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
Claims 9-10, 13, and 17 are objected to because of the following informalities:
Claim 9 line 1 should recite “user-defined inputs comprise”;
Claim 10 line 1 should recite “user-defined inputs comprise a fluid”;
Claim 13 line 1 should recite “user-defined inputs comprise”;
Claim 17 line 1 should recite “a- device type”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 6 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 6 recites the limitation "the gender" in line 1. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, the aforementioned element will be interpreted as “…wherein the details comprise a gender of the user for which the urinary catheter is intended to be used”.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent Claim 1 recites:
A method for identifying urological health information, comprising:
storing user-defined inputs provided by a user;
monitoring a fluid volume of urine processed by the user;
storing parameters regarding the fluid volume of urine;
utilizing a machine learning algorithm to provide processed data based on the user-defined inputs and stored parameters; and
providing feedback based on the processed data.
Step 1:
The examiner finds claims 1-20 drawn to a method.
Step 2A Prong 1:
The above claim limitations constitute an abstract idea that is part of the Mathematical Concepts and/or Mental Processes group identified in the 2019 Revised Patent Subject Matter Eligibility Guidance published in the Federal Register (84 FR 50) on January 7, 2019.
“A mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words ….” October 2019 Update: Subject Matter Eligibility, II. A. i. “[T]here are instances where a formula or equation is written in text format that should also be considered as falling within this grouping.” Id. at II. A. ii. “[A] claim does not have to recite the word “calculating” in order to be considered a mathematical calculation.” Id. at II. A. iii. See for example, SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163-65 (Fed. Cir. 2018).
The claimed step of processing recite a mental process capable of being performed in the human mind.
The examiner notes the steps of “storing” inputs/parameters, “monitoring” fluid volume, and “providing” feedback are insignificant extra-solution activities, such as mere data gathering/output. The step of utilizing “processed” data is an example of a mental process capable of being performed in the human mind. For example, the human mind can take in raw sensory data and process it into a thought or idea.
The claimed step of processing can be practically performed in the human mind using mental steps or basic critical thinking, which are types of activities that have been found by the courts to represent abstract ideas.
“[T]he ‘mental processes’ abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.” MPEP 2106.04(a)(2) III. The pending claims merely recite steps for estimation that include observations, evaluations, and judgments.
Examples of ineligible claims that recite mental processes include:
• a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind,
Electric Power Group, LLC v. Alstom, S.A.;
• claims to “comparing BRCA sequences and determining the existence of alterations,” where the claims cover any way of comparing BRCA sequences such that the comparison steps can practically be performed in the human mind,
University of Utah Research Foundation v. Ambry Genetics Corp.
• a claim to collecting and comparing known information, which are steps that can be practically performed in the human mind, Classen Immunotherapies, Inc. v. Biogen IDEC.
See p. 7-8 of October 2019 Update: Subject Matter Eligibility.
Regarding the dependent claims 2-20, the dependent claims are directed to either 1) steps that are also abstract or 2) additional data output that is well-understood, routine and previously known to the industry. Although the dependent claims are further limiting, they do not recite significantly more than the abstract idea. A narrow abstract idea is still an abstract idea and an abstract idea with additional well-known equipment/functions is not significantly more than the abstract idea.
Step 2A Prong 2:
This judicial exception (abstract idea) in Claims 1--20 is not integrated into a practical application because:
• The abstract idea amounts to simply implementing the abstract idea on a computing device. For example, the recitations regarding the generic computing components for processing merely invoke a computer as a tool.
• The data-gathering step (monitoring) and the data-output step (providing feedback) do not add a meaningful limitation to the method as they are insignificant extra-solution activity.
• There is no improvement to a computer or other technology. “The McRO court indicated that it was the incorporation of the particular claimed rules in computer animation that "improved [the] existing technological process", unlike cases such as Alice where a computer was merely used as a tool to perform an existing process.” MPEP 2106.05(a) II. The claims recite a computing device that is used as a tool for processing.
• The claims do not apply the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition. Rather, the abstract idea is utilized to determine a relationship among data to estimate bio-information.
• The claims do not apply the abstract idea to a particular machine. “Integral use of a machine to achieve performance of a method may provide significantly more, in contrast to where the machine is merely an object on which the method operates, which does not provide significantly more.” MPEP 2106.05(b). II. “Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more.” MPEP 2106.05(b) III. The pending claims utilize a computing device for processing. The claims do not apply the obtained prediction to a particular machine. Rather, the data is merely output in a post-solution step.
