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 .
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.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference character “4015” has been used to designate both a panel in Figure 4A as well as another object. It is unclear if this other object is also a panel because there are items listed in the description that are not labeled in any of the figures. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: “4100” in Figure 4A, “4120” in Figure 4B, “4110” in Figure 4B, “4180” in Figure 4B, “4160” in Figure 4B, “5150” in Figure 5A, “5135” in Figure 5A, “5130” in Figure 5B, “5135” in Figure 5B, and “5150” in Figure 5B. Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “module” in Claim 24.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. The specification recites “module” as processors or processing devices that can include a mobile phone, tablet, or RF sensor based system (Paragraph [0276]).
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-28 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.
Regarding Claim 1, the limitation "combining a result of the classification" recited in lines 13-14 of the claim is indefinite. It is unclear if a classification result always exists given that limitation "transmitting for classifying" recited in the previous line of the claim alludes that a classification can occur at a later step.
Regarding Claim 23, the limitation "combining a result of the classification" recited in lines 11-12 of the claim is indefinite. It is unclear if a classification result always exists given that limitation "transmitting for classifying" recited in the previous line of the claim alludes that a classification can occur at a later step.
Regarding Claim 24, the limitation "combining a result of the classification" recited in lines 13-14 of the claim is indefinite. It is unclear if a classification result always exists given that limitation "transmitting for classifying" recited in the previous line of the claim alludes that a classification can occur at a later step.
Regarding Claim 25, the limitation "combining a result of the classification" recited in lines 11-12 of the claim is indefinite. It is unclear if a classification result always exists given that limitation "transmitting for classifying" recited in the previous line of the claim alludes that a classification can occur at a later step.
Regarding Claim 28, the limitation “social mixing by the person comprising the user’s location data and infection cluster data” is indefinite. It is unclear if “the person” and “the user” is the same person or if these are different individuals. This is being interpreted to mean “social mixing by a user wherein the social mixing comprises the user’s location data and infection cluster data”.
Additionally, the limitation “the user’s” recited in line two of the claim lacks proper antecedent basis. This limitation is being interpreted to mean “a user’s”.
Claims not explicitly rejected above are rejected due to their dependence on the above claims.
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.
Claims 1-8, 12-17, 19-20, 22-23, and 25-26 are rejected under 35 U.S.C. 103 as being unpatentable over Shouldice’873 (WO Publication 2017032873 – cited by applicant) in view of Frank et. al.’873 (U.S. Publication Number 20200245873 – previously cited).
Regarding Claims 1, 23, and 25, Shouldice'873 discloses a processor-readable medium, having stored thereon processor-executable instructions which, when executed by one or more processors, cause the one or more processors to identify coughing by a person (Paragraph [0052] - The method may include, with the processor, tracking at least some of the physiological parameters during daytime and nighttime. In some cases, the tracked physiological parameter(s) may be tracked by an audio sound produced by the user and may be during sleep; Paragraph [0079] - classifying a determined cough signature based on at least one of: whether the cough occurs in a spasm, whether the cough is dry or productive; and whether it is persistent),
the processor-executable instructions configured to execute a method of monitoring a physiological condition of a person (Paragraph [0069] - include a computer- readable memory storage medium having program instructions encoded thereon configured to cause a processor to perform a lifestyle management method for managing a chronic respiratory condition of a use; Paragraph [0070] - The management device may be further configured to track a baseline threshold of the sensed physiological parameter), the method comprising:
identifying coughing by a person by (i) accessing a passive signal generated with a microphone by passive non-contact sensing in a vicinity of the person, the passive signal representing acoustic information detected by the microphone (Paragraph [0120] - For example, the device 201 may be equipped with a microphone or other acoustic/sound sensor (either within the device, or on an earbud/microphone cable, whereby the microphone is brought close to the user's mouth or be in proximity of the microphone's sensing capabilities) in order to record and process breathing sounds of the user so as to serve as an acoustic monitor. A microphone may further be used to monitor and classify sound patterns consistent with chronic cough or snore, and separate those noises from other background noises such as fans, road noise and the like),
(ii) deriving one or more cough related features from the signal (Paragraph [0079] - classifying a determined cough signature based on at least one of: whether the cough occurs in a spasm, whether the cough is dry or productive; and whether it is persistent),
(iii) receiving physiological data associated with one or more physiological parameters of the person (Paragraph [0046] - The method may include deriving one or more physiological parameters, including the first physiological parameter, based on the one or more generated physiological signals), and
(iv) classifying, or transmitting for classifying, the one or more cough related features and the combining a result of the classification with the received physiological data to generate a health indication that the person is suffering or recovering from a respiratory condition associated with an infectious disease (Paragraph [0051] - The method may include, with the processor, tracking a breathing pattern of the user based on combining data associated with the cough signature and at least one of a breathing signal, heart rate data, blood pressure data, and motion sensing data; Paragraph [0056] - In some cases, the trigger pattern indicative of a probable event of exacerbation of the chronic condition is indicative of one of an asthma condition and a chronic obstructive pulmonary disease condition; Paragraph [0108] - other indicators of pneumonia are a shortness of breath (including a difficulty in "catching a breath"), increase in temperature (fever), "chills", congestion, and productive coughs (such as green mucus); Paragraph [0197] -Analysis of a reduction in sleep score due to cough (with wakefulness) or snoring, can be indicative of a worsening respiratory infection, and in turn an increased risk of the subject's condition worsening).
