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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 8/5/26 has been entered.
Response to Amendment
Receipt is acknowledged of applicant's amendment filed on 8/5/26. Claim 11 is cancelled. Claims 1-4, 7, 8, 10, 12-15 and 17-20 are currently pending and an action on the merits is as follows.
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 1-4, 7, 8, 10, 12-15 and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites the steps of determining first snore information before the target audio clip and second snore information after the target audio clip based on the initial audio clips, determining a confidence value for the target audio clip based on the first snore information and the second snore information, wherein the confidence value is configured to represent a possibility that the target audio clip is an abnormal sleep audio clip and determining whether the target audio clip is the abnormal sleep audio clip based on the confidence value of the target audio clip.
The limitation of determining the snore information, determining a confidence value and determining whether the target audio clip is abnormal, as drafted, are processes that, under their broadest reasonable interpretation, cover performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “a processor”, the claims are direct to concepts relating to organizing information in a way that can be performed mentally or analogous to human mental work and nothing in the claim element precludes the steps from practically being performed in the mind. For example, but for the processor, communications interface and output language, “determining” in the context of this claim encompasses the user manually calculating information from the obtained signals. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of obtaining a plurality of initial audio clips. This is just data gathering and amounts to insignificant extra-solutional activity, specifically pre-solutional activity. Additionally, the processor, memory and implied output device are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Similarly, the dependent claims do not include additional elements that amount to significantly more. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept and well-understood, routine and conventional activity is not sufficient to amount to significantly more than the abstract idea itself. The claim is not patent eligible.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-4, 7, 8, 10, 12-15 and 17-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claims 1, 12 and 20 recite that the preset sleep state comprises both hypopnea and apnea within the same initial audio clip. It is unclear if this means that the target clip must contain hypopnea and apnea or that the target clips are either hypopnea or apnea found within the overall initial audio clip. For examination purposes, the Examiner presumes it is the latter.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 7, 12, 18 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ishikawa et al. US 2013/0261485 in view of Fox et al. US 2023/0099622 and Su et al. US 2020/0383581.
Regarding claim 1, 12 and 20, Ishikawa discloses a method for recognizing an abnormal sleep audio clip, performed by an electronic device, comprising:
obtaining a plurality of initial audio clips collected by a sensor, wherein the initial audio clip comprises a first audio clip, a target audio clip, and a second audio clip with continuous timing information ([¶50,51,55-57]);
determining the target audio clip matching a preset sleep state from the initial audio clips, wherein the preset sleep state represent an abnormal sleep state ([FIG4][FIG6b][¶84] one of the midway segments is the target clip with segments before and after);
determining first snore information in the first audio clip before the target audio clip and second snore information in the second audio clip after the target audio clip based on the initial audio clips ([¶84] breathing information before and after the target segment are determined);
determining a confidence value for the target audio clip based on the first snore information and the second snore information, wherein the confidence value is configured to represent a possibility that the target audio clip is an abnormal sleep audio clip ([¶103,104-113] based on the determinations about the previous segment and the following segment and duration criteria it is determined if apnea has occurred); and
determining whether the target audio clip is the abnormal sleep audio clip based on the confidence value of the target audio clip ([¶104-110,163,185-186] the sound level or intensity is used as the confidence value to determine the difference in sound between segments).
wherein determining the confidence value for the target audio clip based on the first snore information and the second snore information comprises:
determining a difference between the first snore intensity in the first snore information and the second snore intensity in the second snore information ([¶10-110,113,163] the sound level between the segments is compared. Specifically, a difference is the sound of the segments is used to determine apnea); and
determining the confidence value for the target audio clip based on the difference, the preset sleep state corresponding to the target audio clip and a duration corresponding to the preset sleep state ([¶113,163,185-186] apnea is determined).
Ishikawa does not specifically disclose a first snore intensity in the first snore information is an average value of snore intensities at respective time points in the first audio clip, or a snore intensity of a last moment in the first audio clip, and a second snore intensity in the second snore information comprises an average of snore intensities at respective time points in the second audio clip, or a snore intensity of a first moment in the second audio clip. Fox teaches a similar device that uses average values in its determinations ([¶115]).
Ishikawa does not specifically disclose the preset sleep state comprises both hypopnea and apnea within the same initial audio clip or the sleep stage determination with machine learning. Fox teaches similar sleep monitoring device that determines apnea and hypopnea events during the audio clips ([¶11,16-17] apnea and hypopnea index are determined so both hypopnea and apnea are detected during the session) and generating a sleep cycle by inputting audio data collected by the sensor into a preset deep learning model ([¶85] the acoustic data can be used to determine respiration rate. [¶167] respiration rate is used to determine sleep stages. [¶23,27,29,138] machine learning can be used to ); generating a sleep curve based on the sleep cycle; and the sleep curve is used to represent sleep states of a user at different time points ([¶167][FIG8]). Therefore, it would have been obvious to one of ordinary skill in the art prior to the time of filing to combine the device of Ishikawa with the teachings of Fox in order to determine an improved sleep index ([¶168]).
