DETAILED ACTION
This Non-Final action is responsive to the continuation filed 6/19/2026.
In the continuation Claims 1-2 and 4-20 are pending. Claim 3 was canceled. Claims 1, 13 and 19 are the independent claims.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Withdrawn Objections
The Objection to the abstract has been withdrawn in light of the amendment.
Withdrawn Rejections
The 35 U.S.C. 103 rejection of claims 1, 3-14 and 16-20 with cited references of Merchant (U.S. Pub 2024/0190440) in view of Dugan (U.S. Pub 2014/0106333) has been withdrawn in light of the amendment.
The 35 U.S.C. 103 rejection of claims 2 and 15 with cited references of Merchant (U.S. Pub 2024/0190440) in view of Dugan (U.S. Pub 2014/0106333) further in view of Breut (U.S. Pub 2025/0157340) has been withdrawn in light of the amendment.
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 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.
7. Claims 1-2 and 4-20 are rejected under 35 U.S.C. 103 as being unpatentable over Merchant (U.S. Pub 2024/0190440, filed Jan. 25, 2023 & previously cited in the 892 dated 9/30/2025) in view of Dugan (U.S. Pub 2014/0106333, filed Oct. 17, 2013) further in view of Dieterich (U.S. Pub 2023/0125334, filed Sep. 16, 2022).
Regarding Dependent claim 1, Merchant discloses A method of mitigating aircraft passenger anxiety during travel, the method comprising:
receiving sensor data associated with physiological measurements of a passenger within an aircraft (see paragraphs 6 and 18, discloses monitoring health information of a passenger of a vehicle that includes an aircraft via one or more sensors. The sensors include in-flight sensors capturing cabin environment data and biometric information of the passenger during a flight such as heart rate, pulse rate, brain activity, skin resistivity, breathing rate etc.);
determining a state of the passenger from the physiological measurements of the passenger (see paragraph 6, discloses generating an indicator value for each of a plurality of parameters from passenger health data disclosed in paragraphs 35-38. The recommendation engine analyzing the biometric and environmental data to determine whether passenger parameters fall below thresholds);
calculating a remedial action associated with the state of the passenger and the aircraft (see paragraphs 6 and 33-35, discloses generating a recommended action based on passenger health data and environmental data. Recommendation engine generating alerts tied to both passenger state and vehicle conditions. Further block 505 discloses a message graphics and/or other information to provide to a passenger being determined based on the measured acceleration data. In addition, disclosing that alerts are communicated to a device in an attempt to dynamically mitigate passenger discomfort); Merchant teaches automated passenger physiological monitoring with recommendations transmitted to aircraft avionics to determine flight diversions (see paragraph 21). Merchant fails to teach using the data to modify a flight envelope for passenger anxiety mitigation.
Dugan discloses:
implementing the remedial action on the aircraft to modify a flight envelope of the aircraft to reduce a detected stressful state of the passenger, wherein modifying the flight envelope includes restricting at least one of a bank angle of the aircraft, a maximum acceleration or deceleration of the aircraft, a maximum climb or descent rate of the aircraft, or an in-plane movement of the aircraft (see paragraphs 40-41, discloses transmission of passenger biometric and stress data to the flight crew to “allow the flight crew to monitor passenger stress level. In addition to compiling route-based historical turbulence maps correlating passenger stress with specific flight conditions). Dugan teaches reducing passenger anxiety during flight and permits monitoring passenger biometric information such as heart rate, pulse, brain activity, skin resistance and breathing rate, but the disclosed response is displaying acceleration information and providing calming content rather than controlling the aircraft in response to the detected physiological state (see paragraph 18). Dieterich discloses a passenger-discomfort-aware flight control system that generates actuator-control signals to control translational and/or rotational aircraft movement about yaw, roll or pitch axes, with the signals being suitable for reducing passenger kinetosis or whole-body vibration (see abstract & paragraphs 19, 37, 40 & 102-103). Further teaching minimizing a passenger-discomfort index by modifying aircraft motion patterns/frequencies (see paragraphs 24, 74 and 77). All three references address the same problem of reducing passenger discomfort/anxiety during aircraft travel. It would have been obvious for one of ordinary skill in the art before the effective filing date of the application to have incorporated into the passenger-state input architecture the physiological anxiety/biometric monitoring of passenger state with passenger discomfort aware aircraft control mechanism. One motivation is to minimize passenger discomfort via aircraft control, which is outlined by Dieterich in paragraph 77.