Shouldice’873 fails to disclose classifying one or more cough related features that include a variability of a cough intensity metric. Frank et. al.’873 teaches analyzing intensity values of different coughing episodes in order to detect coughing sounds in audio recordings (Paragraph [0103] – entire paragraph). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the deriving element of Shouldice’873 that already processes respiratory waveforms (Paragraph [0195]) to include using featured intensity values of coughs in order to detect coughs from audio recordings as seen in Frank et. al.’873.
Regarding Claim 2, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1, but fails to disclose coughing type comprises a cough attribution type indicating a coronavirus disease or coronavirus cough type. Frank et. al.’873 teaches detecting a cough attribution type that indicates signs of a coronavirus disease (Paragraph [0016] - Some aspects of this disclosure involve systems that detect a change to extent of a respiratory tract infection (RTI) based on monitoring coughing. Thus, systems described herein can provide an early warning of infection with a disease like COVID-19). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the classifying element of Shouldice’873 that already detects respiratory-affected diseases to include detecting coronavirus based on coughing as seen in Frank et. al.’873. Frank et. al.’873 teaches respiratory-affected illnesses often experience coughing as an early symptom for diseases such as asthma and COVID-19 – another name for coronavirus - and that coughing can help detect the severity of the diseases (Paragraph [0013]).
Regarding Claim 3, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the one or more physiological parameters comprises one or more of temperature, change or loss of perception of taste and/or smell, and skin appearance (Paragraph [0047] - The additional generated physiological parameter may be detected by the stationary monitor…a gas sensor a galvanic skin response (GSR) sensor, and a temperature sensor).
Regarding Claim 4, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the one or more physiological parameters comprises one or more of blood pressure, SpO2 levels, heart rate, respiration rate, respiration effort, and gastrointestinal disorder (Paragraph [0047] - The additional generated physiological parameter may be detected by the stationary monitor…The first and/or the second monitor may comprise one of: a ballistocardiogram sensor, a heart rate monitor, a photoplethysmography sensor, a breathing monitor).
Regarding Claim 5, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the physiological data comprises (i) objective data generated by one or more sensors, (ii) subjective physiological data, or (iii) both (i) and (ii) (Paragraph [0047] - The additional generated physiological parameter may be detected by the stationary monitor. The first and/or the second monitor may comprise one of: a ballistocardiogram sensor…)
Regarding Claim 6, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses (1) the indication of the one or more events of coughing type comprises a type of cough, and wherein the type of cough comprises any one or more of (a) dry coughing type, (b) productive coughing type, (c) wheezing related coughing type, and (d) spasm related coughing type (Paragraph [0051] - the first physiological parameter may be a cough signature. The method may include, in the processor, classifying the cough signature based on at least one of: whether the cough occurs in a spasm, whether the cough is dry or productive; and whether it is persistent); and/or (2) the indication of the one or more events of coughing type comprises a cough attribution type, and wherein the cough attribution type comprises any one or more of (a) asthmatic coughing type, (b) Chronic obstructive pulmonary (COPD) coughing type, (c) bronchitis coughing type, (d) tuberculosis (TB) coughing type, (e) pneumonia coughing type, (f) lung cancer coughing type, (g) gastroesophageal reflux disease (GERD), and (h) upper airway cough syndrome (Paragraph [0051] - The method may include identifying one of asthma, gastroesophageal reflux disease, upper airway cough syndrome based on the classifying the cough signature).
