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 .
Claim Rejections - 35 USC § 103
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.
Claim(s) 1, 6, 10, 11-13, 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Marquette et al. (DE-102015122245-A1), and further in view of Kollegger et al. (US-20140046546-A1).
Regarding claim 1, Marquette teaches one or more processors comprising one or more processing units to:
receive image sensor data comprising an image sequence representing an occupant of a machine (“The eyelid movement and/or the pupil movement can then be evaluated by an evaluation unit of the camera system with regard to the degree of fatigue of the driver,” Para [0019]);
generate a drowsiness score indication (“degree of fatigue”) associated with the occupant (”the condition describing the degree of fatigue is determined, in particular continuously, during the operation of the motor vehicle by means of the condition monitoring device,” Para [0007]) based at least on by an evaluation unit of the camera system with regard to the degree of fatigue of the driver,” Para [0019]);
and adjust an operation of the machine based at least on the drowsiness score indication (“If the degree of fatigue falls below the fatigue threshold to such an extent that it can no longer be assumed that the driver is able to operate the motor vehicle safely. Thus… the switch to autonomous driving operation of the motor vehicle is also carried out,” Para [0012]).
Marquette fails to teach the following limitations as further claimed. However, Kollegger further teaches:
compute a drowsiness score estimate for the occupant (Kollegger, “the tiredness value (KSS) is calculated using the formula KSS-10.9-0.6(S+C+U)… C denotes the circadian rhythm over a period of 24 hours, which characterises the biological sleep pattern,” Para [0057]) based at least on correlating a circadian rhythm process to the occupant (Kollegger, Equation for C in Para 0017);
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and generate a drowsiness score indication (Marquette, “degree of fatigue”) associated with the occupant (Marquette, “the condition describing the degree of fatigue is determined, in particular continuously, during the operation of the motor vehicle by means of the condition monitoring device,” Para [0007]) based at least on the drowsiness score estimate (Kollegger, “the tiredness value (KSS) is calculated using the formula KSS-10.9-0.6(S+C+U),” Para [0057]).
Kollegger is considered to be analogous to the claimed invention because they are both in the same field of vehicles that track driver tiredness using circadian rhythm. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have incorporated the teachings of Kollegger into Marquette for the benefit of a more accurate reading of driver’s tiredness, and thus reducing false positive alerts of tiredness/wakefulness.
Regarding claim 6, the rejection of claim 1 is incorporated herein. Marquette in view of Kollegger teaches the one or more processors of claim 1, and Kollegger further teaches determine the drowsiness score estimate based at least on an alertness value corresponding to a position on the circadian rhythm process (Fig. 3, with the KSS value representing “predicted tiredness values,” Para [0055]) and is based on the circadian rhythm curve “C”), the position determined based at least on a time of day (“FIG. 3 shows how S, C and U vary over a period of approximately 36 hours,” Para [0080]).
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have incorporated the teachings of Kollegger into Marquette for the benefit of a more accurate reading of driver’s tiredness, regardless of the time of day or the driver’s schedule.
Regarding claim 10, the rejection of claim 1 is incorporated herein. Marquette in view of Kollegger teaches the one or more processors of claim 1, and Marquette further teaches:
predict the inferred drowsiness score of the occupant determined from the image sensor data (“it may be provided that the condition describing the degree of fatigue of the driver is determined by means of a camera system,” Para [0019]) based at least on at least one of: an eye blink rate, an eye blink velocity, an eye blink amplitude, a time of eye closure, a head pose, an eye gaze direction (“measure metrics such as eyelid opening or gaze direction,” Para [0019]), or a pattern of yawning behavior.
Regarding claim 11, the rejection of claim 1 is incorporated herein. Marquette in view of Kollegger teaches the one or more processors of claim 1, and Kollegger further teaches wherein the circadian rhythm process corresponds to a circadian rhythm process C curve (“The process C thus represents the body's biological clock, the circadian rhythm, and is modelled using a sine wave,” Para [0017]; see also Fig. 3 in curve “C” for a visual representation).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have incorporated the teachings of Kollegger into Marquette for the benefit of more accurate level of fatigue estimations/calculations.
