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
Status of Claims
The present Office Action is pursuant to Applicant’s communication on 11-02-2022; current application filed on 11-02-2022.
Information Disclosure Statement
The information disclosure statements (IDS) filed on 11-02-2022, have been acknowledged. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 is/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
Claim(s) 1-20 is/are within the four statutory categories. Claim(s) 1-20 is/are drawn to a method1 system2 and computer program product3 which means that said claims(s) is/are within the four statutory categories (i.e. process). However, as will be shown below, arguendo, Aforementioned claim(s) is/are nonetheless unpatentable under 35 U.S.C. 101.
Prong 1 of Step 2A
Claim(s) 1, 13, 17, which is/are representative of the inventive concept, recite(s):
1. A computer-implemented method of dynamic processing within a computing environment, the computer-implemented method comprising:
automatically obtaining device data from one or more devices for an individual, the one or more devices including one or more medical monitoring devices;
obtaining data from one or more exogenous sources, the data including current data relating to one or more medical resources;
analyzing, using an artificial intelligence agent, the device data obtained from the one or more devices and the data from the one or more exogenous sources; and
providing one or more recommendations, based on the analyzing, the one or more recommendations including an indication of a device to use that is different from the one or more devices to obtain different device data for the individual.
The underlined limitations as shown above, given the broadest reasonable interpretation, cover the abstract ideas of a mental process and/or a certain method of organizing human activity because they recite a process that could be practically performed in the human mind (i.e. observations, evaluations, judgments, and/or opinions – in this case obtaining data from individual users, analyzing the data and providing recommendations to the individual, or using a pen and paper, but for the recitation of generic computer components (i.e. the computer), e.g. see MPEP 2106.04(a)(2). Any limitations not identified above as part of the abstract ideas are deemed “additional elements,” and will be discussed in further detail below.
Dependent claim(s) 2-12, 14-16 and 18-20, include other limitations, for example:
2. The computer-implemented method of claim 1, wherein the analyzing includes obtaining the data from the one or more exogenous sources at selected intervals to obtain the current data relating to the one or more medical resources. 3. The computer-implemented method of claim 1, wherein the analyzing includes comparing the device data to a baseline for the individual to determine that a health- related change has occurred for the individual, and wherein the one or more recommendations are based on the health- related change. 4. The computer-implemented method of claim 1, further comprising providing information of where to obtain the device to use that is different from the one or more devices. 5. The computer-implemented method of claim 1, further comprising initiating performance of one or more actions based on the analyzing, the one or more actions including filing a claim with a health insurance company. 6. The computer-implemented method of claim 1, further comprising initiating performance of one or more actions based on the analyzing, the one or more actions including making an appointment for the individual with a health professional. 7. The computer-implemented method of claim 1, further comprising accessing a smart contract established by the individual to be used in determining the one or more recommendations. 8. The computer-implemented method of claim 7, further comprising: determining that the individual is incapacitated; checking based on determining that the individual is incapacitated the smart contract to determine how to proceed; and alerting at least one entity of the incapacity of the individual based on the smart contract indicating that the at least one entity is to be alerted based on the individual being incapacitated. 9. The computer-implemented method of claim 7, wherein the smart contract explicitly specifies one or more entities to obtain information relating to the individual and one or more types of information to be obtained by the one or more entities. 10. The computer-implemented method of claim 7, wherein the smart contract is stored using a security mecha- nism. 11. The computer-implemented method of claim 1, wherein the one or more recommendations include a specification of one or more providers for the individual. 12. The computer-implemented method of claim 1, wherein the one or more recommendations include a specification of additional data to be obtained for analysis. 14. The computer system of claim 13, wherein the ana- lyzing includes comparing the device data to a baseline for the individual to determine that a health-related change has occurred for the individual, and wherein the one or more recommendations are based on the health-related change. 15. The computer system of claim 13, wherein the method further comprises accessing a smart contract established by the individual to be used in determining the one or more recommendations. 16. The computer system of claim 15, wherein the method further comprises: determining that the individual is incapacitated; checking based on determining that the individual is incapacitated the smart contract to determine how to proceed; and alerting at least one entity of the incapacity of the individual based on the smart contract indicating that the at least one entity is to be alerted based on the individual being incapacitated. 18. The computer program product of claim 17, wherein the analyzing includes comparing the device data to a baseline for the individual to determine that a health-related change has occurred for the individual, and wherein the one or more recommendations are based on the health-related change. 19. The computer program product of claim 17, wherein the method further comprises accessing a smart contract established by the individual to be used in determining the one or more recommendations. 20. The computer program product of claim 19, wherein the method further comprises: determining that the individual is incapacitated; checking based on determining that the individual is incapacitated the smart contract to determine how to proceed; and alerting at least one entity of the incapacity of the individual based on the smart contract indicating that the at least one entity is to be alerted based on the individual being incapacitated.
