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 .
Status of Claims
Claims 1-20 are currently pending and have been examined.
Claims 1-20 have been rejected.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed for parent Application No. JP2021-122300, filed on 16 January 2024.The instant application therefore claims the benefit of priority under 35 U.S.C 119(a)-(d). Accordingly, the effective filing date for the instant application is 27 July 2021 claiming benefit to JP2021-122300.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f):
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f). The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f), is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f). The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
acquisition unit (claims 1 and 19) – see the instant specification in ¶ 0016 defining the unit as a sensor device and as hardware or software or a combination thereof in ¶ 0030
analysis unit (claims 1, 4, 8, 9, 10, 15, and 19) see the instant specification in ¶ 0018 defining the unit as a software algorithm for analyzing the data on a processor and as hardware or software or a combination thereof in ¶ 0030
generation unit (claims 1, 2, 3, 4, and 5) see the instant specification in ¶ 0025 and ¶ 0027 defining the unit as a part of a server and as a software algorithm for generating a medication amount as hardware or software or a combination thereof in ¶ 0030
storage unit (claim 16) see the instant specification in ¶ 0020 defining the unit as a computer memory for storing data and as hardware or software or a combination thereof in ¶ 0030
display information generation unit (claim 17) see the instant specification in ¶ 0029 defining the unit as a software unit for generating display data and as hardware or software or a combination thereof in ¶ 0030
display unit (claim 18) see the instant specification in ¶ 0023 defining the unit as a display device
The disclosure provides that the device for the units may be implemented in software and/or hardware. Therefore, these claim limitations will be interpreted to be a hardware AND software computer program product stored on a memory (see MPEP § 2181(II)(B) wherein when the supporting disclosure for a computer-implemented invention discusses the implementation of the functionality of the invention through hardware, software, or a combination of both, a question can arise as to which mode of implementation supports the means-plus-function limitation. The language of 35 U.S.C. 112(f) requires that the recited "means" for performing the specified function shall be construed to cover the corresponding "structure or material" described in the specification and equivalents thereof. Therefore, by choosing to use a means-plus-function limitation and invoke 35 U.S.C. 112(f) applicant limits that claim limitation to the disclosed structure, i.e., implementation by hardware or the combination of hardware and software, and equivalents thereof. Therefore, the examiner should not construe the limitation as covering pure software implementation).
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f), it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f), applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f).
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 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e. a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1 – Statutory Categories of Invention:
Claims 1-20 are drawn to a system, apparatus, or method which are statutory categories of invention.
Step 2A – Judicial Exception Analysis, Prong 1:
Independent claim 1 recites a system for information processing in part performing the steps of acquire medication action information regarding a medication action of a patient; analyze the medication action information and captures a plurality of predetermined actions related to medication execution; and recognize the medication execution based on the plurality of predetermined actions and generate medication information regarding the medication execution.
Independent claim 19 recites an apparatus for information processing in part performing the steps of acquire medication action information regarding a medication action of a patient; and analyze the medication action information and captures a plurality of predetermined actions related to medication execution.
Independent claim 20 recites a method for information processing in part performing the steps of acquire medication action information regarding a medication action of a patient; and analyze the medication action information and capture a plurality of predetermined actions related to the medication execution.
These steps of gathering patient action data, analyzing said data, and displaying an action recommendation regarding a medication amount to methods of organizing human activity which includes functions relating to interpersonal and intrapersonal activities, such as managing relationships or transactions between people, social activities, and human behavior (MPEP § 2106.04(a)(2)(II)(C) citing the abstract idea grouping for methods of organizing human activity for managing personal behavior or relationships or interactions between people similar to iii. a mental process that a neurologist should follow when testing a patient for nervous system malfunctions, In re Meyer, 688 F.2d 789, 791-93, 215 USPQ 193, 194-96 (CCPA 1982)).
Dependent claim 2 recites, in part, obtain a medication amount of the patient based on the plurality of predetermined actions, and generate the medication information regarding the medication execution and the medication amount.