Regarding claim 12, the rejection of claim 1 is incorporated herein. Marquette in view of Kollegger teaches the one or more processors of claim 1, and Marquette further teaches wherein the one or more processors are comprised in at least one of:
a control system for an autonomous or semi-autonomous machine (“If the degree of fatigue falls below the fatigue threshold to such an extent that it can no longer be assumed that the driver is able to operate the motor vehicle safely. Thus… the switch to autonomous driving operation of the motor vehicle is also carried out,” Para [0012]);
a perception system for an autonomous or semi-autonomous machine;
a system for performing simulation operations;
a system for performing digital twin operations; a system for performing light transport simulation;
a system for performing collaborative content creation for three-dimensional assets;
a system for performing deep learning operations;
a system for performing remote operations;
a system for performing real-time streaming;
a system for generating or presenting one or more of augmented reality content, virtual reality content, or mixed reality content;
a system implemented using an edge device;
a system implemented using a robot; a system for performing conversational AI operations;
a system implementing one or more language models;
a system implementing one or more large language models (LLMs);
a system for generating synthetic data; a system for generating synthetic data using AI;
a system incorporating one or more virtual machines (VMs);
a system implemented at least partially in a data center;
or a system implemented at least partially using cloud computing resources.
(Examiner’s Note: Claim 12 as recited is treated as a “field of use” or “intended use” limitation
and therefore carries no patentable weight although it has been examined in view of the combination of Marquette in view of Kollegger above. The processor(s) as recited has/have been examined as evidenced in claim 1 above. With respect to the enumerated environments that said processor(s) is/are “comprised in”, the specification as disclosed merely mentions these environments as preferred intended use environments without specific details that warrant said processor(s) comprised in these environments resulted in a novel and non-obvious structural change to the processor(s). Reference to MPEP 2112.01 is also made for applicant’s attention.)
Claims 13, 19, and 20 are system or method claims that correspond to the processor claims 1 and 12. The claims are thus rejected for the same reasons as claims 1 and 12.
Claim(s) 2 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Marquette et al. (DE-102015122245-A1) in view of Kollegger et al. (US-20140046546-A1) as applied to claims 1 and 13 above, and further in view of Stiller et al. (US-20200317211-A1).
Regarding claim 2, the rejection of claim 1 is incorporated herein. Marquette in view of Kollegger teaches the one or more processors of claim 1, but fails to teach the following limitations as further claimed. Stiller, however, further teaches:
output the drowsiness score estimate as the drowsiness score indication based at least on determining that the inferred drowsiness score is anomalous (“control unit 100 is designed advantageously to determine the validities of the results, in order to give less weight to or even to rule out such poor or falsified results in determining a final result,” Para [0044], where the results are “results of drowsiness-detection devices 135, 145, 155 [that] have the highest validities,” Para [0046]).
Stiller is considered to be analogous to the claimed invention because they are both in the same field of detecting a driver’s drowsiness levels in a vehicle. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have incorporated the teachings of Stiller into Marquette and Kollegger for the benefit of more accurate drowsiness detections and/or less missed detections of drowsiness.
Claim 14 is a system claim that corresponds to processor claim 2. The claim is thus rejected for the same reasons as claim 2.
Claim(s) 3 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Marquette et al. (DE-102015122245-A1) in view of Kollegger et al. (US-20140046546-A1) as applied to claims 1 and 13 above, and further in view of Hiles (US-10235859-B1).
