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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 03/17/2026 has been entered.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification (MPEP 608.01, ¶6.31).
Claim Rejections - 35 USC § 101
Applicant’s amendments sufficiently integrate the invention into a practical application by actively controlling the vehicle, and thus are considered eligible.
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.
Claim(s) 1-4, 9-14, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Matsunami (US20210197832A1) as modified by Shriberg (US20220328064A1) and Aluf (US20220095975A1).
Regarding claim 1, Matsunami teaches;
A vehicle control apparatus (taught as a safe driving assistance system, element 100), comprising:
a camera for obtaining a facial image of a passenger (taught as acquiring image of the face of the driver, paragraph 0185, using a camera or imaging device, paragraph 0154);
a first detection device configured to detect biometric information of a passenger in a vehicle using a sensor (taught as a sensor to obtain biometric information from the driver, paragraph 0145); wherein the biometric information includes information on a heart rate (taught as measuring the heart rate based on a pulse meter, paragraph 0033), and
a processor electrically connected with the first detection device (taught as a control unit, element 45, which receives signals from sensors, paragraph 0174), wherein the processor is configured to
receive information on setting of an autonomous driving level (taught as determining permission for driving a vehicle paragraph 0122, which indicates a manual driving condition and thus corresponds to any level between 0 [fully manual] and 4 [partially autonomous] control),
determine whether to approve a setting of an autonomous driving level based on a difference between the biometric information and a reference value (taught as comparing sensor values against permissible information, based on biometric data [i.e. a required range or score], for permitting the driver to drive a vehicle, paragraph 0122, for example, criteria determination regarding whether a dangerous value is exceeded, paragraph 0295),
perform voice interaction configured to convert voice of the passenger to text (taught as acquiring the voice emitted by the driver, paragraph 0282; while not explicitly recited, voice recognition programs are well understood to involve converting received voice to text data for analysis),
determine a second pattern of the heart rate based on the biometric information (taught as determining the heart rate measured by the pulse meter and comparing it to a predetermined number, paragraph 0033),
determine whether to perform autonomous driving of the vehicle based on a result of determining whether the passenger has dementia (taught as testing a driver with dementia using permissible information based on a correct answer rate of answer input from the driver, paragraph 0268), and
control the autonomous driving of the vehicle based on the result of determining whether the passenger has dementia (taught as controlling the vehicle based on the determination for permission in a dementia patient, paragraph 0280, such as with emergency control procedures if a permissible cognitive level is not reached, paragraph 0295).
However, Matsunami does not explicitly teach; wherein the biometric information includes information on an electroencephalogram (EEG), determine a first pattern of the EEG, determine an emotional state of the passenger based on at least one of the voice, the first pattern, the second pattern, the facial image, and the text,
based on the setting of the autonomous driving level not being approved, determine whether the passenger has dementia based on the emotional state.
Shriberg teaches; determine an emotional state of the passenger based on at least one [examiner interprets this to only require one of the following] of the voice (taught as automatic speech recognition and emotion classification, paragraph 0050), the first pattern, the second pattern, the facial image, and the text,
based on the setting of the autonomous driving level not being approved, determine whether the passenger has dementia based on the emotional state (taught as a system to predict whether a subject has a behavioral or mental health state of interest based on input speech, including dementia, paragraph 0045).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to interpret emotions from input speech data as taught by Shriberg in the system taught by Matsunami in order to improve detection of behavioral/mental states of interest. Shriberg asserts that improved acoustic models assist in more specific/sensitive determinations of a behavioral or mental state of interest (paragraph 0003). As Matsunami already discloses determining whether a passenger has dementia (such as paragraph 0268), improving such diagnosis of mental impairment in general would be beneficial in preventing negative outcomes.
However, Shriberg does not explicitly teach; wherein the biometric information includes information on an electroencephalogram (EEG), determine a first pattern of the EEG.
Aluf teaches; wherein the biometric information includes information on an electroencephalogram (EEG) (taught as using EEG sensors to detect brainwave activity of a driver, paragraph 0084),
determine a first pattern of the EEG (taught as measuring the brainwave activity of the driver to determine the driver’s cognitive state, paragraph 0084).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate EEG measuring as taught by Aluf in the system taught by Matsunami in order to improve detection of mental impairment. As taught by Aluf, such systems allow for determination of cognitive states of a driver, and thus determine whether a driver is not capable of safe driving outside of direct medical conditions (paragraphs 0084-0085). To reiterate, Matsunami would be modified to include EEG biometrics as additional permissible information to regulate driving permissions.
