DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Objections
Claim 1 objected to because of the following informalities:
The first mention of “SWCNT sensors” in claim 1 should be “single wall continuous nanotube sensors (SWCNT)” as is proper when using abbreviations .
The indentation of the paragraph regarding Bayesian Network makes it unclear if the BN is part of the AI models, or if it is separate due to the indent being different than the other AI models. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1-2 and 4-16 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 contains “a chemiresistor sensor module disposed in a breath sampling chamber of the housing, including one or more chemiresitive gas sensors and configured to, at least in part, gather SWCNT sensor data from one or more SWCNT sensors”. The published specification fails to provide support for one or more chemiresitive gas sensors in addition to SWCNT sensors. The specification only provides support for use of SWCNT sensors. Paragraphs [0012-0014] of the published specification merely teaches “SWCNT sensors”.
Claims not explicitly rejected above are rejected because they depend from claims rejected above as failing to comply with the written description requirement.
Claims 1-2 and 4-16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
. Claim 1 states that the chemiresistive module includes “one or more chemiresistive gas sensors and configured to gather SWCNT sensor data from one or more SWCNT sensors.” It is unclear if the SWCNT sensor is a type of chemiresistive gas sensor, or if there are both chemiresistive sensors and SWCNT sensors within the module. For purposes of examination the claim is being interpreted as “a chemiresistor sensor module disposed in a breath sampling chamber of the housing, comprising one or more SWCNT sensors configured to, at least in part, gather SWCNT sensor data”.
Furthermore, claim 1 it is unclear if the “at least one pair of interdigitated electrodes fabricated by embedding the electrodes on a printed circuit board (PCB) substrate with a finger gap size of 200 m and depositing chemically functionalized carbon nanotubes between the electrodes” are the SWCNT sensors mentioned earlier in the claim, or something separate. According to the specification these appear to just be the specifics of the SWCNT sensors. For purposes of examination the “at least one pair of interdigitated electrodes fabricated by embedding the electrodes on a printed circuit board (PCB) substrate with a finger gap size of 200 m and depositing chemically functionalized carbon nanotubes between the electrodes” are the SWCNT sensors . The same issue is present in claim 7.
Claim 1 recites the limitation "third-party fitness app data" on page 4 line 12. There is insufficient antecedent basis for this limitation in the claim. It is recommended that the claim language of claim 2 is added into claim 1 to fix this issue.
In claim 1 it is unclear if the remote server is required or not in this system claim. The claim merely says that the communication module is operable to send the data to a remote server, but that in of itself does not require that the remote server that carries out the AI models to be part of the system. As there is no positive recitation of a remote server, it is unclear if it is required or not. The examiner encourages the applicant amend the claim to positively recite the remote server.
Regarding claim 1, the phrase " including but not limited to" renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. See MPEP § 2173.05(d). If the server uses the listed AI models and could use more in addition, then claim should amended to say “using a combination of AI models comprising:”
Claims not explicitly rejected above are rejected because they depend from claims rejected above as indefinite.
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 1-2 and 4-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. A streamlined analysis of claim 1 follows.
Regarding claim 1, the claim recites a concrete thing, consisting of parts, or of certain devices and combination of devices, including a user interface screen to display the compiled sensor data. Thus, the claim is directed to a machine, which is one of the statutory categories of invention.
The claim is then analyzed to determine whether it is directed to any judicial exception. Using a Bayesian Network (BN), to analyze and compile, comprehensively, one or more of the first, second, and third outputs and create a comprehensive assessment of the athletic performance and recovery of a human subject. This step describes a concept performed in the human mind (including an observation, evaluation, judgment, opinion). Thus, the claim is drawn to a Mental Process, which is an Abstract Idea. According to section 2106.05(f) of the MPEP, merely using a computer as a tool to perform an abstract idea does not integrate the Abstract Idea into a practical application.
Next, the claim as a whole is analyzed to determine whether the claim recites additional elements that integrate the judicial exception into a practical application. The claim fails to recite an additional element or a combination of additional elements to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limitation on the judicial exception. Claim 1 recites a memory module configured to store the collected sensor data; a communication module operable to transmit collected data from the sensor modules to a mobile communication device; and a user interface screen to display the compiled sensor data., which are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)). The storing, transmitting, and display of the data does not provide an improvement to the technological field, the method does not effect a particular treatment or effect a particular change based on the displayed data, nor does the method use a particular machine to perform the Abstract Idea.
