Ex Parte Aarts

Patent Trial and Appeal Board

Aug 31, 2016

12996034 (P.T.A.B. Aug. 31, 2016)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR
12/996,034 12/03/2010 Ronald M. Aarts
24737 7590 09/02/2016
PHILIPS INTELLECTUAL PROPERTY & STANDARDS
465 Columbus A venue
Suite 340
Valhalla, NY 10595
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www .uspto.gov
ATTORNEY DOCKET NO. CONFIRMATION NO.
2008P00626WOUS 5089
EXAMINER
DOUGHERTY, SEAN PATRICK
ART UNIT PAPER NUMBER
3736
NOTIFICATION DATE DELIVERY MODE
09/02/2016 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address( es):
marianne.fox@philips.com
debbie.henn@philips.com
patti. demichele@Philips.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte RONALD M. AARTS
Appeal2014-008694
Application 12/996,034
Technology Center 3700
Before DONALD E. ADAMS, JEFFREY N. FREDMAN, and
TIMOTHY G. MAJORS, Administrative Patent Judges.
PERCURIAM
DECISION ON APPEAL
This is an appeal 1 under 35 U.S.C. § 134 involving claims to an
acoustical patient monitoring system using a classifier and a microphone.
The Examiner rejected the claims on the grounds of anticipation and
obviousness. We have jurisdiction under 35 U.S.C. § 6(b). We affirm.
1 Appellant identifies the Real Party in Interest as Koninklijke Philips
Electronics N.V. (see App. Br. 1 ).
Appeal2014-008694
Application 12/996,034
Statement of the Case
Background
Appellant's invention relates to "a patient monitoring system [that]
includes one or more microphones that detect acoustic events generated by a
patient and generate signals comprising information describing the acoustic
events, a processor that timestamps the acoustic event signals, and a
classifier that classifies each acoustic event signal into one of a plurality of
acoustic event classes" (Spec. 2: 3-7).
The Claims
Claims 1-11 and 13-20 are on appeal. Independent claim 1 is
representative and reads as follows (emphasis added):
1. A patient monitoring system, including:
one or more microphones that detect acoustic events
generated by a patient, and generate signals compnsmg
information describing the acoustic events;
a processor that timestamps the acoustic event signals;
a classifier that classifies each acoustic event signal
into one of a plurality of acoustic event classes; and
a memory that stores computer-executable instructions
that are executed by the processor, including instructions for:
filtering the acoustic event signal and identifj;ing
signatures associated with the acoustic event signal prior to
digitizing the acoustic event signal;
digitizing the acoustic event signal;
classifj;ing the acoustic event signal into one of a
plurality of acoustic event classes as a function of the
identified signatures.
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Appeal2014-008694
Application 12/996,034
The Issues
A. The Examiner rejected claims 1-7 under 35 U.S.C. § 102(b) as being
anticipated by Shalon2 (Ans. 2--4).
B. The Examiner rejected claims 8-11 and 13-20 under 35 U.S.C.
§ 103(a) as obvious over Shalon, Meyer, 3 and Thiagarajan4 (Ans. 6-8).
A. 35 USC§ 102(b) over Shalon
The Examiner finds that Shalon teaches
a classifier that classifies each acoustic event signal into one
of a plurality of acoustic event classes (deriving an activity
related signature therefrom, thereby enabling classification of
a specific activity associated with the non-verbal acoustic
energy, paragraph 001 O; distinction between, for exampling,
chewing and swallowing, paragraph 0261 ); and
filtering the acoustic event signal (a preprocessing stage
filters out noise, paragraph 0240) and identifying signatures
associated with the acoustic event signal prior to digitizing
the acoustic event signal (a preprocessing module detects the
presence of eating activity and automatically conditions the
signal using automatic gain control on the analog signal prior
to being digitized [emphasis added], paragraph 0254) ....
(Ans. 3.)
The issue with respect to this rejection is: Does the evidence of record
support the Examiner's findings that Shalon anticipates Appellant's claimed
invention?
