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 .
Response to Amendment
Applicant’s remarks and amendments with respect to the specification and claims have been fully considered and overcome each and every objection and rejection under 35 U.S.C. 112(b) previously set forth in the Non-Final Office Action mailed on 09/10/2025. The objections and rejections are withdrawn in view of amendments to the claims. This action is pursuant to claims filed on 01/12/2026. Amended claims 1, 3, 16-18 and 20 are entered. Claims 1-20 remain pending in the application.
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 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-7, 10, 11, and 13-19 are rejected under 35 U.S.C. 103 as being unpatentable over US 2021/0007647 A1 to Bebout et al. (“Bebout”) in view of US 10/561,863 B1 to Dashevsky et al. (“Dashevsky”), and further in view of US 2016/0167672 A1 to Krueger (“Krueger”, cited in Applicant’s 12/22/2022 IDS).
Regarding independent claims 1 and 17: Bebout teaches a system and method (see Fig. 1, Fig. 4, and [0037], “…system and method for effectively monitoring critical respiratory parameters…”) comprising:
a processor (see Fig. 1 and [0037], “…system 100 comprises… a control unit 170”, control unit 170) ; and
a memory (see Fig. 1 and [0041], “…control unit 170 is further configured for storing data acquired during functioning of the system 100”, data storage capabilities indicates the presence of a memory to store such data), the memory comprising instructions that upon execution by the processor (see Fig. 1 and [0041], “… central unit 105 comprises a control unit 170 that contain all the algorithms for SpO2, PR and COHb measurements as well as motion, vibration, pressure and acceleration tolerance, low perfusion performance, alarms and indices of signal strength and signal quality for all parameters”), cause the processor to:
receive raw physiological data from at least one sensor of a biosensing garment of a pilot, the raw physiological data comprising raw respiration data (see Fig. 1 and [0038], “PO sensor 110 is configured to non-invasively determine SpO2 and PR of a person…PO sensor 110 can be configured in a headband of the pilot's helmet and held in place…”, see also [0041]-[0042], “…PO sensor 110 and the CO2 sensor 120 can be connected to the control unit 170… CO2 sensor can be positioned directly into an aviator's mask of the pilot to detect inspired and expired CO2…”, PO sensor 110 and CO2 sensor 120 are positioned on a headband and aviator mask of a pilot’s helmet respectively (i.e., a biosensing garment) and collect respiratory data to be sent to control unit 170 (i.e., control unit 170 receives respiratory data collected by sensors 110 and 120),
extract individual breaths from the raw physiological data (see Fig. 1 and [0042], “… CO2 sensor…detect inspired and expired CO2, to generate continuous CO2 breath-by-breath waveforms…”, breath by breath waveform generation (i.e., extraction of individual breaths)), each individual breath having an associated breath pattern and an association with a time (see [0041], “…integration of inspired and expired CO2 for measurement and detection of respiratory rate and pattern… control unit can be connected to an external computing system for transferring data to allow real-time data acquisition”, integration of values received from sensor 120 (i.e., integration occurring over a time) measures an associated respiratory rate and breath pattern);
receive aircraft environment data associated with an aircraft from at least one aircraft environment sensor, the aircraft environment data is associated with a timeline (see Fig. 1 and [0041], “…barometer 140 or pressure manometer can also be provided for continuous monitoring of cabin pressure…three-dimensional accelerometer 150 can also be housed in the central unit 105 that can be used for continuously monitoring direction and magnitude of G forces…”, barometer 140 and accelerometer 150 monitor aircraft parameters (i.e., aircraft environment sensors) are measured continuously (i.e., over a timeline);
align the individual breaths with the aircraft environment data (see [0042], “…generate continuous CO2 breath-by-breath waveforms… Monitoring may be conducted during the extreme conditions of increased gravitational forces, reduced cabin pressures… Inspired and expired CO2 can be monitored utilizing principles of Capnography for analysis of the data from the CO2 sensor configured in the aviator's mask… calibration curve or curves can be embedded into the pulse oximetry algorithms and based on…high frequency vibration and increased gravitational forces…”, breath-by-breath (i.e., individual breath data) monitored during periods of time aligning with events experienced by the environmental sensor);
classify each individual breath as one of a plurality of different breath types based on the associated breath pattern (see [0041], “…capnography board 160 for integration of inspired and expired CO2 for measurement and detection of respiratory rate and pattern…hyperventilation, hypoventilation hypocapnia, hypercapnia…”, respiratory rate and breath pattern from individual measurements used to determine hyperventilation, hypoventilation hypocapnia, hypercapnia (i.e., classifying individual breaths based on breath patterns)) ;
issue a PE alert (see [0024]-[0025], “… provide an alert upon detecting hypoxemic or hypoxic conditions in the pilot… provide an alert upon detecting hypocapnia in the pilot”, see also [0048], “…algorithms further enable calculation of motion and vibration tolerance, low perfusion performance, alarms and indices of signal strength and signal quality…”, providing an alert/alarms of the presence of a physiological condition).
