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 .
Priority
Priority is acknowledged to JP2024-052727 filed on 03/28/2024.
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 1-5 and 7-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an
abstract idea without significantly more.
Step 1
Claims 1-5 and 7-9 are within the four statutory categories. However, as will be shown below, claims 1-5 and 7-9 are nonetheless unpatentable under 35 U.S.C. 101.
Claims 1, 8, and 9 are representative of the inventive concept and recite:
Claim 1
A medical record support apparatus comprising:
at least one memory;
and at least one processor coupled to the at least one memory, wherein the at least one processor is configured to:
acquire text information of an utterance content converted by speech recognition the text information including text information converted by speech recognition as utterance content of a medical worker and a patient during a medical interview and text information converted by speech recognition as utterance content of the medical worker before and after a medical interview, and the text information being in a text format that distinguishes conversational speech data between the medical worker and the patient during the medical interview;
input an instruction sentence into a language model configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format;
and acquire, from an output of the language model, medical record information of the patient based on the text information, the medical information of the patient being used to store an updated medical record of the patient.
Claim 8
A medical record support system comprising:
an eyewear-type wearable terminal worn by a medical worker during a medical interview;
and an information processing apparatus communicably connected to the eyewear-type wearable terminal, wherein the information processing apparatus includes:
at least one apparatus memory;
and at least one apparatus processor coupled to the at least one apparatus memory, wherein the at least one apparatus processor is configured to:
acquire text information of an utterance content converted by speech recognition, the text information including text information converted by speech recognition as utterance content of a medical worker and a patient during a medical interview and text information converted by speech recognition as utterance content of the medical worker before and after a medical interview, and the text information being in a text format that distinguishes conversational speech data between the medical worker and the patient during the medical interview, and the conversational speech data being collected by the eyewear-type wearable terminal;
input an instruction sentence into a language model configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format;
and acquire, from an output of the language model, medical record information of the patient based on the text information, the medical information of the patient being used to store an updated medical record of the patient, and the eyewear-type wearable terminal includes:
at least one terminal memory;
and at least one terminal processor coupled to the at least one terminal memory,
and the at least one terminal processor is configured to display the medical record information on a wearer screen
Claim 9
A medical record support method executed by a computer, the medical record support method comprising:
acquiring text information of an utterance content converted by speech recognition in which speakers are distinguished for the text information including text information converted by speech recognition as utterance content of a medical worker and a patient during a medical interview and text information converted by speech recognition as utterance content of the medical worker before and after a medical interview, and the text information being in a text format that distinguishes conversational speech data between the medical worker and the patient during the medical interview;
and inputting an instruction sentence into a language model configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format;
and acquiring, from an output of the language model, medical record information of the patient based on the text information, the medical information of the patient being used to store an updated medical record of the patient.
Step 2A Prong One
The broadest reasonable interpretation of these steps includes mental processes because the
highlighted components can practically be performed by the human mind (in this case, the process of
acquiring) or using pen and paper. Other than reciting generic computer components/functions such as “apparatus”, “memory”, “processor coupled to memory”, “system”, “terminal”, nothing in the claims precludes the highlighted portions from practically being performed in the mind. 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/functions, then it falls within “Mental Processes” grouping of abstract ideas. Additionally, the mere nominal recitation of a generic computer does not take the claim limitation out of the mental process grouping. Thus, the claim recites a mental process. Additionally, the recitation of generic computer components and functions also covers behavioral or interactions between people (i.e. the computer), and/or managing personal behavior or relationships or interactions between people (i.e. social activities, teaching, and following rules or instructions), hence the claim falls under “Certain Methods of Organizing Human Activity”.
Dependent claims 2-5 and 7 recite additional subject matter which further narrows or
defines the abstract idea embodied in the claims.
Step 2A Prong Two
This judicial exception is not integrated into a practical application. In particular, the claims
recite the following additional limitations:
Claim 1 recites: “apparatus”, “memory”, “processor coupled to memory”, “system”, “terminal”, “input an instruction sentence into a language model configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format”, and “to store an updated medical record of the patient”.
In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more limitations which:
Amount to mere instructions to apply an exception (MPEP 2106.05(f)). The limitations
are recited as being performed by a “apparatus”, “memory”, “processor coupled to memory”, “system”, “terminal”, and “large language model”. These limitations are recited at a high level of generality and amount to no more than mere instructions to apply the exception using a generic computer. The model is used to generally apply the abstract idea without limiting how it functions.
