DETAILED ACTION
Note: The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Election/Restrictions
Applicant’s election without traverse of claims 20-37 in the reply filed on July 6, 2026 is acknowledged. Claims 1-19 are withdrawn from consideration.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under U.S.C. 120, 121, or 365 is acknowledged. The prior-filed applications (15/752647 filed on 2/14/2018; PCT/EP2016/069496 filed on 8/17/2016; and PRO 62/205823filed on 8/17/2015) are acknowledged.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 16 April 2024, 17 March 2025, 1 April 2025, and 22 October 2025 have been considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 20-37 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. A streamlined analysis of claim 20 follows.
Regarding claim 20, the claim recites an apparatus for detecting an event of sleep disordered breathing of a user. Thus, the claim is directed to a machine/apparatus, which is one of the statutory categories of invention.
The claim is then analyzed to determine whether it is directed to any judicial exception. The following limitations set forth a judicial exception:
“frame the input audio signal into a plurality of frames; filter one or more frames of the plurality of frames to generate audio frequency characteristics of the one or more frames; detect a signal type representing at least one recovery breath, by evaluating the audio frequency characteristics of the one or more frames determined by the filtering, and evaluating respiratory rate of a breathing signal determined from the one or more frames of the received input audio signal…”
These limitations describe a mathematical calculation. Furthermore, the limitations also describe a mental process as the skilled artisan is capable of performing the recited limitations and making a mental assessment thereafter. Examiner also notes that nothing from the claims suggest that the limitations cannot be practically performed by a human, or using simple pen/paper.
Next, the claim as a whole is analyzed to determine whether any element, or combination of elements, integrates the identified judicial exception into a practical application.
For this part of the 101 analysis, the following additional limitations are considered:
“Apparatus for detecting an event of sleep disordered breathing of a user, the apparatus comprising: a sound sensor configured to sense sound proximate to the sensor and transduce the sensed sound to an audio signal representing the sensed sound; and a processor configured to: receive the audio signal… and output an indicator signalling a sleep disordered breathing event based on the detecting the signal type representing the at least one recovery breath”
These additional limitations do not integrate the judicial exception into a practical application. Rather, the additional limitations are each recited at a high level of generality such that it amounts to insignificant extra-solution activity, e.g., mere data gathering steps necessary to perform the identified judicial exception and outputting fail to integrate the claimed invention into a practical application. See MPEP 2106.05(g).
The additional limitations also do not add significantly more to the identified judicial exception because they relate to widely-understood, routine, and conventional components in the field of endeavor. See prior art teachings cited at the end of the current office action for example teachings.
Dependent claims 21-37 also fail to add something more to the abstract independent claims as they merely further limit the abstract idea, recite limitations that do not integrate the claims into a practical application for substantially similar reasons as set forth above, and/or do not recite significantly more than the identified abstract idea for substantially similar reasons as set forth above.
Therefore, claims 20-37 are not patent eligible under 35 USC 101.
Claim Rejections - 35 USC § 102(A)(1)
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claims 20 -37 are rejected under 35 U.S.C. 102(A)(1) as being anticipated by Yang et al. (US PG Pub. No. 2014/0171815 A1) (hereinafter “Yang”).
With respect to claim 20, Yang teaches an apparatus for detecting an event of sleep disordered breathing of a user (abstract “sleep monitoring method and device classify segments of an acoustic physiological signal captured during sleep as snore and apnea segments”), the apparatus comprising: a sound sensor configured to sense sound proximate to the sensor and transduce the sensed sound to an audio signal representing the sensed sound (sound capture element 110 in Fig. 1; par.0034 “Capture element includes a sound transducer, such as a microphone, that continually detects body sound, such as respiration sound, heart sound and other sound, while a person is sleeping”); and a processor configured to: receive the audio signal (acoustic signal processing element 120 in Fig. 1; par.0035 “Processing element 120… receives the physiological signal from capture system 110”); frame the input audio signal into a plurality of frames (par.0038 “energy envelope representing the total energy of the physiological signal during short time windows… length of each time window is between five percent and ten percent of a complete respiration cycle”); filter one or more frames of the plurality of frames to generate audio frequency characteristics of the one or more frames (par.0040 “normalizer 220 first applies a highpass filter that removes the DC energy component of the physiological signal”); detect a signal type representing at least one recovery breath, by evaluating the audio frequency characteristics of the one or more frames determined by the filtering, and evaluating respiratory rate of a breathing signal determined from the one or more frames of the received input audio signal (par.0035 “receives the physiological signal from capture system 110, classifies different time segments of the physiological signal as snore segments, apnea segments and other segments… may additionally generate and transmit to output element 130 values for physiological parameters, such as respiration rate”; par.0048 “apnea detection stage… monitor loudness and rhythm of the physiological signal… second type of event is noise indicative of other than apnea, as evidence by the local maximum exceeding a gasp threshold, which is a loudness threshold set higher than the snore loudness threshold”); and output an indicator signalling a sleep disordered breathing event based on the detecting the signal type representing the at least one recovery breath (par.0049 “transmits sleep profile data to output element 130… display screen for displaying sleep profile data received from processing element 120 and/or information derived from sleep profile data”).