Next, the claim as a whole is analyzed to determine whether any element, or combination of elements, is sufficient to ensure that the claim amounts to significantly more than the exception. Claim 1 also includes a Convolutional Neural Network (CNN), to analyze the chemiresistor sensor module data, including the SWCNT sensor data, and extract relevant features related to discreet molecules in a gas sample as a first output; a Recurrent Neural Network (RNN), to analyze integrated biometric sensor data and capture the temporal dynamics of physiological signals from the integrated sensors as a second output; and a Gradient Boosting Tree (GBT), to analyze third-party fitness app data and identify patterns related to exercise intensity, duration, and type as a third output. Besides the Abstract Idea, the claim recites additional components of a mouthpiece for collecting a breath sample, a chemiresistor sensor module to detect VOCs within the breath sample, a plurality of integrated biometric sensors to detect biometric data, and a first communication interface arranged to receive data from the chemoresistor module, which are all abstract ideas in the form of mental processes carried out by a computer. Collecting a breath sample using a mouthpiece and generating breath sample data using a chemiresistor sensor, as well as collecting biometric data using biometric sensors is well-understood, routine and conventional activity for those in the field of medical diagnostics. Further, the detecting and receiving steps are each recited at a high level of generality such that it amounts to insignificant presolution activity, e.g., mere data gathering step necessary to perform the Abstract Idea. When recited at this high level of generality, there is no meaningful limitation, such as a particular or unconventional step that distinguishes it from well-understood, routine, and conventional data gathering and comparing activity engaged in by medical professionals prior to Applicant's invention. Furthermore, it is well established that the mere physical or tangible nature of additional elements such as the obtaining and comparing steps do not automatically confer eligibility on a claim directed to an abstract idea (see, e.g., Alice Corp. v. CLS Bank Int'l, 134 S.Ct. 2347, 2358-59 (2014)). Further, according to section 2106.05(f) of the MPEP, merely using a computer as a tool to perform an abstract idea does not integrate the Abstract Idea into a practical application.
Consideration of the additional elements as a combination also adds no other meaningful limitations to the exception not already present when the elements are considered separately. Unlike the eligible claim in Diehr in which the elements limiting the exception are individually conventional, but taken together act in concert to improve a technical field, the claim here does not provide an improvement to the technical field. Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claim as a whole does not amount to significantly more than the exception itself. The claim is therefore drawn to non-statutory subject matter.
The dependent claims also fail to add something more to the abstract independent claims as they generally abstract ideas in the form of mathematical concepts and mental processes carried out by a computer. The analyzation of the data recited in the independent claim maintains a high level of generality even when considered in combination with the dependent claims.
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.
Claim(s) 1, 4, and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reddy (US 11045111 B1) in view of Erdman (US 20190254538 A1 - previously cited) in view of Telfort (US 20110213274 A1- previously cited) in view of Agarwal (US 20150295562 A1- previously cited) in view of Anushiravani (US 20200388287 A1 ) in view of Capps (US 20210313066 A1) in view of Heeger (US 20180014784 A1) in view of Thomson (US 20210183063 A1).
In regards to claim 1 Reddy teaches a system, device, and method for athletic readiness and recovery profiling, comprising:
a mouthpiece connected to a housing, the mouthpiece operable to receive the exhaled breath of a human subject (Fig. 1 mouthpiece 106);
a chemiresistor sensor module disposed in a breath sampling chamber of the housing comprising SWCNT sensors (Col 9 lines 35-37, Col 10 lines 60-64 “electrochemical sensors”, (Col 11 lines 52-56) (Col 12 lines 1-3 nanotubules)),
the sensor module operable to detect one or more volatile organic compounds (VOCs) associated with athletic readiness and recovery in the exhaled breath of a human subject, and further operable to collect data associated with the detection of the one or more VOCs (Col 10 48-53),
a chemiresistor sensor module wherein the sensor module comprises of at least one pair of interdigitated electrodes fabricated by embedding the electrodes on a printed circuit board (PCB) substrate (Col 11 lines 52-56) and depositing chemically functionalized carbon nanotubes between the electrodes (Col 12 lines 1-3 nanotubules) ;
a first communication interface arranged to receive a plurality of gas measurements generated by at least one chemiresistive gas sensor of a breath analysis device (Col 9 Lines 57-64; Col 13 lines46-50; communication module 110 receives sensor data);
a microprocessor to gather and analyze data from the connected sensors that is attached to a memory module configured to store the collected sensor data (Col 9 Lines 45-64; Col 13 lines 46-50 communication module 110 processes data and would inherently have a microprocessor);
a communication module disposed in the housing and in communication with the microprocessor, memory module, sensor module, operable to transmit collected data from the sensor modules to a mobile communication device associated with the human subject (Col 9 Lines 45-64 communication module 110 processes and transmits to the mobile communication device and is in communication with memory and sensors);
and a user interface screen to display the compiled sensor data (Col 4 line 48 Display device).