Dependent claim 3 recites, in part, generate the medication information including a medicine name taken by the patient, a medication date and time, and the medication amount.
Dependent claim 4 recites, in part, capture a stationary action when a medicine is taken as one of the plurality of predetermined actions, and obtain the medication amount based on a stationary time of the stationary action.
Dependent claim 5 recites, in part, obtain the medication amount based on the stationary time of the stationary action and a prescribed amount of the medicine.
Dependent claim 6 recites, in part, wherein the stationary action is a stationary action when the medicine is inhaled.
Dependent claim 7 recites, in part, wherein the medication information includes information regarding an inhalation amount of the medicine as the medication amount.
Dependent claim 8 recites, in part, capture a series of actions related to medication as the plurality of predetermined actions.
Dependent claim 9 recites, in part, capture, as the plurality of predetermined actions, an opening action of opening a container containing a medicine and a stationary action of taking the medicine after the opening action.
Dependent claim 10 recites, in part, capture, as the plurality of predetermined actions, an opening action of opening a container containing a medicine, an injection action of injecting the medicine in the container into a medication container, and a stationary action when taking the medicine after the injection action.
Dependent claim 11 recites, in part, wherein the medication action information includes an action on a container that stores a medicine as the medication action.
Dependent claim 12 recites, in part, wherein the action on the container is an opening action of opening the container.
Dependent claim 13 recites, in part, wherein the medication action information includes a stationary action when a medicine is taken as the medication action.
Dependent claim 14 recites, in part, wherein the stationary action is a stationary action when the medicine is inhaled.
Dependent claim 15 recites, in part, generate a learning model for capturing the plurality of predetermined actions from the medication action information, and capture the plurality of predetermined actions from the medication action information based on the learning model generated.
Dependent claim 17 recites, in part, generate medication display information for displaying the medication information.
Dependent claim 18 recites, in part, display an image indicating the medication information based on the medication display information.
Each of these steps of the preceding dependent claims only serve to further limit or specify the features of independent claim 1, and hence are nonetheless directed towards fundamentally the same abstract idea as the independent claim and utilize the additional elements analyzed below in the expected manner.
Step 2A – Judicial Exception Analysis, Prong 2:
This judicial exception is not integrated into a practical application because the additional elements within the claims only amount to instructions to implement the judicial exception using a computer [MPEP 2106.05(f)].
Claim 1 recites an acquisition unit, analysis unit, and generation unit. Claim 19 recites an acquisition unit and analysis unit. Claim 16 recites a storage unit. Claim 17 recites a display information generation unit. Claim 18 recites a display unit. The specification defines each of these units as known generic devices (see the instant disclosure in ¶ 0015-24, ¶ 0029-30, and in the Figures at fig. 2) that amount to hardware and software products (see the instant disclosure in ¶ 0030). The use of these units to collect, analyze, and output data only serve as a tool to apply data to an algorithm and report the results (MPEP § 2106.05(f)(2) see case involving a commonplace business method or mathematical algorithm being applied on a general purpose computer within the “Other examples.. i.”) amounting to instruction to implement the abstract idea using a general purpose computer. Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 134 S. Ct. 2347, 1357 (2014).
The above claims, as a whole, are therefore directed to an abstract idea.
Step 2B – Additional Elements that Amount to Significantly More:
The present claims do not include additional elements that are sufficient to amount to more than the abstract idea because the additional elements or combination of elements amount to no more than a recitation of instructions to implement the abstract idea on a computer.
Claim 1 recites an acquisition unit, analysis unit, and generation unit. Claim 19 recites an acquisition unit and analysis unit. Claim 16 recites a storage unit. Claim 17 recites a display information generation unit. Claim 18 recites a display unit. Each of these elements is only recited as a tool for performing steps of the abstract idea, such as the use of the storage mediums to store data, the computer and data processing devices to apply the algorithm, and the display device to display selected results of the algorithm. These additional elements therefore only amount to mere instructions to perform the abstract idea using a computer and are not sufficient to amount to significantly more than the abstract idea (MPEP 2016.05(f) see for additional guidance on the “mere instructions to apply an exception”).
