Prosecution Insights
Last updated: April 19, 2026
Application No. 17/652,189

PROFICIENCY DETERMINATION APPARATUS, METHOD, AND NON TRANSITORY COMPUTER READABLE MEDIUM

Final Rejection §101§103§112
Filed
Feb 23, 2022
Examiner
NEAL, ALLISON MICHELLE
Art Unit
3625
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Kabushiki Kaisha Toshiba
OA Round
4 (Final)
19%
Grant Probability
At Risk
5-6
OA Rounds
4y 2m
To Grant
46%
With Interview

Examiner Intelligence

Grants only 19% of cases
19%
Career Allow Rate
42 granted / 224 resolved
-33.2% vs TC avg
Strong +27% interview lift
Without
With
+27.4%
Interview Lift
resolved cases with interview
Typical timeline
4y 2m
Avg Prosecution
20 currently pending
Career history
244
Total Applications
across all art units

Statute-Specific Performance

§101
37.3%
-2.7% vs TC avg
§103
34.8%
-5.2% vs TC avg
§102
9.6%
-30.4% vs TC avg
§112
14.1%
-25.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 224 resolved cases

Office Action

§101 §103 §112
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 . DETAILED ACTION The following is a Final Office action. In response to communications received 7/28/2025, Applicant, on 10/28/2025, amended claims 1 and 7, 9 and 14-15. Claims 5 and 12-13 are canceled. Claims 1, 7-11 and 14-15 are pending. Response to Amendment Applicant’s amendments have been considered; however, the 101 rejection remains and is updated below. With respect to Applicant’s amendments and arguments, have been considered. However, the 103 rejection remains and is updated below. Response to Arguments With respect to the 101 rejection, Applicant argues that the amended claim language “makes it clear that the claim cannot practically be considered as covering a method of organizing a human activity” because the determination of “a proficiency of the worker based on the acquired data of at least two separate sensors, improves upon the technological environment for solving this problem” (See Remarks at pg. 9). However, Examiner respectfully disagrees. Applicant further describes the claimed invention by stating the claims define “determining the proficiency of a worker engaged in a technical work in a factory or the like is important to perform training or education necessary to a worker (beginner) having a low proficiency. Accordingly, it is desirable to determine the proficiency about the quality evaluation ability of a worker. However, this ability depends on the subjective recognition of a worker” (See Remarks at pg. 9). The determination of worker proficiency through evaluating the quality of ability of a worker is a method of organizing human activity. The use of separate sensors to acquire worker information recite mere instances of data gathering. Courts have noted that mere data gathering and outputting (e.g. displaying obtained display data) have been found to be insignificant extra-solution activity (See also MPEP 2106.05(h) and Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) whereas). Furthermore, the claim(s) does/do not include additional elements that are sufficient to practically apply the judicial exception, as argued on pg. 9 of Applicant’s Remarks. When the additional elements are taken separately or as a whole, they merely use conventional computer components or technology to receive, process, store and display data and thus do not provide an inventive concept in the claims. See the updated 101 rejection below. With respect to the 103 rejection, Applicant argues that the amended claims, requiring “determine a proficiency of the worker based on whether the frequency in the checking zone when the product is defective is not less than a threshold” is not taught by the previously cited references (See Remarks at pgs. 10-11). Examiner notes that this argument is now moot, as the 103 rejection is now rejected by Fujita et al. (United States Patent Application Publication, 2022/0101224, hereinafter referred to as Fujita) in view of Baek et al. (United States Patent Application Publication, 2022/0237537, hereinafter referred to as Baek) in further view of Ariyama et al. (United States Patent Application Publication, 2022/0409129, hereinafter referred to as Ariyama) in even further view of Ibanez et al. (United States Patent Application Publication, 2011/0028857, hereinafter referred to as Ibanez). See the update 103 rejection below. 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. Claim 15 is 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. The term “controlling detecting, by a working condition sensor that is one or a motion sensor or an image sensor, a working condition of a worker” in claim 15 is an unclear term which renders the claim indefinite. The term “controlling detecting, by a working condition sensor that is one or a motion sensor or an image sensor, a working condition of a worker” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Examiner notes that it is unclear if the claimed working condition sensor is performing the action of controlling or detecting. For purposes of examination, Examiner will interpret the claim of performing the action of “detecting.” 