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 .
The amendment filed on June 23, 2026 has been received and considered. By this amendment, claims 1, 4-6, 8, 10, 16, and 21-30 are amended, claims 2, 3, and 9 are cancelled, claims 31-33 are added, and claims 1, 4-8, and 10-33 are now pending in the application.
Election/Restrictions
Newly submitted claims 30-33 are directed to an invention that is independent or distinct from the invention originally claimed for the following reasons: The originally-claimed invention and the invention of claims 30-33 are related as process and apparatus for its practice. The inventions are distinct if it can be shown that either: (1) the process as claimed can be practiced by another and materially different apparatus or by hand, or (2) the apparatus as claimed can be used to practice another and materially different process. (MPEP § 806.05(e)). In this case the process as claimed can be practiced by another and materially different apparatus, such as one that includes a receiver to receive sensor data rather than an article of furniture comprising one or more sensors.
Since applicant has received an action on the merits for the originally presented invention, this invention has been constructively elected by original presentation for prosecution on the merits. Accordingly, claims 30-33 are withdrawn from consideration as being directed to a non-elected invention. See 37 CFR 1.142(b) and MPEP § 821.03.
To preserve a right to petition, the reply to this action must distinctly and specifically point out supposed errors in the restriction requirement. Otherwise, the election shall be treated as a final election without traverse. Traversal must be timely. Failure to timely traverse the requirement will result in the loss of right to petition under 37 CFR 1.144. If claims are subsequently added, applicant must indicate which of the subsequently added claims are readable upon the elected invention.
Should applicant traverse on the ground that the inventions are not patentably distinct, applicant should submit evidence or identify such evidence now of record showing the inventions to be obvious variants or clearly admit on the record that this is the case. In either instance, if the examiner finds one of the inventions unpatentable over the prior art, the evidence or admission may be used in a rejection under 35 U.S.C. 103 or pre-AIA 35 U.S.C. 103(a) of the other invention.
Claim Objections
Claims 31-33 are objected to because of the following informalities: new claims 31-33 do not include status identifiers. These claims are understood to be new claims and it is recommended that appropriate status identifiers, such as “Currently Amended” or “Previously Presented”, be included in subsequent responses, in accordance with 37 CFR 1.121(c). Appropriate correction is required.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 4-8, 10-15, and 22-29 are rejected under 35 U.S.C. 103 as being unpatentable over Meger (U.S. 2024/0008751, previously cited) in view of Chen et al. (CN118177766A). Regarding claim 1, Meger discloses a computer-implemented method for detecting an anomaly in a physiological condition (“Some applications of the present invention provide methods and systems for monitoring patients for the occurrence or recurrence of a physiological event, for example, a chronic illness or ailment”, paragraph [0010]), the method comprising: predicting future sensor data based on historical sensor data obtained from a plurality of sleep sessions on an article of furniture (“Breathing pattern analysis module 22 and heartbeat pattern analysis module 23 are configured to analyze the respective patterns in order to (a) predict an approaching clinical episode”, paragraph [0087]), the article of furniture comprising one or more sensors 30/60/86/62/81/85/87/80 sensors to measure biological signals to generate the historical sensor data (“in addition to wirelessly-enabled motion sensor 30, control unit 14 is coupled to one or more additional sensors 60 applied to patient 12, such as a blood oxygen monitor 86 (e.g., a pulse oximeter/photoplethysmograph), an ECG monitor 62, weight sensor 81 (e.g. a weight sensor embedded into a bed as manufactured by Stryker Inc. of Kalamazoo, Michigan), a moisture sensor 85, an angle sensor 87, and/or a temperature sensor 80. In accordance with respective applications, one or more of sensors 60 is a contact sensor or a contact-less sensor”, paragraph [0071] and “motion sensor 30 may be placed under a mattress of a bed”, paragraph [0073]), and wherein the future sensor data indicates at least one physiological condition (“Breathing pattern analysis module 22 and heartbeat pattern analysis module 23 are configured to analyze the respective patterns in order to (a) predict an approaching clinical episode”, paragraph [0087]); (b) obtaining current sensor data from the one or more sensors (“a sensor configured to continuously sense vital sign