Regarding Dependent claims 2 and 15, Merchant fails to teach using predicted stress data to modify a flight envelope for passenger anxiety mitigation. Dugan discloses transmission of passenger biometric and stress data to the flight crew to “allow the flight crew to monitor passenger stress level. Dugan fails to teach that the aircraft comprises a eVTOL aircraft.
Dieterich discloses use of electrical VTOL vehicles with the passenger state flight control mechanism (see paragraphs 67 and 125). All three references address the same problem of reducing passenger discomfort/anxiety during aircraft travel. It would have been obvious for one of ordinary skill in the art before the effective filing date of the application to have incorporated into the passenger-state input architecture the physiological anxiety/biometric monitoring of passenger state with passenger discomfort aware aircraft control mechanism. One motivation is to minimize passenger discomfort via aircraft control, which is outlined by Dieterich in paragraph 77.
Regarding Dependent claims 4 and 17, Merchant discloses wherein the remedial action includes rerouting a flight path of the aircraft (see paragraphs 21 and 60, including the explanation provided in the Independent claim).
Regarding Dependent claim 5, with dependency of claim 1, Merchant discloses wherein calculating the remedial action includes: inputting the sensor data and information associated with the aircraft and a travel route into a machine learning model trained on historical data associated with the aircraft and the passenger; producing, by the machine learning model, a remedial action inference; and utilizing the remedial action inference as the remedial action (see paragraphs 58 and 67, including the explanation provided in the Independent claim).
Regarding Dependent claim 6, with dependency of claim 5, Merchant discloses wherein the historical data includes information relating to previous passenger stress indicators along the travel route (see paragraphs 58 and 67, including the explanation provided in the Independent claim). Merchant fails to teach that the historical data is based on travel route. Dugan discloses compiling maps of observed turbulence and passenger stress over particular routes (see paragraph 40). Dugan fails to teach any control of the aircraft based on the state but instead only displays acceleration information. Dieterich discloses a passenger-discomfort-aware flight control system that generates actuator-control signals to control translational and/or rotational aircraft movement about yaw, roll or pitch axes, with the signals being suitable for reducing passenger kinetosis or whole-body vibration (see abstract & paragraphs 19, 37, 40 & 102-103). Further teaching minimizing a passenger-discomfort index by modifying aircraft motion patterns/frequencies (see paragraphs 24, 74 and 77). All three references address the same problem of reducing passenger discomfort/anxiety during aircraft travel. It would have been obvious for one of ordinary skill in the art before the effective filing date of the application to have incorporated into the passenger-state input architecture the physiological anxiety/biometric monitoring of passenger state with passenger discomfort aware aircraft control mechanism. One motivation is to minimize passenger discomfort via aircraft control, which is outlined by Dieterich in paragraph 77.
Regarding Dependent claim 7, with dependency of claim 1, Merchant only teaches general environmental monitoring in paragraph 60. He fails to teach accounting for current weather conditions has a factor in remedial action. Dugan discloses wherein current weather conditions of a travel route of the aircraft is factored when calculating the remedial action (see paragraphs 40-47). Dugan fails to teach any control of the aircraft based on the state but instead only displays acceleration information. Dieterich discloses a passenger-discomfort-aware flight control system that generates actuator-control signals to control translational and/or rotational aircraft movement about yaw, roll or pitch axes, with the signals being suitable for reducing passenger kinetosis or whole-body vibration (see abstract & paragraphs 19, 37, 40 & 102-103). Further teaching minimizing a passenger-discomfort index by modifying aircraft motion patterns/frequencies (see paragraphs 24, 74 and 77). All three references address the same problem of reducing passenger discomfort/anxiety during aircraft travel. It would have been obvious for one of ordinary skill in the art before the effective filing date of the application to have incorporated into the passenger-state input architecture the physiological anxiety/biometric monitoring of passenger state with passenger discomfort aware aircraft control mechanism. One motivation is to minimize passenger discomfort via aircraft control, which is outlined by Dieterich in paragraph 77.