Regarding Claim 7, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1, but fails to disclose the method further comprises generating a coughing intensity metric indicative of a level of intensity of an event of the one or more events of coughing, determining the variability of the coughing intensity metric. Frank et. al.’873 teaches analyzing intensity values of different coughing episodes in order to detect coughing sounds in audio recordings (Paragraph [0103] – entire paragraph). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the deriving element of Shouldice’873 that already processes respiratory waveforms (Paragraph [0195]) to include using featured intensity values of coughs in order to detect coughs from audio recordings as seen in Frank et. al.’873.
Regarding Claim 8, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the one or more cough related features derived from the passive signal comprises any one, more or all of: a frequency feature, a temporal feature, a spectrogram feature and a wavelet feature (Paragraph [0105] - Acoustic analysis can also be applied to estimate the cough frequency, severity, and classify the type of cough).
Regarding Claim 12, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the method further comprises processing the passive signal by voice activation detection to reject background noise in the signal (Paragraph [0120] - A microphone may further be used to monitor and classify sound patterns consistent with chronic cough or snore, and separate those noises from other background noises such as fans, road noise and the like – which are background noises).
Regarding Claim 13, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the method further comprises estimating a cough rate from the signal, and wherein the method further comprises estimating a variation of cough rate (Paragraph [0196] - This pattern may be evident from either or any combination of a contactless sensing signal (e.g., (RF, SONAR, optical), the audio cough signature, and cough repetition rate).
Regarding Claim 14, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the method further comprises extracting respiratory features from a detected breathing waveform and wherein the classifying of the one or more cough related features to generate an indication of one or more events of coughing by the person, is based on one or more respiratory features extracted from the detected breathing waveform, wherein the one or more respiratory features comprises one, more or all of: (1) inspiration time, (2) inspiration depth, (3) expiration time, (4) expiration depth, (5) an inspiration-to-expiration ratio, (6) one or more notches in the breathing waveform due to cough, and (7) breathing rate (Paragraph [0049] - applying trend monitoring to determine the trigger pattern of the user indicative of a probable event of exacerbation of the chronic condition… The analyzing may further include processing any one or more of inspiration time, expiration time, a ratio of inspiration-to-expiration time and respiratory waveform shape).
Regarding Claim 15, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the one or more respiratory features is derived with one or more of passive non-contact sensing and active non- contact sensing; wherein one or more motion signals are generated by sensing with active non-contact sensing apparatus(Paragraph [0125] - passive detection… RF RADAR sensors when included may be used to measure movement; Paragraph [0146] - the system may process movement features, activity features, heart ballistocardiogram features and/or breathing features. Such methods can be applied to active RF sensing systems such as continuous wave (CW)); and wherein
the indication of one or more events of coughing type by the person is generated based on an evaluation of the generated one or more motion signals (Paragraph [0192] - measured based on movement of the chest).
Regarding Claim 16, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the evaluation of the generated one or more motion signals comprises:(a) detection of body position of the person; (b) detection of biometrics particular to the person; and/or (c) a detection of sleep stage information from the one or more motion signals (Paragraph [0048] - The method may include determining, in the processor, a motion of the user from the parameter. The motion may be one of a movement of the user's chest due to respiration, a sway motion, a sway motion cancellation, rollover in bed, and falling out of bed).
Regarding Claim 17, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the method further comprises rejecting an acoustically sensed cough event based on the detection of sleep stage information; and/or attributing an acoustically sensed cough event to the person based on the detection of sleep stage information (Paragraph [0196] - Coughs during REM / deep sleep are rare (and even more unlikely in REM as compared to deep sleep), with the majority of coughing occurring during wakefulness. When the system detects a possible cough signature on the audio processing side, if the subject is determined to be in deep sleep or REM sleep, then the cough signature is assigned as reduced probability of in fact being a cough; Paragraph [0051]; Paragraph [0061]).
Regarding Claim 19, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the method further comprises monitoring sound to detect user environmental interaction wherein:(a) the user environmental interaction comprises detection of user environmental interaction signatures comprising any one of more of a clicker, an appliance and a door; and/or (b) the monitoring sound to detect user environmental interaction comprises assessing a pattern of activity of a monitored person to generate an indication of a need for contact with the monitored person (Paragraph [0120] - A microphone may further be used to monitor and classify sound patterns consistent with chronic cough or snore, and separate those noises from other background noises such as fans - an appliance, road noise and the like).
