DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 December 8th, 2025 has been entered.
Amendment Entered
In response to the amendment filed on November 24th, 2025, amended claims 1, 5, 15-17, 27, and new claim 39 are entered. Claims 18 and 38 are cancelled. Claims 15-17 and 19-37 remain withdrawn from consideration. Claims 1-3, 5-14, and 39 are currently under examination.
Response to Arguments
Applicant's remarks and amendments with respect to the claim objections have been fully considered. The objections are withdrawn in view of the amendment.
Applicant's remarks and amendments with respect to the rejections under 35 U.S.C. 112(b) have been fully considered. The rejections are withdrawn in view of the amendment.
Applicant's remarks and amendments with respect to the rejections under 35 U.S.C. 101 have been fully considered. The rejections are withdrawn in view of the amendment.
Applicant's arguments, filed on November 24th, 2025, with respect to the rejections under 35 U.S.C. 103 have been fully considered but they are not persuasive. The rejections have been maintained, and further clarified, in view of the amendments.
At Pgs. 8-9 of the Reply, Applicant argues that claim 1 is not taught or suggested by the cited references of record because Cho discloses “that a first minute ventilation threshold value and a second minute ventilation threshold value are used to determine a transition from an ‘awake’ state to a ‘sleep’ state”, whereas in contrast, claim 1 of the instant application requires “thresholding the set of respiratory features by applying one or more threshold functions to each feature of the set of respiratory features, wherein the thresholding attributes a sleep state weight output for each respiratory feature of the set of respiratory features for each sleep state of a plurality of sleep states”.
Examiner would like to clarify that an “awake state” may qualify as one of a plurality of “sleep states”, as evidenced by [0013] and [0082] of the Applicant’s Specification. Therefore, Cho teaches wherein the thresholding attributes a sleep state weight output for each respiratory feature of the set of respiratory features for each sleep state of a plurality of sleep states.
Further at Pg. 9 of the Reply, Applicant cites [0181-0182] of the Applicant’s Specification, as it provides examples of thresholding features/functions. These arguments are moot because the claims are significantly broader than the Specification. Examiner emphasizes that the specific thresholding features taught in the specification are not required by the claim limitations. The claimed limitations simply require “thresholding the set of respiratory features by applying one or more threshold functions to each feature of the set of respiratory features”, which is fulfilled by the teachings of Cho.
Cho clearly teaches thresholding the set of respiratory features by applying one or more threshold functions to each feature of the set of respiratory features ((ii) calculating a central tendency of the minute ventilation values; Page 6 Lines 9-10; calculates a central tendency (e.g., a mean) of the minute ventilation values, and calculates a deviation of the minute ventilation values from the central tendency (e.g., a standard deviation of the minute ventilation values). The computational circuitry detects an onset of sleep in the patient when the deviation of the minute ventilation values from the central tendency is less than a predetermined minute ventilation threshold value, and signals the therapy component to modify the therapy when the onset of sleep is detected in the patient. For example, where the computational circuitry calculates a standard deviation of the minute ventilation values, the computational circuitry may detect the onset of sleep in the patient when the standard deviation of the minute ventilation values is less than the minute ventilation threshold value; Page 5 Lines 1-13; Figure 3A), wherein the thresholding attributes a sleep state weight output for each respiratory feature of the set of respiratory features for each sleep state of a plurality of sleep states (During a second step 308 of the preliminary portion 302, the minute ventilation values received during the step 306 are used to determine a first minute ventilation threshold value and a second minute ventilation threshold value. The first and second minute ventilation threshold values are used to determine a transition from an "awake" state of the patient to a "sleep" state of the patient; Page 17 Lines 24-28).
Claim Objections
Claim 39 is objected to because of the following informalities:
Claim 39 recites “states; and” in line 6, but should read “states;”
Claim 39 recites “score,” in line 7, but should read “score; and”
Appropriate correction is required.
Claim Rejections - 35 USC § 103
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 pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 5-7, 13, and 39 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Cho et al (WO 02/100482 A2; cited by Applicant) in view of Rapoport (U.S. Publication No. 2006/0102179; cited by Applicant).