However these dependent claims only serve to further narrow the abstract idea, and a claim may not preempt abstract ideas, even if the judicial exception is narrow, e.g. see MPEP 2106.04. Additionally, any limitations in dependent claim(s) 2-12, 14-16 and 18-20 are deemed additional elements to the abstract idea, and will be further addressed below. Hence dependent claim(s) 2-12, 14-16 and 18-20 are nonetheless directed towards fundamentally the same abstract idea as independent Claim(s) 1, 13, 17.
Prong 2 of Step 2A
Claim(s) 1, 13, 17 is/are not integrated into a practical application because the additional elements (i.e. comprising non-underlined limitations above – in this case devices, memory, one or more processors) amount to no more than limitations which:
amount to mere instructions to apply an exception – for example, the recitation of a computer, which amounts to merely invoking a computer as a tool to perform the abstract idea, e.g. see ¶¶1-101 of the present Specification, see MPEP 2106.05(f);
generally link the abstract idea to a particular technological environment or field of use, which amounts to limiting the abstract idea to the field of healthcare, see MPEP 2106.05(h); and/or
add insignificant extra-solution activity to the abstract idea, see MPEP 2106.05(g).
Additionally, dependent claim(s) 2-12, 14-16 and 18-20 include other limitations, but these limitations also amount to no more than generally linking the abstract idea to a particular technological environment or field of use, and/or do not include any additional elements beyond those already recited in independent Claim(s) 1, 13, 17, hence also do not integrate the aforementioned abstract idea into a practical application.
Step 2B
Claim(s) 1, 13, 17 do/does not include additional elements that are sufficient to amount to “significantly more” than the judicial exception because the additional elements (i.e. comprising non-underlined limitations above – in this case devices, memory, one or more processors), as stated above, are directed towards no more than limitations that amount to mere instructions to apply the exception, generally link the abstract idea to a particular technological environment or field of use, and/or add insignificant extra-solution activity to the abstract idea, wherein the insignificant extra-solution activity comprises limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrated by:
The Specification expressly disclosing that the additional elements are well-understood, routine, and conventional in nature:
¶¶1-101 of the Specification discloses that the additional elements (i.e. the computer) comprise a plurality of different types of generic computing systems that are configured to perform generic computer functions (i.e. receive and process data) that are well-understood, routine, and conventional activities previously known to the pertinent industry (i.e. healthcare);
Relevant court decisions: The following are examples of court decisions demonstrating well-understood, routine and conventional activities, e.g. see MPEP 2106.05(d)(II):
Storing and retrieving information in memory, e.g. see Versata Dev. Group, Inc. v. SAP Am., Inc. – similarly, the current invention recites storing or uploading media;
Dependent claim(s) 2-12, 14-16 and 18-20 include other limitations, but none of these limitations are deemed 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 any additional elements not already recited in independent Claim(s) 1, 13, 17 hence does not amount to “significantly more” than the abstract idea.
Thus, taken alone, the additional elements do not amount to significantly more than the abstract idea identified above. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, claim(s) 1-20 is/are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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 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 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) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kutzko4 in view of Gudibande5.