However, Bebout fails to explicitly disclose “…cause the processor to:…extract individual breaths from the raw physiological data, each individual breath having an associated breath pattern and an association with a breath timeline”.
Dashevsky teaches a wearable device for bio-monitoring (see abstract, “…wearable device for comprehensive bio-monitoring of physiologic metrics to determine metabolic, pulmonary and cardiac function and oxygen saturation measurements from breathing mask apparatuses…”) including a processor that manipulates raw respiration signals over a period of time to extract individual breaths (see col. 32, lines 1-8, “…raw signal traces are sliced to represent individual breaths, and each breath is reduced, via numerical integration and multiplication, to the gases produced and consumed. These breath-by-breath values are read into the buffer of a classifier algorithm, which is trained on these data and directly measured blood gas data at the end of a 5-minute epoch”).
Although Bebout discloses generating extracting individual breaths having breath patterns and real time monitoring, Bebout fails to explicitly disclose that each individual breath has an association with a breath timeline. However, Dashevsky teaches extracting individual breaths from signal data gathered over a predetermined epoch. Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify the processor disclosed by Bebout (to include each individual breath having an associated breath pattern and an association with a breath timeline) for the purpose of accurate estimation of breath timing, as evidence by Dashevsky (see col. 22, lines 22-24). Furthermore, one of ordinary skill in the art would have had predictable success combining Bebout and Dashevsky, since their teachings relate to the same narrow field of endeavor, i.e. wearable devices for monitoring various bio-parameters.
Additionally, Bebout fails to explicitly disclose “…cause the processor to:… receive aircraft environment data associated with an aircraft from at least one aircraft environment sensor wherein the at least one aircraft environment sensor includes a nitrogen level sensor…”.
Krueger teaches a head mounted sensor system for measuring human responses to environments (see abstract) including a sensor measuring environmental factors such as nitrogen (see [0041], “…environmental factors that could be measured by the system and method, to determine if the environment is provocative, can include, but are not limited to, factors and sensors… nitrogen…be measured using gas chromatography, thermal conductivity, or an optical sensor…”).
Although Bebout discloses monitoring aircraft environment data using at least one aircraft environment sensor (see [0041]-[0042]), Bebout fails to explicitly disclose a nitrogen level sensor. Kreuger teaches sensors monitoring aircraft environmental data, including nitrogen levels. Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the Bebout/Dashevsky combination (to include a nitrogen level sensor) for the purpose of measuring environmental inputs to determine if an environment is provocative for a subject, as evidence by Krueger (see [0040]). Furthermore, one of ordinary skill in the art would have had predictable success combining Bebout/Dashevsky and Krueger, since their teachings relate to the same narrow field of endeavor, i.e. wearable devices for monitoring various environmental and bio-parameters.
Additionally, Bebout fails to explicitly disclose “…receive aircraft environment data associated with an aircraft from at least one aircraft environment sensor… and the aircraft environment data being associated with an aircraft environment timeline”.
Dashevsky further teaches an accelerometer including aircraft time synchronization (see col. 30 lines 27-43, “…Accelerometers may be used to measure determine the subject's body position and orientation, g-forces, and provide other functions such as providing time synchronization with the subject's vehicle (e.g., aircraft)… g-forces experienced are compared via time signature…”).
Although Bebout discloses aircraft environment sensors performing continuous monitoring, Bebout fails to explicitly disclose associating aircraft environmental data with an aircraft environment timeline. However, Dashevsky further teaches time synchronization of aircraft sensor measurements, and comparison of aircraft sensor measurements using time signatures. Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor disclosed by Bebout (to include aircraft environment data being associated with an aircraft environment timeline) for the purpose of aligning data points to facilitate analysis, as evidence by Dashevsky (see col. 30, lines 43-47).