Reddy does not explicitly teach the interdigitated electrodes having a finger gap size of 200 pm. Reddy does teach changing the width of the finger gaps can have an impact on sensor performance (Col 12 lines 18-30). It is noted that Applicant has not disclosed in the specification that the claimed 200 pm gap size provides an advantage or unexpected result. As such, it would have been obvious, through routine experimentation, to determine the optimum finger gap size of interdigitated electrodes of Reddy. Furthermore, “where the general conditions of a claim are disclosed in the prior art, it is not inventive to discover the optimum or workable ranges by routine experimentation.” In re Aller, 220 F.2d 454, 456, 105 USPQ 233, 235 (CCPA 1955).
Reddy fails to teach a plurality of integrated biometric sensors including heart rate, blood pressure, EEG, bio-electrical impedance analysis, ECG, airflow, temperature, and humidity the sensors operable to collect biometric data from the human subject; a Convolutional Neural Network (CNN), operable to analyze the collected chemiresistor sensor module data and extract relevant features related to discreet molecules in a gas sample; a Recurrent Neural Network (RNN), operable to analyze integrated biometric sensor data and capture the temporal dynamics of physiological signals from the integrated sensors; a Gradient Boosting Tree (GBT), operable to analyze third-party fitness app data and identify patterns related to exercise intensity, duration, and type; and a Bayesian Network (BN), operable to integrate the outputs of the above models and create a comprehensive assessment of the athletic performance and recovery of a human subject.
Erdman teaches a breath sampling device comprising a plurality of integrated biometric sensors including heart rate, blood pressure, temperature, and humidity ([0009-0010]). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device of Reddy to include the biometric sensors of Erdman and have them be in communication with the communication module. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of measuring biometric data.
Reddy in view of Erdman fails to teach EEG, bio-electrical impedance analysis, ECG, and airflow sensors; a Convolutional Neural Network (CNN), operable to analyze the collected chemiresistor sensor module data and extract relevant features related to discreet molecules in a gas sample; a Recurrent Neural Network (RNN), operable to analyze integrated biometric sensor data and capture the temporal dynamics of physiological signals from the integrated sensors; a Gradient Boosting Tree (GBT), operable to analyze third-party fitness app data and identify patterns related to exercise intensity, duration, and type; and a Bayesian Network (BN), operable to integrate the outputs of the above models and create a comprehensive assessment of the athletic performance and recovery of a human subject.
Telfort teaches an acoustic breath analyzer with bio-electrical impedance analysis, ECG, and airflow sensors ([0071] [0066]). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device of Reddy in view of Erdman to include the biometric sensors of Telfort and have them be in communication with the communication module. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of measuring bio-electrical impedance analysis, ECG, and airflow.
Reddy in view of Erdman further in view of Telfort fails to teach EEG sensors; a Convolutional Neural Network (CNN), operable to analyze the collected chemiresistor sensor module data and extract relevant features related to discreet molecules in a gas sample; a Recurrent Neural Network (RNN), operable to analyze integrated biometric sensor data and capture the temporal dynamics of physiological signals from the integrated sensors; a Gradient Boosting Tree (GBT), operable to analyze third-party fitness app data and identify patterns related to exercise intensity, duration, and type; and a Bayesian Network (BN), operable to integrate the outputs of the above models and create a comprehensive assessment of the athletic performance and recovery of a human subject.
