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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 2, 4 –7, 9, 12, 14, 16, 17, 19 – 22, 24, 25, 27, 29, and 31 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. With regard to claim 1, although the preamble indicates the claim is drawn to a “system” only a single element is positively claimed (“a processing circuitry”); a system, by definition, necessarily requires plural components. As such, it is unclear what constitutes the claimed system, since the elements defining the system are not clearly indicated. Additionally, with regard to claim 1, it is unclear what is intended by indicating that the prediction, which would be understood to refer to a future status, “is indicative of” properties of the measured signal which are from a current or past state, as an animal that is predicted to have death occur within a certain time duration, for example, would not have temperature variations as described once death has happened. Similar issues are raised with regard to claims 9, 16, 24, and 31, which also indicate the prediction “is indicative of” certain signal properties.
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, 4 –7, 9, 12, 14, 16, 19 – 22, 24, 25, 27, 29, and 31 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) processing circuitry configured to perform certain functions, corresponding methods, and a computer readable medium containing the corresponding executable code thereon (which are each within a statutory category of invention) to “analyze” received data and “predict” based on the analysis, which falls in the category of a mental process (see MPEP 2106.04(a)(2)III.). These judicial exceptions are not integrated into a practical application because with regard to Revised step 2A, an exception is present as noted, and with regard to Revised step 2B, the claim does not recite additional elements that integrate the judicial exception into a practical application. In particular, based on the high level of generality/nominal nature of “provide a monitored record” (Examiner notes that the method is performed by a computer accessing data, but the sensor structures do not provide positively claimed details) and “notify a user” to providing an output of the results of use of the judicial exception, one must conclude that these recitations do not impose a meaningful limitation onto the claim scope, as the limitations do not constitute use of the exception in the context of “a particular machine”. Instead, their high level of generality merely points to a generalized pre-processing data gathering and a post-processing data outputting being undertaken. Likewise, the claim(s) does/do not include additional elements/steps that are sufficient to amount to significantly more than the judicial exception because the high level and broad renditions regarding any sensors and generic providing of an indication indicate that no specific sensors or outputting devices are required. Further, the dependent claims generally relate to further aspects of the judicial exceptions, and thus also fail to provide details to integrate the exceptions into a practical application.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 4 - 7, 9, 16, 19 – 22, 24, 25, and 31 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Webster et al. (USPGPub 2016/0037755 – cited by Applicant). Webster et al. teaches a system and method for automated monitoring of ruminant health and breeding, which relies upon measurement of temperature (or other vital sign) for, among other things, analysis/prediction of Health Results of the monitored animal.
As per claim 1, Webster et al. discloses a system for predicting an illness, death or other abnormal condition of a monitored animal (an automated system for obtaining early detection of biological changes or events by assessing core body temperatures that precede the events within individual animals in a production herd; an assessment establishes variations from the baseline, compensates for ambient conditions or identifies patterns of variation, that anticipate estrus, ovulation, illness, calving or other biological events throughout the herd population; paragraph [0012]), the system comprising a processing circuitry configured to:
provide a monitored record for the monitored animal (computer processing and software may be employed to accumulate and store the data, read or assess the bolus data sensed, and may employ algorithms that establish a baseline temperature for the individual animal; paragraph [0013]), the monitored record including a monitored temperature time series of monitored temperature values that are indicative of a temperature of the monitored animal over a given time period (individual animal core body temperature over a predetermined time period; paragraphs [0033], [0126]);
analyze the monitored temperature time-series (the temperature values over the time period are analyzed; paragraphs [0126]-[0127]);
predict (Examiner notes that the metes and bounds of the “predict” process are unclear, in view of the rejections under 35 USC 112(b) as detailed above; Webster et al. is considered to meet the limitations, as best understood in light of the rejection) the illness, death or other abnormal condition of the monitored animal within a given time duration of the given time period, based on the analysis (the monitoring may comprise identifying a temperature variation threshold and/or a pattern of a temperature variation as a condition related to a function of illness; identify patterns of variation, that anticipate illness; paragraphs [0012]; [0126]-[0127]), wherein the monitored temperature time-series is a temperature pattern that includes two or more cycles (the monitored temperature includes a diurnal (cycle) baseline for each animal over a number of days, and thus will comprise a temperature pattern that includes two or more cycles; paragraphs [0025], [0096], [0126], [0134]), each cycle of the cycles being defined by a distance between a given peak of the temperature pattern and a successive peak of the temperature pattern, successive to the given peak, or alternatively, a distance between a given valley of the temperature pattern and a successive valley of the temperature pattern, successive to the given valley (the monitored temperature includes a diurnal baseline for each animal over a number of days, and thus will comprise cycles being defined by a distance between a given peak of the temperature pattern and a successive peak of the temperature pattern, successive to the given peak, or alternatively, a distance between a given valley of the temperature pattern and a successive valley of the temperature pattern, successive to the given valley; paragraphs [0025], [0096], [0126], [0134]); and
notify a user of the system of the prediction (the system monitors the animals, assess the data acquired, and provides a timely communication to owners and operators as deemed appropriate. An assessment may establish a baseline temperature for each animal, and monitor the variations from the baseline, or patterns of variation, that identify or anticipate illness; paragraph [0012]).