Additionally, Bebout fails to explicitly disclose “…cause the processor to:…align the individual breaths with the aircraft environment data in accordance with the breath timeline and the aircraft environment timeline”.
Dashevsky further teaches time synchronization of measured respiratory parameters and aircraft sensor data (see col. 30 lines 27-47, “…time synchronization feature primarily allows for post-mission, or post-application review of data in which the subject's position and orientation, as well as g-forces experienced are compared via time signature to known events or occurrences, such as detected dangerous breathing…”). Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor disclosed by Bebout (to align individual breath data in accordance with the breath timeline and the aircraft environment timeline) for the purpose of analyzing circumstances that lead to dangerous breathing or health conditions, as evidence by Dashevsky (see col. 30, lines 43-47).
Additionally, Bebout fails to explicitly disclose “…cause the processor to:…determine whether the breath types associated with the individual breaths are associated with a physiological episode (PE) profile based at least in part on the aircraft environment data in accordance with the aligned breath and aircraft timelines”.
Dashevsky further teaches identifying dangerous respiratory conditions based on respiratory measurements (see col. 31 lines 44-52, “…processor preferably contains and employs an algorithm for the specific purpose of identifying and predicting dangerous health conditions including, but not limited to hypoxia, hypothermia, hypo- and hyperventilation, G-LOC, atelectasis and other dangerous breathing and physical conditions…”), and further teaches identifying a type of breathing a subject is performing based on respiratory measurements (see col. 32, lines 43-48, “… system may predict the onset of G-force induced loss of consciousness (G-LOC) based on a series of measurements of ventilation or flow rate of the subject's breath and carbon dioxide output which allow the system to determine the subject's breath rate and type of breathing the subject is performing”).
Bebout discloses monitoring individual breath data aligning with events experienced by the environmental sensor (see [0042]), but fails to disclose association with a physiological episode profile. Dashevsky teaches identification of respiratory conditions and identification of types of breathing based on respiratory measurements. Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor disclosed by Bebout (to determine whether the breath types associated with the individual breaths are associated with a physiological episode (PE) profile) for the purpose of robustly monitoring physiological parameters to identify potential dangerous health or breathing conditions, as evidence by Dashevsky (see col. 31, lines 38-44).
Additionally, Bebout fails to explicitly disclose “…cause the processor to:…issue a PE alert based on the determination”.
Dashevsky further teaches generating an alert if it is determined that a dangerous condition is occurring (see col. 31 lines 52-56, “…the processor and algorithm calculate that such a dangerous condition is occurring, or soon will occur, a warning or alert is sent out…”).
Bebout discloses generating an alert, but fails to explicitly disclose generating an alert based on a determination of if the breath types are associated with a physiological episode profile. Dashevsky teaches generating an alert based on a determination of the presence of a dangerous condition. Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor disclosed by Bebout (to issue a physiological episode alert if it is determined that associated breath types are associated with a physiological episode) for the purpose of notifying a user or a third party of the presence of a dangerous breathing or health condition is predicated or detected, as evidence by Dashevsky (see col. 31 lines 7-11).
Regarding claim 2: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky/Krueger combination further teaches applying indices to measured values (see [0043], “…creation of indices corresponding to AI, VI, and GI under controlled conditions and varying conditions of hypobaria…”).
However, the Bebout/Dashevsky/Krueger combination fails to disclose “…apply a first noise filter to the raw respiration data prior to extraction of the individual breaths from the raw physiological data”.
Dashevsky further teaches filtering a detected respiratory signal before processing (see col. 34 lines 43-48, “…one or more electronic components also filter (and possibly amplify) the detected signal and more preferably convert this detected physiological signal, which is in an analog form into a digital signal for transmission to the remote receiving unit”) and further teaches filtering for the purpose of noise reduction (see col. 35 lines 42-45, “…data acquisition circuitry is designed with the goal of reducing size, lowering (or filtering) the noise…”).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky/Krueger combination (to apply a first noise filter to the raw respiration data prior to extraction of the individual breaths from the raw physiological data) for the purpose of filtering out unwanted noise, as evidence by Dashevsky (see col. 35 lines 42-44).