Agarwal teaches a breath analysis device comprising EEG sensors ([0036]). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device of Reddy in view of Erdman further in view of Telfort to include the EEG sensors of Agarwal and have them be in communication with the communication
Reddy in view of Erdman in view of Telfort in view of Agarwal fails to teach a Convolutional Neural Network (CNN), operable to analyze the collected chemiresistor sensor module data and extract relevant features related to discreet molecules in a gas sample; a Recurrent Neural Network (RNN), operable to analyze integrated biometric sensor data and capture the temporal dynamics of physiological signals from the integrated sensors; a Gradient Boosting Tree (GBT), operable to analyze third-party fitness app data and identify patterns related to exercise intensity, duration, and type; and a Bayesian Network (BN), operable to integrate the outputs of the above models and create a comprehensive assessment of the athletic performance and recovery of a human subject.
Anushiravani teaches a Convolutional Neural Network (CNN), operable to analyze raw data to extract features ([0093]). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the processor of Reddy in view of Erdman in view of Telfort in view of Agarwal to include a CNN like the one of Anushiravani configured to analyze the chemoreceptor sensor measurements and extract features related to the VOCs. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of extracting features related to VOCs in a user’s breath.
Reddy in view of Erdman in view of Telfort in view of Agarwal in view of Anushiravani fails to teach a Recurrent Neural Network (RNN), operable to analyze integrated biometric sensor data and capture the temporal dynamics of physiological signals from the integrated sensors; a Gradient Boosting Tree (GBT), operable to analyze third-party fitness app data and identify patterns related to exercise intensity, duration, and type; and a Bayesian Network (BN), operable to integrate the outputs of the above models and create a comprehensive assessment of the athletic performance and recovery of a human subject.
Capps teaches a Recurrent Neural Network (RNN), operable to analyze biometric sensor data and capture the temporal dynamics of physiological signals from the sensors ([0049][0057]). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the processor of Reddy in view of Erdman in view of Telfort in view of Agarwal in view of Anushiravani to include a RNN like the one of Capps configured to analyze the biometric sensor data capture the temporal dynamics of physiological signals from the sensors. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of the temporal dynamics related to physiological signals relating to the user.
Reddy in view of Erdman in view of Telfort in view of Agarwal in view of Anushiravani in view of Capps fails to teach a Gradient Boosting Tree (GBT), operable to analyze third-party fitness app data and identify patterns related to exercise intensity, duration, and type; and a Bayesian Network (BN), operable to integrate the outputs of the above models and create a comprehensive assessment of the athletic performance and recovery of a human subject.
Heeger teaches a Gradient Boosting Tree (GBT), operable to analyze data and identify patterns ([0056]). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the processor of Reddy in view of Erdman in view of Telfort in view of Agarwal in view of Anushiravani in view of Capps to include a GBT like the one of Heeger. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of the temporal dynamics related to identifying patterns within the data.
Reddy in view of Erdman in view of Telfort in view of Agarwal in view of Anushiravani in view of Capps in view of Heeger fails to teach a Bayesian Network (BN), operable to integrate the outputs of the above models and create an assessment of the athletic performance and recovery of a human subject. Thomson teaches integrating parameters using a Bayesian Network and create an assessment of the athletic performance and recovery of a human subject ([0056] [0059] physical determination is an assessment of the athletic performance and recovery of a human subject)). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the processor of Reddy in view of Erdman in view of Telfort in view of Agarwal in view of Anushiravani in view of Capps in view of Heeger to use a Bayesian Network to combine the outputs of the machine learning models in order to output an assessment of the athletic performance and recovery of a human subject like the method of Thomson. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of athletic performance of a user.
In regards to claim 4 modified Reddy teaches the system of claim 1, wherein the VOCs comprise one or more of acetone, ethane, pentane, isoprene, nitric oxide, hydrogen peroxide, carbon dioxide, hydrogen, inteluekin-6, dopamine, amyloid beta, water, lactic acid, acetaldehyde, ammonia, hydrogen sulfide, ferritin, hexane, c-reactive protein, and certain amino acids (Reddy Col 4 Lines 35-38).
In regards to claim 10 modified Reddy teaches the system of claim 1, wherein the sensor array contains at least two SWCNT nanostructure sensors (Reddy Col 4 Lines 20-34).
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reddy (US 11045111 B1) in view of Erdman (US 20190254538 A1 - previously cited) in view of Telfort (US 20110213274 A1- previously cited) in view of Agarwal (US 20150295562 A1- previously cited) in view of Anushiravani (US 20200388287 A1 ) in view of Capps (US 20210313066 A1) in view of Heeger (US 20180014784 A1) in view of Thomson (US 20210183063 A1) as applied to claim 1, further in view of Parker (US 20210183508 A1- previously cited).
