DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claims 1-20 are presented for examination on the merits.
Claim Rejections - 35 USC § 103
2. 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.
3. 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 of this title, 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.
4. Claims 1, 2, 8, 9 and 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Vijaya (US 9956963 B2) in view of Karve (DE 102022121581 A1).
As to claim 1, Vijaya discloses in apparatus for assessing, predicting, and responding to driver fatigue and drowsiness levels having claimed:
a. a driver assistance system, comprising: a wearable device configured to measure an electroencephalogram (EEG) signal and head movement of a driver of a moving device read on Col. 16, Lines 7-20, (present driver characteristics, or driver health information, include and are not limited to: measure of a driver physiological or biometric characteristic, such as of a driver's heart rate (HR), electroencephalogram (EEG), voice, gestures, salinity, breath, temperature, electrocardiogram (ECG), Electrodermal Activity (EDA) or Galvanic Skin Response (GSR), Blood Volume Pulse (BVP), Electromyography (EMG), or the like. driver behavior or feature, such as amount or quality of recent sleep, gestures, head or eye movement (e.g., blinking or closing of the eyes), bodily movement activity, facial features, statements, or utterances of the driver);
b. a mobile terminal including an application configured to: receive the EEG signal measured by the wearable device; receive information about the head movement measured by the wearable device; receive a traveling information signal acquired by the moving device; process and provide to a server the received EEG signal, the received information about the head movement, and the received traveling information signal; and receive big data-based inattentiveness alarm information from the server based on information provided to the server by the mobile terminal read on Col. 8, Lines 29-37 & Col. 9, Line 21-49,(the sensors 60 can include any sensor for measuring a vehicle pose or other dynamics, such as position, speed, acceleration, or height—e.g., vehicle height sensor. The sensors 60 can include any known sensor for measuring an environment of the vehicle, including those mentioned above, and others such as a precipitation sensor for detecting whether and how much it is raining or snowing, a temperature sensor, and any other. The mobile or local computing devices 34 are configured with any suitable structure for performing the operations described for them. Example structure includes any of the structures described in connection with the vehicle computing device 20, such as a hardware-based computer-readable storage medium, or data storage device, like the device 104 of FIG. 2, and also includes a hardware-based processing unit (like the unit 106 of FIG. 2) connected or connectable to the computer-readable storage device by way of a communication link (like link 108), such as a computer bus or wireless structures);
c. a control module configured to: provide an inattentiveness-related alarm to the driver; and control the moving device based on the inattentiveness alarm information read on Col. 20, Lines 30-34 & Col. 22, Lines 8-20 (Vehicle control can include providing driver assistance, such as by providing assistive braking early by a determined amount (e.g., 300 ms) corresponding to a determined driver level of impairment (e.g., drowsiness). The system can, for instance, set or adjust drowsy driver ratings for a driver, timing or type of safety alert (e.g., drowsiness alert), navigation/maneuver timing and mode (e.g., adding haptic or visual alerts for less-fit drivers), and timing of automated driving requests, suggestions or requirements. Such variables can be modified in real-time or generally continuously for a given driver and updated based on the relationships between a large quantity of health (e.g., the length/quality of recent sleep) and driver performance data gathered from previous trips stored either by the vehicle or via a portable device, such as a driver phone or smartwatch). Vijaya does not explicitly recite providing an inattentiveness alarm based on the big data-based inattentiveness alarm information to the driver and controlling the moving device based on the inattentiveness alarm information.
However, Karve in data communications and information systems cures this deficiency by teaching that it may be beneficial wherein:
a. providing an inattentiveness alarm based on the big data-based inattentiveness alarm information to the driver and controlling the moving device based on the inattentiveness alarm information read on Page 4, Para. 4, (Method, comprising: (a) activating full power steering assistance and/or lane keeping assistance in a vehicle; (b) collecting data regarding driver attention; (c) analyzing data for signs of driver inattention; (d) determining whether the driver has become inattentive to the driving task (106), and if so, then performing steps (a), (b), and (c), and if not, reducing or stopping power steering, or Applying a lane keeping assist torque to counteract undesirable yaw or lateral movement of the vehicle; (e) thereafter collecting driver attention data; (f) analyzing data for signs of driver alertness; (g) determining whether the driver has become alert to the driving task, and if not, repeating steps (e), (f) and (g), and if the driver is alert, then applying full power steering or reducing lane keeping assist torque; (h) then repeating steps a) to g)).