Regarding claims 3 and 18: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky/Krueger combination further teaches wherein the memory further comprises instructions that upon execution by the processor, cause the processor (of the Bebout/Dashevsky combination) to receive the aircraft environment data from an aircraft motion sensor, an aircraft g-force sensor, a life support system sensor, an oxygen level sensor, and a cabin pressure sensor (see Bebout [0037], “…system 100 comprises a central unit 105, a PO sensor 110, a CO.sub.2 sensor 120, and an airbladder 130…barometer 110, a three-dimension accelerometer 150, a capnography circuitry 160, and a control unit…”, see also [0041], “…barometer 140 or pressure manometer can also be provided for continuous monitoring of cabin pressure…three-dimensional accelerometer 150 can also be housed in the central unit 105 that can be used for continuously monitoring direction and magnitude of G forces (Gx, Gy and Gz)… capnography board 160 for integration of inspired and expired CO.sub.2 for measurement and detection of respiratory rate and pattern, end tidal CO.sub.2, hyperventilation, hypoventilation hypocapnia, hypercapnia, CO.sub.2 contamination and CO.sub.2 rebreathing….”, cabin pressure sensor, three dimensional accelerometer (i.e., aircraft motion sensor), PO sensor (i.e., pulse oximetry sensor, measuring oxygen level) and G-force sensor) and capnography board (i.e., life support sensor, measuring respiration of a user, the presence of respiration indicating support of life for a user)).
Regarding claim 4: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky/Krueger combination further teaches wherein the memory further comprises instructions that upon execution by the processor, cause the processor to apply an algorithm to the aircraft environmental data (see [0041], “…central unit 105 comprises a control unit 170 that contain all the algorithms for SpO2, PR and COHb measurements as well as motion, vibration, pressure and acceleration tolerance, low perfusion performance, alarms and indices of signal strength and signal quality for all parameters…”).
However, the Bebout/Dashevsky/Krueger combination fails to teach “…cause the processor to apply a smoothing algorithm to the aircraft environmental data”.
Dashevsky further teaches a smoothing algorithm (see col. 35 lines 64-67, “…it preferably is provided in a second-order anti-alias filter, whose cutoff frequency can be adjusted to suit a specific application…”).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky/Krueger combination (to apply a smoothing algorithm) for the purpose of improving measurement of the signal of interest, as evidence by Dashevsky (see col. 35 lines 40-55).
Regarding claim 5: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above.
However, the Bebout/Dashevsky/Krueger combination fails to teach “wherein the memory further comprises instructions that upon execution by the processor, cause the processor to apply a second noise filter to the aircraft environmental data”.
Dashevsky further teaches filtering a detected respiratory signal before processing (see col. 34 lines 43-48, “…one or more electronic components also filter (and possibly amplify) the detected signal and more preferably convert this detected physiological signal, which is in an analog form into a digital signal for transmission to the remote receiving unit”) and further teaches filtering for the purpose of noise reduction (see col. 35 lines 42-45, “…data acquisition circuitry is designed with the goal of reducing size, lowering (or filtering) the noise…”).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky/Krueger combination (to apply a first noise filter to the raw respiration data prior to extraction of the individual breaths from the raw physiological data) for the purpose of filtering out unwanted noise, as evidence by Dashevsky (see col. 35 lines 42-44). Furthermore, it would have been obvious to one having ordinary skill in the art at the time the invention was made to modify the processor of the Bebout/Dashevsky combination to apply a second noise filter since it has been held that mere duplication of the essential working parts of a device involves only routine skill in the art. St. Regis Paper Co. v. Bemis Co., 193 USPQ 8.
Regarding claim 6: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above.
However, the Bebout/Dashevsky/Krueger combination fails to explicitly teach “…cause the processor to: generate at least one breath feature associated with a first breath pattern of a first individual breath; and employ a trained breath classification neural network to classify the first individual breath as one of the plurality of different breath types based on the at least one breath feature”.
Dashevsky further teaches a machine learning classifier classifying individual breath types as healthy or dangerous based on a breath feature (see col. 32 lines 1-30“… breath-by-breath values are read into the buffer of a classifier algorithm…Respiratory…patterns that are reflective of healthy or dangerous conditions may be analyzed and classified via…a machine learning classifier… rely on a feature space selected by known metabolic metrics….breath-by-breath metrics of the feature space most intuitively come from a single breath… classifier is preferably trained to SpO2 bins…”).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky combination (to generate a breath feature associated with a breath pattern of an individual breath; and employ a trained breath classification neural network to classify the first individual breath as one of the plurality of different breath types based on the at least one breath feature) for the purpose of creating a user specific algorithm improving classification accuracy (see Dashevsky col. 32 lines 18-23).