In regards to claim 2 modified Reddy teaches the system of claim 1. Modified Reddy fails to teach a system wherein the communication device is further operable to gather biometric sensor data from third party health and fitness devices by means of application programming interface queries. Parker teaches obtaining data from third party health apps using an application programming interface ([0045] [0092]). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the communication device of modified Reddy to receive third party health data like the system of Parker. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of obtaining more biometric data relating to a subject.
Claim(s) 5-9, 11-12, and 14-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reddy (US 11045111 B1) in view of Erdman (US 20190254538 A1 - previously cited) in view of Telfort (US 20110213274 A1- previously cited) in view of Agarwal (US 20150295562 A1- previously cited) in view of Anushiravani (US 20200388287 A1 ) in view of Capps (US 20210313066 A1) in view of Heeger (US 20180014784 A1) in view of Thomson (US 20210183063 A1)- as applied to claim 1, further in view of Li (US 10566089 B1- previously cited).
In regards to claim 5 modified Reddy teaches the system of claim 1. Modified Reddy fails to teach a system wherein the micro-processor and memory are configured to perform the following steps: receiving a sequence of electrical parameter values measured from each nanostructure sensor of the plurality of nano sensors, each of the sequences corresponding to measured electrical values from a measurement mechanism; generating a normalized amplitude value for one of the measured electrical values measured from each of the plurality of nanostructure sensors to form a set of amplitude values for a sample gas; determining the presence of at least a first specified component in the sample gas by: comparing a normalized amplitude value for the first nanostructure sensor for the sample gas with a reference amplitude value for the first nanostructure sensor for the first specified component to generate a compared value for the first nanostructure sensor; repeating the comparing step for each of the other sensors of the plurality of nanostructure sensors to generate a set of the compared values; aggregating the compared values to generate a set of compared values, wherein the aggregating includes a weighted summation of the compared values, and based on the aggregated compared values, determining whether the specified component is likely present in the sample gas.
Li teaches a method with the following steps:
receiving a sequence of electrical parameter values measured from each nanostructure sensor of a plurality of nano sensors, each of the sequences corresponding to measured electrical values from a measurement mechanism (Col 3 lines 51-56);
generating a normalized amplitude value for one of the measured electrical values measured from each of the plurality of nanostructure sensors to form a set of amplitude values for the sample gas (Col 5 Lines 41-46);
determining the presence of at least a first specified component in the sample gas by: comparing a normalized amplitude value for the first nanostructure sensor for the sample gas with a reference amplitude value for the first nanostructure sensor for the first specified component to generate a compared value for the first nanostructure sensor; repeating the comparing step for each of the other sensors of the plurality of nanostructure sensors to generate a set of the compared values (Col 3 Lines 58-63);
aggregating the compared values to generate a set of compared values, wherein the aggregating includes a weighted summation of the compared values, and based on the aggregated compared values, determining whether the specified component is likely present in the sample gas (Col 3 lines 6-17).
It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the communication module of Modified Reddy to carry out the method of Li. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of determining whether a specified component is likely present in the sample gas.
In regards to claim 6 modified Reddy in view of Li fails to teach the system of claim 1, wherein at least the first SWCNT sensor and the second SWCNT sensor of the sensor array are functionalized with different reactive chemicals to create a differential in selectivity and sensitivity to a specified gas component. Li teaches the a SWCNT sensor and a second SWCNT sensor of a sensor array are functionalized with different reactive chemicals to create a differential in selectivity and sensitivity to a specified gas component (Col 1 Lines 56-61; Col 4 lines 28-33). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the sensors of modified Reddy to be functionalized to be sensitive to different components like the sensors of Li . Doing so would merely be combining prior art elements according to known methods to yield the predictable result of sensing multiple gas components.
In regards to claim 7 modified Reddy in view of Li fails to teach the system of claim 1, wherein each of the SWCNT sensors in the sensor array are differently sensitive to at least two specified component gases. Li teaches the a SWCNT sensor and a second SWCNT sensor of a sensor array are functionalized with different reactive chemicals to create a differential in selectivity and sensitivity to a specified gas component (Col 4 lines 28-33). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the sensors of modified Reddy to be functionalized to be sensitive to different components like the sensors of Li . Doing so would merely be combining prior art elements according to known methods to yield the predictable result of sensing multiple gas components.
