DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Notice of Reply
This communication is responsive to the amendment(s) and/or argument(s) filed 2/13/26. The previous ground(s) of objection and/or rejection is/are withdrawn. The following new and/or reiterated ground(s) of rejection is/are set forth hereinbelow.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-8 and 10-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Rodriguez-Villegas et al. (EP 2593007 B1, hereinafter Rodriguez).
For claim 1, Rodriguez discloses a method, comprising inter alia:
receiving an acoustic signal (110) as input to a device and storing the acoustic signal in a non- transitory computer readable medium (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]);
processing the stored acoustic signal by at least one processor of the device executing programmed code instructions to determine respiratory phases in the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), the acoustic signal being representative of a respiratory activity of an individual ((Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), the respiratory activity being defined by respiratory cycles each comprising an inhalation phase and an exhalation phase (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), the processing comprising:
detecting pause intervals in the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]); and
determining time intervals corresponding to inhalation phases and time intervals corresponding to exhalation phases by comparison, for each time interval, of a duration of the pause interval which precedes said time interval with a duration of the pause interval which follows said time interval (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 2, Rodriguez discloses the method according to claim 1, comprising, in response to the device identifying at an end of the detecting, at least one succession of two pause intervals which are separated in the signal by a time interval, called aberrant interval, of duration less than a predetermined duration threshold (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]):
replacing, for each detected succession, a set consisting of the two pause intervals and said aberrant interval by a new pause interval (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 3, Rodriguez discloses the method according to claim 1, comprising, in response to the device identifying, at the end of the determining, at least one time interval, called indeterminate interval, meeting a predetermined inconsistency criterion (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]):
processing, for each indeterminate interval, a portion of the acoustic signal corresponding to said indeterminate interval, by using a machine learning method (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081], particularly [0078]); and
associating said at least one indeterminate interval with an inhalation or exhalation phase depending on results of processing the portion of the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 4, Rodriguez discloses the method according to claim 1,wherein detecting the pause intervals is based on a processing belonging to the group consisting of: a frequency processing of the acoustic signal; and an energy processing of the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 5, Rodriguez discloses the method according to claim 4, wherein detecting the pause intervals is based on the frequency processing of the acoustic signal, (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]) and the frequency processing comprises:
applying a high-pass anti-noise filter to said signal to remove a first predefined frequency range from said signal and obtain a filtered signal as a function of time (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]);
segmenting said filtered signal to obtain a plurality of samples of said filtered signal and, for each sample, estimating an average power spectral density of said sample so as to obtain a frequency signal representing the centroid frequency as a function of time;
applying a sliding time window of predetermined duration to said frequency signal and, for each window:
detecting a frequency maximum of the frequency signal in said window, and
determining a frequency threshold depending on the frequency maximum detected in said window; and
shaping, from said frequency signal, a first transient logic signal of logic levels defined depending on the frequency thresholds determined for said frequency signal, the pause intervals being detected depending on the first transient logic signal.
For claim 6, Rodriguez discloses the method according to claim 4,wherein detecting the pause intervals is based on the energy processing of the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), wherein the energy processing comprises:
applying a high-pass anti-noise filter and a low-pass filter to remove respectively first and second predefined frequency ranges from said signal and obtain a filtered signal as a function of time (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]);
applying a first sliding time window of predetermined duration to said filtered signal and, for each time window, estimating the acoustic intensity of said filtered signal by applying a root mean square envelope in said window, so as to transform said filtered signal into an energy signal as a function of time;
applying a second sliding time window of duration determined by autocorrelation to said energy signal and, for each window:
detecting a minimum intensity of the energy signal in said window, and
determining an intensity threshold determined as a function of the minimum intensity detected in said window; and
shaping, from said energy signal, a second transient logic signal of logic levels defined depending on the intensity thresholds determined for said energy signal, the pause intervals being detected depending on the second transient logic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 7, Rodriguez discloses the method according to claim 6, comprising shaping, by processing said first and second transient logic signals by an OR-Inclusive logic function, a final logic signal of high logic levels corresponding to said detected pause intervals (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081], particularly [0078]).