Regarding Claim 1, Cho discloses a method for controlling a processor to detect sleep onset from a measured flow of breathable gas, the method for controlling the processor (Method for providing therapy and modifying the therapy after detecting an onset of sleep in patient; Abstract) comprising:
determining a set of respiratory features from a measure of respiratory flow (detection of the onset of sleep includes: (i) receiving multiple minute ventilation values over a period of time, wherein the minute ventilation values are indicative of a minute ventilation of the patient; Page 6 Lines 7-9; Figure 3A);
thresholding the set of respiratory features by applying one or more threshold functions to each feature of the set of respiratory features ((ii) calculating a central tendency of the minute ventilation values; Page 6 Lines 9-10; calculates a central tendency (e.g., a mean) of the minute ventilation values, and calculates a deviation of the minute ventilation values from the central tendency (e.g., a standard deviation of the minute ventilation values). The computational circuitry detects an onset of sleep in the patient when the deviation of the minute ventilation values from the central tendency is less than a predetermined minute ventilation threshold value, and signals the therapy component to modify the therapy when the onset of sleep is detected in the patient. For example, where the computational circuitry calculates a standard deviation of the minute ventilation values, the computational circuitry may detect the onset of sleep in the patient when the standard deviation of the minute ventilation values is less than the minute ventilation threshold value; Page 5 Lines 1-13; Figure 3A), wherein the thresholding attributes a sleep state weight output for each respiratory feature of the set of respiratory features for each sleep state of a plurality of sleep states (During a second step 308 of the preliminary portion 302, the minute ventilation values received during the step 306 are used to determine a first minute ventilation threshold value and a second minute ventilation threshold value. The first and second minute ventilation threshold values are used to determine a transition from an "awake" state of the patient to a "sleep" state of the patient; Page 17 Lines 24-28);
determining a sleep state score based on the thresholding, the sleep state score being indicative of a sleep state of the plurality of sleep states ((iii) calculating a deviation of the minute ventilation values from the central tendency; Page 6 Lines 10-11; calculates a deviation of the minute ventilation values from the central tendency (e.g., a standard deviation of the minute ventilation values); Page 5 Lines 4-6; Figure 3A; the minute ventilation values received during the step 306 are used to determine a first minute ventilation threshold value and a second minute ventilation threshold value. The first and second minute ventilation threshold values are used to determine a transition from an "awake" state of the patient to a "sleep" state of the patient; Page 17 Lines 24-28); and
detecting sleep onset based on the thresholding and the determined sleep state score (The computational circuitry detects an onset of sleep in the patient when the deviation of the minute ventilation values from the central tendency is less than a predetermined minute ventilation threshold value; Page 5 Lines 6-8; (iv) detecting the onset of sleep in the patient if the deviation of the minute ventilation values from the central tendency is less than a predetermined minute ventilation threshold value; Page 6 Lines 11-13; Figures 3A, 3D),
wherein the processor controls, based on the detecting of the sleep onset, a change to a respiratory therapy (The CPU 204 may embody the above described method 300 for detecting onsets of sleep in the patient 108, and/or the method 400 for providing a therapy to a patient. For example, having detected an onset of sleep in the patient 108 (e.g., during the step 334 of the method 300), the CPU 204 may reduce the "low rate limit" value stored in the timing/pacing control circuitry 208 from a normal "resting rate" value (e.g., 60 beats per minute) to a "sleep rate" value, wherein the "sleep rate" value is less than or equal to the "resting rate"…the method 300 may be used to detect onsets of sleep for monitoring sleep-related events (i.e. sleep apnea, etc.), and the method 400 may be used in providing other medical therapies (e.g., electrical shocks for treating atrial fibrillation, administration of medications, etc.); Page 26 Lines 3-17).
Cho fails to disclose wherein the measure of respiratory flow is determined with a flow sensor configured to measure flow of breathable gas attributable to patient respiration. Furthermore, Cho fails to specifically disclose wherein the respiratory therapy is provided by a respiratory therapy device.
In a similar technical field, Rapoport teaches a system and method for diagnosis and treatment of a breathing pattern of a patient (Abstract), wherein the measure of respiratory flow is determined with a flow sensor configured to measure flow of breathable gas attributable to patient respiration (The mask 20 covers the patient's nose and/or mouth. Conventional flow sensors 23 are coupled to the tube 21. The sensors 23 detect the rate of airflow to/from patent and/or a pressure supplied to the patent by the generator 22; [0028]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the flow sensor teachings of Rapoport into the invention of Cho in order to measure a number of parameters from flow data, which may include but are not limited to a peak flow, an inspiration time, an expiration time, a frequency and a total breath time. Although the present invention will be described with respect to measurement of the parameters for individual breaths, those of skill in the art will understand that the parameters may be measured for any number of consecutive breaths or breaths having a predetermined time/breath interval therebetween (Rapoport [0053]).