Add insignificant extra-solution activity (MPEP 2106.05(g)) to the abstract idea such as the
recitation of “input an instruction sentence into a language model configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format” and “to store an updated medical record of the patient”.
Dependent claims 2 and 4 recite “display”
In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more limitations which:
Add insignificant extra-solution activity (MPEP 2106.05(g)) to the abstract idea such as the
recitation of “display”.
Dependent claims 3, 5, and 7 do not include additional elements beyond those already recited in
Independent claims 1, 8, and 9, and hence do not integrate the aforementioned abstract idea into a
practical application. Looking at the limitations as an ordered combination adds nothing that is not
already present when looking at the elements taken individually. There is no indication that the
combination of elements improves the functioning of a computer, machine learning model, or any other
technology. Their collective function merely provides conventional computer implementation and do
not impose a meaningful limit to integrate the abstract idea into a practical application.
Step 2B
Claims 1, 8, and 9 do not include additional elements that are sufficient to amount to significantly more
than the judicial exception. As discussed above with respect to discussion of integration of the abstract
idea into a practical application, the additional elements: A system in claim 1; amount to no more than
mere instructions to apply an exception to the abstract idea. Additionally, the additional limitations,
other than the abstract idea per se, amount to no more than limitations which amount to elements that
have been recognized as well-understood, routine, and conventional activity in particular fields as
demonstrated by the recitation of:
Display, which refers to showing information on a screen(Para 0039, Cachro(US 20230216923 A1) discloses: “The display 308, may comprise any conventional display mechanism such as a cathode ray tube (CRT), flat panel display, or any other display mechanism known to those having ordinary skill in the art.”) in a manner that would be well-understood, routine, and conventional.
Input, which refers to entering information into a system or machine (Para 0003, Lee(US 20220028381 A1) discloses: “In addition to conventional input method using a keyboard or a mouse, electronic devices have recently supported various input methods.”) in a manner that would be well-understood, routine, and conventional.
Storing, which refers to retaining digital information on a physical or cloud-based medium to be accessed at a later date (Para 0084, Abouzour(US 20220164335 A1) discloses: “However, I/O characteristics of object stores are different than those of conventional storage solutions such as hard disk drives or solid state drives.”) in a manner that would be well-understood, routine, and conventional.
Dependent claims 3, 5, and 7 do not include additional elements beyond those already recited in
Independent claims 1, 8, and 9. Therefore, they are not deemed to be significantly more
than the abstract idea because, as stated above, the limitations of the aforementioned dependent
claims amount to no more than generally linking the abstract idea to a particular technological
environment or field of use, and/or do not recite additional elements not already recited in
independent claims 1, 8, and 9 hence do not amount to “significantly more” than the abstract idea.
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.
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.
Claims 1-5 and 7-9 are rejected under 35 U.S.C. 103 is being unpatentable over Haddick(US20130127980A1) in view of Sugiyama(US20250149140A1) and Pinter(US20180308565A1).
Claim 1
Haddick discloses:
A medical record support apparatus comprising: at least one memory(Para 0285, Haddick discloses memory); and at least one processor coupled to the at least one memory(Para 0285, Haddick discloses a processor which contains memory), wherein the at least one processor is configured to: acquire text information of an utterance content converted by speech recognition(Para 0684, Haddick discloses speech recognition) the text information including text information converted by speech recognition as utterance content of a medical worker and a patient during a medical interview(Para 0692, Haddick discloses an interaction between patient and physician) and text information converted by speech recognition as utterance content of the medical worker before and after a medical interview(Para 0464, Haddick discloses transcribing voice to text, which can occur before or after an interview), and the text information being in a text format that distinguishes conversational speech data between the medical worker and the patient during the medical interview(Para 0824, Haddick discloses speech identification);
Haddick does not explicitly disclose:
input an instruction sentence into a language model
configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format
acquire, from an output of the language model, medical record information of the patient
the medical information of the patient being used to store an updated medical record of the patient
Sugiyama discloses:
input an instruction sentence into a language model(Para 0018, Sugiyama discloses an prompt sentence input into a large language model)
acquire, from an output of the language model, medical record information of the patient(Figure 9, Sugiyama discloses acquiring patient and examination information)
Before the effective filing date of the claimed invention, it would have been obvious to one of
ordinary skill in the art to have modified the system for video display based on sensor input of Haddick, to add input an instruction sentence into a language model and acquire, from an output of the language model, medical record information of the patient, as taught by Sugiyama. One of ordinary skill would have been so motivated to provide a way for medical data to be easily processed and converted to more easily be integrated into a medical record, but in this case for a system which provides medical examination support (Para 0005, Sugiyama discloses: “However, such techniques tend to basically add the same tags to the same sentences or words so that it may be difficult to perform tagging with each patient's background taken into account.”).