In regards to claim 8 modified Reddy teaches the system of claim 1. Reddy fails to teach a system further comprising a measurement mechanism electrically coupled to each of the individual SWCNT nanostructures operable for the measuring the electrical parameter values generated by each nanostructure sensor in response to exposure to a sample gas. Li teaches a system further comprising a measurement mechanism electrically coupled to each of the individual SWCNT nanostructures operable for the measuring the electrical parameter values generated by each nanostructure sensor in response to exposure to the sample gas (Li Col 5 Lines 41-46). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the communication module of Modified Reddy to carry out the method of Li. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of determining whether a specified component is likely present in a sample gas.
In regards to claim 9 modified Reddy in view of Li teaches the system of claim 1, wherein the electrical parameter values include one or more of electrical current voltage difference, resistance, impedance, conductance and capacitance (Li Col 2 Lines 43-45).
In regards to claim 11 modified Reddy teaches the of claim 1, Reddy fails to teach a system wherein the plurality of SWCNT sensors is refreshed for repeated testing after being exposed to ultraviolet lights from light-emitting diodes and a heating element for a duration of 1 to 100 seconds. Li teaches refreshing sensors for repeated testing by being exposed to ultraviolet lights from light-emitting diodes and a heating element for a duration of 1 to 100 seconds (Col 4 Lines 49-55). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of modified Reddy in view of Li to refresh the sensors using the method of Li . Doing so would merely be combining prior art elements according to known methods to yield the predictable result of recycling sensors after a use.
In regards to claim 12 modified Reddy in view of Li teaches the system of claim 5, wherein the step of determining whether the specified component is likely present in a sample gas includes the steps of generate an error value based on the aggregated compared values; comparing the error value with a threshold error value; and determine presence of the sampled gas if the error value is less than the threshold error value (Li Col 8 line 67 – Col line 6).
In regards to claim 14 modified Reddy teaches the system of claim 1. Reddy fails to teach the micro-processor and memory systems further configured to perform the steps of: analyzing a reference sample gas, the reference gas comprising a mixture of healthy or optimal sample gas having a known concentration of a specified component, the analyzing comprising determination of two or more electrical parameter values that associate the known concentration with a measured electrical value for the reference sample gas; and determining a concentration of the specified component in a sample gas based on: the set of measured electrical values for the sampled gas, and the two or more parameter values as determined in the analyzing the reference sample gas.
Li teaches a method of analyzing a reference sample gas, the reference gas comprising a mixture of healthy or optimal sample gas having a known concentration of a specified component, the analyzing comprising determination of two or more electrical parameter values that associate the known concentration with a measured electrical value for the reference sample gas (Col 2 lines 36-42); and determining a concentration of the specified component in a sample gas based on: the set of measured electrical values for the sampled gas, and the two or more parameter values as determined in the analyzing the reference sample gas (Col 3 Lines 58-63). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the communication module of Modified Reddy to carry out the method of Li. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of determining whether a specified component is likely present in the sample gas.
In regards to claim 15 modified Reddy in view of Li teaches the system of claim 14, wherein the process of identifying two or more parameter values that link the measured electrical value with the known concentration involves determining either a linear or quadratic relationship between the known concentration and the measured electrical value (Li Col 12-17).
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reddy (US 11045111 B1) in view of Erdman (US 20190254538 A1 - previously cited) in view of Telfort (US 20110213274 A1- previously cited) in view of Agarwal (US 20150295562 A1- previously cited) in view of Anushiravani (US 20200388287 A1 ) in view of Capps (US 20210313066 A1) in view of Heeger (US 20180014784 A1) in view of Thomson (US 20210183063 A1) as applied to claim 1, further in view of Odom (US 20240081675 A1- previously cited) as evidenced Miekisch (“Diagnostic potential of breath analysis—focus on volatile organic compounds” - previously cited).