Each additional element under Step 2A, Prong 2 is analyzed in light of the specification’s explanation of the additional element’s structure. The claimed invention’s additional elements do not have sufficient structure in the specification to be considered a not well-understood, routine, and conventional use of generic computer components. Note that the specification can support the conventionality of generic computer components if “the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a)” (Berkheimer in III. Impact on Examination Procedure, A. Formulating Rejections, 1. on p. 3).
Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. Their collective functions merely provide conventional computer implementation.
Claims 1-20 are therefore rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter.
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Pratt et al. (US Patent Pub No 2022/0361811 - continuation of application No. 16/731,765, filed on Dec. 31, 2019, now Patent 11,457,861)[hereinafter Pratt].
Claim 1 is rejected because Pratt teaches on all elements of the claim:
an information processing system comprising is taught in the Detailed Description in ¶ 0026, ¶ 0145, ¶ 0150, in the Figures at fig. 6, and fig. 10 (teaching on a medication adherence system for monitoring patient medication intake)
an acquisition unit that acquires medication action information regarding a medication action of a patient is taught in the Detailed Description in ¶ 0028 and ¶ 0143 (teaching on acquiring patient medication intake data from a plurality of environmental sensors)
an analysis unit that analyzes the medication action information and captures a plurality of predetermined actions related to medication execution; and is taught in the Detailed Description in ¶ 0035, ¶ 0146, and in the Figures at fig. 7 (teaching on analyzing the patient medication intake motion pattern via a learning model to determine a gesture pattern for a particular prescription)
a generation unit that recognizes the medication execution based on the plurality of predetermined actions and generates medication information regarding the medication execution is taught in the Detailed Description in ¶ 0029, ¶ 0149, and in the Figures at fig. 9 (teaching on generating prescription usage record (treated as synonymous to medication execution) based on the gesture pattern learning model)
As per claim 2, Pratt discloses all of the limitations of claim 1. Pratt also discloses the following:
the information processing system according to claim 1, wherein the generation unit obtains a medication amount of the patient based on the plurality of predetermined actions, and is taught in the Detailed Description in ¶ 0034, ¶ 0039, and ¶ 0072 (teaching on receiving prescription data and new gesture pattern data; the prescription data includes the name or identifier of the prescription, method of administration, the prescribed rate of administration, the historical record of adherence to the prescription, steps required for administration, and prescription usage history)
generates the medication information regarding the medication execution and the medication amount is taught in the Detailed Description in ¶ 0072, ¶ 0029, ¶ 0149, and in the Figures at fig. 9 (teaching on generating adherence confirmation data for the prescription usage record when an ingestion gesture pattern matches the prescription gesture pattern)
As per claim 3, Pratt discloses all of the limitations of claim 2. Pratt also discloses the following:
the information processing system according to claim 2, wherein the generation unit generates the medication information including a medicine name taken by the patient, a medication date and time, and the medication amount is taught in the Detailed Description in ¶ 0034, ¶ 0039, and ¶ 0072 (teaching on receiving prescription data and new gesture pattern data; the prescription data includes the name or identifier of the prescription, method of administration, the prescribed rate of administration, the historical record of adherence to the prescription, steps required for administration, and prescription usage history)
As per claim 4, Pratt discloses all of the limitations of claim 2. Pratt also discloses the following:
the information processing system according to claim 2, wherein the analysis unit captures a stationary action when a medicine is taken as one of the plurality of predetermined actions, and the generation unit obtains the medication amount based on a stationary time of the stationary action is taught in the Detailed Description in ¶ 0028, ¶ 0049, ¶ 0143, and ¶ 0155 (teaching on acquiring patient medication intake data from a plurality of environmental sensors wherein the intake data includes actions related to the dispensing and ingesting of a medicine (treated as synonymous to a stationary action) wherein the gesture pattern includes an expected time to take the medicine)
As per claim 5, Pratt discloses all of the limitations of claim 4. Pratt also discloses the following:
the information processing system according to claim 4, wherein the generation unit obtains the medication amount based on the stationary time of the stationary action and a prescribed amount of the medicine is taught in the Detailed Description in ¶ 0028, ¶ 0049, ¶ 0143, and ¶ 0155 (teaching on acquiring patient medication intake data from a plurality of environmental sensors wherein the intake data includes actions related to the dispensing and ingesting of a medicine (treated as synonymous to a stationary action) wherein the gesture pattern includes an expected time to take the medicine)
As per claim 6, Pratt discloses all of the limitations of claim 4. Pratt also discloses the following:
the information processing system according to claim 4, wherein the stationary action is a stationary action when the medicine is inhaled is taught in the Detailed Description in ¶ 0044-45 and ¶ 0154 (teaching on the prescribed medicine being an inhaler OR a nebulizer and the gesture pattern being an inhaling action)
As per claim 7, Pratt discloses all of the limitations of claim 6. Pratt also discloses the following:
the information processing system according to claim 6, wherein the medication information includes information regarding an inhalation amount of the medicine as the medication amount is taught in the Detailed Description in ¶ 0044-45 and ¶ 0154 (teaching on the prescribed medicine being an inhaler and the gesture pattern being an inhaling action of a metered "puff" (treated as synonymous to an amount of medicine) OR the time from starting and stopping a nebulizer device)
As per claim 8, Pratt discloses all of the limitations of claim 1. Pratt also discloses the following:
the information processing system according to claim 1, wherein the analysis unit captures a series of actions related to medication as the plurality of predetermined actions is taught in the Detailed Description in ¶ 0035, ¶ 0146, and in the Figures at fig. 7 (teaching on analyzing the patient medication intake motion pattern via a learning model to determine a gesture pattern for a particular prescription)
As per claim 9, Pratt discloses all of the limitations of claim 1. Pratt also discloses the following:
the information processing system according to claim 1, wherein the analysis unit captures, as the plurality of predetermined actions, an opening action of opening a container containing a medicine and a stationary action of taking the medicine after the opening action is taught in the Detailed Description in ¶ 0038 (teaching on receiving a motion pattern data related to opening a pill bottle and ingesting the pill as the gesture pattern for consuming a pill medication)
As per claim 10, Pratt discloses all of the limitations of claim 1. Pratt also discloses the following:
the information processing system according to claim 1, wherein the analysis unit captures, as the plurality of predetermined actions, an opening action of opening a container containing a medicine, an injection action of injecting the medicine in the container into a medication container, and a stationary action when taking the medicine after the injection action is taught in the Detailed Description in ¶ 0039 (teaching on receiving a motion pattern data related to opening and loading a syringe and injecting the medication as the gesture pattern for consuming a pill medication)
As per claim 11, Pratt discloses all of the limitations of claim 1. Pratt also discloses the following:
the information processing system according to claim 1, wherein the medication action information includes an action on a container that stores a medicine as the medication action is taught in the Detailed Description in ¶ 0038 (teaching on receiving a motion pattern data related to opening a pill bottle and ingesting the pill as the gesture pattern for consuming a pill medication)
As per claim 12, Pratt discloses all of the limitations of claim 11. Pratt also discloses the following:
the information processing system according to claim 11, wherein the action on the container is an opening action of opening the container is taught in the Detailed Description in ¶ 0038 (teaching on receiving a motion pattern data related to opening a pill bottle and ingesting the pill as the gesture pattern for consuming a pill medication)
As per claim 13, Pratt discloses all of the limitations of claim 1. Pratt also discloses the following:
the information processing system according to claim 1, wherein the medication action information includes a stationary action when a medicine is taken as the medication action is taught in the Detailed Description in ¶ 0038 (teaching on receiving a motion pattern data related to opening a pill bottle and ingesting the pill as the gesture pattern for consuming a pill medication)
As per claim 14, Pratt discloses all of the limitations of claim 13. Pratt also discloses the following:
the information processing system according to claim 13, wherein the stationary action is a stationary action when the medicine is inhaled is taught in the Detailed Description in ¶ 0044-45 and ¶ 0154 (teaching on the prescribed medicine being an inhaler OR a nebulizer and the gesture pattern being an inhaling action)
As per claim 15, Pratt discloses all of the limitations of claim 1. Pratt also discloses the following:
the information processing system according to claim 1, wherein the analysis unit generates a learning model for capturing the plurality of predetermined actions from the medication action information, and captures the plurality of predetermined actions from the medication action information based on the learning model generated is taught in the Detailed Description in ¶ 0035, ¶ 0146, and in the Figures at fig. 7 (teaching on analyzing the patient medication intake motion pattern via a learning model to determine a gesture pattern for a particular prescription)
As per claim 16, Pratt discloses all of the limitations of claim 1. Pratt also discloses the following:
the information processing system according to claim 1, further comprising a storage unit that stores the medication information is taught in the Detailed Description in ¶ 0094 (teaching on a storage medium for storing the prescription data and patient medication intake data)
As per claim 17, Pratt discloses all of the limitations of claim 1. Pratt also discloses the following:
the information processing system according to claim 1, further comprising a display information generation unit that generates medication display information for displaying the medication information is taught in the Detailed Description in ¶ 0027 and ¶ 0034-35 (teaching on generating display information regarding the prescription user data (treated as synonymous to medication display information) for the user)
As per claim 18, Pratt discloses all of the limitations of claim 17. Pratt also discloses the following:
the information processing system according to claim 17, further comprising a display unit that displays an image indicating the medication information based on the medication display information is taught in the Detailed Description in ¶ 0027 and ¶ 0034-35 (teaching on a wearable device display for displaying information regarding the prescription user data (treated as synonymous to medication display information) for the user)
Claim 19 is rejected because Pratt teaches on all elements of the claim:
an information processing apparatus comprising is taught in the Detailed Description in ¶ 0026, ¶ 0145, ¶ 0150, in the Figures at fig. 6, and fig. 10 (teaching on a medication adherence system for monitoring patient medication intake)
an acquisition unit that acquires medication action information regarding a medication action of a patient; and is taught in the Detailed Description in ¶ 0028 and ¶ 0143 (teaching on acquiring patient medication intake data from a plurality of environmental sensors)
an analysis unit that analyzes the medication action information and captures a plurality of predetermined actions related to medication execution is taught in the Detailed Description in ¶ 0035, ¶ 0146, and in the Figures at fig. 7 (teaching on analyzing the patient medication intake motion pattern via a learning model to determine a gesture pattern for a particular prescription)
Claim 20 is rejected because Pratt teaches on all elements of the claim:
an information processing method in which a computer is configured to is taught in the Detailed Description in ¶ 0026, ¶ 0145, ¶ 0150, in the Figures at fig. 6, and fig. 10 (teaching on a medication adherence system for monitoring patient medication intake)
acquire medication action information regarding a medication action of a patient; and is taught in the Detailed Description in ¶ 0028 and ¶ 0143 (teaching on acquiring patient medication intake data from a plurality of environmental sensors)
analyze the medication action information and capture a plurality of predetermined actions related to the medication execution is taught in the Detailed Description in ¶ 0035, ¶ 0146, and in the Figures at fig. 7 (teaching on analyzing the patient medication intake motion pattern via a learning model to determine a gesture pattern for a particular prescription)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Chen and Kehtarnavaz, A Medication Adherence Monitoring System for Pill Bottles Based on a Wearable Inertial Sensor, Annu Int Conf IEEE Eng Med Biol Soc 4983-4986 (2014) teaching on a medication adherence monitoring with physical action detection via a trained model in the § A. Training Phase or Signal Template Setup on p. 4984 and § D. Pill Intake Detection on p. 4985
Lee and Kim (US Patent Pub No 2022/0054081) teaching on monitoring and processing via a machine learning model motion actions of a user to determine if a medication has been consumed including an inhaler in the Detailed Description in ¶ 0124-125 and ¶ 0445
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/JORDAN L JACKSON/Primary Examiner, Art Unit 3682