Furthermore, Rapoport teaches wherein the processor controls, based on the detected sleep onset state, a change to a respiratory therapy provided by a respiratory therapy device (The system 1 may include a mask 20 which is connected via a tube 21 to receive airflow having a particular pressure from a flow generator 22. The amount of pressure provided to a particular patient varies depending on patient's particular condition. Such amount of pressure may be determined utilizing any conventional PAP therapy methods…the processing arrangement 24 outputs a signal to a conventional flow control device 25 to control a pressure applied to the flow tube 21 by the flow generator 22. Those skilled in the art will understand that, for certain types of flow generators which may by employed as the flow generator 22, the processing arrangement 24 may directly control the flow generator 22; [0027-0028]; The processing arrangement 24 may utilize a predetermined algorithm for adjusting the pressure after the state of the patient has been identified. A method 400 according to this embodiment is shown in FIG. 12. In step 402, the system 1 is initialized and the processing arrangement 24 supplies the pressure to the patient at a default level. In step 404, the processing arrangement 24 determines whether, the patient's breathing pattern is indicative of the sleep disorder breathing state. In step 406, when the sleep disorder breathing state has been detected, the processing arrangement 24 increases the pressure in predetermined increments toward a first predetermined pressure (e.g., a therapeutic pressure); [0057-0058]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the respiratory therapy device teachings of Rapoport into the invention of Cho in order to provide the appropriate therapeutic pressure to the patient based on the obtained measurements of the patient’s current state (Rapoport [0057-0058]).
Regarding Claim 2, Cho discloses wherein the set of respiratory features comprises a function of a determined expiratory peak flow location (A histogram may be formed reflecting the deviations of the minute ventilation values received during the time intervals from the central tendencies. A pair of peaks may be located in the histogram; Page 7 Lines 14-16).
Regarding Claim 3, Cho discloses wherein the function is a difference between (a) a ratio of the expiratory peak flow location and an expiratory time and (b) an average of a plurality of ratios of expiratory peak flow location and expiratory time determined over a number of breaths (the minute ventilation sensing circuit 210 (Fig. 2) may produce a new minute ventilation value at the end of predetermined time intervals (e.g., 2- second time intervals). The CPU 204 (Fig. 2) may keep a running estimates of mean values (i.e., average values) of minute ventilation values received during various predetermined periods of time or time "windows." The CPU 204 may update the running estimates of the mean values each time a new minute ventilation value is produced by the minute ventilation sensing circuit 210 using: Mean(i) = MV(i)/p + Mean(i-1) - Mean(i-1)/p…During a decision step 314, the "MV Stdev Long" value is compared to the first minute ventilation threshold value determined during the step 308. If the "MV Stdev Long" value is less than the first minute ventilation threshold value, an optional step 316 may be accomplished. On the other hand, if the "MV Stdev Long" value is greater than or equal to the first minute ventilation threshold value, a step 336 is accomplished; Page 20 Line 29 – Page 22 Line 16).
Regarding Claim 5, Cho discloses wherein the plurality of sleep states includes an awake state and an asleep state (an "awake" state of the patient; a "sleep" state of the patient; Page 17 Lines 27-28).
Regarding Claim 6, Cho fails to disclose wherein the plurality of sleep states includes a non-Rapid Eye Movement (non-REM) sleep state and a Rapid Eye Movement (REM) sleep state.
Rapoport teaches wherein the plurality of sleep states includes a non-Rapid Eye Movement (non-REM) sleep state and a Rapid Eye Movement (REM) sleep state (FIG. 8 shows a period of REM sleep…The type of irregularity seen during REM differs from that seen in wakefulness in several key parameters. This REM associated pattern of breathing may include, e.g., the absence of larger breaths, especially after pauses, generally high respiratory rates and low flow rates, and a tendency for clustering of small breaths; [0036]; In step 106, the processing arrangement 24 determines whether the breathing pattern is identifiable as the REM sleep state…after the REM sleep state has been identified, the processing arrangement 24 may continue identifying the breathing patterns of the patient to determine a termination of the REM sleep state; [0044-0045]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the non-REM sleep state and REM sleep state teachings of Rapoport into the invention of Cho because REM sleep may represent a potential exception to the use of irregularity to indicate wakefulness with anxiety, as during this type of breathing, the patient is asleep and the applied pressure must be maintained (i.e., not reduced as during wakefulness). The type of irregularity seen during REM differs from that seen in wakefulness in several key parameters. This REM associated pattern of breathing may include, e.g., the absence of larger breaths, especially after pauses, generally high respiratory rates and low flow rates, and a tendency for clustering of small breaths. These differences in the pattern of the respiratory airflow signal from those seen during troubled wakefulness allow the separation of these states and can be used to make a change in the applied pressure (Rapoport [0036]).