Regarding claim 7: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky/Krueger combination further teaches an algorithm applying linear regression coefficients (see Bebout [0040], “Arterial blood SaO2 and heart rate data can be compared to SpO2 and PR values…numerical relationships between accuracy (bias, precision, root mean square of the differences and linear regression coefficients)…” measured values compared to known control values, linear regression coefficients between measured and control determined).
However, the Bebout/Dashevsky/Krueger combination fails to explicitly teach “…classify a first individual breath as one of a plurality of different breath types based on an associated first breath pattern using at least one of a decision tree and a regression model”.
Dashevsky further teaches a machine learning classifier receiving individual breath values as an input, analyzing respiratory patterns and predicting future respiratory blood gas values, to classify a respiratory state as healthy or dangerous (see col. 32 lines 4- , “…breath-by-breath values are read into the buffer of a classifier algorithm… classifier then uses the respiratory gas calculations to predict subsequent blood gas values… Respiratory and gas exchange patterns that are reflective of healthy or dangerous conditions may be analyzed and classified…via a machine learning classifier…based off of a “strong learning” method, such as an artificial neural network, a support vector machine, or a Bayes classifier…”, using a respiratory pattern to classify an individual breath as healthy or dangerous (i.e., as one of a plurality of different breath types) using a machine learning classifier).
Although the Bebout/Dashevsky/Krueger combination teaches applying linear regression coefficients to compare measured numerical blood gas values to known controls, the Bebout/Dashevsky/Krueger combination fails to explicitly teach classifying an individual breath using at least one of a decision tree and a regression model. Dashevsky further teaches classifying individual breaths into a plurality of breath types (i.e., healthy or dangerous) based on machine learning classifier analysis of respiratory patterns and blood gas values.
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky/Krueger combination (to classify an individual breath as one of a plurality of breath types based on an associated breath pattern using a regression model), for the purpose of improving the acceptability of the model for various population types, by applying training data from multiple individuals to any user, as evidence by Dashevsky (see col. 32 lines 16-17).
Regarding claims 10 and 19: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky/Krueger combination further teaches wherein the memory further comprises instructions that upon execution by the processor, cause the processor to classify each individual breath as one of the plurality of different breath types based on the associated breath pattern, the plurality of different breath types comprising shallow breathing, hyperventilation breathing, coughing breathing, talking breathing, deep breathing, normal breathing, apnea, big breath, and AGSM (see Bebout [0041], “…detection of respiratory rate and pattern…hyperventilation, hypoventilation hypocapnia, hypercapnia…”, respiratory rate and breath pattern from individual measurements used to determine hyperventilation, hypoventilation (i.e., shallow breathing)) ;.
Regarding claim 11: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky/Krueger combination further teaches, wherein the memory further comprises instructions that upon execution by the processor, cause the processor to: receive the raw physiological data from at least one sensor of the biosensing garment of the pilot (see Fig. 1 and [0038], “…PO sensor 110 can be configured in a headband of the pilot's helmet and held in place…”, see also [0041]-[0042], “…PO sensor 110 and the CO2 sensor 120 can be connected to the control unit 170… CO2 sensor can be positioned directly into an aviator's mask of the pilot to detect inspired and expired CO2…”, PO sensor 110 and CO2 sensor 120 are positioned on a headband and aviator mask of a pilot’s helmet respectively (i.e., a biosensing garment) and collect physiological data to be sent to control unit 170 (i.e., control unit 170 receives physiological data collected by sensors 110 and 120), calculate at least one of heart rate and heart rate variability; and determine whether the breath types associated with the individual breaths are associated with the PE profile based in part on at least one of the heart rate and the heart rate variability (see Bebout [0040], “…heart rate data can be compared to SpO2 and PR values to determine accuracy under control conditions…”, heart rate data for comparison).
However, the Bebout/Dashevsky/Krueger combination fails to teach “…the raw physiological data comprising electrocardiogram data; calculate at least one of heart rate and heart rate variability based on the electrocardiogram data; and determine whether the breath types associated with the individual breaths are associated with the PE profile based in part on at least one of the heart rate and the heart rate variability”.