Regarding Claim 20, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the server is configured to receive requests for downloading the processor-executable instructions of the processor-readable medium to a processing device over a network (Paragraph [0076] - server may include, for example, a local or remote processing device configured for communications across a network, such as an internet, and/or for local and/or remote communication with another processing or communication device, such as a mobile phone; Paragraph [0126] - the device 201 may be capable of communicating an alert or receiving information to/from a physician, clinician or other person with information relevant to the monitored condition of the user 202).
Regarding Claim 22, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice'873 further discloses the method comprising receiving, at the server, a request for downloading the processor-executable instructions of the processor-readable medium to a processing device over a network (Paragraph [0076] - server may include, for example, a local or remote processing device configured for communications across a network, such as an internet, and/or for local and/or remote communication with another processing or communication device, such as a mobile phone; Paragraph [0126] - the device 201 may be capable of communicating an alert or receiving information to/from a physician, clinician or other person with information relevant to the monitored condition of the user 202), and
transmitting the processor-executable instructions to the processing device in response to the request (Paragraph [0231] - A physician may optionally be required to accept a suggested medication change for the patient before the dosage change is recommended by the system (human intervention / safeguard)).
Regarding Claim 26, Shouldice’873 in view of Frank et. al.’873 discloses the method outlined in Claim 25. Shouldice’873 further discloses an exposure risk being based on cough related classifications from multiple users (Paragraph [0155] - Trend monitoring may involve learning from a wider set of data, derived from the broader population, about risk factors; such risk factors may be localized areas of airborne irritants, seasonal factors, local weather factors (including forecasting data), room environmental data, exercise levels, breathing patterns, cardiac patterns (including breathing waveforms and acoustic characteristics such as cough, sneezing and wheezing), changes in skin temperature, skin coloration, sleep quality changes, and blood pressure).
It is noted by the examiner that the primary reference states “It is to be understood that one or more features of any one example may be combinable with one or more features of another example or other examples. In addition, any single feature or combination of features in any of the examples may constitute a further example” (Paragraph [0102]).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Shouldice’873 (WO Publication 2017032873 – cited by applicant) in view of Frank et. al.’873 (U.S. Publication Number 20200245873 – previously cited), as applied to Claim 8 above, further in view of Abeyratne et. al.’908 (WO Publication 2013142908 – previously cited).
Regarding Claim 9, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 8, but fails to disclose (a) a frequency related feature of the one or more cough related features derived from the passive signal comprises any one, more or all of: (1) one or more Mel-frequency cepstral coefficients (MFCCs), (2) a local peak, (3) a ratio of a dominant peak to one or more surrounding peaks, (4) a local maxima, (5) a global maxima; (6) harmonics, (7) an integration of one or more frequency components, (8) a ratio of different frequency energy estimates, (9) spectral flux, (10) a spectral centroid, (11) a harmonic product spectrum, (12) a spectral spread, (13) one or more spectral autocorrelation coefficients, (14) a spectral kurtosis, and (15) a linear Predictive Coding (LPC); and/or(b) a temporal related feature of the one or more cough related features derived from the signal comprises any one, more or all of: (1) a root mean square (RMS) value, (2) a zero-crossing rate, (3) an envelope; and (4) a pitch based on an auto correlation function. Abeyratne et. al.’908 teaches using Mel-frequency cepstral coefficients (MFCCs) to analyze cough signals such as frequencies (Page 18 lines 7-15 - Mel-frequency cepstral coefficients (MFCCs): MFCC is widely used in speech processing [16, 17], and were found to be highly useful for snore analysis [18-21] as well. In this work, inspired by the similarities of cough/respiratory sounds to snores and speech, we explore the use of MFCC in Cough Segmentation). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the processor-readable instructions of Shouldice’873 in view of Frank et. al.’873 to include (MFCCs) as a way to analyze cough-related sounds through extracting certain features while using a method already used in the art for sound processing from the mouth as seen in Abeyratne et. al.’908 (Page 18 line 2 – obtain features of the sound signal; Page 25 line 6 - feature extraction of MFCC).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Shouldice’873 (WO Patent Application 2017032873 – cited by applicant) in view of Frank et. al.’873 (U.S. Publication Number 20200245873 – previously cited) as applied to Claim 8 above, further in view of Stamatopoulos et. al.'047 (U.S. Publication Number 20190192047 – previously cited).