Regarding Claim 7, Cho discloses wherein each of the sleep state output weights is determined empirically from a group of measured respiratory data from a number of patients or from a single patient (During the preliminary portion 302, two minute ventilation threshold values are determined. At least some of the steps of the recurrent portion 304 are carried out at predetermined time intervals. The minute ventilation threshold values determined during the preliminary portion 302 are used during the recurrent portion 304 to determine the onset of sleep in a patient having the implantable medical device implanted therein; Page 17 Line 4 – Page 18 Line 14; Figure 3A).
Regarding Claim 13, Cho discloses based on the detecting, outputting a sleep onset index representing a transition into a first sleep period for a treatment session (A time of day labeled "Sleep Onset" in Fig. 6 is a time the method 300 of Figs. 3A-3D determine an onset of sleep in the patient…A time of day labeled "Sleep Onset" in Fig. 7 is a time the method 300 of Figs. 3A-3D determine an onset of sleep in the patient; Page 28 Line 30 – Page 30 Line 11; Figures 6 and 7).
Regarding Claim 39, Cho discloses a method (Method for providing therapy and modifying the therapy after detecting an onset of sleep in patient; Abstract) comprising:
determining a set of respiratory features from a measure of respiratory flow (detection of the onset of sleep includes: (i) receiving multiple minute ventilation values over a period of time, wherein the minute ventilation values are indicative of a minute ventilation of the patient; Page 6 Lines 7-9; Figure 3A);
thresholding the set of respiratory features by applying one or more threshold functions to each feature of the set of respiratory features ((ii) calculating a central tendency of the minute ventilation values; Page 6 Lines 9-10; calculates a central tendency (e.g., a mean) of the minute ventilation values, and calculates a deviation of the minute ventilation values from the central tendency (e.g., a standard deviation of the minute ventilation values). The computational circuitry detects an onset of sleep in the patient when the deviation of the minute ventilation values from the central tendency is less than a predetermined minute ventilation threshold value, and signals the therapy component to modify the therapy when the onset of sleep is detected in the patient. For example, where the computational circuitry calculates a standard deviation of the minute ventilation values, the computational circuitry may detect the onset of sleep in the patient when the standard deviation of the minute ventilation values is less than the minute ventilation threshold value; Page 5 Lines 1-13; Figure 3A);
determining a sleep state score based on the thresholding (During a second step 308 of the preliminary portion 302, the minute ventilation values received during the step 306 are used to determine a first minute ventilation threshold value and a second minute ventilation threshold value. The first and second minute ventilation threshold values are used to determine a transition from an "awake" state of the patient to a "sleep" state of the patient; Page 17 Lines 24-28), the sleep state score being indicative of a sleep state of a plurality of sleep states ((iii) calculating a deviation of the minute ventilation values from the central tendency; Page 6 Lines 10-11; calculates a deviation of the minute ventilation values from the central tendency (e.g., a standard deviation of the minute ventilation values); Page 5 Lines 4-6; Figure 3A; the minute ventilation values received during the step 306 are used to determine a first minute ventilation threshold value and a second minute ventilation threshold value. The first and second minute ventilation threshold values are used to determine a transition from an "awake" state of the patient to a "sleep" state of the patient; Page 17 Lines 24-28); and
detecting sleep onset based on the thresholding and the determined sleep state score (The computational circuitry detects an onset of sleep in the patient when the deviation of the minute ventilation values from the central tendency is less than a predetermined minute ventilation threshold value; Page 5 Lines 6-8; (iv) detecting the onset of sleep in the patient if the deviation of the minute ventilation values from the central tendency is less than a predetermined minute ventilation threshold value; Page 6 Lines 11-13; Figures 3A, 3D),
adjusting, based on the detecting of sleep onset, a respiratory therapy (The CPU 204 may embody the above described method 300 for detecting onsets of sleep in the patient 108, and/or the method 400 for providing a therapy to a patient. For example, having detected an onset of sleep in the patient 108 (e.g., during the step 334 of the method 300), the CPU 204 may reduce the "low rate limit" value stored in the timing/pacing control circuitry 208 from a normal "resting rate" value (e.g., 60 beats per minute) to a "sleep rate" value, wherein the "sleep rate" value is less than or equal to the "resting rate"…the method 300 may be used to detect onsets of sleep for monitoring sleep-related events (i.e. sleep apnea, etc.), and the method 400 may be used in providing other medical therapies (e.g., electrical shocks for treating atrial fibrillation, administration of medications, etc.); Page 26 Lines 3-17).