2 Shalon et al., US 2006/0064037 Al, published Mar. 23, 2006.
3 Meyer et al., US 6,063,043, issued May 16, 2000.
4 Thiagarajan, US 7,806,833 B2, issued Oct. 5, 2010.
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Appeal2014-008694
Application 12/996,034
Findings of Fact
1. Shalon teaches
a system for detecting activity related to non-verbal
acoustic energy generated by a subject comprising: (a) a
sensor mountable on or in a body region of the subject, the
sensor being capable of sensing the non-verbal acoustic
energy; and (b) a processing unit being capable of processing
the non-verbal acoustic energy sensed by the sensor and
deriving an activity related signature therefrom, thereby
enabling classification of a specific activity associated with
the non-verbal acoustic energy.
(Shalon i-f 10; see also Ans. 2-3.)
2. Shalon teaches
Acoustic energy generated by chewing, swallowing,
biting, sipping, drinking, teeth grinding, teeth clicking,
tongue clicking, tongue movement, jaw muscles or jaw bone
movement, spitting, clearing of the throat, coughing,
sneezing, snoring, breathing rate, breathing depth, nature of
the breath, heart beat, digestion, motility to or through the
intestines, tooth brushing, smoking, screaming, user;s voice
or speech, other user generated sounds, and ambient noises in
the user's immediate surroundings can be monitored through
one or more sensors (e.g. microphones) positioned in or
around the ear area, on the skull, neck, throat, chest, back or
abdomen regions. . . . Microphones in different positions or
orientations can be tuned to detect sounds originating within
the user's body as opposed to ambient sounds surrounding the
user. ... Each microphone can be optimized to receive a
specific range of sound frequencies corresponding to the
signal to be measured. The sensing element can be designed
to be sensitive to a wide range of frequencies of the acoustic
energy generated in the head region, ranging from
approximately 0.001 hertz up to approximately 100 kilohertz.
The sensing element can be sensitive to just a narrow range
of frequencies and a multiplicity of sensing elements used to
cover a broader range of frequencies.
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Application 12/996,034
(Shalon il I 17; see also Ans. 4.)
3. Shalon teaches
The sensed ingestion activity can be transmitted
without being preprocessed in which case it can represent a
simple time and duration of ingestion, intensity and rate of
ingestion, count of bites, chews, swallows, etc., over a time
period. If desired, transmitted non-processed data, such as by
way of example raw audio recordings of ingestion sounds,
can be processed by the third party to derive activity related
signatures etc.
(Shalon i-f 192; see also Ans. 3.)
4. Shalon teaches
The bone conduction microphone is designed to sense
the acoustic energy generated within the mouth during eating.
The microphone's analogue electrical output is transmitted to
processing unit 14 for signal processing. A preprocessing
stage filters out noise, normalizes the energy level, and
segments the sampled sound into analysis frames. Features
are then extracted from the signal using spectral signature
analysis to identify waveforms with eating microstructure
events (signatures). The extracted components are then
evaluated by a statistical classifier that combines the observed
data (the features) with prior information about the patterns to
segment the input data into specific event categories such as
chews, sips, and speech. The extracted acoustic energy
patterns are then mapped into food intake events.
(Shalon i-f 240; see also Ans. 3.)
5. Shalon teaches
Sensor unit 12 (bone conduction microphone in this
case) records the sounds made by chewing, swallowing,
biting, sipping, and drinking. The salient acoustic features are
extracted using a statistical-based pattern recognition system
to classify the sounds into specific events. The output of the
recognizer can be a hypothesized event sequence that can be
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Appeal2014-008694
Application 12/996,034
used to track the flow of ingested food. The accuracy of the
hypothesized output can be validated using a database of
sounds annotated by a panel ofhmnan expert listeners.
(Shalon i-f 252; see also Ans. 3--4.)
6. Shalon teaches that "[a] preprocessing module detects the
presence of eating activity and automatically conditions the signal using
automatic gain control on the analog signal prior to being digitized" (Shalon
i-f 254; see also Ans. 3).
7. Shalon teaches "band-pass filters (BPF) 104 and low-pass filter
(LPF) 106 to allow signals of certain frequency through" (Shalon i-f 271; see
also Ans. 4 ).
