window 150 to be used by the step
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`counting logic 130.” Id. at 3:11–14. Cadence window 150 is “a window of
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`time since a last step was counted that is looked at to detect a new step.” Id.
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`at 3:65–4:1. Initially, cadence window 150 is set to a default value, but that
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`default value can be dynamically updated after each step once a minimum
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`number of steps have been detected to reflect the cadence or period of the
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`detected steps. Id. at 3:57–61, 4:22–28, 4:61–5:6. The cadence or stepping
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`period can be determined as a “rolling average of the stepping periods over
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`previous steps.” Id. at 3:61–62.
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`Cadence logic 132 also determines “one or more sample periods to be
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`used by the rolling average logic 135.” Id. at 3:11–14, 5:31–34. The sample
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`period is set to be “the length of, or longer than, the stepping period,”
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`including a “multiple of the stepping period.” Id. at 5:34–37. Rolling
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`average logic 135 “creates one or more rolling averages of accelerations . . .
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`measured by the inertial sensor(s) over the sample period(s) set by the
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`cadence logic 132.” Id. at 5:39–41. These rolling averages are used to
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`determine an orientation of the electronic device and a threshold against
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`which acceleration measurements are compared. Id. at 5:41–45.
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`Dominant axis logic 127 includes dominant axis setting logic 140,
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`which determines an orientation of device 100 or the inertial sensor(s) within
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`device 100. Id. at 6:8–10. This may be done “based upon the rolling
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`averages of accelerations created by the rolling average logic 135.” Id. at
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`6:10–12. In particular, “[t]he axis with the largest absolute rolling average”
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`over a given sampling period is identified as the “axis most influenced by
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`gravity,” and is designated the dominant axis. Id. at 6:14–18, 6:23–25. The
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`’902 patent explains that because the device orientation may change over
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`time, the rolling average acceleration may change and “a new dominant axis
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`may be assigned when the orientation of the electronic device 100 and/or the
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`inertial sensor(s) attached to or embedded in the electronic device 100
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`changes.” Id. at 6:16–22. In addition, dominant axis setting logic 140 can
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`set the dominant axis to be a virtual “axis that is defined as approximately
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`aligned to gravity” that is found “by doing trigonometric calculations on the
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`actual axes based on the gravitation influence” on those axes. Id. at 6:25–
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`34.
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`Step counting logic 130 includes measurement selection logic 145,
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`measurement comparator 155, and threshold comparator 160. Id. at 6:38–
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`41. Measurement selection logic 145 “monitor[s] accelerations relative to
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`the dominant axis, and select[s] only those measurements with specific
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`relations to the dominant axis.” Id. at 6:44–47. “Selected measurements
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`[are] forwarded to the measurement comparator 155 and the threshold
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`comparator 160 to determine whether a step has occurred.” Id. at 6:57–59.
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`A method for determining whether a step has occurred is disclosed in
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`Figure 8 of the ’902 patent, which is reproduced below.
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`Figure 8 is a flow diagram of a method for recognizing that a step has
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`occurred. Id. at 2:1–4, 12:25–27. Acceleration measurement data is
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`received and filtered to remove low and high frequency components. Id. at
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`12:31–38, Fig. 8 (steps 805 and 810). A dominant axis is assigned as
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`described above. Id. at 40–44, Fig. 8 (step 812). Because only steps within
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`the cadence window are counted, a determination is made whether the
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`measured acceleration is within the cadence window. Id. at 12:45–48, Fig. 8
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`(step 815). If it is, three additional tests are performed to determine whether
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`the measured acceleration can be counted as a step. First, the absolute value
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`of the measured acceleration along the dominant axis must be greater than a
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`lower threshold, such as the rolling average acceleration along the dominant
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`axis. Id. at 7:9–12, 12:51–55, 12:64–65, Fig. 8 (step 820). Second, the
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`absolute value of the measured acceleration along the dominant axis must be
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`greater than the absolute value of previous measured accelerations along the
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`dominant axis. Id. at 7:9–12, 13:34–38, 13:53–56, Fig. 8 (step 825). Third,
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`the absolute value of the measured acceleration along the dominant axis
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`must be lower than an upper threshold. Id. at 7:9–12, 13:59–62, 13:66–14:1,
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`Fig. 8 (step 830). The upper threshold “prevent[s] sudden accelerations such
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`as taps from being counted as steps.” Id. at 14:1–3.