Regarding claim(s) 1, 13, 17, Kutzko discloses: A computer-implemented method of dynamic processing within a computing environment, the computer-implemented method comprising, A computer system for dynamic processing within a computing environment, the computer system comprising: a memory; and one or more processors in communication with the memory, wherein the computer system is configured to perform a method, A computer program product for dynamic processing within a computing environment, said computer program product comprising: one or more computer readable storage media and program instructions collectively stored on the one or more computer readable storage media readable by at least one processing circuit to perform a method comprising, said method comprising [20:6-28]:
automatically obtaining device data from one or more devices for an individual, the one or more devices including one or more medical monitoring devices; [“in another embodiment, the artificial intelligence system is connected to a smart-home device which is operable to interact with the patient audibly, visibly, or both. The smart- home device is operable to detect side effects of disease- related issues, such as, but not limited to, slurred speech and nystagmus”6, systems implementing [a] by connecting to "smart-home device[s]"7 and “consumer devices [ (e.g., smart phones, smart watches)]”8 to automatically “pick[ing] up patient information every day9” and “detect[ing]” specific health indicators like speech or eye movement by employing artificial intelligence as opposed to direct human control, to perform said detection based on detected “deviations”10 from baselines created by the artificial intelligence system]
obtaining data from one or more exogenous sources, the data including current data relating to one or more medical resources; [“Single agents that are approved by the FDA for the treatment of hypertension are located [that is, obtained] in a database in the artificial intelligence algorithm and identified by NDC code. Combination therapies approved by the FDA in the treatment of hypertension are available in fixed-combinations listed in the blockchain database as well”11, [b] implemented by accessing a “database in the artificial intelligence algorithm”12 and a "blockchain database13" that “house [approved agents and therapies]”14, serving as the exogenous source of medical resource data]
analyzing, using an artificial intelligence agent, the device data obtained from the one or more devices and the data from the one or more exogenous sources; [“In one example, the artificial intelligence system is operable to recognize vocal biomarkers or deviations from a vocal baseline created by the artificial intelligence system from audio analysis of data received from the smart-home device or other consumer device”15, [c] implemented using an AI agent, the AI agent analyzes audio data to identify "deviations from a vocal baseline"16 which directly implements comparing device data to a baseline to determine a health-related change, by way of example, “[o]ther baselines include a coughing baseline which indicates a typical cough or range of coughs for a patient and a breathing baseline which indicates typical breathing for a patient including breathing during different positions” or “states such as sleeping, exercising, resting, etc. In another embodiment, the artificial intelligence system is operable to create a visual baseline, such as a visual baseline of a patient's face including eyes, mouth, certain areas of the face, etc. based on video and or photo imagery”17]
Kutzko does not explicitly disclose as disclosed by Gudibande:
providing one or more recommendations, based on the analyzing, the one or more recommendations including an indication of a device to use that is different from the one or more devices to obtain different device data for the individual (i.e., wherein additional data from a different device may be used to make one or more recommendations for actions to improve outcomes18); [“The sensing kit of claim 49, wherein the plurality of discrete sensors comprises a first sensor and a second sensor both configured to detect a target analyte, wherein the first sensor has a higher sensitivity than the second sensor”, said kit facilitating “enhance[d] sensitivity in detection and monitoring of different target analytes19” by allowing the processing module to “selectively activate a greater number”20 of sensors when higher precision is required21: different sensors offer different sensitivities (Claim 55, 61), enabling the confirmation of analyte presence and concentration (Claim 65), which feeds back into the recommendation engine (Claim 48) which is configured to “prescribe certain corrective or mitigative actions to the subject, based on the detected levels of the one or more target analytes”, facilitating a confirmation of analyte levels by using a first and second sensor22, enabling prompt advisory of a patient regarding corrective actions]
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 Kutzko, including mechanism(s) [d] as taught by Gudibande. One of ordinary skill would have been so motivated to employ said mechanism(s) to facilitate a confirmation of different analyte levels23, providing additional data, enabling prompt advisory of a patient regarding corrective actions.
Regarding claim(s) 2, Kutzko-Gudibande as a combination discloses: The computer-implemented method of claim 1, Kutzko disclosing: wherein the analyzing includes obtaining the data from the one or more exogenous sources at selected intervals to obtain the current data relating to the one or more medical resources. [“Single agents that are approved by the FDA for the treatment of hypertension are located [that is, obtained] in a database in the artificial intelligence algorithm and identified by NDC code. Combination therapies approved by the FDA in the treatment of hypertension are available in fixed-combinations listed in the blockchain database as well”24, [b] implemented by accessing a “database in the artificial intelligence algorithm”25 and a "blockchain database26" that “house [approved agents and therapies]”27, serving as the exogenous source of medical resource data]
Regarding claim(s) 3, 14, 18, Kutzko-Gudibande as a combination discloses: The computer-implemented method of claim 1, system claim of 13, computer program of claim 17, Kutzko disclosing: wherein the analyzing includes comparing the device data to a baseline for the individual to determine that a health-related change has occurred for the individual, and wherein the one or more recommendations are based on the health-related change. [“In one example, the artificial intelligence system is operable to recognize vocal biomarkers or deviations from a vocal baseline created by the artificial intelligence system from audio analysis of data received from the smart-home device or other consumer device”28, [c] implemented using an AI agent, the AI agent analyzes audio data to identify "deviations from a vocal baseline"29 which directly implements comparing device data to a baseline to determine a health-related change, by way of example, “[o]ther baselines include a coughing baseline which indicates a typical cough or range of coughs for a patient and a breathing baseline which indicates typical breathing for a patient including breathing during different positions” or “states such as sleeping, exercising, resting, etc. In another embodiment, the artificial intelligence system is operable to create a visual baseline, such as a visual baseline of a patient's face including eyes, mouth, certain areas of the face, etc. based on video and or photo imagery”30]
Regarding claim(s) 4, Kutzko-Gudibande as a combination discloses: The computer-implemented method of claim 1, Gudibande disclosing [a]: further comprising providing information of where to obtain the device to use that is different from the one or more devices (i.e., providing configuration choices corresponding to a plurality of different multiplexed configurations). [“The sensing kit of claim 49, wherein the plurality of discrete sensors comprises a first sensor and a second sensor both configured to detect a target analyte, wherein the first sensor has a higher sensitivity than the second sensor”, said kit facilitating “enhance[d] sensitivity in detection and monitoring of different target analytes31” by allowing the processing module to “selectively activate a greater number”32 of sensors when higher precision is required33: different sensors offer different sensitivities (Claim 55, 61), enabling the confirmation of analyte presence and concentration (Claim 65), which feeds back into the recommendation engine (Claim 48) which is configured to “prescribe certain corrective or mitigative actions to the subject, based on the detected levels of the one or more target analytes”, facilitating a confirmation of analyte levels by using a first and second sensor34, enabling prompt advisory of a patient regarding corrective actions]
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 Kutzko, including mechanism(s) [a] as taught by Gudibande. One of ordinary skill would have been so motivated to employ said mechanism(s) to facilitate a confirmation of different analyte levels35, providing additional data, enabling prompt advisory of a patient regarding corrective actions.