information of a patient and generate a sensor signal in response thereto”, paragraph [0039]); detecting a difference between the future sensor data and the current sensor data (“pattern analysis module 16 combines clinical parameter data generated from one or more of analysis modules 20, 22, 23, 26, 28, 29, and 31, and analyzes the data in order to predict and/or monitor a clinical event”, paragraph [0093] and “pattern analysis module 16 derives a score for each parameter based on the parameter's deviation from baseline values (either for the specific patient or based on population averages). Pattern analysis module 16 optionally combines the scores, such as by computing an average, maximum, standard deviation, or other function of the scores. The combined score is compared to one or more threshold values (which may or may not be predetermined) to determine whether an episode is predicted, currently occurring, or neither predicted nor occurring, and/or to monitor the severity and progression of an occurring episode”, paragraph [0094]); determining an anomaly in the at least one physiological condition (“pattern analysis module 16 derives a score for each parameter based on the parameter's deviation from baseline values (either for the specific patient or based on population averages). Pattern analysis module 16 optionally combines the scores, such as by computing an average, maximum, standard deviation, or other function of the scores. The combined score is compared to one or more threshold values (which may or may not be predetermined) to determine whether an episode is predicted, currently occurring, or neither predicted nor occurring, and/or to monitor the severity and progression of an occurring episode”, paragraph [0094]); and generating a health risk report in response to the detected difference indicative of the anomaly in the at least one physiological condition (“Pattern analysis module typically further includes alert-generation-functionality 92 that is configured to generate an alert in response to the signal analysis that is performed by the signal analysis functionality.”, paragraph [0095]). However, Meger fails to disclose that the determination of an anomaly is based on an amount of the detected difference. Chen teaches a cardiovascular and cerebrovascular health monitoring method and system that includes predicting future sensor data based on historical sensor data (“equally dividing the history standard sequence of the physiological index according to the time sequence, respectively giving the weight, calculating the weighted average value, and defining it as the standard predicted value”, translation page 3, lines 28-30), obtaining current sensor data (“the sensor directly collects or calculates the sensor signal such as PPG to obtain the current physiological index monitoring value”, translation page 3, lines 19-20), detecting a difference between the future sensor data and the current sensor data (“calculating the difference between the normalized current physiological index monitoring value and the standard predicted value”, translation page 3, lines 30-31), and determining, based on an amount of the detected difference, an anomaly in at least one physiological condition (“judging whether it is in the error allowable range according to the size of the difference value”, translation page 3, line 32). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Meger such that the determination of an anomaly is based on an amount of the detected difference, as taught by Chen, as it has been held that combining prior art elements according to known methods to yield predictable results requires only routine skill in the art. KSR Int'l Co. v. Teleflex Inc., 127 S.Ct. 1727, 1742, 82 USPQ2d 1385, 1396 (2007).
Regarding claim 4, Meger discloses that the article of furniture is a mattress, a blanket, a pillow, or a mattress cover (“motion sensor 30 may be placed under a mattress of a bed”, paragraph [0073]).
Regarding claim 5, Meger discloses that the plurality of sleep sessions comprises a plurality of consecutive sleep sessions (“a sensor configured to continuously sense vital sign information of a patient and generate a sensor signal in response thereto”, paragraph [0039], where the continuous sensing is considered to result in consecutive sleep sessions being monitored).
Regarding claim 6, Meger discloses identifying from the historical sensor data one or more sensor data signatures associated with the at least one physiological condition, wherein the predicting the future sensor data is based on the one or more sensor data signatures (“Breathing pattern analysis module 22 is configured to extract breathing patterns from the motion data, as described hereinbelow with reference to FIG. 3, and heartbeat pattern analysis module 23 is configured to extract heartbeat patterns from the motion data”, paragraph [0083], where the patterns are considered the sensor data signatures as claimed).