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`Device 100 is battery operated, and therefore has multiple operating
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`modes to preserve battery life, including sleep mode 305, entry mode 315,
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`stepping mode 325, and exit mode 335. Id. at 8:16–18. The power level of
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`device 100 is linked to these modes. Id. at 8:18–19. The different modes
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`and the relationships between them are shown in Figure 3 of the ’902 patent,
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`which is reproduced below.
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`Figure 3 of the ’902 patent is a state diagram showing the different modes of
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`electronic device 100. Id. at 1:52–54. When no acceleration data is
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`measured, device 100 is in sleep mode 305. Id. at 8:20–22. When
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`acceleration data is detected, device 100 enters entry mode 315 to detect
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`steps in the acceleration data. Id. at 8:22–25. If a predetermined number
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`(N) of steps are detected in a sampling period, device 100 enters stepping
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`mode 325; otherwise it reverts to sleep mode 305. Id. at 8:25–28. In
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`stepping mode 325, steps are detected and counted as described above until
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`no steps are detected within the cadence window, at which point device 100
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`enters exit mode 335. Id. at 8:30–37. In exit mode 335, device 100
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`determines whether a predetermined number (X) of steps are detected at a
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`particular cadence. Id. at 8:38–40. If so, device 100 reverts to stepping
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`mode 325; if not, device 100 reverts to entry mode 315. Id. at 8:41–44.
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`The method by which device 100 transitions from entry mode 315 to
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`stepping mode 325 is shown in Figure 5, which is reproduced below.
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`Figure 5 of the ’902 patent is a flow chart of device 100 operating in entry
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`mode 315. Id. at 1:58–60. After setting a sampling rate (504), a first step is
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`detected in the acceleration data (510), a default cadence window is set
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`(514), and a temporary or buffered step count is set to one (520). Id. at
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`9:55–10:8, 10:25. Next, additional steps are searched for in the acceleration
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`data (524) using the criteria discussed above, including whether the
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`acceleration data falls within the cadence window. Id. at 10:25–30, 12:45–
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`46, Fig. 8.
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`
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`When additional steps are detected in the acceleration data (524), they
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`are added to the buffered step count (560). Id. at 10:46–47. When the
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`number of steps in the buffered step count is less than a predetermined
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`number M (564), additional steps are looked for in the acceleration data
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`(524). Id. at 10:47–52. When the number of steps in the buffered step count
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`reaches predetermined number M (564), a new cadence window is set based
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`on the cadence of the M steps (574), and additional steps are looked for in
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`the acceleration data (524). Id. at 10:53–57. When the number of steps in
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`the buffered step count is greater than predetermined number M (564), the
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`new cadence window is used to look for additional steps in the acceleration
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`data (524) until a predetermined number of N steps is counted in the
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`buffered step count (580). Id. at 10:57–67. When the number of steps in the
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`buffered step count reaches predetermined number N, the number of
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`buffered steps are added to an actual step count, and device 100 enters
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`stepping mode 325. Id. at 10:67–11:3. In stepping mode 325, the cadence
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`window is dynamically updated based on the rolling average of previously
`
`measured stepping periods. Id. at 11:13–17.
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`As discussed above, measured acceleration data is only counted as a
`
`step when it falls within the cadence window. Id. at 10:25–30, 12:45–46,
`
`Fig. 8. Measured acceleration data can fall outside the cadence window
`
`because it is too early or too late. If too early, and time remains within the
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`cadence window (530), additional steps are looked for in the acceleration
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`data (524). Id. at 10:32–36. If too late, no time remains within the cadence
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`window (530), the buffered step count is reset (534), and the acceleration
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`data is searched for another first step (540/510). Id. at 10:36–43.
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`B. Illustrative Claims
`
`Of the challenged claims, claims 1 and 5 of the ’902 patent are
`
`independent. Other challenged claims depend directly from claims 1 and 5.
`
`Claim 1 is reproduced below.