For claim 8, Rodriguez discloses the method according to claim 7, comprising in response to the device identifying, at the end of the shaping the final logic signal, at least one succession of two pause intervals which are separated by an aberrant interval detected in said final logic signal of duration less than the predetermined duration threshold:
replacing, for each succession detected in said final logic signal, a set consisting of the two pause intervals and said aberrant interval by a new pause interval (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 10, Rodriguez discloses a computer-readable and non-transitory storage medium storing a computer program product comprising program code instructions for implementing a method (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), when said program is executed on a processor of a device, the method comprising inter alia:
receiving an acoustic signal as input to the device and storing the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]); and
processing the stored acoustic signal by the device to determine respiratory phases in the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), the acoustic signal being representative of a respiratory activity of an individual (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), the respiratory activity being defined by respiratory cycles each comprising an inhalation phase and an exhalation phase (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), the processing comprising:
detecting pause intervals in the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]); and
determining time intervals corresponding to inhalation phases and time intervals corresponding to exhalation phases by comparison, for each time interval, of a duration of the pause interval which precedes said time interval with a duration of the pause interval which follows said time interval (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 11, Rodriguez discloses a device, comprising inter alia:
at least one processor (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]); and
at least one non-transitory computer readable medium (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]) comprising instructions stored thereon (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]) which when executed by the at least one processor configure the device to:
receive an acoustic signal as input and store the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]);
process the stored acoustic signal to determine respiratory phases in an acoustic signal representative of a respiratory activity of an individual (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), the respiratory activity being defined by respiratory cycles each comprising an inhalation phase and an exhalation phase (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), wherein the determining comprises:
detecting pause intervals in the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]); and
determining activity intervals corresponding to inhalation phases and activity intervals corresponding to exhalation phases taking account by comparison of the duration of the pause intervals (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 12, Rodriguez discloses the device according to claim 11, wherein the instructions configure the device to, in response to the device identifying, at an end of the detecting, at least one succession of two pause intervals which are separated in the signal by a time interval, called aberrant interval, of duration less than a predetermined duration threshold (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]):
replace, for each detected succession, a set consisting of the two pause intervals and said aberrant interval by a new pause interval (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 13, Rodriguez discloses the device according to claim 11, wherein the instructions configure the device to, in response to the device identifying, at the end of the determining, at least one time interval, called indeterminate interval, meeting a predetermined inconsistency criterion (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]):
process, for each indeterminate interval, a portion of the acoustic signal corresponding to said indeterminate interval, by using a machine learning method (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]); and
associate said at least one indeterminate interval with an inhalation or exhalation phase depending on results of processing the portion of the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 14, Rodriguez discloses the device according to claim 11, wherein detecting the pause intervals is based on a processing belonging to the group consisting of: a frequency processing of the acoustic signal; and an energy processing of the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 15, Rodriguez discloses the device according to claim 14, wherein detecting the pause intervals is based on the frequency processing of the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), and the frequency processing comprises:
applying a high-pass anti-noise filter to said signal to remove a first predefined frequency range from said signal and obtain a filtered signal as a function of time (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]);
segmenting said filtered signal to obtain a plurality of samples of said filtered signal and, for each sample, estimating an average power spectral density of said sample so as to obtain a frequency signal representing the centroid frequency as a function of time;
applying a sliding time window of predetermined duration to said frequency signal and, for each window:
detecting a frequency maximum of the frequency signal in said window, and
determining a frequency threshold depending on the frequency maximum detected in said window; and
shaping, from said frequency signal, a first transient logic signal of logic levels defined depending on the frequency thresholds determined for said frequency signal, the pause intervals being detected depending on the first transient logic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 16, Rodriguez discloses the device according to claim 14, wherein detecting the pause intervals is based on the energy processing of the acoustic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]), wherein the energy processing comprises:
applying a high-pass anti-noise filter and a low-pass filter to remove respectively first and second predefined frequency ranges from said signal and obtain a filtered signal as a function of time (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]);
applying a first sliding time window of predetermined duration to said filtered signal and, for each time window, estimating the acoustic intensity of said filtered signal by applying a root mean square envelope in said window, so as to transform said filtered signal into an energy signal as a function of time;
applying a second sliding time window of duration determined by autocorrelation to said energy signal and, for each window:
detecting a minimum intensity of the energy signal in said window, and
determining an intensity threshold determined as a function of the minimum intensity detected in said window; and
shaping, from said energy signal, a second transient logic signal of logic levels defined depending on the intensity thresholds determined for said energy signal, the pause intervals being detected depending on the second transient logic signal (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 17, Rodriguez discloses the device according to claim 16, wherein the instructions configure the device to shape, by processing said first and second transient logic signals by an OR-Inclusive logic function, a final logic signal of high logic levels corresponding to said detected pause intervals (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 18, Rodriguez discloses the device according to claim 17, wherein the instructions configure the device to, in response to the device identifying, at the end of the shaping the final logic signal, at least one succession of two pause intervals which are separated by an aberrant interval detected in said final logic signal of duration less than the predetermined duration threshold (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]):
replace, for each succession detected in said final logic signal, a set consisting of the two pause intervals and said aberrant interval by a new pause interval (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 19, Rodriguez discloses the method according to claim 1, wherein the receiving comprises receiving the acoustic sound signal from a sensor (102), which is configured to capture sound pressure waves (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
For claim 20, Rodriguez discloses the method according to claim 1, which further comprises capturing the acoustic pressure waves with the sensor and generating the acoustic signal from the captured acoustic pressure waves (Figs 2-11, especially 2,6,7,11) ([0001-0083], especially [0066-0081]).