Regarding Claim 10, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 8. Additionally, Shouldice’873 discloses “’deep learning’ using neural networks” (Paragraph [0215]) and identifying a cough based on the probability assigned to the cough signature that indicates a probability that a person experienced coughing (Paragraph [0196] – entire paragraph - the cough signature is assigned as reduced probability of in fact being a cough… using the knowledge, for instance, that an arousal followed by a cough is significantly more common than a cough during sleep followed by arousal), but fails to disclose the method further comprises inputting the derived one or more cough related features to a convolutional neural network (CNN) to generate a probability of cough for a predetermined time period of the passive signal. Stamatopoulos et. al.'047 teaches using a CNN (Paragraph [0294] - In one embodiment, as discussed in connection with FIG. 25B, the descriptors are fed into a machine learning system (e.g., Deep CNN, or other types of ANNs) that classifies a respiratory recording as healthy or unhealthy). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the learning system of Shouldice’873 in view of Frank et. al.’873 to include a CNN – which is a type of deep learning neural network – in order to classify respiratory related features – such as coughing – from recordings since they are well known in the art and can be trained to determine diseases (Paragraph [0280] - Artificial neural networks are widely used in science and technology; Paragraph [0421]) as seen in Stamatopoulos et. al.’047.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Shouldice’873 (WO Patent Application 2017032873 – as cited by applicant) in view of Frank et. al.’873 (U.S. Publication Number 20200245873 – previously cited) as applied to Claim 1 above, further in view of Davis et. al.'810 (U.S. Publication Number 20140378810 – previously cited).
Regarding Claim 11, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1. Shouldice’873 further discloses identifying a cough based on the probability assigned to the cough signature that indicates a probability that a person experienced coughing (Paragraph [0196] – entire paragraph - the cough signature is assigned as reduced probability of in fact being a cough… using the knowledge, for instance, that an arousal followed by a cough is significantly more common than a cough during sleep followed by arousal), but fails to disclose the classifying comprises generating a binary flag representing identification of coughing, wherein the binary flag is based on a probability of cough for a predetermined time period of the passive signal, and, wherein the binary flag represents a positive indication of cough when the probability is determined to satisfy or exceed a threshold. Davis et. al.'810 teaches using a binary classifier – also known as a binary flag – to identify a cough type based on a predetermined threshold (Paragraph [0281] - the learning process automatically takes these variables into account (to the extent to which the database is varied enough to span this metadata space). In the case of an ANN, a single network output may be provided for each cough type to be recognized; a specific cough type may then be identified by choosing the cough type with the strongest response over a predetermined threshold (assuming exclusivity among cough types). In the case of an SVM, coughs may be classified into many (>2) classes, based on the design of several binary classifiers). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the processor-executable instructions of Shouldice’873 in view of Frank et. al.’873 to include a binary classifier – or binary flag – in order to recognize and identify a cough based on a predetermined threshold and while using a learning network as seen in Davis et. al.’810.
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Shouldice’873 (WO Patent Application 2017032873 – cited by applicant) in view of Frank et. al.’873 (U.S. Publication Number 20200245873 – previously cited) as applied to Claim 17 above, further in view of Morris et. al.'484 (U.S. Publication Number 20150199484 – previously cited).
Regarding Claim 18, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 17, but fails to disclose the method further comprises:(a) communicating data concerning the indication of the one or more events of coughing type by the person and the physiological data associated with one or more physiological parameters of the person to recommend further investigation of the physiological condition and/or to control one or more of: an environmental parameter, a setting on a treatment device, a behavioural change and/or a treatment parameter; and/or (b) generating a reminder to change or wash bedclothes. Morris et. al.'484 teaches communicating coughing events and physiological data within a system in order to set/control a treatment parameter (Paragraph [0037] - For example, based on the demographic information of the user 102 (e.g., the user 102 is a female who weighs 125 pounds) and audio data collected from a microphone (e.g., the sensor(s) 110 and/or the external sensor(s) 112 can include the microphone) by the data collection component 122 since a first dose of the medication 104 was administered (e.g., the data collection component 122 can track a number of coughs of the user 102 since administration of the first dose of the medication 104), the dosage determination component 130 can determine a minimum dose required for maintaining cough suppression for a next four hours. However, it is to be appreciated that the claimed subject matter is not limited to the foregoing example; Paragraph [0047] - The external sensor(s) 112, for example, can further include other types of sensors that measure physiological indicators pertaining to sleep, such as heart rate). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the processor-executable instructions of Shouldice’873 that already includes instruction for treatment based on monitored conditions (Paragraph [0115]) in view of Frank et. al.’873 to include a communication system that takes into coughing events and physiological data in order to impact cough suppression directly as seen in Morris et. al.’484.