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 therefore, subject to the conditions and requirements of this title. Claims 1, 7-11 and 14-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-patentable subject matter. The claims are directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. In accordance with Step 1, it is first noted that the claimed apparatus in claims 1 and 7-11; the claimed method in claim 14 and the claims non-transitory computer readable medium in claim 15 are directed to a potentially eligible category of subject matter (i.e., processes, machine etc.). Thus, Step 1 is satisfied with respect to claims 1, 7-11 and 14-15. In accordance with Step 2A, Prong One, claims 1, 7-11 and 14-15, the claimed invention recites an abstract idea. Specifically, the independent claim(s) recite(s) (abstract idea recited in italics and additional elements recited in bold): Claim 1 A proficiency determination system comprising: a working condition sensor, that is one of a motion sensor or an image sensor, configured to detect a working condition of a worker; a biological sensor configured to attach to a body surface of the worker; and a processing circuit configured to: acquire data from the working condition sensor and determine a predetermined period when the worker is performing work based on the acquired data; acquire, from the biological sensor attached to a body surface of the worker, first time-series data about biological information of the worker in the predetermined period and a checking zone in which the worker checks the quality of a product during the predetermined period; calculate second time-series data about a physiological index indicating a mental stress on the worker by analyzing the first time-series data; calculate a frequency of a local maximum of the physiological index by analyzing the second time-series data; and determine a proficiency of the worker based on whether the frequency in the checking zone when the product is defective is not less than a threshold. Claim 14: A proficiency determination method comprising: detecting, by a working condition sensor that is one of a motion sensor or an image sensor, a working condition of a worker; acquiring data from the working sensor and determining a predetermined period when the worker is performing work based on the acquired data; acquiring, from a biological sensor attached to a body surface of the worker, first time-series data about biological information of the worker in the predetermined period and a checking zone in which the worker checks the quality of a product during the predetermined period; calculating second time-series data about a physiological index indicating a mental stress on the worker by analyzing the first time-series data; calculating a frequency of a local maximum of the physiological index by analyzing the second time-series data; and determining a proficiency of the worker based on whether the frequency in the checking zone when the product is defective is not less than a threshold. Claim 15 A non-transitory computer readable medium including computer executable instructions, wherein the instructions, when executed by a processor, cause the processor to perform a method comprising: controlling detecting, by a working condition sensor that is one of a motion sensor or an image sensor, a working condition of a worker; acquiring data from the working condition sensor and determining a predetermined period when the worker is performing work based on the acquired data; acquiring, from a biological sensor attached to a body surface of the worker, first time-series data about biological information of the worker in the predetermined period and a checking zone in which the worker checks the quality of a product during the predetermined period; calculating second time-series data about a physiological index indicating a mental stress on the worker by analyzing the first time-series data; calculating a frequency of a local maximum of the physiological index by analyzing the second time-series data; and determining a proficiency of the worker based on whether the frequency in the checking zone when the product is defective is not less than a threshold. The above-recited limitations viewed as an abstract idea are certain methods of organizing human activity (i.e., fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)) and mental processes (i.e., concepts performed in the human mind (including an observation, evaluation, judgment, opinion)). Specifically, the claimed invention recites steps for determining the proficiency of a worker by analyzing the physiological data of a worker, which is a certain method of organizing human activity. The analysis of the proficiency determination of a worker is performed evaluating a physiological index of a worker by observing the biological information, which is a mental process. According to Step 2A, prong two, this judicial exception is not integrated into a practical application because the use of bolded additional elements for receiving/transmitting data (e.g., “acquire data from the working condition sensor and determine a predetermined period when the worker is performing work based on the acquired data; acquire, from the biological sensor attached to a body surface of the worker, first time-series data about biological information of the worker in the predetermined period and a checking zone in which the worker checks the quality of a product during the predetermined period;” etc.); processing data (e.g., “calculate second time-series data about a physiological index indicating a mental stress on the worker by analyzing the first time-series data; calculate a frequency of a local maximum of the physiological index by analyzing the second time-series data; and determine a proficiency of the worker based on whether the frequency in the checking zone when the product is defective is not less than a threshold;” etc.); storing data; displaying data and repeating steps is merely implementing the abstract idea steps of valuing an idea in the manner of “apply it”. The claim(s) does/do not include