Response to Arguments
Applicant’s arguments, see pages 10-12, filed 2/13/26, with respect to the 112 and 101 rejections of the claims in view of the amendments have been fully considered and are persuasive. The 112 and 101 rejections of the amended claims have been withdrawn.
Applicant's arguments, see pages 12-14, filed 2/13/26, with respect to the 102 rejections of the claims in view of the amendments have been fully considered but they are not persuasive.
Regarding the 102 rejection of the claims as being anticipated by Rodriguez, Applicant argues the following:
Rodriguez fails to teach implementation of the following steps (using terms of claim 1):
detecting pause intervals in the acoustic signal; and
determining time intervals corresponding to inhalation phases and time intervals corresponding to exhalation phases by comparison, for each time interval, of a duration of the pause interval which precedes said time interval with a duration of the pause interval which follows said time interval.
Paragraphs [0036-0037 and 0065, 0068, 0070, 0077-0077] of Rodriguez describe how, after detecting "candidate segments" of breathing, the system decides which ones are true respiratory events (inhalation/exhalation), how it improves the reliability of this decision using temporal rules, and how this information is then used to detect apnea and classify respiratory cycles. Rodriguez explicitly refers to breathing pauses or periods without detected breathing and their role in the algorithm
Rodriguez also refer to the use of breathing pauses, but to estimate background noise (which contains signal minima). Two types of pauses are described: short pauses within a cycle between inhalation and exhalation, and long pauses between two successive cycles. An associated problem is described whereby short pauses may be too brief to reach a true minimum (hardware delays, signal inertia), which can distort the noise estimate. To avoid this, the system observes at least one complete cycle (inhalation, intermediate pause, exhalation, and final pause), stores the minima, and calculates the noise from the relevant minimum, to subtract it from the signal in each band.
However, these passages of Rodriguez make no reference to a mechanism that compares, for each time interval, the duration of the pause interval preceding said time interval with the duration of the pause interval following said time interval for the purpose of determining the inspiration phases and the expiration phases. In other words, although it teaches the possibility of identifying pause intervals in an acoustic signal, Rodriguez does not use these pause intervals to determine the inspiration and expiration phases of the signal, but rather to measure the background noise of the acoustic signal.
In response, the Examiner respectfully disagrees and notes the following:
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “a mechanism that compares, for each time interval, the duration of the pause interval preceding said time interval with the duration of the pause interval following said time interval for the purpose of determining the inspiration phases and the expiration phases” and/or “use these pause intervals to determine the inspiration and expiration phases of the signal”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Conversely, the claims merely require “determining time intervals corresponding to inhalation phases and time intervals corresponding to exhalation phases by comparison, for each time interval, of a duration of the pause interval which precedes said time interval with a duration of the pause interval which follows said time interval.”
The mere fact that Rodriguez is primarily concerned with identifying true respiratory events of inhalation and exhalation from candidate segments, determining the noise minima therebetween, and/or determining apnea events without breathing does not preclude the disclosure of Rodriguez from disclosing the “determining time intervals” of breathing “pause interval”(s) before, after, and/or during respiratory events.
In discriminating candidate breathing events via the dynamic algorithmic comparisons in Figures 6-7, Rodriguez is identifying time intervals corresponding to inhalation and exhalation events, even for partial inhalation/exhalation, via comparison updated data segmentation threshold adaptation and is also identifying time intervals including the pause interval preceding and following the time intervals of inhalation and expiration as evidenced at least in Figure 11. The time intervals for preceding and following pauses between inhalation and exhalation must be identified in Rodriguez in order to discriminate between routine breathing pauses and non-breathing apnea events that are determined. For example at least, Rodriguez Figure 11 reproduced below and [0070-0081] clearly demonstrates the identification of breathing events and their corresponding segmented classification rankings over time, where the time therebetween corresponds to the pause interval that is compared with preceding and following values to identify inhalation and expiration over time to further evaluate respiratory rate.
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Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jeffrey G. Hoekstra whose telephone number is (571)272-7232. The examiner can normally be reached Monday through Thursday from 5am-3pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Charles A. Marmor II can be reached at (571)272-4730. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Jeffrey G. Hoekstra
Primary Examiner
Art Unit 3791
/JEFFREY G. HOEKSTRA/ Primary Examiner, Art Unit 3791
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