Regarding claim(s) 5, Kutzko-Gudibande as a combination discloses: The computer-implemented method of claim 1, Kutzko disclosing: further comprising initiating performance of one or more actions based on the analyzing, the one or more actions including filing a claim with a health insurance company (i.e., facilitating claim operations including authorizing payment for healthcare services). [17:46-50]Regarding claim(s) 6, Kutzko-Gudibande as a combination discloses: The computer-implemented method of claim 1, Kutzko disclosing: further comprising initiating performance of one or more actions based on the analyzing, the one or more actions including making an appointment for the individual with a health professional. [34:45-65: scheduling appointments]
Regarding claim(s) 7, 15, 19, Kutzko-Gudibande as a combination discloses: The computer-implemented method of claim 1, system of claim 13, computer program product of claim 17, Kutzko disclosing: further comprising accessing a smart contract established by the individual to be used in determining the one or more recommendations. [Employing smart contracts in association with treatment plan recommendations36]
Regarding claim(s) 8, 16, 20, Kutzko-Gudibande as a combination discloses: The computer-implemented method of claim 7, system of claim 15, computer program product of claim 19, Kutzko disclosing: further comprising:
determining that the individual is incapacitated; [The smart- home device is operable to detect side effects of disease- related issues, such as, but not limited to, slurred speech and nystagmus”37, systems implementing [a] by connecting to "smart-home device[s]"38, serving as a trigger for further action]
checking based on determining that the individual is incapacitated the smart contract to determine how to proceed (i.e., wherein therapies or methods are linked stored data in a smart contract); [33:45-67] and
alerting at least one entity of the incapacity of the individual based on the smart contract indicating that the at least one entity is to be alerted based on the individual being incapacitated. [“The devices and artificial intelligence system are operable to pick up patient information every day, analyze this information, and better update physicians as to patient health, such that health visits are only scheduled when truly necessary”39]
Regarding claim(s) 9, Kutzko-Gudibande as a combination discloses: The computer-implemented method of claim 7, Kutzko disclosing: wherein the smart contract explicitly specifies one or more entities to obtain information relating to the individual and one or more types of information to be obtained by the one or more entities (i.e., facilitating receipt of information). [“Single agents that are approved by the FDA for the treatment of hypertension are located [that is, obtained] in a database in the artificial intelligence algorithm and identified by NDC code. Combination therapies approved by the FDA in the treatment of hypertension are available in fixed-combinations listed in the blockchain database as well”40, [b] implemented by accessing a “database in the artificial intelligence algorithm”41 and a "blockchain database42" that “house [approved agents and therapies]”43, serving as the exogenous source of medical resource data]
Regarding claim(s) 10, Kutzko-Gudibande as a combination discloses: The computer-implemented method of claim 7, Kutzko disclosing: wherein the smart contract is stored using a security mechanism (i.e., employing hashing within a blockchain). [15:1-41]
Regarding claim(s) 11, Kutzko-Gudibande as a combination discloses: The computer-implemented method of claim 1, Kutzko disclosing: wherein the one or more recommendations include a specification of one or more providers for the individual (i.e., therapies associated with providers). [17:45-60]
Regarding claim(s) 12, Kutzko-Gudibande as a combination discloses: The computer-implemented method of claim 1, Gudibande disclosing [a]: wherein the one or more recommendations include a specification of additional data to be obtained for analysis (i.e., wherein additional data from a different device may be used to make one or more recommendations for actions to improve outcomes44); [“The sensing kit of claim 49, wherein the plurality of discrete sensors comprises a first sensor and a second sensor both configured to detect a target analyte, wherein the first sensor has a higher sensitivity than the second sensor”, said kit facilitating “enhance[d] sensitivity in detection and monitoring of different target analytes45” by allowing the processing module to “selectively activate a greater number”46 of sensors when higher precision is required47: different sensors offer different sensitivities (Claim 55, 61), enabling the confirmation of analyte presence and concentration (Claim 65), which feeds back into the recommendation engine (Claim 48) which is configured to “prescribe certain corrective or mitigative actions to the subject, based on the detected levels of the one or more target analytes”, facilitating a confirmation of analyte levels by using a first and second sensor48, enabling prompt advisory of a patient regarding corrective actions]
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 Kutzko, including mechanism(s) [a] as taught by Gudibande. One of ordinary skill would have been so motivated to employ said mechanism(s) to facilitate a confirmation of different analyte levels49, providing additional data, enabling prompt advisory of a patient regarding corrective actions.
