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 § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an
abstract idea without significantly more. Claim 1 recite an apparatus with instructions for performing operations of the device comprising:
determine whether a brain wave of the user corresponds to a sleep wave or an awake wave;
classify a sleep state of the user as one of a plurality of categories by comparing the determination result with sensor data wherein the sensor data is time synchronized to the EEG signal;
To determine whether a claim satisfies the criteria for subject matter eligibility, the claim is
evaluated according to a stepwise process as described in MPEP 2106(III) and 2106.03-2106.05. The instant claims are evaluated according to such analysis.
Step 1: Is the claim to a process, machine, manufacture or composition of matter?
Claim 1 is directed to an apparatus with instructions to perform the steps thus meet the
requirements for step 1.
Step 2A (Prong 1): Does the claim recite an abstract idea, law of nature, or natural
phenomenon?
Claim 1 recite an apparatus with instructions for performing operations of the device comprising:
determine whether a brain wave of the user corresponds to a sleep wave or an awake wave;
classify a sleep state of the user as one of a plurality of categories by comparing the determination result with sensor data wherein the sensor data is time synchronized to the EEG signal;
If a claim limitation, under its broadest reasonable interpretation, covers performance of the
limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Therefore, claim 1 recite an abstract idea of a mental process.
Claim 1 recite the abstract idea of a mental process. The limitations as drafted in the
claims, under its broadest reasonable interpretation, covers performance of the claimed steps in the mind, but for the recitation of a generic processor. Other than reciting a generic processing system and memory, nothing in the elements of the claims precludes the step from practically being performed in the mind or manually by a clinician. For example:
“Determine whether a brain wave of the user corresponds to a sleep wave or an awake wave;” A physician may observe brain wave data and determine which waves corresponds to a sleep wave or an awake wave.
“Classify a sleep state of the user as one of a plurality of categories by comparing the determination result with sensor data wherein the sensor data is time synchronized to the EEG signal;” A physician may compare sensor data and determination results to classify a sleep state of a patient. A physician may also timestamp sensor data collected manually to an EEG signal.
Furthermore claims 2-4 and 6-8 recite additional steps that can be manually performed by the
Clinician.
Claim 2
“determine whether the sensor data corresponds to an activity posture or a lie- down posture, and classify the sleep state of the user;” A physician may determine a posture of a patient based on sensor data and observational data.
Claim 3
“classify the sleep state of the user as one of the plurality of states during a time interval between a first time point corresponding to an entry to sleep of the user and a second time point corresponding to exiting sleep of the user and provide a result sequence of the state classification over time as a sleep monitoring result of the user.” A physician may classify different states between different time points based on observational analysis and using manual sensors. Classifying the entry and exiting of sleep may be done manually as discussed.
Claim 4
“classify the sleep state of the user as one of the plurality of states at a predetermined cycle during the time interval.” A physician may set a predetermined cycle and use it to classify the sleep state of the user during the time interval.
Claim 6
“when the sleep state of the user is classified as one of the plurality of states at the predetermined cycle, segment one cycle into a plurality of time segments, determine the sleep state of the user corresponding to each time segment as one of the plurality of states using the sensor data for each of the plurality of time segments, and determine a major state that forms the majority for the cycle to be a representative state of the cycle.” A physician may classify a plurality of states at the predetermined cycle and segment one cycle into a plurality of time segments. A physician may then determine a major state based on the majority/frequency at each time segment.
Claim 7
“provide a sleep quality index corresponding to a ratio of a sum of intervals classified as the lie-down posture and sleep wave state (SS) to an entirety of the time intervals, based on the classification result.” A physician may provide a sleep metric value based on a ratio of a sum of intervals posture, sleep state, and classification result.