Principles of Law
A prior art reference can only anticipate a claim if it discloses all the
claimed limitations "arranged or combined in the same way as in the claim."
Wm. Wrigley Jr. Co. v. Cadbury Adams USA LLC, 683 F.3d 1356, 1361
(Fed. Cir. 2012).
Analysis
We adopt the Examiner's findings of fact and reasoning regarding the
scope and content of the prior art (Ans. 2-11; FF 1-7) and agree that claims
1-7 are anticipated by Shalon. We address Appellant's arguments below.
Claim 1
Appellant contends that "[ n ]othing in the cited passage describes the
claimed feature of filtering detected acoustic events and identifying signal
signatures prior to digitization" (App. Br. 6; see also Reply Br. 3).
Appellant further argues that "Shalon states 'The signals received from
sensor unit 12 (and other input systems) are preferably first digitized,"' and
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Application 12/996,034
that "Shalon teaches away from identifying signatures in a signal prior to
digitization of the signal, in favor of digitizing the signal prior to any
processing or signal signature identification" (App. Br. 6; see also Reply Br.
3-5).
We are not persuaded. Shalon teaches that "[a] preprocessing module
detects the presence of eating activity and automatically conditions the
signal using automatic gain control on the analog signal prior to being
digitized" (FF 6 (emphasis added)), and "band-pass filters (BPF) 104 and
low-pass.filter (LPF) 106 to allow signals of certain frequency through" (FF
7 (emphasis added)). Therefore, Shalon is expressly teaching an example
where signals are filtered prior to being digitized, even if this is not preferred
(FF 6). See Merck & Co. Inc. v. Biocraft Labs. Inc., 874 F.2d 804, 807 (Fed.
Cir. 1989) ("'the fact that a specific [embodiment] is taught to be preferred
is not controlling, since all disclosures of the prior art, including unpreferred
embodiments, must be considered."') Moreover, the concept of teaching
away is inapplicable when, as here, the rejection is based on anticipation.
See Celeritas Techs., Ltd. v. Rockwell Int'! Corp., 150 F.3d 1354, 1361 (Fed.
Cir. 1998) ("Thus, the question whether a reference 'teaches away' from the
invention is inapplicable to an anticipation analysis.").
Therefore, we agree with the Examiner that
Shalon discloses the filtering of the acoustic event
signal in a preprocessing state that filters out noise (paragraph
0240) and the identifying of signatures associated with an
acoustic event signal prior to digitizing the acoustic event, as
Shalon discloses a preprocessing module that detects the
presence of eating activity and automatically conditions the
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Application 12/996,034
signal using automatic gain control on the analog signal prior
to being digitized as set forth at paragraph 0254 of Shalon.
(Ans. 9.)
We also agree with the Examiner that "the detection performed by the
preprocessing module reads upon the 'identifying' limitation, the signal
which is conditioned and normalized prior to digitization reads upon the
'signal' limitation, and the amplitude of the signal generated by the sensor
unit 12 reads upon the 'signature' limitation" (id.), and that "the gain control
performed on the signal detected by the preprocessing module, as set forth in
paragraph 0254, is another type of identifying a signal signature performed
before digitization" (id. at 10).
We recognize, but find unpersuasive, Appellant's contention that
"[ s ]ince the microphone is designed to detect a single type of acoustic event
(chewing), Shalon is not concerned with identifying signatures associated
with the acoustic event, nor does it classify the acoustic event since the type
of event is known upon detection by the specially-designed bone conduction
microphone" (Reply Br. 4). Shalon teaches
Acoustic energy generated by chewing, swallowing,
biting, sipping, drinking, teeth grinding, teeth clicking,
tongue clicking, tongue movement, jaw muscles or jaw bone
movement, spitting, clearing of the throat, coughing,
sneezing, snoring, breathing rate, breathing depth, nature of
the breath, heart beat, digestion, motility to or through the
intestines, tooth brushing, smoking, screaming, user's voice
or speech, other user generated sounds, and ambient noises in
the user's immediate surroundings can be monitored through
one or more sensors (e.g. microphones) positioned in or
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Appeal2014-008694
Application 12/996,034
around the ear area, on the skull, neck, throat, chest, back or
abdomen regions.