additional elements that are sufficient to practically apply the judicial exception because they, whether taken separately or as a whole, merely use conventional computer components or technology to receive, process, store and display data and thus do not provide an inventive concept in the claims. It is to be noted that the additional elements “a proficiency determination system comprising: a working condition sensor, that is one of a motion sensor or an image sensor, configured to detect a working condition of a worker; a biological sensor configured to attach to a body surface of the worker; and a processing circuit” and “a biological sensor attached to a body surface of the worker” perform mere data gathering steps whereas information is merely acquired to implement the abstract idea of analyzing the proficiency of a worker. Examiner notes that steps that amount to mere data gathering or data output (e.g. “acquiring data from the working condition sensor and determining a predetermined period when the worker is performing work based on the acquired data; acquiring, from a biological sensor attached to a body surface of the worker, first time-series data about biological information of the worker in the predetermined period and a checking zone in which the worker checks the quality of a product during the predetermined period;” etc.) have been found to be insignificant extra-solution activity (See MPEP 2106.05(g)). The acquired worker data performed by the additional elements above is then used to calculate time-series data and a frequency of a local maximum to determine a proficiency of a worker. The claimed limitations present mere data gathering in a manner similar to the court provided example, OIP Technologies, 788 F.3d at 1363, 115 USPQ2d at 1092-93 (See MPEP 2106.05(g)). In accordance with Step 2B, the claims only recite the above bolded additional elements. The additional elements are recited at a high-level of generality (i.e., as a generic computer performing generic computer operations for determining the proficiency of a worker) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Further, as evidence of generic computer implementation and an indication that the claimed invention does not amount to significantly more, it is first noted in the Applicant’s Specification at page 41 that “the proficiency determination apparatus 1 includes a processing circuit 10, a memory 11, a display 12, a speaker 13, an input interface 14, and a communication interface 15. These components are connected by a bus as a common signal transmission path such that they can communicate with each other. Each component need not be implemented by one hardware. For example, at least two components can also be implemented by one hardware. The processing circuit 10 controls the operation of the proficiency determination apparatus 1. The processing circuit 10 includes a processor such as a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or a GPU (Graphics Processing Unit) as hardware.” As additional evidence of conventional computer implementation, it is noted in the MPEP, the courts have recognized that additional elements that “receive or transmit data over a network, e.g., using the Internet to gather data” (e.g. “acquiring data from the working condition sensor and determining a predetermined period when the worker is performing work based on the acquired data; acquiring, from a biological sensor attached to a body surface of the worker, first time-series data about biological information of the worker in the predetermined period and a checking zone in which the worker checks the quality of a product during the predetermined period”) and “performing repetitive calculations to be well‐understood, routine, and conventional functions” when they are claimed in a merely generic manner (See MPEP 2106.05(d)). See also MPEP 2106.05(h) and Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) whereas mere data gathering and outputting have been found to be insignificant extra-solution activity. Therefore, “a working condition sensor, that is one of a motion sensor or an image sensor, configured to detect a working condition of a worker; a biological sensor configured to attach to a body surface of the worker; and a processing circuit” and “a biological sensor attached to a body surface of the worker” perform mere data gathering steps of “acquiring” biological information and image information, respectively. From the interpretation of the MPEP and the Specification, one would reasonably deduce that the additional elements are merely embodies generic computers and generic computing functions. With respect to the dependent claims, claim 7 recite (abstract idea recited in italics and additional elements recited in bold): The system according to claim 1, a camera configured to capture an image of the worker and acquire image information indicating an action of the worker in the predetermined period, where the processing circuit is further configured to: analyze the image information and specify time period in which the worker takes a specific action or posture in a working zone, cause a display to display display data obtained by relating at least one of the first time series data, the second time series data, the frequency, and the proficiency of the worker to the image information, and cause the display to display the display data of a past work of the worker or another worker in relation to the display data of a current work of the worker. The additional elements “a camera configured to capture an image of the worker and acquire image information indicating an