Regarding Dependent claim 8, with dependency of claim 1, Merchant discloses wherein the sensor data is received from a plurality of sensors positioned in and around the aircraft (see paragraph 30, including the explanation provided in the Independent claim).
Regarding Dependent claim 9, with dependency of claim 1, Merchant discloses wherein the physiological measurements includes a blood pressure, a heart rate, a blood oxygen level, and a body temperature associated with the passenger (see paragraph 19, including the explanation provided in the Independent claim).
Regarding Dependent claim 10, with dependency of claim 1, Merchant discloses wherein the sensor data is received from a personal device associated with the passenger (see paragraph 6, including the explanation provided in the Independent claim).
Regarding Dependent claim 11, with dependency of claim 10, Merchant discloses wherein the personal device is paired to the aircraft and configured to transmit the sensor data to the aircraft (see paragraph 6, including the explanation provided in the Independent claim).
Regarding Dependent claim 12, with dependency of claim 1, Merchant discloses receiving additional sensor data associated with the physiological measurements of the passenger after the remedial action is implemented on the aircraft; determining an updated state of the passenger, based, at least in part, on the physiological measurements of the passenger received from the additional sensor data; calculating an updated remedial action associated with the updated state of the passenger and the remedial action previously implemented; and implementing the updated remedial action on the aircraft to alter the updated state of the passenger (see paragraphs 35-39, including the explanation provided in the Independent claim).
Regarding Independent claim 13, Merchant discloses A vehicle comprising: one or more memories that store processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively configured to, in association with executing the code, cause the vehicle to:
determine a state of a passenger from sensor data associated with physiological measurements of the passenger in the vehicle (see paragraphs 6 and 18, discloses monitoring health information of a passenger of a vehicle that includes an aircraft via one or more sensors. The sensors include in-flight sensors capturing cabin environment data and biometric information of the passenger during a flight such as heart rate, pulse rate, brain activity, skin resistivity, breathing rate etc. Further discloses generating an indicator value for each of a plurality of parameters from passenger health data disclosed in paragraphs 35-38. The recommendation engine analyzing the biometric and environmental data to determine whether passenger parameters fall below thresholds);
calculate a remedial action associated with the state of the passenger and the vehicle (see paragraphs 6 and 33-35, discloses generating a recommended action based on passenger health data and environmental data. Recommendation engine generating alerts tied to both passenger state and vehicle conditions. Further block 505 discloses a message graphics and/or other information to provide to a passenger being determined based on the measured acceleration data. In addition, disclosing that alerts are communicated to a device in an attempt to dynamically mitigate passenger discomfort); Merchant teaches automated passenger physiological monitoring with recommendations transmitted to aircraft avionics to determine flight diversions (see paragraph 21). Merchant fails to teach using the data to modify a flight envelope for passenger anxiety mitigation.