(FF 2.) Therefore, Shalon teaches detecting acoustic events other than
chewing. "Attorney's argument in a brief cannot take the place of
evidence." In re Pearson, 494 F.2d 1399, 1405 (CCPA 1974).
Claim 4
Appellant argues that "the cited passage mentions that each
microphone can be optimized to receive a specific frequency range, but is
silent with regard to employing active noise cancellation, let alone ANC that
suppresses non-patient generated acoustic events" (App. Br. 7; see also
Reply Br. 8-9). Appellant also argues that "the fact that Shalon optimizes
microphone position and tuning to avoid unwanted frequencies is further
evidence that Shalon does not employ active noise cancellation to suppress
such frequencies" (Reply Br. 9).
We do not find these arguments persuasive. Shalon teaches
Microphones in different positions or orientations can
be tuned to detect sounds originating within the user's body
as opposed to ambient sounds surrounding the user.
. . . Each microphone can be optimized to receive a specific
range of sound frequencies corresponding to the signal to be
measured. The sensing element can be designed to be
sensitive to a wide range of frequencies of the acoustic energy
generated in the head region, ranging from approximately
0.001 hertz up to approximately 100 kilohertz. The sensing
element can be sensitive to just a narrow range of frequencies
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Appeal2014-008694
Application 12/996,034
and a multiplicity of sensing elements used to cover a broader
range of frequencies.
(FF 2 (emphasis added).) Accordingly, we agree with the Examiner that the
"suppression of non-patient generated acoustic even[t]s is also fully
disclosed because Shalon explicitly states at paragraph 0117 that by using
ANC, "sounds surrounding the user" can be avoided by optimizing
positions, orientations and frequency ranges of the microphones.
(Ans. 11; cf Shalon i-f 121 ("[t]he ambient noise or the noise of the speaker
can be cancelled out from the microphone input using passive and active
means"); i-f 340 ("[ t ]he system can also be used as noise cancellation
headphones by monitoring the ambient noise arriving in the ear region of the
user and then generating the opposite sound pattern and transmitting this
cancellation wave through the bones of the user to the ear").) See In re
Sneed, 710 F.2d at 1548.
Accordingly, we affirm the rejection of claim 1. Appellant does not
argue the claims 2, 3, and 5-7 separately, and therefore, claims 2, 3, and 5-7
fall with claim 1.
B. 35 USC§ 103(a) over Shalon, Meyer, and Thiagarajan
Claims 11, 19 and 20
Appellant similarly argues that "[ n ]othing in the cited passage
describes the claimed feature of filtering detected acoustic events and
identifying signal signatures prior to digitization," and "Shalon states 'The
signals received from sensor unit 12 (and other input systems) are preferably
first digitized"' (App. Br. 8-11; see also Reply Br. 6-8). We are not
persuaded for the reasons discussed above.
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Application 12/996,034
Claim 17
Appellant similarly argues that "the cited passage mentions that each
microphone can be optimized to receive a specific frequency range, but is
silent with regard to employing active noise cancellation, let alone ANC that
suppresses non-patient generated acoustic events" (App. Br. 10; see also
Reply Br. 8-9). We are not persuaded for the reasons discussed above.
Accordingly, we affirm the rejection of claims 11, 17, 19 and 20.
Appellant does not argue the other claims separately, and therefore, claims
13-16 fall with claim 11, and claim 19 falls with claim 18.
SUMMARY
In summary, we affirm the rejection of claim 1 under 35 U.S.C.
§ 102(b) as being anticipated by Shalon. Claims 2-7 fall with claim 1.
We affirm the rejection of claims 8-11, 19, and 20 under 35 U.S.C.
§ 103(a) as obvious over Shalon, Meyer, and Thiagarajan. Claims 13-17
fall with claim 11, and claim 19 falls with claim 18.
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a).
AFFIRMED
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