Using the system in its intended manner, one would necessarily perform the method steps of Claim 16. Additionally, one in possession of the system of claim 1 would also be in possession of the non-transitory computer readable medium having the details as set forth in claim 31.
As per claim 4 and parallel method claim 19, Webster et al. further discloses wherein, for each cycle of the cycles, a temperature difference between a peak temperature value of the monitored temperature values in the respective cycle and a valley temperature value of the monitored temperature values in the respective cycle is greater than or equal to a predetermined difference (the system detects diurnal temperature cycles, which includes difference between a daily maximum temperature and a daily minimum temperature of the animal, and comparing the animal data record of read temperature to a baseline diurnal value and, given that difference, signal disease when that difference falls outside a threshold parameter; paragraphs [0126), [0134], [0139]).
As per claim 5 and parallel method claim 20, Webster et al. further discloses wherein the predetermined difference is at least 4 °C (the system detects diurnal temperature cycles, which includes the difference between a maximum temperature and a minimum daily temperature of the animal, and comparing the animal data record of read temperature to a baseline diurnal value and, given that difference, signal disease when that difference falls outside a threshold parameter, and so is capable of having a difference of a least 4 °C; paragraphs [0126], [0134], [0139]).
As per claim 6 and parallel method claim 21, Webster et al. further discloses wherein the given time period is two to five days (data from the past five days is analyzed for a pattern occurring at a predetermined frequency; paragraph [0096]).
As per claim 7 and parallel method claim 22, Webster et al. further discloses wherein the given time duration is two months or less (these alerts permit early awareness for physical observation of the cow for the following 3 to 4 days to pick up early clinical symptoms; paragraph [0084]).
As per claim 9 and parallel method claim 24, Webster et al. further discloses wherein the processing circuitry is further configured to: determine, for each cycle of the cycles, whether the peak temperature value for the respective cycle is greater than or equal to a temperature threshold (after a baseline is established, the default setting may be revised to a high alert temperature of 105.5° F. or 40.8° C; paragraph [0090]); wherein the predict is indicative of a number of the cycles for which the peak temperature value is greater than or equal to the temperature threshold being greater than or equal to a predefined number (an alert is only created once a specific percentage of temperature points are outside of the set temperature parameters over a specific period of time; paragraphs [0055], [0084], [0097]).
Claim(s) 1, 2, 12, 14, 16, 17, 27, and 29 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Singh et al. (USPGPub 2019/0053470 – cited by Applicant).