Dashevsky further teaches collecting electrocardiogram data to determine heart rate (see col. 29 lines 49-55, “…If electrodes are used to pick up the electro-physiological signals, these electrodes for example when measuring cardiac signals using an ECG, may be placed at specific points on the subject's body. The ECG is used to measure the rate and regularity of heartbeats…”) and using ECG to determine physiological abnormalities (see col. 29 lines 57-60, “…ECG is important as a tool to detect the cardiac abnormalities that can be associated with respiratory-related disorders”).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky/Krueger combination (to measure ECG data, calculate heart rate based on ECG data collected, and determine whether breath types associated with individual breaths (of the Bebout/Dashevsky combination) are associated with the PE profile based on heart rate), for the purpose of identifying and predicting dangerous health conditions, as evidence by Dashevsky (see col. 30 lines 59-64).
Regarding claim 13: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky/Krueger combination further teaches wherein the memory further comprises instructions that upon execution by the processor, cause the processor to issue the PE alert (of the Bebout/Dashevsky combination), the PE alert comprising at least one of a cockpit haptic PE alert, a cockpit audio PE alert, a cockpit display PE alert, a pilot training display PE alert, and a third-party display PE alert (see Bebout [0024]-[0025], “… provide an alert upon detecting hypoxemic or hypoxic conditions in the pilot… provide an alert upon detecting hypocapnia in the pilot”, see also [0048], “…algorithms further enable calculation of motion and vibration tolerance, low perfusion performance, alarms and indices of signal strength and signal quality…”, providing an alert/alarms of the presence of a physiological condition to a pilot).
However, the Bebout/Dashevsky/Krueger combination fails to explicitly teach “…the PE alert comprising at least one of a cockpit haptic PE alert, a cockpit audio PE alert, a cockpit display PE alert, a pilot training display PE alert, and a third-party display PE alert”.
Dashevsky further teaches various means of alerting of the presence of dangerous breathing conditions (see col. 50, lines 20-25, “…mask with heads up display comprises visual indicators which may be used as part of the warning and alert system for identifying and predicting dangerous breathing or other health conditions…”, see also col. 50 lines 42-49, “…heads up display 141 then displays the warning…flashing or blinking lights, preferably LEDs, an auditory signal or message, a scrolling textual alert…”, display, and audio alert).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky/Krueger combination (to provide the PE alert as a display or audio alert), for the purpose of alerting a pilot or third party user to the presence of a dangerous health condition due to a high g-force condition or maneuver, as evidence by Dashevsky (see col. 30 lines 35-37).
Regarding claim 14: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky/Krueger combination further teaches wherein the PE alert comprises a potential PE episode alert (see Bebout [0024]-[0025], “… provide an alert upon detecting hypoxemic or hypoxic conditions in the pilot… provide an alert upon detecting hypocapnia in the pilot”, see also [0048], “…algorithms further enable calculation of motion and vibration tolerance, low perfusion performance, alarms and indices of signal strength and signal quality…”, providing an alert/alarms of the presence of a physiological condition).
However, the Bebout/Dashevsky/Krueger combination fails to explicitly teach “…wherein the PE alert comprises a potential PE episode alert”.
Dashevsky further teaches alerting a user or third party of a potential onset of a dangerous physiological condition prior to the occurrence of the dangerous physiological condition (see col. 45 lines 50-63, “…processor and algorithm calculate that such a dangerous condition is occurring, or soon will occur, a warning or alert is sent out…to the subject or wearer of the mask, to a third person, such as a remote monitoring system…or to an internal or external system…put the receiver of the alert on notice that the subject is experiencing, or is about to experience a dangerous breathing condition, and allows that person to either come to the subjects aid, or to help prevent the onset of more serious conditions”).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky/Krueger combination (to provide the PE alert as a potential PE episode alert), for the purpose of providing a warning signal prior to the onset of a dangerous physiological event, as evidence by Dashevsky (see col. 5 line 65 – col. 6 line 5).
Regarding claim 15: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky/Krueger combination further teaches wherein the memory further comprises instructions that upon execution by the processor, cause the processor to: determine whether the breath types associated with the individual breaths is associated with the PE profile.
However, the Bebout/Dashevsky/Krueger combination fails to explicitly teach “…the PE profile being associated with a pilot incapacitating PE; and automatically implement aircraft action comprising at least one of a life support system action and an aircraft control action based on the determination”.
Dashevsky further teaches issuing an alert allowing automatic control of an aircraft if a pilot is rendered incapacitated (see col. 55 lines 7-13, “…upon receiving an alert or warning from the biometric monitoring system, automatically take control of the subject's vessel or equipment. Such systems are particularly useful for the fighter pilot embodiments where dangerous conditions may render the subject incapacitated and in severe danger of crashing and death”).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky/Krueger combination (to automatically implement aircraft control action based on determination of breath types associated with a PE profile associated with a pilot incapacitating PE), for the purpose of maintaining loft of an aircraft while a pilot is experiencing an incapacitating event, as evidence by Dashevsky (see col. 55 lines 13-18).