Regarding claim 2, Matsunami as modified by Shriberg and Aluf teaches;
The vehicle control apparatus of claim 1 (see claim 1 rejection). Matsunami further teaches; wherein the processor is configured to turn off an autonomous driving function (taught as, when the permissible information is not fulfilled [less than a threshold correct answer rate, for example], paragraph 0268, where the permissible information acts as a criteria for restricting the driving of the driver, paragraph 0122) and output a warning indicating that it is impossible to drive in response to determining that the passenger has dementia (taught as outputting an alert or warning to the driver when the permissible information is not satisfied, paragraph 0155, and further only starting the engine of the vehicle when the biometric information are within permissible ranges, paragraph 0322).
Regarding claim 3, Matsunami as modified by Shriberg and Aluf teaches;
The vehicle control apparatus of claim 1 (see claim 1 rejection). Matsunami further teaches; wherein the processor is configured to output a virtual sound based on a vehicle environment in response to determining that the autonomous driving level is approved (taught as outputting a sound in response to the signal received from the criteria determination unit, paragraph 0172).
Regarding claim 4, Matsunami as modified by Shriberg and Aluf teaches;
The vehicle control apparatus of claim 3 (see claim 3 rejection). Matsunami further teaches; wherein the processor is configured to tune the virtual sound in conjunction with the biometric information (taught as outputting a sound based on the correct answer rate, paragraph 0279).
Regarding claim 9, Matsunami as modified by Shriberg and Aluf teaches;
The vehicle control apparatus of claim 1 (see claim 1 rejection). Matsunami further teaches; wherein the biometric information includes at least one of an EEG, heart rate (taught as an electrocardiograph for measuring heart rate and condition, paragraph 0234), blood pressure (taught as sensors monitoring blood pressure, paragraph 0238), breathing sound, body temperature (taught as detecting a skin temperature change, paragraph 0123), or a combination thereof.
Regarding claim 10, Matsunami as modified by Shriberg and Aluf teaches;
The vehicle control apparatus of claim 1 (see claim 1 rejection). Matsunami further teaches; wherein the first detection device includes at least one of a non-contact EEG sensor, a heart rate sensor (taught as an electrocardiograph for measuring heart rate and condition, paragraph 0234), a body temperature sensor (taught as a thermometer to measure body temperature, paragraph 0145), a blood pressure sensor (taught as sensors monitoring blood pressure, paragraph 0238), a microphone (taught as a microphone to acquire the voice of the driver, paragraph 0282), or a combination thereof.
Regarding claims 11-14 and 19, it has been determined that no further limitations exist apart from those previously addressed in claims 1-4 and 9. Therefore, claims 11-14 and 19 are rejected under the same rationale as claims 1-4 and 9 respectively.
Claim(s) 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Matsunami (US20210197832A1) as modified by Shriberg (US20220328064A1) and Aluf (US20220095975A1), and further in view of Belloni (US20190332106A1).
Regarding claim 5, Matsunami as modified by Shriberg and Aluf teaches;
The vehicle control apparatus of claim 1 (see claim 1 rejection).
Matsunami does not explicitly teach the trigger; in response to determining that the passenger does not have dementia. However, because Matsunami does not explicitly recite an order for embodiments to be performed in, and does not require extensive modification to perform, it would be a matter of simple experimentation to change the order of potential checks on mental cognition and stability (e.g., checking for dementia first, then checking for arrythmia would result in a similar outcome as the reverse scenario).
However, Matsunami does not explicitly teach; wherein the processor is configured to output a virtual sound based on an emotional state of the passenger.
Belloni teaches; wherein the processor is configured to output a virtual sound based on the emotional state of the passenger (taught as detecting a voice pattern, such as cursing indicative of potential impairment, paragraph 0066, where high levels of impairment results in an alert notification through speakers, paragraph 0094, and if its high enough, requires immediate stopping of the vehicle, paragraph 0101).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to detect other potential impairments, such as emotional, as taught by Belloni in the system taught by Matsunami in order to improve safety. As suggested by Belloni, driving when impaired is one of the most common causes of accidents (paragraph 0002), and specifically includes emotional response like cursing as an indication of impairment (paragraph 0066). To reiterate, in the system of Matsunami, when the driver passes a dementia check, other checks may be performed. One of ordinary skill in the art would think to include a more voice/emotion based check to identify mental impairment, as taught by Belloni, to address impairments not specifically covered by stricter medical diagnostics, to further improve safety on the road.