Regarding claim 7, Meger discloses that the one or more sensor data signatures comprise a pattern of sensor data or a range of sensor data values (“Breathing pattern analysis module 22 is configured to extract breathing patterns from the motion data, as described hereinbelow with reference to FIG. 3, and heartbeat pattern analysis module 23 is configured to extract heartbeat patterns from the motion data”, paragraph [0083]).
Regarding claim 8, Meger discloses that the one or more sensor data signatures comprise a respiratory rate, a breath cycle, a heart rate, a heart rate variability (HRV), a vibration, a perspiration, a blood pressure, a body temperature, or a combination thereof (“Breathing pattern analysis module 22 is configured to extract breathing patterns from the motion data, as described hereinbelow with reference to FIG. 3, and heartbeat pattern analysis module 23 is configured to extract heartbeat patterns from the motion data”, paragraph [0083] and “ In some applications, system 10 continuously measures heart rate and respiratory rate and uses the latest spot check results of blood pressure and temperature readings”, paragraph [0102]).
Regarding claim 10, Meger discloses that the one or more sensor data signatures comprise at least two members selected from the group consisting of the respiratory rate, the heart rate, and the HRV (“Breathing pattern analysis module 22 is configured to extract breathing patterns from the motion data, as described hereinbelow with reference to FIG. 3, and heartbeat pattern analysis module 23 is configured to extract heartbeat patterns from the motion data”, paragraph [0083] and “ In some applications, system 10 continuously measures heart rate and respiratory rate and uses the latest spot check results of blood pressure and temperature readings”, paragraph [0102]).
Regarding claim 11, Meger discloses that the at least one physiological condition comprises a cardio-respiratory condition (“For some applications, this indication is used to identify deterioration in the condition of chronic patient suffering from chronic respiratory or cardiac conditions such as congestive heart failure, chronic obstructive pulmonary disease, cystic fibrosis, and/or asthma.”, paragraph [0321]).
Regarding claim 12, Meger discloses that the cardio-respiratory condition is selected from the group consisting of heart attack, stroke, heart failure, arrhythmia, coronary artery disease, peripheral artery disease, aortic disease, congenital heart disease, chronic bronchitis, chronic obstructive pulmonary disease, and congestive heart failure (“For some applications, this indication is used to identify deterioration in the condition of chronic patient suffering from chronic respiratory or cardiac conditions such as congestive heart failure, chronic obstructive pulmonary disease, cystic fibrosis, and/or asthma.”, paragraph [0321]).
Regarding claim 13, Meger discloses that the at least one physiological condition comprises a sleep disorder (“techniques of this embodiment are used to treat a subject suffering from obstructive sleep apnea (OSA)”, paragraph [0417]).
Regarding claim 14, Meger discloses that the sleep disorder is selected from the group consisting of insomnia, sleep apnea, snoring, circadian rhythm sleep disorder, and restless legs syndrome (“techniques of this embodiment are used to treat a subject suffering from obstructive sleep apnea (OSA)”, paragraph [0417]).
Regarding claim 15, Meger discloses that the predicting is based on a moving-average model (“when the score changes versus the patient's baseline (which may be calculated, for example, by averaging the previous 24 hours of scores”, paragraph [0102], where the “averaging the previous 24 hours of scores” is considered to satisfy the “moving-average model” recitation).
Regarding claim 22, Meger discloses that one or more data points in the historical sensor data are labeled with at least one event associated with a time when the one or more data points was generated (see Figures 6-10).
Regarding claim 23, it is respectfully submitted that the recitation “the one or more data points is manually labeled via a graphical user interface (GUI) of a user device” fails to further define the claimed invention over that of the prior art because it is directed to an intended function or action, but fails to positively recite an active method step to further define the claimed invention over that of the prior art.