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`1. A method comprising:
`
`detecting motion by an inertial sensor included in a
`mobile device;
`
`determining, by the mobile device, whether the
`motion has a motion signature indicative of a user
`activity that the mobile device is configured to
`monitor;
`
`when the motion does not have a motion signature
`of a user activity that the mobile device is
`configured to monitor, entering a sleep mode.
`
`Ex. 1001, 15:10–18. Claim 5 is reproduced below.
`
`5. A method for a mobile device comprising:
`
`receiving acceleration data that meets stepping
`criteria from an accelerometer included in the
`mobile device;
`
`incrementing a step count in a step count buffer;
`
`when at least one of a) the step count is below a step
`count threshold, or b) a current user cadence fails to
`match a step cadence of a user profile, using a
`default step cadence window to identify a time
`frame within which to monitor for a next step; and
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`when the step count is at or above the step count
`threshold, determining a dynamic step cadence
`window and using the dynamic step cadence
`window to identify the time frame within which to
`monitor for the next step.
`
`Ex. 1001, 15:46–16:6.
`
`C. Claim Construction
`
`In an inter partes review, claim terms of an unexpired patent are given
`
`their broadest reasonable interpretation in light of the specification of the
`
`patent in which they appear. 37 C.F.R. § 42.100(b). Under the broadest
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`reasonable interpretation standard, claim terms are generally given their
`
`ordinary and customary meaning, as would be understood by one of ordinary
`
`skill in the art, in the context of the entire disclosure. In re Translogic Tech.,
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`Inc., 504 F.3d 1249, 1257 (Fed. Cir. 2007). Only claim terms which are in
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`controversy need to be construed and only to the extent necessary to resolve
`
`the controversy. See Vivid Techs., Inc. v. Am. Sci. & Eng’g, Inc., 200 F.3d
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`795, 803 (Fed. Cir. 1999).
`
`Petitioner proposes constructions for the terms “dominant axis” and
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`“cadence window.” Pet. 6–7. Patent Owner argues neither term requires
`
`express construction. Prelim. Resp. 4–6. We address these claim terms
`
`below, as well as the claim term “periodically sampling acceleration data at
`
`a predetermined sampling rate, wherein each sample includes acceleration
`
`data measured by the inertial sensor over a predetermined time period,”
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`which is recited in claim 3.
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`1. dominant axis
`
`Petitioner argues the term “dominant axis” means “the axis most
`
`influenced by gravity.” Pet. 6. Patent Owner challenges this construction as
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`importing limitations from the Specification into the claims because the term
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`“dominant axis” is not limited to an axis influenced by gravity. Prelim.
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`Resp. 5–6. At this stage of the proceeding, on the record before us, we adopt
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`Petitioner’s proposed construction of “dominant axis” to mean “the axis
`
`most influenced by gravity.”
`
`The Specification supports this construction. Specifically, it discloses
`
`dominant axis setting logic 140 assigns a dominant axis to electronic device
`
`100 or an embedded inertial sensor by determining the inertial sensor’s
`
`orientation “based upon the rolling averages of accelerations created by the
`
`rolling average logic 135.” Ex. 1001, 6:8–14. The Specification discloses
`
`assigning the dominant axis as the axis “with the largest absolute rolling
`
`average over the sample period,” and identifies this axis as “the axis most
`
`influenced by gravity.” Id. at 6:16–18, 6:23–25.
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`The disclosed method of assigning the dominant axis allows the
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`assignment to change over time as the orientation of electronic device 100
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`changes over time. Id. at 6:16–22. The Specification also discloses that the
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`dominant axis can be a virtual axis in a virtual coordinate system “that is
`
`defined as approximately aligned to gravity.” Id. at 6:25–30. The virtual
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`axis can be determined, e.g., “by performing a true gravity assessment, such
`
`as by doing trigonometric calculations on the actual axes based on the
`
`gravitational influence.” Id. at 6:30–34. Taken together, these disclosures
`
`identify the dominant axis as an axis in a coordinate system that is most
`
`nearly aligned with the gravitational axis. The coordinate system can be a
`
`real coordinate system defined by the dimensions of electronic device 100 or
`
`its embedded inertial sensors, or a virtual coordinate system derived from
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`these real coordinate system axes having an axis that is aligned to the
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`gravitational axis.