Regarding claims 15, it has been determined that no further limitations exist apart from those previously addressed in claims 5. Therefore, claims15 are rejected under the same rationale as claims 5 respectively.
Claim(s) 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Matsunami (US20210197832A1) as modified by Shriberg (US20220328064A1) and Aluf (US20220095975A1), and further in view of Doan (Predicting Dementia With Prefrontal Electroencephalography and Event-Related Potential, 2021)
Regarding claim 6, Matsunami as modified by Shriberg and Aluf teaches;
The vehicle control apparatus of claim 1 (see claim 1 rejection). Matsunami further teaches; wherein the processor is configured to: determine whether the setting of the autonomous driving level is less than or equal to a reference autonomous driving level determine not to approve autonomous driving, when the setting of the autonomous driving level is less than or equal to the reference autonomous driving level (taught as comparing [biometric] sensor values against permissible information for permitting the driver to drive a vehicle, paragraph 0122). However, Matsunami does not explicitly teach;
compare an electroencephalogram (EEG) measurement value with a predetermined reference EEG value, when a peak is detected at a specified frequency of EEG;
when a difference between the EEG measurement value and the reference EEG value is greater than or equal to a threshold.
Aluf teaches; compare an electroencephalogram (EEG) measurement value with a predetermined reference EEG value (Taught as determining EEG brain dynamics to determine driver capabilities of operating the vehicle safely and comparing to reference levels, paragraph 0084).
it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate EEG measuring as taught by Aluf in the system taught by Matsunami in order to improve detection of mental impairment. As taught by Aluf, such systems allow for determination of cognitive states of a driver, and thus determine whether a driver is not capable of safe driving outside of direct medical conditions (paragraphs 0084-0085). To reiterate, Matsunami would be modified to include EEG biometrics as additional permissible information to regulate driving permissions.
However, Aluf does not explicitly teach; compare an electroencephalogram (EEG) measurement value with a predetermined reference EEG value, when a peak is detected at a specified frequency of EEG; when a difference between the EEG measurement value and the reference EEG value is greater than or equal to a threshold.
Doan teaches; compare an electroencephalogram (EEG) measurement value with a predetermined reference EEG value, when a peak is detected at a specified frequency of EEG; when a difference between the EEG measurement value and the reference EEG value is greater than or equal to a threshold (Taught as EEG being a more effective diagnosis of early dementia than mini-mental status examinations, especially when paired with neural networks (introduction) In particular using peak frequency, “the median frequency, peak frequency, alpha-to-theta ratio, frontal asymmetry and average response time tend to be independent from the demographic risk factors and may represent risk factors of dementia.” (results, page 11)).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to analyze EEG to detect dementia for cognitive impairment as taught by Doan in the system taught by Matsunami as modified by Aluf in order to improve detection of dementia. As taught by Doan, the models and results of EEG allow for representative risk factors of dementia, independent of demographics (results).
Regarding claims 16, it has been determined that no further limitations exist apart from those previously addressed in claims 6. Therefore, claims 16 are rejected under the same rationale as claims 6.
Claim(s) 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Matsunami (US20210197832A1) as modified by Shriberg (US20220328064A1), Aluf (US20220095975A1), and Doan (Predicting Dementia With Prefrontal Electroencephalography and Event-Related Potential, 2021) and further in view of Lee (US20220032919A1) and Calza (Linguistic features and automatic classifiers for identifying mild cognitive impairment and dementia, 2020).
Regarding claim 7, Matsunami as modified by Shriberg, Aluf, and Doan teaches;
The vehicle control apparatus of claim 6 (see claim 6 rejection). Matsunami further teaches; wherein the processor is configured to:
obtain a physical parameter (taught as biometric information relating to the criteria for permitting driving, paragraph 0122, including sensors such as pulse, thermometer, paragraph 0145, etc.) based on the voice interaction (taught as analyzing the correct answer rate to questions, paragraph 0268),
determine that the setting of the autonomous driving level is less than or equal to the reference autonomous driving level (taught as comparing [biometric] sensor values against permissible information for permitting the driver to drive a vehicle, paragraph 0122),
determine not to approve autonomous driving in response to determining that the setting of the autonomous driving level is less than or equal to the reference autonomous driving level (taught as comparing [biometric] sensor values against permissible information for permitting the driver to drive a vehicle, paragraph 0122).