Regarding claim 16: The Bebout/Dashevsky combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky combination further teaches wherein the memory further comprises instructions that upon execution by the processor, cause the processor (of the Bebout/Dashevsky combination) to issue the PE alert in accordance with communication criteria see Bebout [0024]-[0025], “… provide an alert upon detecting hypoxemic or hypoxic conditions in the pilot… provide an alert upon detecting hypocapnia in the pilot”, see also [0048], “…algorithms further enable calculation of motion and vibration tolerance, low perfusion performance, alarms and indices of signal strength and signal quality…”, providing an alert/alarms of the presence of a physiological condition to a pilot, based on a communication criteria (i.e., detecting hypoxemic, hypoxic, or hypocapnia in a pilot)).
However, the Bebout/Dashevsky/Krueger combination fails to teach “…the communication criteria comprising at least one of a pilot behavior associated with the breath types, an urgency criterion, and an aircraft environmental parameter associated with the breath types”.
Dashevsky further teaches utilizing additional criteria, such as environmental data and breathing information, to issue an alert regarding a dangerous physiological condition (see col. 54 lines 45-56, “…processor…takes the sensor measured values and calculates a number of additional metrics…measured values and calculated metrics are then combined and correlated…resulting calculated biometric data 335 represents the subject's health status, breathing information, environmental data…determines, based on the resultant biometric data, whether the subject is experiencing a dangerous condition”).
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky/Krueger combination (to include communication criteria comprising at least one of a pilot behavior associated with the breath types, an urgency criterion, and an aircraft environmental parameter associated with the breath types), for the purpose of predicting the onset of a dangerous physiological condition, as evidence by Dashevsky (see col. 54 lines 56-65).
Claims 8, 9, 12, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Bebout in view of Dashevsky and Kreuger, and further in view of US 2005/0202375 A1 to Nevo et al. “Nevo”.
Regarding claims 8 and 20: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky/Krueger combination further teaches wherein the memory further comprises instructions that upon execution by the processor (of the Bebout/Dashevsky/Krueger combination), cause the processor to: make a first determination regarding whether the aircraft environment data comprises at least one of aircraft motion data associated with generation of aircraft g-forces and aircraft g-force data (see Bebout [0041], “…accelerometer 150 can also be housed in the central unit 105 that can be used for continuously monitoring direction and magnitude of G forces (Gx, Gy and Gz), determine g-force data presence…”, determination of g-force presence); and issue the PE alert based on the first determination (see Bebout [0048] “… three-dimensional accelerometer and a computer readable program to measure gravitational forces in at-least three…enable calculation of motion and vibration tolerance, low perfusion performance, alarms and indices of signal strength and signal quality” issues an alert condition based on determination of G-force magnitude).
However, the Bebout/Dashevsky combination fails to disclose “…make a second determination regarding whether the breath types associated with the individual breaths comprise an anti-G straining maneuver (AGSM); and issue the PE alert based on the first and second determination… the PE alert comprising an AGSM alert”.
Nevo teaches systems and methods for detecting conditions resulting in gravity induced loss of conciousness in pilots (see abstract) by comparing measured pilot data to stored data indicating gravity induced loss of conciousness (see [0042], “… processor 60 compares the real-time head position pattern to the stored reference data, as explained above, and if a state of G-LOC is detected the processor…initiate various responses…”), further including monitoring pilot breathing patterns associated with an anti-G straining maneuver (see [0043], “…breathing pattern of the pilot can be easily recorded from the microphone, from the oxygen regulator of the pilot, or from air-flow sensor that is integrated into the oxygen mask of the pilot…pilot performs anti-G straining maneuver (AGSM) that involves a typical breathing pattern… airflow pattern in the oxygen mask during AGSM can be recorded and used as an additional variable in the reference envelopes”) and issuing an alert based on a potential gravity induced loss of conciousness state (see [0039] “… G-LOC detection and response system should communicate with the avionic bus through the communication channel and transmit the status of "pilot in G-LOC" to the bus 30…”).
Although the Bebout/Dashevsky/Krueger combination fails to teach association of individual breaths with an anti-G straining maneuver, the Bebout/Dashevsky/Krueger combination teaches issuing an alert based on detection of G-force data.