Sugiyama does not explicitly disclose:
configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format
the medical information of the patient being used to store an updated medical record of the patient
Pinter discloses:
configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format(Para 0015, Pinter discloses an output being automatically incorporated into the EMR, which necessitates text information in medical record format)
the medical information of the patient being used to store an updated medical record of the patient(Para 0015, Pinter discloses an output being automatically incorporated(stored) into the EMR, which inherently updates the medical record)
Before the effective filing date of the claimed invention, it would have been obvious to one of
ordinary skill in the art to have modified the system for video display based on sensor input of Haddick to add configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format and the medical information of the patient being used to store an updated medical record of the patient, as taught by Pinter. One of ordinary skill would have been so motivated to provide a way to integrate data from a medical interview into a medical record to better improve patient outcomes, but in this case for automated transcription and documentation of tele-health encounters(Para 0012, Pinter discloses: “The automated generation of a SOAP note from a live encounter can greatly increase the time a physician has available to be with patients. Medical providers, such as physicians for example, typically devote a significant portion of the day to administrative tasks such as generating documentation of patient consultations and the like.”).
Claim 2
Haddick discloses:
The medical record support apparatus according to claim 1, wherein the medical record support apparatus is an eyewear-type wearable terminal worn by the medical worker during the medical interview(Figure 1, Haddick discloses an eyepiece), and the at least one processor is configured to: acquire the converted text information based on the conversational speech data collected by the eyewear-type wearable terminal(Para 0684, Haddick discloses speech recognition by the eyepiece); and display the acquired medical record information on a wearer screen of the eyewear-type wearable terminal(Para 0683, Haddick discloses an eyepiece which displays content).
Claim 3
Haddick discloses:
The medical record support apparatus according to claim 2, wherein the at least one processor is configured to perform the speech recognition in which the speakers are distinguished(Para 0824, Haddick discloses speech identification) based on at least one of a volume and a speech collection direction of the conversational speech data(Para 0608, Haddick discloses sound direction sensing) collected by the eyewear-type wearable terminal(Figure 1, Haddick discloses an eyepiece), and the at least one processor is configured to distinguish the speakers(Para 0824, Haddick discloses speech identification) and acquire the text information converted from a recognition result of the speech recognition(Para 0464, Haddick discloses transcribing voice to text).
Claim 4
Haddick discloses:
The medical record support apparatus according to claim 1, wherein the at least one processor is configured to: acquire the converted text information based on the conversational speech data (Para 0464, Haddick discloses transcribing voice to text) collected by the eyewear-type wearable terminal worn by the medical worker during the medical interview(Figure 1, Haddick discloses an eyepiece); and perform control to display the medical record information(Para 1123, Haddick discloses displaying patient data on eyepiece) on a wearer screen of the eyewear-type wearable terminal(Figure 7, Haddick discloses displaying content on eyepiece screen, which can be a medical record).
Claim 5
Haddick discloses:
The medical record support apparatus according to claim 4, wherein the at least one processor is configured to perform the speech recognition in which the speakers are distinguished(Para 0824, Haddick discloses speech identification) based on at least one of a volume and a speech collection direction of the conversational speech data(Para 0608, Haddick discloses sound direction sensing) collected by the eyewear-type wearable terminal(Figure 1, Haddick discloses an eyepiece), and the at least one processor is configured to distinguish the speakers(Para 0824, Haddick discloses speech identification) and acquire the text information converted from a recognition result of the speech recognition(Para 0464, Haddick discloses transcribing voice to text).
Claim 7
Haddick discloses:
The medical record support apparatus according to claim 1, wherein the medical worker is a nurse(Para 1126, Haddick discloses medical personnel), and the medical record information includes information of a nursing record.
Haddick does not explicitly disclose: nursing record
Sugiyama discloses: nursing record(Para 0070, Sugiyama discloses different types of medical records)
Before the effective filing date of the claimed invention, it would have been obvious to one of
ordinary skill in the art to have modified the system for video display based on sensor input of Haddick to add nursing record, as taught by Sugiyama. One of ordinary skill would have been so motivated to provide a way to process all data related to a patient for improved diagnosis and patient outcomes, but in this case for a system which provides medical examination support (Para 0005, Sugiyama discloses: “However, such techniques tend to basically add the same tags to the same sentences or words so that it may be difficult to perform tagging with each patient's background taken into account.”).