Cho fails to specifically disclose wherein the respiratory therapy is provided by a respiratory therapy device.
In a similar technical field, Rapoport teaches a system and method for diagnosis and treatment of a breathing pattern of a patient (Abstract), wherein the respiratory therapy is provided by a respiratory therapy device (The system 1 may include a mask 20 which is connected via a tube 21 to receive airflow having a particular pressure from a flow generator 22. The amount of pressure provided to a particular patient varies depending on patient's particular condition. Such amount of pressure may be determined utilizing any conventional PAP therapy methods…the processing arrangement 24 outputs a signal to a conventional flow control device 25 to control a pressure applied to the flow tube 21 by the flow generator 22. Those skilled in the art will understand that, for certain types of flow generators which may by employed as the flow generator 22, the processing arrangement 24 may directly control the flow generator 22; [0027-0028]; The processing arrangement 24 may utilize a predetermined algorithm for adjusting the pressure after the state of the patient has been identified. A method 400 according to this embodiment is shown in FIG. 12. In step 402, the system 1 is initialized and the processing arrangement 24 supplies the pressure to the patient at a default level. In step 404, the processing arrangement 24 determines whether, the patient's breathing pattern is indicative of the sleep disorder breathing state. In step 406, when the sleep disorder breathing state has been detected, the processing arrangement 24 increases the pressure in predetermined increments toward a first predetermined pressure (e.g., a therapeutic pressure); [0057-0058]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the respiratory therapy device teachings of Rapoport into the invention of Cho in order to provide the appropriate therapeutic pressure to the patient based on the obtained measurements of the patient’s current state (Rapoport [0057-0058]).
Claims 8-12 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Cho and Rapoport as applied to Claim 1 above, and further in view of Hatlestad et al (U.S. Publication No. 2005/0042589; cited by Applicant).
Regarding Claim 8, Cho and Rapoport fail to disclose including combining the sleep state weight outputs of one or more respiratory features of the set of respiratory features in patterns to calculate pattern weights.
In a similar technical field, Hatlestad discloses a sleep quality data collection and evaluation approach (Abstract), including combining the sleep state weight outputs of one or more respiratory features of the set of respiratory features in patterns to calculate pattern weights (As illustrated in FIGS. 18C-G, a respiration pattern detected as a disordered breathing episode may include only an apnea respiration cycle 1810 (FIG. 18C), only hypopnea respiration cycles 1850 (FIG. 18F), or a mixture of hypopnea and apnea respiration cycles 1820 (FIG. 18D), 1830 (FIG. 18E), 1860 (FIG. 18G). A disordered breathing event 1820 may begin with an apnea respiration cycle and end with one or more hypopnea cycles. In another pattern, the disordered breathing event 1830 may begin with hypopnea cycles and end with an apnea cycle. In yet another pattern, a disordered breathing event 1860 may begin and end with hypopnea cycles with an apnea cycle in between the hypopnea cycles. Analysis of the characteristic respiration patterns associated with various types of disordered breathing may be used to detect, classify and evaluate disordered breathing episodes; [0124]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the respiratory feature pattern teachings of Hatlestad into those of Cho and Rapoport in order to detect, classify and evaluate disordered breathing episodes from analysis of the characteristic respiration patterns associated with various types of disordered breathing (Hatlestad [0124]).
Regarding Claim 9, Cho and Rapoport fail to disclose biasing the pattern weights with biasing factors in the calculation of the pattern weights.
In a similar technical field, Hatlestad discloses a sleep quality data collection and evaluation approach (Abstract), further biasing the pattern weights with biasing factors in the calculation of the pattern weights (a patient's medical/psychological history, gender, age, weight, body mass index, neck size, drug use, and emotional state may be detected and used in connection with sleep quality evaluation and sleep disorder diagnosis…Each of the conditions listed in Table 1 may serve a variety of purposes in evaluating sleep quality. For example, a subset of the conditions may be used to detect whether the patient is asleep and to track the various stages of sleep and arousal incidents. Another subset of the conditions may be used to detect disordered breathing episodes…some or all of the listed conditions may be collected over a relatively long period of time and used to analyze long term sleep quality trends. Trending may be used in connection with an overall assessment of sleep quality and diagnosis and treatment of sleep-disordered breathing, movement disorders, and/or other sleep disorders; [0057-0058]; Table 1).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the biasing factor teachings of Hatlestad into those of Cho and Rapoport in order to detect whether the patient is asleep and to track the various stages of sleep and arousal incidents, as many different factors and conditions may be collected over a relatively long period of time and used to analyze long term sleep quality trends (Hatlestad [0057-0058]).