Dugan discloses:
implement the remedial action to the vehicle to modify a flight envelope of the vehicle to reduce a detected stressful state of the passenger, wherein modifying the flight envelope includes restricting at least one of a bank angle of the aircraft, a maximum acceleration or deceleration of the aircraft, a maximum climb or descent rate of the aircraft, or an in-plane movement of the vehicle (see paragraphs 40-41, discloses transmission of passenger biometric and stress data to the flight crew to “allow the flight crew to monitor passenger stress level. In addition to compiling route-based historical turbulence maps correlating passenger stress with specific flight conditions). Dugan teaches reducing passenger anxiety during flight and permits monitoring passenger biometric information such as heart rate, pulse, brain activity, skin resistance and breathing rate, but the disclosed response is displaying acceleration information and providing calming content rather than controlling the aircraft in response to the detected physiological state (see paragraph 18). Dieterich discloses a passenger-discomfort-aware flight control system that generates actuator-control signals to control translational and/or rotational aircraft movement about yaw, roll or pitch axes, with the signals being suitable for reducing passenger kinetosis or whole-body vibration (see abstract & paragraphs 19, 37, 40 & 102-103). Further teaching minimizing a passenger-discomfort index by modifying aircraft motion patterns/frequencies (see paragraphs 24, 74 and 77). All three references address the same problem of reducing passenger discomfort/anxiety during aircraft travel. It would have been obvious for one of ordinary skill in the art before the effective filing date of the application to have incorporated into the passenger-state input architecture the physiological anxiety/biometric monitoring of passenger state with passenger discomfort aware aircraft control mechanism. One motivation is to minimize passenger discomfort via aircraft control, which is outlined by Dieterich in paragraph 77.
Regarding Dependent claim 14, with dependency of claim 13, Merchant discloses wherein the vehicle is an aircraft (see paragraphs 18-19, including the explanation provided in the Independent claim).
Regarding Dependent claim 16, with dependency of claim 13, Merchant teaches automated passenger physiological monitoring with recommendations transmitted to aircraft avionics to determine flight diversions (see paragraph 21). Merchant fails to teach using the data to modify a flight path for passenger anxiety mitigation. Dugan discloses wherein the remedial action includes altering a flight path of the vehicle (see paragraphs 40-41). Dugan fails to teach any control of the aircraft based on the state but instead only displays acceleration information. Dieterich discloses a passenger-discomfort-aware flight control system that generates actuator-control signals to control translational and/or rotational aircraft movement about yaw, roll or pitch axes, with the signals being suitable for reducing passenger kinetosis or whole-body vibration (see abstract & paragraphs 19, 37, 40 & 102-103). Further teaching minimizing a passenger-discomfort index by modifying aircraft motion patterns/frequencies (see paragraphs 24, 74 and 77). All three references address the same problem of reducing passenger discomfort/anxiety during aircraft travel. It would have been obvious for one of ordinary skill in the art before the effective filing date of the application to have incorporated into the passenger-state input architecture the physiological anxiety/biometric monitoring of passenger state with passenger discomfort aware aircraft control mechanism. One motivation is to minimize passenger discomfort via aircraft control, which is outlined by Dieterich in paragraph 77.
Regarding Dependent claim 18, with dependency of claim 13, Merchant discloses wherein calculating the remedial action cause the vehicle to: input the sensor data and information associated with the vehicle and a travel route into a machine learning model trained on historical data associated with the vehicle and the passenger; produce, by the machine learning model, a remedial action inference; and utilize the remedial action inference as the remedial action (see paragraphs 58 and 67, including the explanation provided in the Independent claim).
Regarding Independent claim 19, Merchant discloses A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors of an aircraft, cause the processors to:
receive information associated with an aircraft and a passenger within the aircraft (see paragraphs 6 and 18, discloses monitoring health information of a passenger of a vehicle that includes an aircraft via one or more sensors. The sensors include in-flight sensors capturing cabin environment data and biometric information of the passenger during a flight such as heart rate, pulse rate, brain activity, skin resistivity, breathing rate etc.);
calculate a preemptive remedial action associated with the source of passenger stress (see paragraph 46, discloses preemptive alerts transmitted to flight crew before threshold breaches. Further teaching gradual cabin adjustments initiated in anticipation of passenger discomfort); Merchant teaches automated passenger physiological monitoring with recommendations transmitted to aircraft avionics to determine flight diversions (see paragraph 21). Merchant fails to teach using predicted stress data to modify a flight envelope for passenger anxiety mitigation.