Claim 8
Haddick discloses:
A medical record support system comprising: an eyewear-type wearable terminal worn by a medical worker during a medical interview(Figure 1, Haddick discloses an eyepiece); and an information processing apparatus communicably connected to the eyewear-type wearable terminal(Para 0477, Haddick discloses a processor connected to the eyepiece), wherein the information processing apparatus includes: at least one apparatus memory(Para 0285, Haddick discloses a processor which contains memory); and at least one apparatus processor coupled to the at least one apparatus memory(Para 0285, Haddick discloses a processor which contains memory), wherein the at least one apparatus processor is configured to: acquire text information of an utterance content converted by speech recognition(Para 0684, Haddick discloses speech recognition), the text information including text information converted by speech recognition as utterance content of a medical worker and a patient during a medical interview (Para 0692, Haddick discloses an interaction between patient and physician) and text information converted by speech recognition as utterance content of the medical worker before and after a medical interview(Para 0464, Haddick discloses transcribing voice to text, which can occur before or after an interview), and the text information being in a text format that distinguishes conversational speech data between the medical worker and the patient during the medical interview(Para 0824, Haddick discloses speech identification), and the conversational speech data being collected by the eyewear-type wearable terminal(Para 0684, Haddick discloses speech recognition by the eyepiece); (Para 0285, Haddick discloses a processor which contains memory), and the at least one terminal processor is configured to display the medical record information on a wearer screen(Para 0683, Haddick discloses an eyepiece which displays content).
Haddick does not explicitly disclose:
input an instruction sentence into a language model
convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format(Para 0015, Pinter discloses an output being automatically incorporated into the EMR, which necessitates text information in medical record format)
acquire, from an output of the language model, medical record information of the patient
the medical information of the patient being used to store an updated medical record of the patient(Para 0015, Pinter discloses an output being automatically incorporated(stored) into the EMR, which inherently updates the medical record)
Sugiyama discloses:
input an instruction sentence into a language model(Para 0018, Sugiyama discloses an prompt sentence input into a large language model)
acquire, from an output of the language model, medical record information of the patient(Figure 9, Sugiyama discloses acquiring patient and examination information)
Before the effective filing date of the claimed invention, it would have been obvious to one of
ordinary skill in the art to have modified the system for video display based on sensor input of Haddick, to add input an instruction sentence into a language model and acquire, from an output of the language model, medical record information of the patient, as taught by Sugiyama. One of ordinary skill would have been so motivated to provide a way for medical data to be easily processed and converted to more easily be integrated into a medical record, but in this case for a system which provides medical examination support (Para 0005, Sugiyama discloses: “However, such techniques tend to basically add the same tags to the same sentences or words so that it may be difficult to perform tagging with each patient's background taken into account.”).
Sugiyama does not explicitly disclose:
configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format
the medical information of the patient being used to store an updated medical record of the patient
Pinter discloses:
configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format(Para 0015, Pinter discloses an output being automatically incorporated into the EMR, which necessitates text information in medical record format)
the medical information of the patient being used to store an updated medical record of the patient(Para 0015, Pinter discloses an output being automatically incorporated(stored) into the EMR, which inherently updates the medical record)
Before the effective filing date of the claimed invention, it would have been obvious to one of
ordinary skill in the art to have modified the system for video display based on sensor input of Haddick to add configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format and the medical information of the patient being used to store an updated medical record of the patient, as taught by Pinter. One of ordinary skill would have been so motivated to provide a way to integrate data from a medical interview into a medical record to better improve patient outcomes, but in this case for automated transcription and documentation of tele-health encounters(Para 0012, Pinter discloses: “The automated generation of a SOAP note from a live encounter can greatly increase the time a physician has available to be with patients. Medical providers, such as physicians for example, typically devote a significant portion of the day to administrative tasks such as generating documentation of patient consultations and the like.”).