Conclusion
The prior art made of record50 and NOT relied upon is considered pertinent to applicant's disclosure: Ohnemus51:
In one or more implementations, the present application includes a system and method to classify user activity. A passive tracking device, a processor configured to receive information from the tracking device, and a database are disclosed, in which the database is accessible by the processor and stores tracking device information, user profile information and external information. The processor is configured to execute instructions that cause the processor to perform various steps, such as to define a first activity unit having a first start time that corresponds to detection of the user being engaged in an activity, and monitor the tracking device information, the external information or both. The processor is further configured to establish a first end time of the first activity unit using the monitored information, and automatically ascribe a classification of the first activity unit. The classification of the first activity unit is output to a display of a computing device, and the classification of the first activity unit is stored in the database. Moreover, a user interface is provided that includes selectable options associated with the first activity unit. Thereafter, in response to at least a received selection of at least one of the selectable options, the classification is revised by: joining the first activity unit and a second activity unit having a second start time and a second end time, such that the revised classification has a start time equal to the first start time and an end time equal to the second end time. Further, the first activity unit is merged with a second activity unit having a second start time and a second end time, such that the revised classification has a start time equal to the first start time and an end time equal to the second end time. Alternatively, the first activity unit is divided into at least two activity units, each of at least two activity units having a different respective start time and a different respective end time. The revised classification is output to a display of a computing device, the revised classification is stored in the database.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL EZEWOKO whose telephone number is 571 272 7850. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fonya Long can be reached on 571 270 5096. The fax phone number for the organization where this application or proceeding is assigned is 571-273-7850.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MICHAEL I EZEWOKO/Primary Examiner, Art Unit 3682
1 Claim(s) 1-12
2 Claim(s) 13-16
3 Claim(s) 17-20
4 US 10,991,463 (primary reference); See Form 892
5 WO 2019/183279 PCT/0S2019/023255; See Form 892
6 43:46-52
7 43:49-50
8 43:58-44:15
9 43:65
10 44:1-16
11 42:3-8
12 42:4-5
13 42:8
14 42:12-33
15 44:1-6
16 44:3
17 44:6-14
18 Consistent with Applicant specification, ¶8
19 Page 63
20 Page 63
21 Consistent with Page 63 with regard to claim 58’s multiplexed configurations
22 Page 63
23 ¶16: different multiplexed configurations permit a plurality of different target analytes to be detected from a sample of the subject collected on the device when the subject is wearing the device or in proximity to the device
24 42:3-8
25 42:4-5
26 42:8
27 42:12-33
28 44:1-6
29 44:3
30 44:6-14
31 Page 63
32 Page 63
33 Consistent with Page 63 with regard to claim 58’s multiplexed configurations
34 Page 63
35 ¶16: different multiplexed configurations permit a plurality of different target analytes to be detected from a sample of the subject collected on the device when the subject is wearing the device or in proximity to the device
36 34:7-32
37 43:46-52
38 43:49-50
39 43:47-15
40 42:3-8
41 42:4-5
42 42:8
43 42:12-33
44 Consistent with Applicant specification, ¶8
45 Page 63
46 Page 63
47 Consistent with Page 63 with regard to claim 58’s multiplexed configurations
48 Page 63
49 ¶16: different multiplexed configurations permit a plurality of different target analytes to be detected from a sample of the subject collected on the device when the subject is wearing the device or in proximity to the device
50 Please see Form 892 for complete listing
51 US 2018/0350451; Please see Form 892 for complete listing
Prosecution Insights