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`2. cadence window
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`Petitioner argues the term “cadence window” is defined in the
`
`Specification to mean “a window of time since a last step was counted that is
`
`looked at to detect a new step.” Pet. 7 (citing Ex. 1001, 3:66–4:1). Patent
`
`Owner does not dispute this construction, but argues the term need not be
`
`construed. Prelim. Resp. 6. At this stage of the proceeding, we agree with
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`Patent Owner that the term “cadence window” need not be construed
`
`because its express construction is not needed to resolve any contention
`
`between the parties.
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`3. periodically sampling acceleration data at a predetermined
`sampling rate, wherein each sample includes acceleration data
`measured by the inertial sensor over a predetermined period of
`time
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`Although neither party asks us to construe this claim 3 limitation, its
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`construction is required because it is unclear whether “each sample” in the
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`“wherein” clause refers to all of the acceleration data measured over each
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`sampling period, or instead refers to each sample of acceleration data that is
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`measured over each sampling period. The ambiguity arises because the
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`Specification discloses periodically sampling the acceleration data (e.g.,
`
`every 10 seconds) for a predetermined period of time (e.g., one second), and
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`further sampling each sample of acceleration data so obtained at a
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`predetermined sampling rate (e.g., 50 Hz). Ex. 1001, 9:5–11. Thus, “each
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`sample” of the acceleration data measured over a predetermined period of
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`time can refer to the acceleration data that is measured for one second out of
`
`every ten seconds, or could refer to one of the fifty acceleration data samples
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`that is measured during one of the one-second sampling periods (sampling
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`one second of acceleration data at 50Hz amounts to taking fifty samples of
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`acceleration data).
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`At this stage of the proceeding, on the record before us, we construe
`
`the term “periodically sampling acceleration data at a predetermined
`
`sampling rate, wherein each sample includes acceleration data measured by
`
`the inertial sensor over a predetermined period of time,” as recited in claim
`
`3, to mean “periodically obtaining acceleration data by sampling the
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`acceleration data over a predetermined period of time.”
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`D. Level of Ordinary Skill in the Art
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`Petitioner contends a person of ordinary skill in the art would have
`
`had a Bachelor of Science degree or equivalent training in electrical
`
`engineering, computer engineering, or computer science, and approximately
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`two years of hardware or software design and development experience
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`related to micro-electro-mechanical (MEM) devices and body motion
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`sensing systems. Pet. 5 (citing Ex. 1003 ¶ 16).3 Patent Owner does not
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`dispute Petitioner’s contention, and does not offer an alternative set of
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`qualifications for a person of ordinary skill in the art. Prelim. Resp. 2–3.
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`At this stage of the proceedings, we find Petitioner’s description to be
`
`reasonable, and adopt it as our own for purposes of this Decision.
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`E. Overview of the Prior Art
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`1. Mitchnick
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`Mitchnick discloses “a device for participant monitoring . . . that
`
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`3 Petitioner cites to the page number of Exhibit 1003. We cite here to the
`paragraph number of Dr. Paradiso’s declaration.
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`automatically collects data with little or no participant attention.” Ex. 1007
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`¶ 1. The device “includes sensors for, at least, detecting and storing the
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`occurrences of sexual activity. . . . by observing characteristic patterns of
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`participant motion as sensed by an acceleration.” Id. ¶ 12. Mitchnick’s
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`preferred embodiment describes a vaginally implanted device; however,
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`Mitchnick discloses alternative embodiments that can reside “elsewhere in
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`or on the body [for] detecting other parameters of medical/clinical interest.”
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`Id. ¶ 43.
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`Figure 1 of Mitchnick is reproduced below.
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`Figure 1 of Mitchnick is a schematic illustration of Mitchnick’s activity
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`monitoring device. Id. ¶ 49. The device includes housing 1, batteries 13,
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`and accelerometer 7 “mounted so that its acceleration measurements are
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`correctly oriented with respect to the housing.” Id. The device is controlled
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`by a microprocessor that “implements general-purpose and power
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`management instructions,” including processing analog sensor signals from
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`the accelerometer. Id. ¶¶ 50, 66, Fig. 2. The device may also include a
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`radio-frequency transceiver for communicating with external devices. Id.