Claim 8
“when classifying: after the activity posture and awake wave state (AA) changes to the lie-down posture and awake wave state (SA), in case of a first change from the lie- down posture and awake wave state (SA) to the lie-down posture and sleep wave state (SS), when the EEG signal is a non-rapid eye movement (REM) level 2 sleep state, classify the sleep state of the user as the lie-down posture and sleep wave state (SS).” A physician may make classification analysis based on changes of posture and sleep state.
Step 2A (Prong 2): Does the claim recite additional elements that integrate the judicial
exception into a practical application?
Claims 1 and 9-11 recite the additional elements of a “a processor”, “activity sensor”, “microphone” and “expansion electrode” which are being interpreted as a processor of a data gathering device.
The activity sensor, microphone, and expansion electrodes are recited as pre-solution activity to collect motion sensor data, EEG data, and sound data.
However, these elements are recited at a high level of generality performing the function of generic data processing such that they amount to no more than mere instructions to simply implement the abstract idea using generic computer components. See MPEP 2106.05(b) and (f).
Accordingly, the additional elements do not integrate the abstract idea into a practical
application.
Step 2B: Does the claim recite additional elements that amount to significantly more than the
judicial exception?
The additional elements when considered individually and in combination are not enough to
qualify as significantly more than the abstract idea.
The activity sensor, microphone, and expansion electrodes are recited as pre-solution activity to collect motion sensor data, EEG data, and sound data.
As discussed above with respect to integration of the abstract idea into a practical application, “a processor”, “activity sensor”, “microphone” and “expansion electrode” which are being interpreted as a processor of a data gathering device as recited to perform the steps of:
determine whether a brain wave of the user corresponds to a sleep wave or an awake wave;
classify a sleep state of the user as one of a plurality of categories by comparing the determination result with sensor data wherein the sensor data is time synchronized to the EEG signal;
amount to no more than mere instructions to apply the exception using generic computer
components. Mere instructions to apply an exception using generic components cannot provide an inventive concept. These additional elements are well‐understood, routine (For example LIM KYUNG SOO et al. KR Pub.: KR 20200033522 A hereinafter Soo) teaches a data gathering device with a processor, and conventional limitations that amount to mere instructions or elements to implement the abstract idea. In addition, the end result of the system/method, the essence of the whole, is a patent-ineligible concept. Therefore, the claims are not patent eligible.
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.
Claims 1-5 and 8-10 are rejected under 35 U.S.C. 103 as being unpatentable by LIM KYUNG
SOO et al. KR Pub.: KR 20200033522 A hereinafter Soo in view of STOCHHOLM et al.: Automatic sleep stage classification using ear-EEG. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Pp. 4751-4754, 16, August 2016, hereinafter Stochholm.
Regarding claim 1, Soo teaches a user sleep monitoring device, the sleep monitoring device (110) comprising: a communication interface (35) (fig. 1; paragraph 35);
and a processor, wherein the processor is configured to determine whether a brain wave of the user corresponds to a sleep wave or an awake wave using an electroencephalogram (EEG) signal measured by an EEG measurement unit of an wearable device worn by the user (fig. 1; paragraph 35 and 112); A microprocessor is disclosed. Biosignals collected during a sleep study of a group estimated to be in the REM sleep period can be used as a label indicating REM sleep. Biosignals collected during the corresponding period of a group estimated to be in the non-REM sleep period can be utilized as a label indicating non-REM sleep. Different weights based on criteria can be assigned to the EMG, safety, EEG, ECG, and EMG signals for each sleep cycle.
and classify a sleep state of the user as one of a plurality of categories by comparing the determination result with sensor data measured by an activity sensor comprised in the wearable device, wherein the sensor data is time synchronized to the EEG signal (fig. 1; paragraph 35, 60, 82 and 112); A motion sensor that senses the movement of the wearer and acts as an activity sensor used in combination with EEG data to classify a sleep state of the user. It is disclosed that base station can synchronize and aggregate the pair of biosignal data to generate one biosignal data set.
However, Soo does not explicitly teach a plurality of categories for classifying sleep state.