With respect to claim 21, Yang teaches wherein, to detect the signal type representing the at least one recovery breath, the processor is further configured to analyse audio level determined from the one or more frames of the received input audio signal (par.12, 16, 18, 22, 48).
With respect to claim 22, Yang teaches wherein, to detect the signal type representing the at least one recovery breath, the processor is configured to classify an event as recovery breathing (par.12, 16, 18, 22, 48).
With respect to claim 23, Yang teaches wherein, to filter the one or more frames, the processor is further configured to group a plurality of frequency components of the input audio signal into categories of audio frequency bands based upon signal energy in the audio frequency bands (par.10, 13, 25, 37, 41-42, 44, 47).
With respect to claim 24, Yang teaches wherein the processor is further configured to summate audio signal level for each of the audio frequency bands (par.10, 13, 25, 37, 41-42, 44, 47).
With respect to claim 25, Yang teaches wherein the processor is configured to characterize the signal type representing at least one recovery breath by frequency components in a frequency band of 100 Hertz to 4000 Hertz (par.10, 13, 25, 37, 41-42, 44, 47).
With respect to claim 26, Yang teaches wherein, to detect the signal type representing the at least one recovery breath the processor is further configured to detect an audio level amplitude that is higher than an average amplitude of breathing (par.12, 16, 18, 22, 48).
With respect to claim 27, Yang teaches wherein the detected audio level amplitude is at least twice as high as the average amplitude of breathing (par.12, 16, 18, 22, 48).
With respect to claim 28, Yang teaches wherein, to detect the signal type representing the at least one recovery breath, the processor is further configured to detect an audio level amplitude that is higher than an average amplitude of snoring (par.12, 16, 18, 22, 48).
With respect to claim 29, Yang teaches wherein, to detect the signal type representing the at least one recovery breath, the processor is further configured to detect a breathing rate that is higher than an average breathing rate (par.12, 16, 18, 22, 30, 48).
With respect to claim 30, Yang teaches wherein the detected breathing rate is in a range of 20 beats per minute to 30 beats per minute (par.39).
With respect to claim 31, Yang teaches wherein, to detect the at least one recovery breath, the processor is further configured to detect an audio frequency that is higher than an average frequency of snoring (par.12, 16, 18, 22, 48).
With respect to claim 32, Yang teaches wherein, to detect the at least one recovery breath, the processor is further configured to detect an audio frequency that is higher than an average frequency of breathing (par.12, 16, 18, 22, 48).
With respect to claim 33, Yang teaches wherein, to detect the signal type representing the at least one recovery breath, the processor is further configured to compute a probability value for the signal type representing the at least one recovery breath (par.12, 16, 18, 22, 48).
With respect to claim 34, Yang teaches wherein the probability value is a highest probability value of a plurality of computed probability values for a group of different signal types (par.12, 16, 18, 22, 48).
With respect to claim 35, Yang teaches wherein the at least one recovery breath is associated with an end of an apnea (par. 35-36, 47-48).
With respect to claim 36, Yang teaches wherein the at least one recovery breath is a gasp with snoring (par.12, 16, 18, 22, 48).
With respect to claim 37, Yang teaches wherein the processor is further configured to detect, based on the detected signal type representing the at least one recovery breath, a presence of apnea by detecting a period of silence preceding the detected signal type representing the at least one recovery breath (par. 12, 16, 18, 22, 48).
Prior Art of Record
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US PG Pub. No. 2008/0243017 A1
US PG Pub. No. 2012/0071741 A1
US PG Pub. No. 2013/0331722 A1
Conclusion
No claim is allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PUYA AGAHI whose telephone number is (571)270-1906. The examiner can normally be reached M-F 8 AM - 5 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alexander Valvis can be reached at 5712724233. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PUYA AGAHI/Primary Examiner, Art Unit 3791
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