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky/Krueger combination (to make a second determination regarding whether the breath types associated with the individual breaths comprise an anti-G straining maneuver (AGSM) and issue the PE alert based on the first and second determination and a PE alert comprising an AGSM alert) for the purpose of adapting reference values specific to each pilot, as evidence by Nevo (see [0029]). Furthermore, one of ordinary skill in the art would have had predictable success combining Bebout/Dashevsky/Krueger and Nevo since their teachings relate to the same narrow field of endeavor, i.e., wearable devices for monitoring various pilot bio-parameters.
Regarding claim 9: The Bebout/Dashevsky/Krueger/Nevo combination teaches the system of claim 8/1, as discussed above. The Bebout/Dashevsky/Kreuger/Nevo combination further teaches wherein the memory further comprises instructions that upon execution by the processor, cause the processor to issue the AGSM alert as at least one of a cockpit display PE alerts and a pilot training display PE alert (see Nevo Fig. 1 and [0037], “…first operation of the G-LOC detection and response system is to activate a visual and/or audio warning alarm…”).
Regarding claim 12: The Bebout/Dashevsky/Krueger combination teaches the system of claim 1, as discussed above. The Bebout/Dashevsky/Krueger combination further teaches storing measured data (see Bebout [0041], “…control unit 170 is further configured for storing data acquired during functioning of the system…connected to an external computing system for transferring data to allow real-time data acquisition”) and comparison of measured respiration data to known metrics under varying aircraft conditions (see Bebout [0042], “…calibration curve or curves can be embedded into the pulse oximetry algorithms and based on arterial blood studies conducted during hypoxia, CO exposure, hypobaria, high frequency vibration and increased gravitational forces…”)
However, the Bebout/Dashevsky/Krueger combination fails to teach “…cause the processor to store the determination regarding whether the breath types associated with the individual breaths are associated with the PE profile in a database to enable an assessment of whether there is a correlation between the PE profile and an aircraft event”.
Nevo teaches systems and methods for detecting conditions resulting in gravity induced loss of conciousness in pilots (see abstract) using a processor including a database to compare measured values to reference patterns stored in a database to indicate the onset of a physiological event (see [0020], “…a processor including a database for storing reference motion patterns of the helmet for each of a plurality of tasks to be performed by the pilot…compare in real time said tracked motion pattern of the helmet with said stored reference motion patterns…when a tracked motion pattern deviates from said stored referenced patterns such as to indicate the onset of a G-LOC state in the pilot”).
Although the Bebout/Dashevsky/Krueger combination fails to teach a database storing PE profiles and assessing a correlation between a PE profile and an aircraft event based on the PE breath type association, the Bebout/Dashevsky/Krueger combination teaches storing respiration data, and further teaches comparing measured respiration data to known data under varying aircraft conditions. Nevo teaches a database storing reference patterns, and comparing measured respiration patterns to stored patterns to determine an association between a pattern deviation and a physiological event occurrence.
Therefore, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the processor of the Bebout/Dashevsky/Krueger combination (to store the determination regarding whether the breath types associated with the individual breaths are associated with the PE profile in a database to enable an assessment of whether there is a correlation between the PE profile and an aircraft event) for the purpose of determining a significant deviation from stored reference data , as evidence by Nevo (see [0033]). Furthermore, one of ordinary skill in the art would have had predictable success combining Bebout/Dashevsky/Krueger and Nevo since their teachings relate to the same narrow field of endeavor, i.e., wearable devices for monitoring various pilot bio-parameters.
Response to Arguments
Applicant’s arguments, filed on 01/12/2026, with respect to the rejection of record of claims 1-7, 10, 11, and 13-19 under 35 U.S.C. 103 as being unpatentable over Bebout in view of Dashevsky (see page 7 of remarks) 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, as necessitated by amendment.
In particular, on page 7 of the remarks, Applicant argues that Bebout and Dashevsky, taken individually or in combination, fail to teach or suggest “at least one aircraft environment sensor includes a nitrogen level sensor” as recited in independent claims 1 and 17 respectively. This argument is considered not persuasive in view of the treatment of independent claims 1 and 17 above.
Therefore, claims 1-20 remain rejected under 35 U.S.C. 103.
Conclusion
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.
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/ALYSSA PAIGE NOVAK/ Examiner, Art Unit 3791
/ERIC J MESSERSMITH/ Primary Examiner, Art Unit 3791