In regards to claim 13 modified Reddy teaches the system in claim 1, wherein a sample gas is received from the user. Reddy fails to teach a sample gas being received from the user by inhaling a deep breath and exhaling the contents of the lung completely in one continuous breath; wherein the highest concentration of VOC's is found in the alveolar air that is exhaled at the very end of the sample. Odom teaches inhaling deeply and exhaling completely to collect a breath sample ([0049]). It would have been prima facie obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the breath collection step of Modified Reddy to include inhaling a deep breath and exhaling like the method of Odom. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of exhaling the contents of the lung completely. By exhaling completely, the end of the breath sample would include alveolar air which is known to have the highest concentration of VOCs. This is evidenced by Miekisch that teaches the highest concentration of VOC's is found in the alveolar air that is exhaled at the very end of a breath sample (Pages 30-31 Section 3.1 Sampling).
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reddy (US 11045111 B1) in view of Erdman (US 20190254538 A1 - previously cited) in view of Telfort (US 20110213274 A1- previously cited) in view of Agarwal (US 20150295562 A1- previously cited) in view of Anushiravani (US 20200388287 A1 ) in view of Capps (US 20210313066 A1) in view of Heeger (US 20180014784 A1) in view of Thomson (US 20210183063 A1) in view of Li (US 10566089 B1- previously cited) as applied to claim 14, further in view of King (US 20170036065 A1- previously cited) further in view of Eleftheriou (US 20220061726 A1- previously cited).
In regards to claim 16 modified Reddy teaches system of claim 14. Modified Reddy Fails to teach the processor and memory system is further configured to perform the steps of: determining the athletic fitness level of a user based upon specified gas components as compared to the relative electrical values of gas samples provided by elite athletes that have completed similar testing as part of the comparison matrix; determining the athletic fitness level of a user based on a data compilation of biometric sensor readings over a period of time as compared to a database of similar biometric readings from elite athletes as part of the comparison matrix; and validating the fitness level of a user by gathering fitness data from third party fitness tracking devices to validate or invalidate data from integrated sensors disposed in the housing of the presented invention.
King teaches determining a fitness level of a user by comparing values to a reference dataset that includes correlated information for a range of individuals of different, known fitness levels ([0011]). It would have been prima facie obvious to a person of ordinary skill in the art to modify the processor of Reddy to compare the gas components and biometric sensor readings to a reference dataset to determine a fitness level as taught by King. It would have also been obvious to include readings by “elite athletes” within the data set as they would be at the highest end of a range of fitness levels. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of determining the athletic fitness level of a user.
Modified Reddy in view of King fails to teach validating the fitness level of a user by gathering fitness data from third party fitness tracking devices to validate or invalidate data from integrated sensors disposed in the housing of the presented invention. Eleftheriou teaches using third party data to validate biosignal data ([0024]). It would have been prima facie obvious to a person of ordinary skill in the art to modify the processor of Reddy to use third party fitness data to ensure the sensor data is within an acceptable range like the system of Eleftheriou. Doing so would merely be combining prior art elements according to known methods to yield the predictable result of validating the sensor data.
Response to Arguments
Applicant’s arguments, see remarks, filed 11/17/2025, in regards to the 35 U.S.C. 112(b) rejections of claims 1-17 have been fully considered and are persuasive. The 35 U.S.C. 112(b) rejections of claims 1-17 have been withdrawn. However, new 35 U.S.C. 112(b) rejections have been made in response to amendment.
Applicant's arguments filed 11/17/2025, in regards to the 35 U.S.C. 101 rejections of claims 1-16 have been fully considered but they are not persuasive. The applicant contends that the steps performed in claim 1 cannot be performed in the human mind. The examiner disagrees. A human could analyze data by looking at it and decide which features are meaningful, identify the temporal dynamics of data, and identify patterns. A human can also analyze and compile outputs to create an assessment of athletic performance of a subject. The artificial intelligence models are using computers as tools to carry out these ideas that can be performed in the human mind.
Applicant’s arguments, see remarks, filed 11/17/2025, in regards to the 35 U.S.C. 103 rejections of claims 1-17 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Reddy (US 11045111 B1) in view of Erdman (US 20190254538 A1 - previously cited) in view of Telfort (US 20110213274 A1- previously cited) in view of Agarwal (US 20150295562 A1- previously cited) in view of Anushiravani (US 20200388287 A1 ) in view of Capps (US 20210313066 A1) in view of Heeger (US 20180014784 A1) in view of Thomson (US 20210183063 A1).
Conclusion
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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/LUCY EPPERT/Examiner, Art Unit 3791
/ADAM J EISEMAN/Primary Examiner, Art Unit 3791