As per claim 1, Singh et al. discloses a system for predicting an illness, death or other abnormal condition of a monitored animal (a system for tracking, analyzing, and diagnosing the health of an individual animal or an animal population and for communicating the likelihood of illness of one or more members of the given animal population; paragraph [0027]), the system comprising a processing circuitry configured to:
provide a monitored record for the monitored animal (processor 130 to receive raw data from one or more tag assemblies 102 of the animal population; paragraph [0055]), the monitored record including a monitored temperature time series of monitored temperature values that are indicative of a temperature of the monitored animal over a given time period (the raw data comprises temperatures for a given time period; paragraphs [0056], [0079], [00801);
analyze the monitored temperature time-series (the temperature readings are analyzed; paragraph [0071]);
predict (Examiner notes that the metes and bounds of the “predict” process are unclear, in view of the rejections under 35 USC 112(b) as detailed above; Singh et al. is considered to meet the limitations, as best understood in light of the rejection) the illness, death or other abnormal condition of the monitored animal within a given time duration of the given time period, based on the analysis (determine if an animal is healthy, sick, diseased, or showing early warning signs of sickness based on analysis of the temperature data; paragraph [0071]); and
notify a user of the system of the prediction (tracking, analyzing, and diagnosing the health of an individual animal or an animal population and for communicating the likelihood of illness of one or more members of the given animal population; paragraph [0027]).
Using the system in its intended manner, one would necessarily perform the method steps of Claim 16.
As per claim 2 and parallel claim 17, Singh et al. further discloses wherein the processing circuitry is configured to analyze the monitored temperature time series using a Machine Learning "ML" model (the temperatures are analyzed using a machine learning model; paragraph [0078]), the ML model being trained based on a data repository of historical records for a plurality of animals (train a machine learning classifier using datasets taken from animals with known physiological and behavioral characteristics; paragraphs [0066], [0182]), each historical record of the historical records including: A) a historical temperature time series of historical temperature values that are indicative of the temperature of a respective animal of the plurality of animals over an earlier time period (temperature readings obtained from animals with known bacterial infections may be used to train the machine learning classifier; wherein the data is obtained over a given time period; paragraphs [0171], [0172], [0182]), being earlier than and of an identical duration to the given time period (the animal's average historical temperature readings are determined as an average for the same selected time period for which the one or more temperature readings are being collected; paragraphs [0193]-[0194]), and B) a target field that indicates whether the respective animal became ill, died, or developed any other abnormal condition within the given time duration of the earlier time period (temperature readings obtained from animals with known bacterial infections may be used to train the machine learning classifier; paragraph [0182]).
As per claim 12 and parallel claim 27, Singh et al. further discloses wherein the monitored record includes a monitored acceleration time series of monitored acceleration values over the given time period (the record includes a monitored acceleration time series of monitored acceleration values over the given time period; paragraph [0087]), the given time period including a plurality of identical and consecutive sub-periods (the acceleration is monitored between the hours of 1 AM and 2AM to obtain a historical acceleration metric; paragraphs [0087], [0193]), and each monitored acceleration value of the monitored acceleration values being indicative of an acceleration of the monitored animal over a respective sub-period of the sub-periods (the monitored acceleration metric is indicative of the acceleration of the animal over the time period; paragraphs [0087]. [0193], [0194]), wherein the processing circuitry is further configured to: determine the monitored acceleration values in the monitored acceleration time-series that are less than or equal to an acceleration threshold (temperature readings above a certain temperature and movement readings below a certain level may be associated with an infected animal; paragraphs [0066], [0087]); and wherein the predict is also based on a determination that at least a predefined percentage of the monitored acceleration values are less than or equal to the acceleration threshold (movement readings below a certain level are associated with an infected animal, the average time the head tilt is above/below a particular threshold may be used to determine the health state of the animal; paragraphs [0066], [0125]).
As per claim 14 and parallel claim 29, Singh et al. further discloses wherein the processing circuitry is further configured to: provide historical acceleration values for one or more animals (historical acceleration values of the animals; paragraph [0087]), each historical acceleration value of the historical acceleration values being indicative of the acceleration of a respective animal of the one or more animals over a second respective sub-period (the historical acceleration values being indicative of the acceleration of a respective animal of the one or more animals over a period of 1AM-2AM; paragraphs [0087], [0193]), being earlier than and of an identical duration to the respective sub-period (the historical acceleration values will inherently be earlier than the respective sub-period; paragraph [0087]); and determine the acceleration threshold, based on the historical acceleration values (the acceleration threshold is based on the historical acceleration values; paragraphs [0087], [0193]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ERIC FRANK WINAKUR whose telephone number is (571)272-4736. The examiner can normally be reached Mon-Fri 9 am - 6 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, Chuck Marmor, II can be reached at 571-272-4730. 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.
/ERIC F WINAKUR/Primary Examiner, Art Unit 3791