Therefore, It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate the steering wall modulation based on driver attention to avoid random lane changes of Karve into Vijaya in order to provide a flag confirming that the driver has been judged to be "inattentive", the steering system will reduce the assistance levels.
As to claim 2, Vijaya further discloses:
a. wherein the inattentiveness alarm information includes at least one of information determined based on at least one of traveling information obtained by a plurality of moving devices, the EEG signal for each piece of the traveling information, the information about the head movement for each piece of the traveling information, or any combination thereof read on Col. 16, Lines 7-27 and Col. 23, Lines 16-45, (electroencephalogram (EEG), voice, gestures, salinity, breath, temperature, electrocardiogram (ECG), Electrodermal Activity (EDA) or Galvanic Skin Response (GSR), Blood Volume Pulse (BVP), Electromyography (EMG), or the like. driver behavior or feature, such as amount or quality of recent sleep, gestures, head or eye movement (e.g., blinking or closing of the eyes), bodily movement activity, facial features, statements, or utterances of the driver. driver context, such as recent diet, or medications taken or not taken. a driver-state determination, such as a drowsiness or lack of sleep determination, such as in a message or signal from a bed, via the internet, for instance, configured like that mentioned above, or a fatigue or anxiety determination made by an external system. The vehicle can be configured so that, if the driver is determined impaired, a higher setting (more lead time) is selected with or possibly without driver discretion. 2. LDW example: a. A LDW related factor such as a threshold amount of distance to lane or road edge, or time to lane- or road-edge crossing, is adjusted by the system based on driver state (present health, history, learned data, etc.) to give driver more warning of potential unwanted lane drift, accommodating a perceived lowered driver reaction time. The adjustment can change a default setting, such as by moving a default setting to an earlier warning distance/timing setting if very impaired. Some vehicles are already configured to allow a driver to control such settings. The vehicle can be configured so that, if the driver is determined impaired, a higher setting (more lead time) is selected with or without driver discretion. b. The LDW setting can be presented by).
As to claim 8, Vijaya further discloses:
a. wherein the wearable device includes: a measurer configured to be worn on an ear of the driver read on Col. 3, Lines 34-44, wearables 32, 33 include smart apparel, such as a shirt or belt, an accessory such as an arm strap, or smart jewelry, such as earrings, necklaces, and lanyards. Non-wearable remote examples are also contemplated, such as devices placed on, or part of, a bed that measure movement activity while a person is sleeping);
b. a functional member including a battery configured to supply power to the measurer, wherein the functional member is configured to be fixed to a body part other than the ear of the driver or to a fixed object read on Fig. and Col. 4, Lines 42-42. Note: it is inherent that the wrist watch, the glass and the mobile has a battery to communicate).
As to claim 9, the claim is interpreted and rejected as to claim 1.
As to claim 14, Vijaya further discloses:
a. wherein the measuring of the EEG signal further includes: measuring an EEG characteristic of the driver using the EEG signal measured during a predetermined time period while the driver is wearing a wearable device and driving the moving device; and measuring the EEG signal after the predetermined time period based on the EEG characteristic of the driver read on Col. 2, Lines 38-47, (Example foundational measurements for determining whether the driver is impaired include and are not limited to measurements of a driver's movement activity during sleep, heart rate (HR), electroencephalogram (EEG), voice, gestures, salinity, breath, temperature, electrocardiogram (ECG), Electrodermal Activity (EDA) or Galvanic Skin Response (GSR), Blood Volume Pulse (BVP), Electromyography (EMG), or the like. Each can be evaluated at one or more times).
As to claim 15, the claim is interpreted and rejected as to claim 1.
As to claim 16, the claim is interpreted and rejected as to claim 2.
5. Claims 3-5, 10 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Vijaya in view of Karve and further in view of Choi (KR 20190053643 A).
As to claim 3, Vijaya in view of Karve does not explicitly recite wherein the information about the head movement includes at least one of a difference between a head angle of the driver and a reference angle, the number of changes in the head angle of the driver, a duration of a changed head angle of the driver, or any combination thereof.