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`¶ 49.
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`The microprocessor’s power management instructions allow the
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`device to operate in either “a very low power . . . sleep mode,” an optional
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`“low power mode,” and a “normal operational mode.” Id. ¶¶ 50, 67. At
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`least some of these modes are shown in Figure 3 of Mitchnick, which is
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`reproduced below.
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`
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`Figure 3 of Mitchnick is a flow chart showing the operating states of
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`Mitchnick’s device and transitions between those operating states. Id. ¶ 67,
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`Fig. 3. The device is in wait/sleep state 71 when it is initially powered on or
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`after the microprocessor receives and executes a SLEEP instruction. Id.
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`¶ 68. The device transitions from wait/sleep state 71 to operational/sleep
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`state 73 when the microprocessor receives an interrupt signal generated by
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`either an internal timer or a wake-up circuit responding to an external event.
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`Id. ¶¶ 68, 72. Mitchnick discloses:
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`Because sexual activity is intermittent, power and
`memory can be advantageously further conserved,
`further extended, by only
`and device
`life
`intermittently sampling 75 for sexual activity and
`by storing sensor detail data only if sexual activity
`is observed. If sexual activity is not detected, the
`device remains in a low-power sleep state.
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`Id. ¶ 69 (emphases added). The timer can periodically wake up the device
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`every 10 minutes, placing it in operational/sleep state 73, to search for
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`sexual activity. Id.
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`When in operational/sleep state 73, the device samples accelerometer
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`data at a predetermined sampling rate and checks for sexual activity over a
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`sampling period that is sufficient to achieve accuracy. Id. ¶¶ 69, 72, 73, Fig.
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`3 (step 75). For example, the sampling period can be chosen so that the
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`device has a 10% duty cycle, and the sampling rate can be 10 Hz. Id. ¶¶ 69,
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`73. Thus, if the device enters operational state 73 every 10 minutes, it will
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`sample the accelerometer data for a period of 1 minute (10% duty cycle),
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`and in the course of that minute it will obtain 600 acceleration data samples
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`(10 Hz sampling rate).
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`The device identifies sexual activity by matching characteristics of the
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`sampled accelerometer data to templates containing accelerometer data
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`characteristics that are indicative of sexual activity, such as peaks in the
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`accelerometer data and time intervals between the peaks. Id. ¶ 70. If the
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`device identifies sexual activity in the accelerometer data, it remains in
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`operational state 73, continuously samples and records the accelerometer
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`data, and checks for additional sexual activity. Id. ¶ 72, Fig. 3 (steps 75, 77,
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`79). However, if the device fails to detect sexual activity in operational state
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`73, it reverts to or remains in sleep state 71. Id. ¶¶ 69, 72.
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`2. Sheldon
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`Sheldon discloses “a rate responsive pacemaker employing a body
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`position sensor to distinguish stair climbing from other activities.” Ex.
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`1009, 4:19–24. The pacemaker includes an accelerometer that “can be used
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`to derive the level of patient activity from the number of changes in signal
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`levels exceeding a certain threshold occurring in a given sampling period.”
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`Id. at 5:14–17. The patient’s posture can also be determined by aligning the
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`accelerometer’s sensitive axis “with the pacemaker case and the patient’s
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`anterior-posterior (A-P) body axis.” Id. at 4:52–56. The accelerometer’s
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`output can be sampled at 200 Hz over a 2 second sampling period, the DC
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`component of the sampled output (i.e., the accelerometer’s “tilt”) can be
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`used to determine the patient’s posture, and the AC component of the
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`sampled output (i.e., the accelerometer’s “activity count”) can be used to
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`determine the patient’s activity level. Id. at 11:64–12:3.
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`3. Tanenhaus
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`Tanenhaus discloses a low power monitoring device that includes a
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`plurality of MEMS (micro-electro-mechanical system) sensors, including at
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`least an accelerometer and a wake-up circuit. Ex. 1008, 4:15–20, 4:29,
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`4:36–38. The wake-up circuit senses an activity, such as a movement, and
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`sends a wake-up signal to a data acquisition processing circuit. Id. at 4:38–
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`41. The wake-up circuit consists of a buffer and absolute value circuit, and a
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`threshold detecting circuit. Id. at 4:53–56, 4:62–66. The buffer and absolute
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`value circuit stores an absolute value of the sampled MEMS output, and the
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`threshold detecting circuit determines whether the buffered output exceeds a
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`predetermined threshold. Id. When it does, a switching circuit connected to
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`the threshold detecting circuit switches the data acquisition processing
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`circuit from a sleep-type low power condition to a wake-up high power
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`condition. Id. at 5:9–14.