Claims 21 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Shouldice’873 (WO Patent Application 2017032873 – as cited by applicant) in view of Frank et. al.’873 (U.S. Publication Number 20200245873 – previously cited) as applied to Claim 1 above, further in view of Gollakota et. al.'927 (WO Publication 2016093927 – previously cited).
Regarding Claim 21, Shouldice'873 in view of Frank et. al.’873 discloses the processor-readable medium outlined above in Claim 1 with the one or more processors ([0052] - the method may include, with the processor). Shouldice’873 also discloses a microphone (Paragraph [0120] - equipped with a microphone) and a speaker (Paragraph [0134] - include an output interface 316 (e.g., a display, vibrator, speaker)), but fails to disclose a microphone coupled to the one or more processors and a speaker coupled to the one or more processors and/or a radio frequency sensor coupled to the one or more processors. Gollakota et. al.'927 teaches a microphone being coupled to a processor (Paragraph [0032] - microphone 126 of FIG. operatively coupled to the processor) and a speaker being coupled to a processor (Paragraph [0032] - speaker 125 of FIG. 1 operatively coupled to the processor). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the processor-readable medium of Shouldice’873 in view of Frank et. al.’873 to include a microphone coupled to a processor and a speaker coupled to a processor in order to have direct contact/connection as seen in Gollakota et. al.’927. Additionally, in accordance to section 21044.04 V.B. of the MPEP, the use of one piece construction instead of the structure disclosed in Shouldice’873 would be merely a matter of obvious engineering choice. The microphone and speaker perform the same functions corresponding with the processors. Therefore, the microphone and speaker in Shouldice’873 could be coupled to the processor.
Shouldice’873 further discloses wherein a processing device comprises any one or more of a smart phone, a tablet computer, a general computing device, a smart speaker, a smart TV, a smart watch, and a respiratory therapy device (Paragraph [0054]- The device configured to manage the chronic condition may include a smart- phone or smart-watch; Paragraph [0057] - The method may include communicating to the user a respiratory treatment for the chronic condition with a respiratory pressure therapy device and a patient interface; Paragraph [0119] - subsystem 130 may be realized as one or more software programs or applications running on a portable device 201 , such as of the user 202, such as smart-phone, tablet, smart-watch, or other wearable or portable smart-device, with a processor and optional data link to a server).
Regarding Claim 24, Shouldice'873 discloses a processing device comprising: one or more microphones configured for passive non-contact sensing, wherein the one or more microphones generates a signal by passive non-contact sensing in a vicinity of a person, the signal representing acoustic information detected by the one or more microphones (Paragraph [0069] - include a computer- readable memory storage medium having program instructions encoded thereon configured to cause a processor to perform a lifestyle management method for managing a chronic respiratory condition of a user; Paragraph [0120] - For example, the device 201 may be equipped with a microphone or other acoustic/sound sensor (either within the device, or on an earbud/microphone cable, whereby the microphone is brought close to the user's mouth or be in proximity of the microphone's sensing capabilities) in order to record and process breathing sounds of the user so as to serve as an acoustic monitor. A microphone may further be used to monitor and classify sound patterns consistent with chronic cough or snore, and separate those noises from other background noises such as fans, road noise and the like),
a module configured to derive one or more features from the signal (Paragraph [0079] - classifying a determined cough signature based on at least one of: whether the cough occurs in a spasm, whether the cough is dry or productive; and whether it is persistent),
a module configured to receive physiological data associated with one or more physiological parameters of the person (Paragraph [0046] - The method may include deriving one or more physiological parameters, including the first physiological parameter, based on the one or more generated physiological signals),
a module configured to classify, or transmit for classifying, the one or more cough related features and combining a result of the classification with physiological data associated with one or more physiological parameters to generate a health indication that the person is suffering or recovering from a respiratory condition associated with an infectious disease (Paragraph [0051] - The method may include, with the processor, tracking a breathing pattern of the user based on combining data associated with the cough signature and at least one of a breathing signal, heart rate data, blood pressure data, and motion sensing data; Paragraph [0056] - In some cases, the trigger pattern indicative of a probable event of exacerbation of the chronic condition is indicative of one of an asthma condition and a chronic obstructive pulmonary disease condition; Paragraph [0108] - other indicators of pneumonia are a shortness of breath (including a difficulty in "catching a breath"), increase in temperature (fever), "chills", congestion, and productive coughs (such as green mucus); Paragraph [0197] -Analysis of a reduction in sleep score due to cough (with wakefulness) or snoring, can be indicative of a worsening respiratory infection, and in turn an increased risk of the subject's condition worsening), wherein,