action of the worker in the predetermined period” perform mere data gathering steps whereas information is merely acquired. As described above, the courts have recognized that mere instances of data gathering performed by an additional element result in an insignificant extra solution activity. See the Step 2A prong 2 and Step 2B above. The additional elements, “a processing circuit” and “cause a display to display,” identified in the dependent claims above recite additional instances of generic computer components that implement the generic computing functions of displaying to provide a data output. These additional elements fail to practically apply the judicial exception. Also, the above additional elements are specified at a high level of generality. In accordance with the evidence provided in the above step 2B section, the additional elements recited in the dependent claims are well-understood, routine and conventional and do not amount to significantly more. Aside from the additional elements identified in claim 7 above, the dependent claims 8-11 recite elements that narrow the metes and bounds of the abstract idea of collecting and analyzing worker information to analyze proficiency, but do not provide ‘something more’. Specifically, claim 8 recites limitations reciting data gathering and outputting. Claim 9 recites limitations of outputting analyzed worker information. Claim 10-11 recites limitations that further describe the type of information included in the physiological index provided from the analyzed worker information. These dependent claims do not remedy these deficiencies. 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. This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. Claim(s) 1, 7-11 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Fujita et al. (United States Patent Application Publication, 2022/0101224, hereinafter referred to as Fujita) in view of Baek et al. (United States Patent Application Publication, 2022/0237537, hereinafter referred to as Baek) in further view of Ariyama et al. (United States Patent Application Publication, 2022/0409129, hereinafter referred to as Ariyama) in even further view of Ibanez et al. (United States Patent Application Publication, 2011/0028857, hereinafter referred to as Ibanez). As per Claim 1, Fujita discloses a proficiency determination system comprising a processing circuit configured to: A biological sensor configured to attach to a body surface of the worker (Fujita: See ¶0176 where the biometric data of the worker is obtained by a wearable device.); and A processing circuit configured to: acquire data from the… sensor and determine a predetermined period when the worker is performing work based on the acquired data (Fujita: See ¶0181-0182 and Fig. 17 where the obtained sensed acceleration data determines whether the worker is working in a predetermined period.); Acquire, from a biological sensor attached to a body surface of a worker, first time-series data about biological information of the worker in the predetermined period, and a checking zone in which the worker checks quality of a product during the predetermined period (Fujita: ¶0058-0059: A first time-series data acquired is biometric data, such as heart rate (cardiac cycle), a pulse rate, a nictation rate, an ocular potential, a line of sight, a body surface temperature, a core body temperature, a blood pressure, a respiration rate, a sweat rate, a skin potential, or the like of the worker. See ¶0176 where the biometric data of the worker is obtained by a wearable device. See ¶0071 where time-series data is acquired in a predetermined time period (e.g., 30min, 1, min). See ¶0122-0123 where the time series data can be acquired when the worker is in the inspection (i.e., checking) zone. See ¶0101-0103 where defective rate is computed for the production time for each work and used to determine the proficiency of a worker during their working time based on the average of the time-series data. Examiner notes that the defective rate is rate at which the quality of a product is defective based on the proficiency of the worker.); Calculate… maximum of the physiological index by analyzing the second time-series data (Fujita: ¶0104-0108: An average value, a maximum value, and a minimum value of the nictation rate within a certain time interval on the basis of the time series data is calculated. See also Fig. 6 for physiological index information. Examiner notes that the appearance condition is the frequency or magnitude of a parameter including a local maximum, a local minimum, a mean, a dispersion, a fluctuation, a global maximum, a global minimum, a differential value, and an integral value (See Applicant’s Specification at pg. 7).); and determine a proficiency of the worker based on whether the… [maximum]… in the checking zone and when the product is detective is not less than a threshold (Fujita: ¶0108-0110: A work efficiency and concentration level can be calculated from the average value, a maximum value, and a minimum value of the nictation rate within a certain time interval on the basis of the time series data is calculated. See also Fig. 6 for physiological index information. See ¶0117-0118 where based on the condition of work efficiency and concentration levels, a proficiency of a worker is determined. See Fig. 13 where the workers levels are determined in the inspection (i.e., checking) zone. See ¶0101-0103 where defective rate is computed for the production time for each work and used to determine the proficiency of a worker during their working time based on the average of the time-series