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`4. Fabio
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`Fabio discloses a method for “controlling a pedometer based on the
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`use of inertial sensors.” Ex. 1006, 1:10–11. The pedometer can be
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`“integrated within a portable electronic device, such as a cell phone.” Id. at
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`2:34–36. The method involves:
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`generating a signal correlated to movements of a
`user of the pedometer; detecting steps of the user
`based on the signal; checking whether sequences of
`the detected steps satisfy pre-determined conditions
`of regularity; updating a total number of valid steps
`if the conditions of regularity are satisfied; and
`preventing updating of the total number of valid
`steps if the conditions of regularity are not satisfied.
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`Id. at 1:62–2:3. Fabio detects user steps from the sampled acceleration data
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`AZ of its inertial sensor according to a method illustrated in Figures 5 and 6,
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`which are reproduced below.
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`Figure 5 of Fabio is a graph illustrating quantities used to detect user steps
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`from acceleration data. Id. at 2:22–23. A step is detected when a positive
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`peak of acceleration signal AZ is greater than threshold AZP, and a negative
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`peak is less than threshold AZN and falls within fixed time window TW from
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`the positive peak. Id. at 4:15–21.
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`
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`A detected step is validated as a step when it falls within a variable
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`time window TV, which is illustrated in Figure 6, reproduced below.
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`Figure 6 of Fabio is a graph illustrating quantities used to validate user steps
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`detected from acceleration data. Id. at 2:24–25. Figure 6 illustrates a
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`sequence of user steps detected at times TR(1), TR(2) . . . TR(K-2), TR(K-1),
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`and TR(K) according to the method disclosed in Figure 5. The time between
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`steps detected at times TR(K-1) and TR(K-2) is ∆TK-1; the time between steps
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`detected at times TR(K) and TR(K-1) is ∆TK. Id. at 4:28–35. For the step
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`detected at time TR(K) to be validated as a step, it must fall within variable
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`time window TV; i.e., TR(K) must be greater than TR(K-1) + ½ (∆TK-1) and
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`less than TR(K-1) + 2 (∆TK-1). Id. at 4:35–52. Although Figure 6 depicts TV
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`having a variable width ∆TK-1 (e.g., because it depends on the variable time
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`between previous steps) that is asymmetric about time TR(K-1) + ∆TK-1,
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`Fabio discloses time window TV can be “symmetrical and a have a different
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`amplitude.” Id. at 4:52–53. Fabio further discloses that time window TV
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`ensures “the duration ∆TK of a current step K is substantially homogeneous
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`with respect to the duration ∆TK-1 of an immediately preceding step.” Id. at
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`4:28–31.
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`When counting steps, Fabio discloses that isolated “or very brief
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`sequences of steps are far from significant and should preferably be ignored
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`because they are, in effect, irrelevant.” Id. at 1:47–50. To ignore such steps,
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`Fabio discloses a two-stage counting procedure, illustrated in Figure 3,
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`which is reproduced below.
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`
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`Figure 3 of Fabio is a flow chart depicting a two-stage counting procedure.
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`Id. at 2:17–19. Initially, valid step counter NVT, valid control step counter
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`NVC, and invalid step counter NINV are set to zero (100). Id. at 3:13–18.
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`Next, first counting procedure 110 counts steps by sampling acceleration
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`signal AZ at a predetermined frequency. Id. at 3:19–21. First counting
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`procedure 110 terminates and sets a state flag to C when “a regular gate of
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`the user is recognized,” or terminates and sets the state flag to PD when “a
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`time interval . . . that has elapsed from the last step recognized is longer than
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`a first time threshold.” Id. at 3:27–36. If the state flag is set to C, second
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`counting procedure 130 executes; otherwise survey procedure 140 executes
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`and the pedometer is pla
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