the processing device comprises any one or more of a smart phone, a tablet computer, a general computing device, a smart speaker, a smart TV, a smart watch and a respiratory therapy device (Paragraph [0054]- The device configured to manage the chronic condition may include a smart- phone or smart-watch; Paragraph [0057] - The method may include communicating to the user a respiratory treatment for the chronic condition with a respiratory pressure therapy device and a patient interface).
Shouldice’873 fails to disclose a module configured to classify one or more cough related features that include a variability of a cough intensity metric. Frank et. al.’873 teaches analyzing intensity values of different coughing episodes in order to detect coughing sounds in audio recordings (Paragraph [0103] – entire paragraph). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the deriving element of Shouldice’873 that already processes respiratory waveforms (Paragraph [0195]) to include using featured intensity values of coughs in order to detect coughs from audio recordings as seen in Frank et. al.’873.
Shouldice'873 fails to disclose one or more processors coupled to the one or more microphones, the one or more processors comprising: a module configured to access the signal generated with the one or more microphones. Gollakota et. al.'927 teaches a microphone being coupled to a processor (Paragraph [0032] - microphone 126 of FIG. operatively coupled to the processor) and a speaker being coupled to a processor (Paragraph [0032] - speaker 125 of FIG. 1 operatively coupled to the processor). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the processor-readable medium of Shouldice’873 in view of Frank et. al.’873 to include a microphone coupled to a processor and a speaker coupled to a processor in order to have direct contact/connection as seen in Gollakota et. al.’927. Additionally, in accordance to section 21044.04 V.B. of the MPEP, the use of one piece construction instead of the structure disclosed in Shouldice’873 would be merely a matter of obvious engineering choice. The microphone and speaker perform the same functions corresponding with the processors. Therefore, the microphone and speaker in Shouldice’873 could be coupled to the processor.
Claim 27 is rejected under 35 U.S.C. 103 as being unpatentable over Shouldice’873 (WO Publication 2017032873 – cited by applicant) in view of Frank et. al.’873 (U.S. Publication Number 20200245873 – previously cited) as applied to Claim 26, and further in view of Reiner'979 (U.S. Publication Number 20170199979).
Regarding Claim 27, Shouldice’873 in view of Frank et. al.’873 discloses the method outlined in Claim 26. Shouldice’873 further discloses estimating a change of rate in health risks for a user based on a location within a time window (Paragraph [0053] - The method may include, with the processor, analyzing received or accessed geographical data to determine whether there is a risk, or a change in risk, of exacerbation of the chronic condition; Paragraph [0177] - an increase in skin temperature is detected along with a subsequent or simultaneous increase in breathing rate and an initially stable heart rate which subsequently becomes elevated, such detection may be an indication of an onset of a virus or bacterial infection; Paragraph [0237] - The system can also detect and record initial asthma trigger parameters which led to an asthma attack (sensed physiological conditions, location, and environmental / weather conditions), and can also estimate the risk of a subsequent airway obstruction (e.g., within 3 to 8 hours) after the initial exposure to these parameters, and recommend a mitigation such as inhaled steroids), but fails to explicitly disclose forecasting infection rates of a locality. Reiner'979 teaches observing locality-related rates of infection (Paragraph [0132] - The ability of the program 110 to sample and characterize the agents allows for scientists, healthcare, and law enforcement officials to determine the number and locations of outbreaks, biologic risk, and potential sources of the act. In the example of a naturally occurring exposure (e.g., influenza), the collection and analysis of sources by the program 110 over different geographic regions and time periods allows for scientific classification of the agent, mutational changes, biologic risk, and treatment planning. Once again, the derived data could be cross-referenced by the program 110 with centralized and local profile databases 113, 114 to identify individuals at high risk and used for notification and preventative action). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Shouldice’873 in view of Frank et. al.’873 to include a treatment program that references locality programs centered around disease control in order to provide specific feedback to a user about what type of infectious-related agents are in proximity to a user that could be causing health-related issues to the user as seen in Reiner’979 (Paragraph [0108] - providing continuous updates and analysis of exposure specific to the individual end-user…provide continuous monitoring and analysis data specific to the agent).