However, Choi in a method of preventing drowsiness using a wearable drowsiness prevention apparatus cures this deficiency by teaching that it may be beneficial:
a. wherein the information about the head movement includes at least one of a difference between a head angle of the driver and a reference angle, the number of changes in the head angle of the driver, a duration of a changed head angle of the driver, or any combination thereof read on Page 3, Para. 8, (the reference value setting unit 210 receives a slope value and an eyeball non-exposure time as criteria for determining a user's drowsy state. For example, assuming that the reference slope value is 50 degrees, the angle sensor 120 may determine that the user is in a drowsy state when the user's head is moved by 50 degrees. Or more).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of invention was filed to incorporate the drowsiness prevention method using wearable drowsiness prevention device of Choi into Vijaya in view of Karve in order to provide a drowsiness prevention device which uses an angle sensor attached to a head-shaped guide to determine a drowsiness state of a user through movement of the head of the user.
As to claim 4, Vijaya further discloses:
a. wherein the inattentiveness alarm information includes at least one of information about a posture of the driver, information about a drowsy state of the driver, or any combination thereof read on Col. 22, Lines 8-20, (the system can learn and adapt to driver behavior over time. The system can, for instance, set or adjust drowsy driver ratings for a driver, timing or type of safety alert (e.g., drowsiness alert), navigation/maneuver timing and mode (e.g., adding haptic or visual alerts for less-fit drivers), and timing of automated driving requests, suggestions or requirements. Such variables can be modified in real-time or generally continuously for a given driver and updated based on the relationships between a large quantity of health (e.g., the length/quality of recent sleep) and driver performance data gathered from previous trips stored either by the vehicle or via a portable device, such as a driver phone or smartwatch).
As to claim 5, Vijaya further discloses:
a. wherein the control module is further configured to provide at least one of the inattentiveness-related alarm to the driver according to one or more of the postures, the drowsy state related to the inattentiveness alarm information, or any combination thereof read on Col. 22, Lines 8-20, (the system can learn and adapt to driver behavior over time. The system can, for instance, set or adjust drowsy driver ratings for a driver, timing or type of safety alert (e.g., drowsiness alert), navigation/maneuver timing and mode (e.g., adding haptic or visual alerts for less-fit drivers), and timing of automated driving requests, suggestions or requirements. Such variables can be modified in real-time or generally continuously for a given driver and updated based on the relationships between a large quantity of health (e.g., the length/quality of recent sleep) and driver performance data gathered from previous trips stored either by the vehicle or via a portable device, such as a driver phone or smartwatch).
As to claim 10, the claim is interpreted and rejected as to claim 3.
As to claim 17, the claim is interpreted and rejected as to claim 3.
6. Claims 6, 11, 12 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Vijaya in view of Karve and further in view of Burton (US 2021/0169417 A1).
As to claim 6, Vijaya in view of Karve does not explicitly recite wherein the application is further configured to: measure a correct posture characteristic of the driver using the information about the head movement measured during a predetermined time period while the driver wears the wearable device and drives the moving device; and measure the head movement of the driver after the predetermined time period based on the correct posture characteristic of the driver.
However, Burton in medicine techniques for evaluating and recording the electrical activity produced by EEG or EMG signals to detect medical abnormalities cures this deficiency by teaching that it may be beneficial:
a. wherein the application is further configured to: measure a correct posture characteristic of the driver using the information about the head movement measured during a predetermined time period while the driver wears the wearable device and drives the moving device; and measure the head movement of the driver after the predetermined time period based on the correct posture characteristic of the driver read on ¶ 1837, (whereby said "monitoring relevant parameters" includes (but are not limited to) any of or any combination of motion, travel pathways, geographical locational pathways (i.e. GPS; GMS), accelerometer measures (i.e. range of different multi-axis accelerometer sensors), subject-posture or position measures, properties or patterns of movements, spectral nature of monitored movement signals, signal dynamic properties (i.e. non-linear dynamic, complexity, entropy analysis etc.) of monitored movement signals, coherence interrelationships between monitored movement signals, symmetry, multi-source (i.e. limbs, body, head and other extremities) movement symmetry and/or fluidity and/or synchronization and/or patterns and/or gait and/or associated trends or changes over time).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of invention was filed to incorporate the mobile wearable monitoring systems of Burton into Vijaya in view of Karve in order to provide a sleep and fitness tracking capability applicable to the said subject via a wearable information indicator device (such as watch or bangle) or other subject wearable or attachable device.
As to claim 11, the claim is interpreted and rejected as to claim 6.