Step 2B:
The additional elements are identified as follows: microphone, phone, watch, sensor, machine learning algorithm.
Those in the relevant field of art would recognize the above-identified additional elements as being well-understood, routine, and conventional means for data-gathering and computing, as demonstrated by
• Applicant’s specification (e.g. par. 0024) which discloses that the microphone are typically available through common input devices such as tablets, smartphones, and smartwatches;
• Applicant’s specification (e.g. par. 0024) which discloses that “(T)he monitoring device 162 may be any type of sensor capable of identifying a state of a user”;
• Recentive Analytics, Inc. v. Fox Corp., Case No. 2023-2437 (Apr. 18, 2025) which found that patents that merely apply generic machine learning techniques to new data environments or fields of use—without disclosing specific improvements to the machine learning models or methods themselves—are not patent-eligible under § 101;
• Applicant’s specification par. 0026 which discloses “The machine-learning algorithm may utilize any machine learning and/or artificial intelligence algorithm…”;
• Applicant’s Background in the specification.
Thus, the claimed additional elements “are so well-known that they do not need to be described in detail in a patent application to satisfy 35 U.S.C. § 112(a).” Berkheimer Memorandum, III. A. 3.
Furthermore, the court decisions discussed in MPEP § 2106.05(d)(lI) note the well-understood, routine and conventional nature of such additional generic computer components as those claimed. See option III. A. 2. in the Berkheimer memorandum.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the units associated with the steps do not add meaningful limitation to the abstract idea. A computer, processor, memory, or equivalent hardware is merely used as a tool for executing the abstract idea(s). The process claimed does not reflect an improvement in the functioning of the computer.
When considered in combination, the additional elements (i.e. the generic computer functions and conventional equipment/steps) do not amount to significantly more than the abstract idea. Looking at the claim limitations as a whole 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 or improves any other technology. Their collective functions merely provide conventional computer implementation.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1 and 14 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Lee (US 20220215960 A1).
Regarding claim 1, Lee teaches a method for identifying urological health information, comprising:
storing user-defined inputs provided by a user [0056 “…the urinary system data 20 stored in advance in the database 490 may be learned, the urinary system data 20 including the age, urination pattern (e.g. number of urinations, residual urine volume, number of urinary urgencies, and number of night urinations), uroflowmetry index, prostate symptom score, past medical history and voiding efficacy of the examinee”];
monitoring a fluid volume of urine processed by the user [0056 “…residual urine volume…”];
storing parameters regarding the fluid volume of urine [0056 “…residual urine volume…”];
utilizing a machine learning algorithm to provide processed data based on the user-defined inputs and stored parameters [0060 “…the present disclosure may further include a first neural network 411 for predicting the degree of BOO and a second neural network 412 for predicting the degree of DUA”]; and
providing feedback based on the processed data [Fig. 8 and 9, par. 0049 “…the user terminal 80 indicates a device which can receive the prediction result data 30 and display the prediction result data 30 to a user”].
Regarding claim 14, Lee teaches the method of claim 1, wherein the user-defined inputs comprise one or more of gender, age [0056], weight, height, specific injury, frequency of device use, and survey data.
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.
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.
Claims 2-3 are rejected under 35 U.S.C. 103 as being unpatentable over Lee as applied to claim 1 above, and further in view of Conner (US 20170119300 A1).
Regarding claim 2, Lee teaches the method of claim 1, wherein the method comprises monitoring the volume of urine, but fails to teach the volume of urine is processed by a user through a urinary catheter.
Conner teaches the volume of urine is processed by a user through a urinary catheter [0049 “The volume of urine entering the urine meter 14 from the catheter in communication with the patient may be determined by a fluid level assembly that can include a sensor 42, such as an ultrasound or capacitive sensor”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and incorporate the teachings of Conner to include the volume of urine is processed by a user through a urinary catheter. Doing so configures the system to collect clean, contaminant-free urine sample, relieve obstruction in the urinary tract (such as kidney stones), and to provide an accurate urine output measurement which is essential for monitoring fluid balance, kidney function, and/or treatment response.