Stochholm, in the same field of endeavor, teaches a plurality of categories for classifying sleep state (page 4751; right column, lines 16-17). Sleep can be divided into 5 stages: Wake, REM, N1, N2, and N3.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the classification of sleep from Soo to include the 5 sleep stages from Stochholm for the benefit of accurately identifying the closest sleep state of the patient.
Regarding claim 2, Soo in view of Stochholm teaches the claimed invention and Soo further
teaches wherein the processor is configured to determine whether the sensor data measured by the activity sensor corresponds to an activity posture or a lie-down posture, and classify the sleep state of the user as one of a plurality of states comprising:
1) lie-down posture and sleep wave state (SS);
2) activity posture and awake wave state (AA);
3) lie-down posture and awake wave state (SA);
4) activity posture and sleep wave state (AS).
Status measurement data may include patient posture, which can be used in combination with the sleep wave data collected by EEG to classify the sleep state of the user (paragraph 84 and 103).
Regarding claim 3, Soo in view of Stochholm teaches the claimed invention and Soo further
teaches wherein the processor is configured to continuously classify the sleep state of the user as one of the plurality of states during a time interval between a first time point corresponding to an entry to sleep of the user and a second time point corresponding to exiting sleep of the user and provide a result sequence of the state classification over time as a sleep monitoring result of the user (fig. 1; paragraph 40). The wearable device (110) must be capable of continuous operation for 9 hours before and after human sleep
Regarding claim 4, Soo in view of Stochholm teaches the claimed invention and Soo further
teaches wherein the processor is configured to classify the sleep state of the user as one of the plurality of states at a predetermined cycle during the time interval (fig. 1; paragraph 101 and 112). The control unit, which comprises the microprocessor, may execute a sleep monitoring application to display a sleep state of a patient at a sleep pattern or cycle during a time interval.
Regarding claim 5, Soo in view of Stochholm teaches the claimed invention and Soo further
teaches wherein the processor is configured to, when the sleep state of the user is classified as one of the plurality of states at the predetermined cycle, apply a smoothing filter to remove an outlier from at least one piece of the sensor data measured by the activity sensor and the EEG signal within a cycle and determine the sleep state of the user corresponding to the cycle to be one of the plurality of states (paragraph 36 and 112). A filter module that removes noise that includes any outlier from the sensor data and/or EEG signal. A sleep state is determined at a predetermined cycle for a plurality of states.
Regarding claim 8, Soo in view of Stochholm teaches the claimed invention and Soo further
teaches wherein the processor is configured to, when classifying: after the activity posture and awake wave state (AA) changes to the lie-down posture and awake wave state (SA), in case of a first change from the lie-down posture and awake wave state (SA) to the lie-down posture and sleep wave state (SS), when the EEG signal is a non-rapid eye movement (REM) level 2 sleep state, classify the sleep state of the user as the lie-down posture and sleep wave state (SS) (paragraph 84 and 103). Status measurement data may include patient posture, which can be used in combination with the sleep wave data collected by EEG to classify the sleep state of the user. A lie-down posture and awake wave state may be detected using the activity sensor and the EEG signals from the device. Therefore, a detection of change for both posture and wave state is disclosed. A sleep state classification based on these changes may be done.
Regarding claim 9, Soo in view of Stochholm teaches the claimed invention and Soo further
teaches wherein the sensor data measured by the activity sensor comprises: a direction sensing value that determines whether the user raises or lays down their head while wearing the wearable device on the ear; and an acceleration sensing value that determines whether the user moves at a predetermined level or more while wearing the wearable device on the ear, and wherein the processor is configured to temporarily defer the classification when the acceleration sensing value indicates the state in which the user moves at the predetermined level or more (paragraph 60). A gyrosensor measure a change in rotational angle, which equates to a directional measurement. An acceleration sensor is further disclosed.