Regarding claim 3, the rejection of claim 1 is incorporated herein. Marquette in view of Kollegger teach the one or more processors of claim 1, but fail to teach the following limitations as further claimed. However, Hiles further teaches:
compute the drowsiness score indication based at least on combining the inferred drowsiness score with the drowsiness score estimate using a smoothing algorithm (Col. 13, lines 4-13 and 19-23, “the data interpreter 208 may be configured to collectively interpret the received data 140, 142, 142, 145, 148, 149 to determine, detect, and/or predict a drowsy or sleepy driving condition of the user 110… the data interpreter 208 may perform one or more data transformations 208b of the data 140, 142, 145, 148, 149, e.g., to standardized data element names and data values from various data sources 202, to smooth received data over time”).
Hiles is considered to be analogous to the claimed invention because they are both in the same field of detecting drowsy drivers. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have incorporated the teachings of Hiles into Marquette and Kollegger for the benefit of removing unneeded noise in the varied sensor data.
Claim 15 is a system claim that corresponds to processor claim 3. The claim is thus rejected for the same reasons as claim 3.
Claim(s) 4-5, 7, and 16-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Marquette et al. (DE-102015122245-A1) in view of Kollegger et al. (US-20140046546-A1) as applied to claims 1 and 13 above, and further in view of Kaplan et al. (US-20160071393-A1).
Regarding claim 4, the rejection of claim 1 is incorporated herein. Marquette in view of Kollegger teaches the one or more processors of claim 1, where Marquette teaches:
predict the inferred drowsiness score based at least on the image sensor data (“The eyelid movement and/or the pupil movement can then be evaluated by an evaluation unit of the camera system with regard to the degree of fatigue of the driver,” Para [0019]).
Marquette in view of Kollegger fails to teach the following limitations as further claimed. However, Kaplan teaches:
predict the inferred drowsiness score based at least on at least one personal calibration parameter (“user’s distal skin temperature”) derived from the circadian rhythm process (“the measurements of a user's distal skin temperature can be used to accurately estimate the user's personal circadian rhythm by correlating the distal skin temperature with core body temperature, which follows the circadian rhythm of the user,” Para [0057]).
Kaplan is considered to be analogous to the claimed invention because they are in the same field of monitoring alertness of a person in a vehicle or elsewhere. Therefore, it would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to have incorporated the teachings of Kaplan into Marquette and Kollegger for the benefit of more accurate alertness monitoring, and/or the reduction of false positives of said monitoring.
Regarding claim 5, the rejection of claim 4 is incorporated herein. Marquette in view of Kollegger and Kaplan teach the one or more processors of claim 4, and Kollegger further teaches:
reference the at least one personal calibration parameter (“inter alia information about driving and rest times for the driver”) from a memory based at least on determining an identity associated with the occupant (Kollegger, “The vehicle further comprises a driver's card input unit 8 adapted to generate a driver's card signal 10 containing inter alia information about driving and rest times for the driver,” Para [0052]).
It would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to have incorporated the teachings of Kaplan into Marquette and Kollegger for the benefit of more accurate alertness monitoring, and/or the reduction of false positives of said monitoring.
Regarding claim 7, the rejection of claim 1 is incorporated herein. Marquette in view of Kollegger teaches the one or more processors of claim 1, and Kollegger further teaches determine the drowsiness score estimate based at least on an alertness value corresponding to a position on the circadian rhythm process (Fig. 3, with the KSS value representing “predicted tiredness values,” Para [0055]) and is based on the circadian rhythm curve “C”), the position determined based at least on a time of day (“FIG. 3 shows how S, C and U vary over a period of approximately 36 hours,” Para [0080]).
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Marquette in view of Kollegger fail to teach the following limitations as further claimed. However, Kaplan further teaches:
determine the drowsiness score estimate (This provides a model of alertness levels for the user”) based at least on an alertness value corresponding to a position on the circadian rhythm process, the position determined based at least on a time of day (Fig. 2, x-axis) and sensor data (“a user's distal skin temperature can be used to accurately estimate the user's personal circadian rhythm”) representing sleep information measured from the occupant (“Therefore, the measurements of a user's distal skin temperature can be used to accurately estimate the user's personal circadian rhythm by correlating the distal skin temperature with core body temperature, which follows the circadian rhythm of the user. This provides a model of alertness levels for the user,” Para [0057]).