Matsunami does not explicitly teach; when the difference between the EEG measurement value and the reference EEG value is not greater than or equal to the threshold. However, because Matsunami does not explicitly recite an order for embodiments to be performed in, and does not require extensive modification to perform, it would be a matter of simple experimentation to change the order of potential checks on mental cognition and stability (e.g., checking for dementia first, then checking for arrythmia would result in a similar outcome as the reverse scenario).
However, Matsunami does not teach;
an emotional parameter based on the voice interaction, analyze a linguistic characteristic of the passenger based on the physical parameter and the emotional parameter;
compare the linguistic characteristic of the passenger with a linguistic characteristic of a dementia patient;
when a similarity between the linguistic characteristic of the passenger and the linguistic characteristic of the dementia patient is greater than or equal to a predetermined reference value.
Lee teaches; an emotional parameter based on the voice interaction, (taught as determining the emotion of the driver and classifying it, e.g. paragraph 0047, examples of emotions include paragraphs 0048-0052), analyze a linguistic characteristic of the passenger based on the physical parameter and the emotional parameter (taught as analyzing an emotion of the driver, e.g paragraph 0047, with voice utterance information and sensors to obtain passenger riding information, paragraph 0040)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to account for emotions of a driver as taught by Lee in the system taught by Matsunami in order to improve safety. Such a system allows chances to implement solutions to induce a change in emotion to correct potential issues with driving, as suggested by Lee (paragraph 0016).
However, Lee does not explicitly teach;
compare the linguistic characteristic of the passenger with a linguistic characteristic of a dementia patient;
when a similarity between the linguistic characteristic of the passenger and the linguistic characteristic of the dementia patient is greater than or equal to a predetermined reference value.
Calza teaches; analyze a linguistic characteristic of the passenger based on the physical parameter and the emotional parameter (taught as taking into consideration a set of acoustical, rhythmical, morpho-syntactic and lexical features to classify patients, section 2.3 Linguistic features);
compare the linguistic characteristic of the passenger with a linguistic characteristic of a dementia patient (taught as comparing the parameters and extracting features to classify patients based on the linguistic features, section 2.5 Automatic classifiers);
when a similarity between the linguistic characteristic of the passenger and the linguistic characteristic of the dementia patient is greater than or equal to a predetermined reference value (Taught as linguistic alterations being an early sign of the pathology of cognitive decline, section 1.2 Quantitative linguistic methods and NLP techniques for cognitive frailty screening, resulting in the classification of dementia, section 3 Results, e.g. page 15).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate linguistic checks as taught by Calza in the system taught by Matsunami in order to improve dementia detection. As suggested by Calza, speech screening allows one to distinguish between controls and mild cognitive impairment/dementia (section 1.2 Quantitative linguistic methods and NLP techniques for cognitive frailty screening). Thus, one of ordinary skill in the art would find it obvious to incorporate additional diagnostic techniques to determine driver impairment, such as in the system taught by Matsunami, for better accuracy and redundancy.
Regarding claims 17, it has been determined that no further limitations exist apart from those previously addressed in claims 7. Therefore, claims 17 are rejected under the same rationale as claims 7.
Claim(s) 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Matsunami (US20210197832A1) as modified by Shriberg (US20220328064A1), Aluf (US20220095975A1), and Doan (Predicting Dementia With Prefrontal Electroencephalography and Event-Related Potential, 2021), and further in view of Kundu (US20180312167A1).
Regarding claim 8, Matsunami as modified by Shriberg, Aluf, and Doan teaches;
The vehicle control apparatus of claim 6 (see claim 6 rejection). Matsunami further teaches; wherein the processor is configured to: detect an arrhythmia pattern based on a heart rate signal (taught as detecting arrhythmias with electrocardiographic information and heart rate, paragraph 0233), and
determine whether to approve the reference autonomous driving level (taught as comparing [biometric] sensor values against permissible information for permitting the driver to drive a vehicle, paragraph 0122).