Regarding claim 10, Soo in view of Stochholm teaches the claimed invention and Soo further
teaches wherein the processor sleep monitoring device is configured to further receive a sound collected through a microphone of the wearable device and when the sound corresponds to snoring, distinguish whether the sound is snoring of the user or snoring of other surrounding person using the acceleration sensing value (paragraph 77, 82-86, 94, 101, and 104-105).
Claims 6-7, and 11 are rejected under 35 U.S.C. 103 as being unpatentable by Soo in view of
Stochholm in view of Burton US Pub.: US 20210169417 A1.
Regarding claim 6, Soo in view of Stochholm does not teach wherein the processor is configured
to, when the sleep state of the user is classified as one of the plurality of states at the predetermined cycle, segment one cycle into a plurality of time segments, determine the sleep state of the user corresponding to each time segment as one of the plurality of states using the sensor data measured by the activity sensor and the EEG signal for each of the plurality of time segments, and determine a major state that forms the majority for the cycle to be a representative state of the cycle.
Burton, in the same field of endeavor, teaches wherein the processor is configured
to, when the sleep state of the user is classified as one of the plurality of states at the predetermined cycle, segment one cycle into a plurality of time segments, determine the sleep state of the user corresponding to each time segment as one of the plurality of states using the sensor data measured by the activity sensor and the EEG signal for each of the plurality of time segments, and determine a major state that forms the majority for the cycle to be a representative state of the cycle (paragraph 270 and 3271). The monitoring system provides continuous EEG monitoring with associated analysis capable of the determination of epoching (time period segmentation) and epoch-based sleep stages (i.e. such as but not limited to wake, N1, N2, N3, REM). Epilepsy can be more predominant in certain sleep states so be enabling the present invention to define events of interest by wake or sleep state (i.e. stage N1, N2, N3 or REM) and biomarker events or clusters of biomarkers can provide a more patient-specific and accurate prognostic or diagnostic capability.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the classification of sleep from Soo in view of Stochholm to include the segmentation and detection for sleep state majority step from Burton for the benefit of providing a more patient-specific and accurate prognostic or diagnostic capability for sleep disorders of a patient.
Regarding claim 7, Soo in view of Stochholm does not teach wherein the processor is configured
to provide lie-down posture and sleep wave state (SS) to an entirety of the time intervals, based on the classification result (paragraph 84 and 103). Status measurement data may include patient posture, which can be used in combination with the sleep wave data collected by EEG to classify the sleep state of the user.
Burton, in the same field of endeavor, teaches wherein the processor is configured to provide a
sleep quality index corresponding to a ratio of a sum of intervals classified as the lie-down posture and sleep wave state (SS) to an entirety of the time intervals, based on the classification result (paragraph 4417). An index for sleep quality at different criteria’s such as arousal, respiratory, and RERA are disclosed.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the classification of sleep from Soo in view of Stochholm to include the sleep quality index from Burton for the benefit of enabling a subject or subject's health carer enhanced information access for improved sleep management.
Regarding claim 11, Soo in view of Stochholm does not teach wherein wearable device is
configured to measure the user's EEG signal through an expansion electrode attached to the user's forehead.
Burton, in the same field of endeavor, teaches wherein wearable device is configured to
measure the user's EEG signal through an expansion electrode attached to the user's forehead (paragraph 142). The headband sensor is capable of continuous monitoring of sleep parameters (EEG, EOG, EMG).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the sensor device from Soo in view of Stochholm to add the headband expansion electrode from Burton for the benefit of accurately determining brain signals with the closest proximity to the brain.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to THIEN J TRAN whose telephone number is (571)272-0486. The examiner can normally be reached M-F. 8:30 am - 5:30 pm.
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, Benjamin Klein can be reached at 571-270-5213. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/T.J.T./Examiner, Art Unit 3792
/Benjamin J Klein/Supervisory Patent Examiner, Art Unit 3792