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It would have been obvious to one of ordinary skill in the art before the effective fling date of the claimed invention to have incorporated the teachings of Kaplan into Marquette and Kollegger for the benefit of more accurate alertness monitoring, and/or the reduction of false positives of said monitoring.
Claims 16 and 17 are system claims that correspond to processor claims 4 and 7. The claims are thus rejected for the same reasons as claim 4 and 7.
Claim(s) 8-9 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Marquette et al. (DE-102015122245-A1) in view of Kollegger et al. (US-20140046546-A1) as applied to claims 1 and 13 above, and further in view of Palshof et al. (US-20120133515-A1).
Regarding claim 8, the rejection of claim 1 is incorporated herein. Marquette in view of Kollegger teaches the one or more processors of claim 1, and Kollegger further teaches determine the drowsiness score estimate based at least on an alertness value corresponding to a position on the circadian rhythm process (Fig. 3, with the KSS value representing “predicted tiredness values,” Para [0055]) and is based on the circadian rhythm curve “C”), the position determined based at least on a time of day (“FIG. 3 shows how S, C and U vary over a period of approximately 36 hours,” Para [0080]).
Marquette in view of Kollegger fail to teach the following limitations as further claimed. However, Palshof further teaches:
the position determined based at least on
Palshof is considered to be analogous to the claimed invention because they are in the same field of monitoring driver fatigue in a vehicle. Additionally, despite the questionnaire not being related to the position on a circadian rhythm curve, asking an occupant to answer a questionnaire with sleep-related questions would achieve the same result as in claim 7, where position on a circadian rhythm can be determined based on distal skin temperature measured by a sensor. This is due to the fact that “hours of sleep last night compared to a normal night, hours awake before this drive, use of medicine, intake of alcohol”, and other questions related to sleep do affect sleep, and therefore will disrupt or change a person’s personal circadian rhythm. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have incorporated the teachings of Palshof into Marquette and Kollegger for the benefit of more accurate circadian rhythm readings and fewer false positives in regards to whether a driver is fatigued or not.
Regarding claim 9, the rejection of claim 1 is incorporated herein. Marquette in view of Kollegger teach the one or more processors of claim 1, and Kollegger further teaches:
compute one or more corrections to the inferred drowsiness score based at least on an alertness value corresponding to a position on the circadian rhythm process (Kollegger, Fig. 3, Circadian rhythm “C” affects “KSS” (Karolinska Sleepiness Scale), or a tiredness value).
Kollegger fails to teach the following limitations as further claimed. Palshof, however, further teaches:
compute one or more corrections to the inferred drowsiness score based at least on time-on-task data associated with the occupant operating the machine (“The fatigue factors also referred to as fatigue data affecting the fatigue level FL of a person… such as e.g. time since the last rest, total amount of driving time, time of the day/night, reaction time, etc,” Para [0148]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have incorporated the teachings of Palshof into Marquette and Kollegger for the benefit of more accurate degree of fatigue readings.
Claim 18 is a system claim that corresponds to processor claim 8. The claim is thus rejected for the same reasons as claim 8.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Omi (US-20100090839-A1) teaches an apparatus for estimating whether a state of a driver is normal or abnormal.
Reifman (US-20240199061-A1) teaches a method for advising a driver of a vehicle to take driving breaks using circadian rhythm.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RACHEL A OMETZ whose telephone number is (571)272-2535. The examiner can normally be reached 6:45am-4:00pm ET Monday-Thursday, 6:45am-1:00pm ET every other Friday.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vu Le can be reached at 571-272-7332. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Rachel Anne Ometz/ Examiner, Art Unit 2668 1/13/26
/VU LE/ Supervisory Patent Examiner, Art Unit 2668