Claim 9
Haddick discloses:
A medical record support method executed by a computer, the medical record support method comprising: acquiring text information of an utterance content converted by speech recognition(Para 0684, Haddick discloses speech recognition) the text information including text information converted by speech recognition as utterance content of a medical worker and a patient during a medical interview(Para 0692, Haddick discloses an interaction between patient and physician) and text information converted by speech recognition as utterance content of the medical worker before and after a medical interview(Para 0464, Haddick discloses transcribing voice to text, which can occur before or after an interview), and the text information being in a text format that distinguishes conversational speech data between the medical worker and the patient during the medical interview(Para 0824, Haddick discloses speech identification);
Haddick does not explicitly disclose:
input an instruction sentence into a language model
convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format(Para 0015, Pinter discloses an output being automatically incorporated into the EMR, which necessitates text information in medical record format)
acquire, from an output of the language model, medical record information of the patient
the medical information of the patient being used to store an updated medical record of the patient(Para 0015, Pinter discloses an output being automatically incorporated(stored) into the EMR, which inherently updates the medical record)
Sugiyama discloses:
input an instruction sentence into a language model(Para 0018, Sugiyama discloses an prompt sentence input into a large language model)
acquire, from an output of the language model, medical record information of the patient(Figure 9, Sugiyama discloses acquiring patient and examination information)
Before the effective filing date of the claimed invention, it would have been obvious to one of
ordinary skill in the art to have modified the system for video display based on sensor input of Haddick, to add input an instruction sentence into a language model and acquire, from an output of the language model, medical record information of the patient, as taught by Sugiyama. One of ordinary skill would have been so motivated to provide a way for medical data to be easily processed and converted to more easily be integrated into a medical record, but in this case for a system which provides medical examination support (Para 0005, Sugiyama discloses: “However, such techniques tend to basically add the same tags to the same sentences or words so that it may be difficult to perform tagging with each patient's background taken into account.”).
Sugiyama does not explicitly disclose:
configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format
the medical information of the patient being used to store an updated medical record of the patient
Pinter discloses:
configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format(Para 0015, Pinter discloses an output being automatically incorporated into the EMR, which necessitates text information in medical record format)
the medical information of the patient being used to store an updated medical record of the patient(Para 0015, Pinter discloses an output being automatically incorporated(stored) into the EMR, which inherently updates the medical record)
Before the effective filing date of the claimed invention, it would have been obvious to one of
ordinary skill in the art to have modified the system for video display based on sensor input of Haddick to add configured to convert information in the text format into a medical record format, the instruction sentence including the text information and being in a format for causing the language model to output at least part of the text information in the medical record format and the medical information of the patient being used to store an updated medical record of the patient, as taught by Pinter. One of ordinary skill would have been so motivated to provide a way to integrate data from a medical interview into a medical record to better improve patient outcomes, but in this case for automated transcription and documentation of tele-health encounters(Para 0012, Pinter discloses: “The automated generation of a SOAP note from a live encounter can greatly increase the time a physician has available to be with patients. Medical providers, such as physicians for example, typically devote a significant portion of the day to administrative tasks such as generating documentation of patient consultations and the like.”).
Response to Arguments
35 U.S.C 101
(Page 12) Regarding the assertion that the amended claim does not recite an abstract idea.
Applicant's arguments filed have been fully considered but they are not persuasive. The acquiring steps are abstract and can be considered mental process or certain methods of organizing human activity. Please refer to the 101 analysis above.
(Page 13-14) Regarding the assertion that the amended claim recites a practical application and is similar to is similar to Example 42, claim 1, not claim 2.
Applicant's arguments filed have been fully considered but they are not persuasive. If one were to remove the general computing elements and the model, the steps of the amended claims can be performed by a human. The argued conversion of text information in medical record format and distinguishing conversational speech data can be performed by a human. If one were to perform a similar exercise on Example 42, claim 1, the steps cannot be performed by a human and necessitate the need for the computing elements to perform the functions.
(Page 15) Regarding the assertion that the amended claim integrates the abstract idea into a practical application.
Applicant's arguments filed have been fully considered but they are not persuasive. The additional elements identified above do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more limitations which amount to mere instructions to apply an exception (MPEP 2106.05(f)) and add insignificant extra-solution activity (MPEP 2106.05(g)) to the abstract idea.
(Page 15) Regarding the assertion that the amended claim recites significantly more than the abstract idea.
Applicant's arguments filed have been fully considered but they are not persuasive. Claims 1, 8, and 9 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements: A system in claim 1; amount to no more than mere instructions to apply an exception to the abstract idea. Additionally, the additional limitations,
other than the abstract idea per se, amount to no more than limitations which amount to elements that
have been recognized as well-understood, routine, and conventional activity.
35 U.S.C 103
Applicant’s arguments with respect to claim(s) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tran(US11304023B1) discloses an enhanced hearing system that is coupled to a virtual reality system.
Hannaford(US9645785B1) discloses a heads-up display for augmented reality in a medical environment.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/S.G.P./Examiner, Art Unit 3685
/KAMBIZ ABDI/Supervisory Patent Examiner, Art Unit 3685
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