Regarding claim 24, Meger discloses that the detected difference between (i) the generated future sensor data and (ii) the current sensor data being different by a predetermined threshold metric indicates the anomaly (“pattern analysis module 16 derives a score for each parameter based on the parameter's deviation from baseline values (either for the specific patient or based on population averages). Pattern analysis module 16 optionally combines the scores, such as by computing an average, maximum, standard deviation, or other function of the scores. The combined score is compared to one or more threshold values (which may or may not be predetermined) to determine whether an episode is predicted, currently occurring, or neither predicted nor occurring, and/or to monitor the severity and progression of an occurring episode”, paragraph [0094]).
Regarding claim 25, Meger discloses that the predetermined threshold metric is characterized by a deviation of the current sensor data by one or more standard deviations from the generated future sensor data (“Pattern analysis module 16 optionally combines the scores, such as by computing an average, maximum, standard deviation, or other function of the scores.”, paragraph [0094]).
Regarding claim 26, Meger discloses that the predicting the future sensor data is performed during a concurrent use of the article of furniture (the analysis is performed while the patient is lying on the bed and, thus, is considered to satisfy the claim limitations).
Regarding claim 27, Meger discloses that the predicting the future sensor data is performed substantially in real-time relative to the obtaining of the current sensor data (the analysis is performed while the patient is lying on the bed and, thus, is considered to satisfy the claim limitations).
Regarding claim 28, Meger discloses that the detecting the difference is performed after determining that a user is sleeping on the article of furniture (“pattern analysis module 16 of system 10 (e.g., signal analysis functionality 90 of the pattern analysis module) identifies a sleep condition of the patient (e.g., by identifying that the patient is asleep, or by identifying a current sleep stage of the patient) by analyzing the signal from sensor 30”, paragraph [0177]).
Regarding claim 29, Meger discloses displaying the health risk report on a graphical user interface (GUI) of a user device (“Typically, user interface 24 includes a display.”, paragraph [0062]).
Claims 16 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Meger (U.S. 2024/0008751, previously cited) in view of Chen et al. (CN118177766A), as applied to claims 1, 4-8, 10-15, and 22-29 above, and further in view of McNair (U.S. Patent No. 10,390,765, previously cited). Regarding claims 16 and 17, Meger discloses the invention substantially as claimed, but fails to disclose that the moving-average model assigns a greater weight or influence to one or more recent data in the historical sensor data set as compared to one or more older data in the historical sensor data set or the moving-average model comprises one or more members selected from the group consisting of Exponential Moving Average (EMA), Simple Moving Average (SMA), Weighted Moving Average (WMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Smoothed Moving Average (SMMA), Adaptive Moving Average (AMA), Linear Weighted Moving Average (LWMA), and Hull Moving Average (HMA). McNair teaches a decision support system for predicting an ischemic myocardial event that utilizes an exponentially-weighted moving average in order to smooth the time series signal in order to determine a likelihood of an event occurring (“in one embodiment, the time series may be smoothed such as by applying using Exponentially-Weighted Moving Average (EWMA). A likelihood of future myocardial ischemia occurrence is then determined within a future time interval, based on whether threshold for the smoothed cusp model is transgressed or, alternately, based on whether a threshold for the ratio of linear-to-cusp model values is exceeded.”, col. 4, ln. 34-41). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Meger such that the moving-average model assigns a greater weight or influence to one or more recent data in the historical sensor data set as compared to one or more older data in the historical sensor data set and the moving-average model comprises an Exponentially-Weighted Moving Average, as taught by McNair, as it has been held that combining prior art elements according to known methods to yield predictable results requires only routine skill in the art. KSR Int'l Co. v. Teleflex Inc., 127 S.Ct. 1727, 1742, 82 USPQ2d 1385, 1396 (2007).
Allowable Subject Matter
Claims 18-21 are 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.
Response to Arguments
Applicant’s arguments with respect to the claims have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Holley et al. (WO 2022/058964).
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 TAMMIE K MARLEN whose telephone number is (571)272-1986. The examiner can normally be reached Monday through Friday from 8 am until 4 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Carl Layno can be reached at 571-272-4949. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/TAMMIE K MARLEN/Primary Examiner, Art Unit 3796
Prosecution Insights