Dugan discloses:
predicting a source of passenger stress associated with the information (see paragraph 49, discloses that passengers may receive notifications in real-time that an area the flight is approaching includes turbulence thus predicting upcoming stress source before it is encountered. Further outlining in paragraph 45 that web server predict likelihood of a smooth future flight based on historical turbulence and pilot data);
implementing the preemptive remedial action on the aircraft to modify a flight envelope of the aircraft to reduce a detected stressful state of the passenger, wherein modifying the flight envelope includes restricting at least one of a bank angle of the aircraft, a maximum acceleration or deceleration of the aircraft, a maximum climb or descent rate of the aircraft, or an in-plane movement of the aircraft (see paragraphs 40-41, discloses transmission of passenger biometric and stress data to the flight crew to “allow the flight crew to monitor passenger stress level. In addition to compiling route-based historical turbulence maps correlating passenger stress with specific flight conditions). Dugan teaches reducing passenger anxiety during flight and permits monitoring passenger biometric information such as heart rate, pulse, brain activity, skin resistance and breathing rate, but the disclosed response is displaying acceleration information and providing calming content rather than controlling the aircraft in response to the detected physiological state (see paragraph 18). Dieterich discloses a passenger-discomfort-aware flight control system that generates actuator-control signals to control translational and/or rotational aircraft movement about yaw, roll or pitch axes, with the signals being suitable for reducing passenger kinetosis or whole-body vibration (see abstract & paragraphs 19, 37, 40 & 102-103). Further teaching minimizing a passenger-discomfort index by modifying aircraft motion patterns/frequencies (see paragraphs 24, 74 and 77). All three references address the same problem of reducing passenger discomfort/anxiety during aircraft travel. It would have been obvious for one of ordinary skill in the art before the effective filing date of the application to have incorporated into the passenger-state input architecture the physiological anxiety/biometric monitoring of passenger state with passenger discomfort aware aircraft control mechanism. One motivation is to minimize passenger discomfort via aircraft control, which is outlined by Dieterich in paragraph 77.
Regarding Dependent claim 20, with dependency of claim 19, Merchant discloses wherein predicting the source of passenger stress includes: inputting the information associated with the aircraft into a machine learning model trained on historical data associated with the aircraft and the passenger; producing, by the machine learning model, a source of stress inference; and utilizing the source of stress inference as the source of passenger stress (see paragraphs 58 and 67, including the explanation provided in the Independent claim). Merchant fails to teach that the historical data is based on travel route. Dugan discloses compiling maps of observed turbulence and passenger stress over particular routes (see paragraph 40). Dugan fails to teach any control of the aircraft based on the state but instead only displays acceleration information. Dieterich discloses a passenger-discomfort-aware flight control system that generates actuator-control signals to control translational and/or rotational aircraft movement about yaw, roll or pitch axes, with the signals being suitable for reducing passenger kinetosis or whole-body vibration (see abstract & paragraphs 19, 37, 40 & 102-103). Further teaching minimizing a passenger-discomfort index by modifying aircraft motion patterns/frequencies (see paragraphs 24, 74 and 77). All three references address the same problem of reducing passenger discomfort/anxiety during aircraft travel. It would have been obvious for one of ordinary skill in the art before the effective filing date of the application to have incorporated into the passenger-state input architecture the physiological anxiety/biometric monitoring of passenger state with passenger discomfort aware aircraft control mechanism. One motivation is to minimize passenger discomfort via aircraft control, which is outlined by Dieterich in paragraph 77.
It is noted that any citation [[s]] to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. [[See, MPEP 2123]]
Response to Arguments
8. Applicant’s arguments filed 6/19/2026 has been considered but are moot in view of the new grounds of rejection.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MANGLESH M PATEL whose telephone number is (571)272-5937. The examiner can normally be reached on M-F from 10:30 am to 7:30 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Erin D. Bishop, can be reached at telephone number 571-270-3713. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Manglesh M Patel/
Primary Examiner, Art Unit 3665
9/5/2026
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