As to claim 12, Vijaya further discloses:
a. the drowsy state related to the inattentiveness alarm information, or any combination thereof read on Col. 15, Lines 30-50, (the association may connect (1) a particularly driver characteristic, such as heart-rate profile measured, to (2) a fitness determination made on a past occasion by the system, such as a score, level, or fit/not-fit determination assigned or determined in connection with the particular driver characteristic. Driver reaction to stimuli. The data may indicate how the driver reacted to a stimulus, such as an alert of apparent drowsiness while driving. The data may show that the driver reacted well in response to a prior alert, when HR measures indicated drowsiness, such as by stopping at a rest area, and having better HR measurements for the driver thereafter. Or the data may show how the driver changed behavior in response to an alert or message, such as by not driving in the first place, taking a nap, getting more sleep, eating better, etc. Or the data may show that some alerts were more effective than others in obtaining desired driver behavior, such as pulling over, as mentioned, not driving in the first place, taking a nap, getting more sleep, eating better, etc.).
Burton further teaches:
b. wherein the providing of the alarm further includes providing at least one of the inattentiveness-related alarm to the driver according to one or more of the postures read on Page 122, Para. 1, (current sleep in terms of sleep architecture; inbuilt or other forehead monitoring device with steep posture training function with inbuilt (self-contained) training system capable of detecting snoring (i.e. via inbuilt breathing sound or snoring monitoring function (i.e. accelerometer vibration or microphone sensor) in a manner whereby subject/patient can be alerted or awoken (including headband attached vibration or sound alarm device)).
As to claim 18, the claim is interpreted and rejected as to claim 4.
As to claim 19, the claim is interpreted and rejected as to claim 5.
As to claim 20, the claim is interpreted and rejected as to claim 6.
7. Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Vijaya in view of Karve and further in view of Seo (KR 20200075329 A).
As to claim 7, Vijaya in view of Karve does not explicitly recite wherein the application is further configured to: measure an EEG characteristic of the driver using the EEG signal measured during a predetermined time period while the driver is wearing the wearable device and driving the moving device; and measure the EEG signal after the predetermined time period based on the EEG characteristic of the driver.
However, Seo in vehicle interlocked with a wearable device cures this deficiency by teaching that it may be beneficial:
a. wherein the application is further configured to: measure an EEG characteristic of the driver using the EEG signal measured during a predetermined time period while the driver is wearing the wearable device and driving the moving device; and measure the EEG signal after the predetermined time period based on the EEG characteristic of the driver The updated internal data is data measured by the wearable device at a predetermined time period after the vehicle starts driving read on Page 7, Para. 8-11, (the updated internal data is data measured by the wearable device at a predetermined time period after the vehicle starts driving. For this, the updated external data may be transmitted to the wearable device through a network with the integrated server at a predetermined time period after the vehicle starts to be operated and received. Meanwhile, the updated internal data may be measured by the wearable device at a predetermined time period from the time when the vehicle is started, in addition to the above, at the measurement time of the wearable device. The updated external data may be measured by updating the external data at a predetermined time period after the vehicle starts operating. To this end, a fine dust meter for measuring the external fine dust concentration of the vehicle may be installed in the grill portion of the vehicle, and the vehicle may acquire updated external data through the fine dust meter. The above-described internal update data and external update data may be set by a user directly inputting a predetermined time period into the vehicle. For example, the predetermined time period may be divided into real time, 5 minute period, 10 minute period, 15 minute period, and 30 minute period).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of invention was filed to incorporate the method for controlling of wearable device interworking vehicle fine dust response system of Seo into Vijaya in view of Karve in order to provide information on heart rate or oxygen saturation of the driver by a sensor unit facing the wrist and analyzes the current driver's biometric information in real time based on the driver's biometric information analyzed from the average value of the driver's bio-information is greater than the bio-information of the driver and determined that the driver is in a drowsy driving and provide a warning sound to the drive.
Allowable Subject Matter
8. Claim 13 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. However, an updated search will need to be performed after the next response from Applicant.
Response to Arguments
9. Applicant's arguments with respect to claims 1-20 have been considered but are moot in view of the new ground(s) of rejection that was necessitated by Applicant's amendment.
Citation of pertinent Prior Arts
10. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: see PTO-892 Notice of References Cited.
Conclusion
11. 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).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Fekadeselassie Girma whose telephone number is (571) 270-5886. The examiner can normally be reached on Monday thru Friday, 8:30 – 5:00. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Joseph H. Feild can be reached on (571) 272-4090. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Fekadeselassie Girma/
Primary Examiner Art Unit 2689
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