Matsunami does not explicitly teach the trigger conditions/order of steps such that sensing is performed; when the peak is not detected at the specific frequency of the EEG; and when the arrhythmia pattern and the breathing instability are detected. However, because Matsunami does not explicitly recite an order for embodiments to be performed in, and does not require extensive modification to perform, it would be a matter of simple experimentation to change the order of potential checks on mental cognition and stability (e.g., checking for dementia first, then checking for arrythmia would result in a similar outcome as the reverse scenario).
However, Matsunami does not explicitly teach; detect breathing instability based on a breathing rate and a breathing sound; determine whether to approve the reference autonomous driving level based on the result of comparing the EEG measurement value with the reference EEG value.
Aluf teaches; compare the EEG measurement value with a reference EEG value (Taught as determining EEG brain dynamics to determine driver capabilities of operating the vehicle safely and comparing to reference levels, paragraph 0084).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate EEG measuring as taught by Aluf in the system taught by Matsunami in order to improve detection of mental impairment. As taught by Aluf, such systems allow for determination of cognitive states of a driver, and thus determine whether a driver is not capable of safe driving outside of direct medical conditions (paragraphs 0084-0085). To reiterate, Matsunami would be modified to include EEG biometrics as additional permissible information to regulate driving permissions.
However, Aluf does not explicitly teach;. detect breathing instability based on a breathing rate and a breathing sound.
Kundu teaches; detect breathing instability based on a breathing rate and a breathing sound (taught as determining a breathing pattern, which is used to classify a user condition, paragraph 0020).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to detect breathing conditions of a driver as taught by Kundu in the system taught by Matsunami in order to improve safety. As suggested in Kundu,, breathing pattern information can assist in determining a likely physical condition of a vehicle operator (paragraph 0020), and be used to assess and address potential abnormalities or emergencies (paragraph 0021). This would benefit the system of Matsunami, as Matsunami already include the physical components (electrodes) required (paragraph 0118), and would then be able to further predict driver states with additional/redundant techniques.
Regarding claims 18, it has been determined that no further limitations exist apart from those previously addressed in claims 8. Therefore, claims 18 are rejected under the same rationale as claims 8.
Response to Arguments
Applicant argues on page 8 of the remarks that the amendments to the claims overcome the 101 rejection.
The examiner agrees and withdraws the rejection, as noted above.
Applicant argues on pages 10-11 of the remarks that the recited prior art does not teach the amended material regarding detecting an emotional state based on voice speech data.
The examiner agrees that Matsunami does not explicitly teach determining the emotional state of a user based on voice/speech data, and withdraws the previous rejection. However, a new rejection in light of Shriberg has been presented above to address emotional classification and dementia diagnosis from speech recognition and emotional classification (paragraphs 0045, 0050 for example). As Matsunami teaches acquiring the voice emitted by the driver and recognizing the answer from the voice data (paragraph 0282), one of ordinary skill in the art would recognize the combination to improve speech recognition and emotional classification for analysis.
Furthermore, the argument that Shriberg does not teach operational steps to determine emotional steps is unpersuasive, as the claim language only suggests that at least one of “the voice, the first pattern, the second pattern, the facial image, and the text” is used to determine an emotional state, not how such a state is determined. As Shriberg suggests the detection of mental state, such as determining dementia, based on voice input (one of the suggested inputs in the claim language), Shriberg is seen to adequately teach such a limitation.
However, the examiner does agree that neither Matsunami nor Shriberg explicitly teaches the use of EEG, and thus withdraws the previous rejection. However, a new rejection in light of Aluf has been made above to rectify the deficiencies of Matsunami and Shriberg. [The examiner also notes that Westbrook also satisfies the deficient material, and is noted below].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
For further cognitive response tests; US20210291650A1
For further emotion prediction and breathing patterns; US20190038201A1 and US20190307388A1, and US20190056731A1
In particular, US20190056731A1 teaches relevant material regarding EEG and emotional states, such as; wherein the biometric information includes information on an electroencephalogram (EEG) (taught as using EEG sensors to detect brainwave activity of a driver, paragraph 0030), for the purposes of determining a driver emotional state.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GABRIEL ANFINRUD whose telephone number is (571)270-3401. The examiner can normally be reached M-F 9:30-5:30.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jelani Smith can be reached at (571)270-3969. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/GABRIEL ANFINRUD/Examiner, Art Unit 3662
/JELANI A SMITH/Supervisory Patent Examiner, Art Unit 3662