data. Examiner notes that the defective rate is rate at which the quality of a product is defective based on the proficiency of the worker.); Fujita discloses biometric sensors to acquire worker information including worker motion. Fujita does not explicitly disclose; however, Baek discloses: A working condition sensor, that is one of a motion sensor or an image sensor configured to detect a working condition of a worker (Baek: See ¶0040 where the imaging sensor captures images of a worker performing a task.); and acquire data from the working condition sensor (Baek: See ¶0040 where the imaging sensor captures images of a worker performing a task.); It would have been obvious to one of ordinary skill in the before the effective filing date of the claimed invention to combine Fujita with Baek’s assessment of physiological data of a worker because the references are analogous/compatible since each is directed toward analyzing worker data to determine the condition of a worker, and because incorporating Baek’s assessment of physiological data of a worker in Fujita would have served Fujita’s pursuit of acquiring biometric information on a living body of the worker to estimate a mental/physical condition of a worker (See Fujita Abstract); and further obvious since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Fujita discloses the calculation of a first and second time series of biometric and production data of the worker. Fujita does not explicitly disclose; however, Ariyama discloses: calculate second time-series data about a physiological index indicating a mental stress on the worker by analyzing the first time-series data (Ariyama: ¶0057-0059: A LF/HF parameter is obtained based on the analysis of the biometric (e.g., fluctuation value of a heart rate estimated from electrocardiogram data, a fluctuation value of a pulse rate or a respiratory rate calculated by estimation from the pulse wave data) time-series data. The value of the LF/HF parameter is a measure that determines if the individual is stressed. Examiner notes that Applicant’s Specification at pg. 7 recites that the physiological index is the LF/HF ratio.); It would have been obvious to one of ordinary skill in the before the effective filing date of the claimed invention to combine Fujita with Ariyama’s time series data used for calculating mental stress because the references are analogous/compatible since each is directed toward analyzing time-series data to determine the mental condition of a person, and because incorporating Ariyama’s time series data used for calculating mental stress in Fujita would have served Fujita’s pursuit of analyzing time-series data of a worker to estimate a mental/physical condition of a worker (See Fujita Abstract); and further obvious since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Fujita discloses calculating maximum of physiological time series data. Fujita does not explicitly disclose; however, Ibanez discloses: calculate a frequency of a local maximum of the physiological index by analyzing the second time-series data (Ibanez: ¶0035-0039: Determining an individual’s state of attention by analyzing an individual’s respiratory levels. See ¶0064-0068 where the evaluation calculation includes calculating a frequency of a local maximum.); determine a proficiency of the worker based on whether the frequency (Ibanez: ¶0035-0039: Determining an individual’s state of attention by analyzing an individual’s respiratory levels. See ¶0064-0068 where the evaluation calculation includes calculating a frequency of a local maximum.); It would have been obvious to one of ordinary skill in the before the effective filing date of the claimed invention to combine Fujita with Ibanez’s calculation of an individual’s physiological index because the references are analogous/compatible since each is directed toward analyzing time-series data to determine the mental condition of a person, and because incorporating Ibanez’s calculation of an individual’s physiological index in Fujita would have served Fujita’s pursuit of analyzing time-series data of a worker to estimate a mental/physical condition of a worker (See Fujita Abstract); and further obvious since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Claims 14 and 15 recite limitations already addressed by the rejection of claim 1; therefore, the same rejection applies. As per Claim 7, Fujita in view of Ariyama in further view of Baek in even further view of Ibanez discloses the apparatus according to claim 1, wherein the processing circuit is further configured to… cause a display to display display data obtained by relating at least one of the first time series data, the second time series data, the frequency, and the proficiency of the worker to the image information, and cause the display to display the display data of a past work of the worker or another worker in relation to the display data of a current work of the worker (Fujita: See Figs. 9-10 of first and second time series data displayed. See Fig. 21 and ¶0209 where the display data presents past work of the worker in relation to their current work to indicate the effective changes in concentration level.). Fujita does not explicitly disclose; however, Baek discloses a camera configured to capture an image of the worker and acquire image information indicating an action of the worker in the predetermined period, wherein the processing circuit is further configured to analyze image information and specify a time period in which the worker takes a specific action or posture in a working zone (Baek: See ¶0094-0099 where images captured of a