Ishikawa as modified does not specifically disclose labeling the abnormal sleep audio clip in the sleep curve. Su teaches a similar sleep and snore monitoring device that displays the sleep stages with tags or labels for abnormal clips ([FIG.6B,7][¶54,55]). Therefore, it would have been obvious to one of ordinary skill in the art prior to the time of filing been obvious to one of ordinary skill in the art at the time of filing to combine the device of Ishikawa with the display of Su in order to allow the user to identify sleep disturbances ([¶52]).
Regarding claims 7 and 18, Ishikawa discloses determining whether the target audio clip is the abnormal sleep audio clip based on the confidence value of the target audio clip comprises:
determining that the target audio clip is the abnormal sleep audio clip in response to the confidence value of the target audio clip being greater than a threshold ([¶111,112] if enough threshold conditions are met or exceed apnea is determined).
Regarding claims 8 and 19, Fox teaches a similar machine learning based apnea detector that further comprises: obtaining a historical abnormal clip based on a sleep state of the abnormal sleep audio clip, wherein the historical abnormal clip is an abnormal clip determined by a user operation; and determining whether the abnormal sleep audio clip is a true abnormal clip based on the historical abnormal clip ([¶127] the classifier is trained on previous patient data and features associated with sleep and the medical conditions).
Regarding claim 10, Fox teaches obtaining and displaying sleep aid device information and/or medical aid resource information corresponding to the abnormal sleep audio clip ([¶65] the display displays information about the state of the sleep aid device)
Claim(s) 2-4 and 13-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ishikawa in view of Fox and Su further in view of Zheng US 2015/0342519.
Regarding claims 2 and 13, Ishikawa does not specifically disclose using a sleep event recognition model that matches the audio clip. Zheng teaches a similar apnea detection system that determines the sleep event by
obtaining a sleep event recognition result corresponding to each initial audio clip by inputting the initial audio clips into a preset sleep event recognition model ([¶40] the analysis engine is a rules-based classifier model);
for each initial audio clip, determining a sleep state recognition result of the initial audio clip in response to the sleep event recognition result corresponding to the initial audio clip matching a preset sleep event, wherein the sleep state recognition result comprise the preset sleep state ([¶41]); and
determining the initial audio clip as the target audio clip in response to a sleep state of the initial audio clip being the preset sleep state ([¶41] the processing model determines the sleep state). Therefore, it would have been obvious to one of ordinary skill in the art prior to the time of filing to combine the device of Ishikawa with the teachings of Zheng in order to determine an overall sleep index ([¶43]).
Regarding claims 3 and 14, Ishikawa discloses determining the sleep state recognition result of the initial audio clip, comprises: extracting an audio feature of the initial audio clip; and determining the sleep state identification result of the initial audio clip based on the audio feature of the initial audio clip ([¶63] frame noise and volume is determined).
Regarding claims 4 and 15, Zheng discloses the preset sleep event comprises a snoring event within a same initial audio clip and a breathing ([¶40-41]).
Response to Arguments
Applicant’s arguments, see pgs. 13-20, filed 8/5/26, with respect to the rejection(s) of claim(s) 1-4, 7, 8, 10, 12-15 and 17-20 under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Fox and Su.
Applicant's remaining arguments filed 8/5/26 have been fully considered but they are not persuasive.
Regarding Applicant’s arguments against the 101 rejection, Examiner respectfully disagrees. Applicant argues that the smartphone performs the determinations steps and therefore the determination is not a mental process. This is the same as implementing the determinations on a processor, the generic smartphone or processor performing the determinations is not a practical application. It merely links the abstract idea to the field of mobile devices. It is also noted that the claims do not recite the use of a smartphone just a generic electronic device. The use of the machine learning is also akin to claims that recite that the abstract mental determination steps are implemented on a processor. The machine learning, as claimed, is not a particular machine, it is a generic recitation that merely links the abstract idea to the field of machine learning classifiers but this does not provide a practical application of the judicial exception.
Applicant argues that the claims provide a technical improvement because the processing is simplified to allow for data processing speed and performance improvements. This, however, is not clearly linked to the current claim language. Applicant argues that the device only analyzes a select section of the audio waveform rather than the whole audio waveform but it is unclear how that is different or an improvement from the prior art. Specifically, prior art devices analyze windows or segments of the audio sample data, Fox, Su, Ishikawa and Zheng are analyzes specific segments or blocks of the signal to speed up processing. The current device analyzes the target clip in further processing of the apnea or disease determinations but the prior art also only analyzes the abnormal sections.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL ANTHONY CATINA whose telephone number is (571)270-5951. The examiner can normally be reached 10-6pm.
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/MICHAEL A CATINA/Examiner, Art Unit 3791 /TSE CHEN/Supervisory Patent Examiner, Art Unit 3791
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