Regarding Claim 10, Cho and Rapoport fail to disclose wherein the biasing factors are based on one or more characteristics of a patient.
In a similar technical field, Hatlestad discloses a sleep quality data collection and evaluation approach (Abstract), wherein the biasing factors are based on one or more characteristics of a patient (a patient's medical/psychological history, gender, age, weight, body mass index, neck size, drug use, and emotional state may be detected and used in connection with sleep quality evaluation and sleep disorder diagnosis…Each of the conditions listed in Table 1 may serve a variety of purposes in evaluating sleep quality. For example, a subset of the conditions may be used to detect whether the patient is asleep and to track the various stages of sleep and arousal incidents. Another subset of the conditions may be used to detect disordered breathing episodes…some or all of the listed conditions may be collected over a relatively long period of time and used to analyze long term sleep quality trends. Trending may be used in connection with an overall assessment of sleep quality and diagnosis and treatment of sleep-disordered breathing, movement disorders, and/or other sleep disorders.; [0057-0058]; Table 1).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the patient characteristic teachings of Hatlestad into those of Cho and Rapoport in order to detect whether the patient is asleep and to track the various stages of sleep and arousal incidents, as a patient's medical/psychological history, gender, age, weight, body mass index, neck size, drug use, and emotional state may be detected and used in connection with sleep quality evaluation and sleep disorder diagnosis (Hatlestad [0057-0058]).
Regarding Claim 11, Cho and Rapoport fail to disclose wherein the sleep state score is determined based on the calculated pattern weights for each sleep state.
In a similar technical field, Hatlestad discloses a sleep quality data collection and evaluation approach (Abstract), wherein the sleep state score is determined based on the calculated pattern weights for each sleep state (the sleep quality analysis unit 290 may include a processor for evaluating sleep quality 296, for example, by calculating one or more metrics quantifying the patient's sleep quality; [0070]; The analysis unit 2020 may calculate one or more sleep quality metrics quantifying the patient's sleep quality. A representative set of the sleep quality metrics include, for example, sleep efficiency, sleep fragmentation, number of arousals per hour, denoted the arousal index (AI). The analysis unit 2020 may also compute one or more metrics quantifying the patient's disordered breathing, such as the apnea hypopnea index (AHI) providing the number of apneas and hypopneas per hour, and the percent time in periodic breathing (% PB); [0135-0136]; Further, sleep summary metrics may be computed, either directly from the collected patient condition data, or by combining the above-listed sleep quality and sleep disorder metrics. In one embodiment, a composite sleep disordered respiration metric (SDRM) may be computed by combining the apnea hypopnea index AHI and the arousal index AI; [0139]; a composite sleep disorder index SDI quantifying the combined effect of both respiratory and movement disorders may be computed by combining the apnea hypopnea index (AHI), the movement disorder index (MDI), and the arousal index (AI). A sleep disturbance index (SDI) may be computed as a linear combination of the AHI, and the combined disorder index DIc. The combined disorder index may include both abnormal breathing and movement components; [0154-0157]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the score calculation teachings of Hatlestad into those of Cho and Rapoport in order to evaluate sleep quality by calculating one or more metrics quantifying the patient's sleep quality, which may be computed, either directly from the collected patient condition data, or by combining the above-listed sleep quality and sleep disorder metrics (Hatlestad [0154-0157]).
Regarding Claim 12, Cho discloses wherein sleep onset is determined when the sleep state score indicates a transition from an awake state to an asleep state has occurred (a "trough" between the first and second peaks representing deviations of minute ventilation values from the mean value when the patient is. transitioning between the "awake" state and the "sleep" state; Page 19 Lines 18-20).
Allowable Subject Matter
Claim 14 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHANEL J JHIN whose telephone number is (571) 272-2695. The examiner can normally be reached on Monday-Friday 9:00AM-5:00PM.
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/CHANEL J JHIN/Examiner, Art Unit 3791