worker indicate joint posture information in predetermined minute periods according to the captured frame. See also ¶0040 where the analysis of the images identifies the worker’s tasks performed.); It would have been obvious to one of ordinary skill in the before the effective filing date of the claimed invention to combine Fujita with Baek’s assessment of physiological data of a worker because the references are analogous/compatible since each is directed toward analyzing worker data to determine the condition of a worker, and because incorporating Baek’s assessment of physiological data of a worker in Fujita would have served Fujita’s pursuit of acquiring biometric information on a living body of the worker to estimate a mental/physical condition of a worker (See Fujita Abstract); and further obvious since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. As per Claim 8, Fujita in view of Ariyama in further view of Baek in even further view of Ibanez discloses the system according to claim 1, wherein the processing circuit is further configured to: acquire improvement proposal information for proposing a method of improving the action of the worker in the predetermined period, and cause a reporting unit to report the improvement proposal information to the worker (Fujita: ¶0169-0171: The appearance condition of the physiological index is computed of the worker and transmitted via the notification unit. The notification unit can notify a manager of a proposed work assignment that can improve the accuracy of the physiological index of the worker. See ¶0146 where the notification unit is displayed on a display monitor.). As per Claim 9, Fujita in view of Ariyama in further view of Baek in even further view of Ibanez discloses the system according to claim 8, wherein the processing circuit is configured not to cause the reporting unit to report the improvement proposal information when the proficiency of the worker is not less than the threshold, and configured to cause the reporting unit to report the improvement proposal information when the proficiency of the worker is less than the threshold (Fujita: ¶0165-0169 and 0171: The worker efficiency information is compared against a threshold value a reported to a notification unit for the development of proposed work assignment information to improve the estimation accuracy of the mental and physical condition.). As per Claim 10, Fujita in view of Ariyama in further view of Baek in even further view of Ibanez discloses the system according to claim 1, wherein the biological information or the physiological index is information about an NN interval, an electrodermal activity, perspiration, a blood flow, a body temperature, or a brain wave (Fujita: ¶0058-0059: A first time-series data acquired is biometric data, such as heart rate (cardiac cycle), a pulse rate, a nictation rate, an ocular potential, a line of sight, a body surface temperature, a core body temperature, a blood pressure, a respiration rate, a sweat rate, a skin potential, or the like of the worker. See ¶0104-0108 for an example of a physiological index calculated of the above information.). As per Claim 11, Fujita in view of Ariyama in further view of Baek in even further view of Ibanez discloses the system according to claim 1, wherein the physiological index is an LF/HF (Low Frequency/High Frequency) ratio, an LF (Low Frequency) value, an HF (High Frequency) value, a VLF (Very Low Frequency) value, a total power value, an HR (Heart Rate) value, a Mean NN (Mean of NN intervals) value, an SDNN (Standard Deviation of NN intervals) value, an RMSSD (Root Mean Square of Successive Differences) value, an NN50 (total number of heartbeats for which successive differences exceed 50 ms) value, a pNN50 (ratio of heartbeats for which successive differences exceed 50 nms) value, or a CVRR (Coefficient of Variation of R-R Interval) value related to the NN interval (Fujita: See Fig. 2 for heart rate values. Also see ¶0058-0059: A first time-series data acquired is biometric data, such as heart rate (cardiac cycle), a pulse rate, a nictation rate, an ocular potential, a line of sight, a body surface temperature, a core body temperature, a blood pressure, a respiration rate, a sweat rate, a skin potential, or the like of the worker. See ¶0104-0108 for an example of a physiological index calculated of the above information.). Conclusion THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALLISON MICHELLE NEAL whose telephone number is (571)272-9334. The examiner can normally be reached 9-2pm ET, M-F. 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, Brian Epstein can be reached at 5712705389. 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. /ALLISON M NEAL/Primary Examiner, Art Unit 3625
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Prosecution Timeline

Feb 23, 2022
Application Filed
Sep 07, 2024
Non-Final Rejection — §101, §103, §112
Feb 10, 2025
Response Filed
Feb 25, 2025
Final Rejection — §101, §103, §112
May 22, 2025
Request for Continued Examination
May 25, 2025
Response after Non-Final Action
Jul 24, 2025
Non-Final Rejection — §101, §103, §112
Oct 22, 2025
Applicant Interview (Telephonic)
Oct 22, 2025
Examiner Interview Summary
Oct 28, 2025
Response Filed
Mar 12, 2026
Final Rejection — §101, §103, §112 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

5-6
Expected OA Rounds
19%
Grant Probability
46%
With Interview (+27.4%)
4y 2m
Median Time to Grant
High
PTA Risk
Based on 224 resolved cases by this examiner. Grant probability derived from career allow rate.

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