Claim 28 is rejected under 35 U.S.C. 103 as being unpatentable over Shouldice’873 (WO Publication 2017032873 – cited by applicant) in view of Frank et. al.’873 (U.S. Publication Number 20200245873 – previously cited) as applied to Claim 25, and further in view of Shimada et. al.'926 (U.S. Publication Number 20120046926).
Regarding Claim 28, Shouldice’873 in view of Frank et. al.’873 discloses the method of Claim 25. Shouldice’873 further discloses analyzing health data and geographical parameters related to multiple users in order to determine health risks applicable to each respective user (Paragraph [0053] - In some versions, the plurality of physiological and environmental parameters may include an environmental parameter based on at least one of climate data and geographic data. The method may include, with the processor, interfacing with a medical information system storing medical records of one or both of the user and other users, and wherein the analyzing of the plurality of physiological and environmental parameters comprises analyzing a parameter based on data accessed from the medical records of one or both of the user and the other users. The method may include, with the processor, analyzing received or accessed geographical data to determine whether there is a risk, or a change in risk, of exacerbation of the chronic condition), but fails to disclose comprising an extent of social mixing by the person comprising the user’s location data and infection cluster data. Shimada et. al.’926 teaches observing social interactions between a user and other individuals based on location and infection state (Paragraph [0055] - If an analyzing target is an infection risk of a virus of a flu, a certain person entering/leaving a certain room corresponds to an event. In this case, the starting date and time of the event corresponds to a date and time that the person enters the room (the date and time may include a year, a month, a minute, a second and the like in addition to one of a date and a time or their combination if a time may be uniquely specified according to the exemplary embodiment, and so forth). A date and time that the person leaves the room corresponds to the ending date and time of the event. The room corresponds to the place for the occurrence of the event; Paragraph [0066] - indicates a possibility that an infection from the target person A to the target person B might be carried out even if the target person B does not directly meet the target person A in the case in which the target person A is infected with a certain virus). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Shouldice’873 in view of Frank et. al.’873 to include recording social interaction as an environmental factor in order to more deeply track plausible cause for presence of infection in a user as seen in Shimada et. al.’926.
Response to Amendment
Applicant's arguments filed 02 December 2025 have been fully considered and they are not entirely persuasive.
Applicant’s amendments have overcome the drawing objections referring to the specification containing elements that are not addressed in drawings. However, the drawing objection regarding element "4015" remains as this objection was not addressed by the applicant. Additionally, the drawing objection regarding elements "4100", "4120", etc. remains as this objection was not addressed by the applicant.
Applicant’s amendments have overcome the prior claim objections.
Applicant’s amendments did not overcome the prior claim interpretations and therefore have been addressed above in Paragraph 6.
Applicant’s amendments have overcome the prior 35 U.S.C. 112b rejections, but additional rejections based on the amendments are addressed in Paragraph 7 above.
Applicant’s amendments have overcome the prior 35 U.S.C. 102 rejections and Claims 1-28 are rejected under 35 U.S.C. 103 as necessitated by amendments. Additional prior art has been referenced by the examiner. These rejections are addressed in Paragraphs 8-15 above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Troxell et. al.'585 (U.S. Publication Number 20190151585) teaches a cough detection component that predicts the probability that a cough occurred in a certain instance of time.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 SARAH ANN WESTFALL whose telephone number is (571) 272-3845. The examiner can normally be reached Monday-Friday 7:30am-4:30pm EST.
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/SARAH ANN WESTFALL/Examiner, Art Unit 3791
/ETSUB D BERHANU/Primary Examiner, Art Unit 3791