Regarding claim 3, Lee and Conner teach the method of claim 2, wherein the combination of Lee and Conner teach using a microphone to record audio during a catheterization process to determine the fluid volume of urine transferred during the catheterization process [Conner par. 0050 “…the ultrasonic sensor sends a brief chirp with an ultrasonic speaker and makes it possible for the integrated circuit associated with the ultrasonic sensor to measure the time it takes the echo to return to its ultrasonic microphone after rebounding from the float”, see also 0050 “…you can then use the speed of sound in air to calculate the distance in centimeters, inches, feet, volume, etc. of the float from the sensor thereby determining the fluid volume in the urine meter”] with the machine learning algorithm [Lee 0060 “…the present disclosure may further include a first neural network 411 for predicting the degree of BOO and a second neural network 412 for predicting the degree of DUA”].
Claims 4 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Lee and Conner as applied to claim 3 above, and further in view of Liu (US 20200108192 A1).
Regarding claim 4, Lee and Conner teach the method of claim 3, wherein Lee teaches storing details about the patient [Lee par. 0056 “age”] and the combination of Lee and Conner teach considering details to determine fluid volume of urine [Lee 0056 “residual urine volume”] transferred during the catheterization process [0049 “The volume of urine entering the urine meter 14 from the catheter in communication with the patient may be determined by a fluid level assembly that can include a sensor 42, such as an ultrasound or capacitive sensor”], but fail to teach the details are about the urinary catheter.
Liu teaches the details are about the urinary catheter [0039 “…the data stored in the repository 140 may have various attributes such as gender, age, ejection fraction, type of catheter used (e.g. Swan-Ganz)…”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and Conner and incorporate the teachings of Liu to include the details are about the urinary catheter. Doing so configures the system to determine “how various types of features and treatments can be combined to determine the treatment with the highest predicted survival rate”, as recognized by Liu para. 0039.
Regarding claim 6, Lee, Conner, and Liu teach the method of claim 4, further wherein the details comprise the gender for which the urinary catheter is intended to be used [Liu par. 0039 “…the data stored in the repository 140 may have various attributes such as gender, age…”].
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Lee, Conner, and Liu as applied to claim 4 above, and further in view of Maher (US 20200060545 A1).
Regarding claim 5, Lee, Conner, and Liu teach the method of claim 4, wherein Liu teaches the details are about the catheter [Liu 0039 “…the data stored in the repository 140 may have various attributes such as gender, age, ejection fraction, type of catheter used (e.g. Swan-Ganz)…”], but fail to explicitly teach the details comprise a urinary catheter gauge.
Maher teaches the details comprise a urinary catheter gauge [par. 0121 “…system 100 may also collect and store data on one or more of (…), Catheter size/gauge…”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee, Conner, and Liu and incorporate the teachings of Maher to include the details comprise a urinary catheter gauge. Doing so configures the system to record and consider information about the catheter that may skew acquired data, thus providing for an accurate assessment of the patient’s condition.
Claims 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Lee and Conner as applied to claim 3 above, and further in view of Connor (US 20140349256 A1).
Regarding claim 7, Lee and Conner teach method of claim 3, wherein the method includes using a microphone [Conner par. 0050 “…the ultrasonic sensor sends a brief chirp with an ultrasonic speaker and makes it possible for the integrated circuit associated with the ultrasonic sensor to measure the time it takes the echo to return to its ultrasonic microphone after rebounding from the float”], but fail to teach the microphone is on a wristwatch.
Connor teaches the microphone is on a wristwatch [par. 0335 “…smart watch 201 can monitor (…) using one or more sensors selected from the group consisting of: (…), miniature microphone…”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and Conner and incorporate the teachings of Connor to include the microphone is on a wristwatch. Doing so configures the system to record audio signals from an accessible device, improving the accessibility in acquiring the audio signals.
Regarding claim 8, Lee and Conner teach method of claim 3, wherein the method includes using a microphone [Conner par. 0050 “…the ultrasonic sensor sends a brief chirp with an ultrasonic speaker and makes it possible for the integrated circuit associated with the ultrasonic sensor to measure the time it takes the echo to return to its ultrasonic microphone after rebounding from the float”], but fail to teach the microphone is on a phone.
Connor teaches the microphone is on a phone [par. 0189 “…a wearable device can automatically trigger a smart phone or other portable electronic device to start recording audio information using the smart phone's microphone…”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and Conner and incorporate the teachings of Connor to include the microphone is on a phone. Doing so configures the system to record audio signals from an accessible device, improving the accessibility in acquiring the audio signals.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Lee as applied to claim 1 above, and further in view of Kataria (US 20190027248 A1).
Regarding claim 9, Lee teaches the method of claim 1, wherein method stores user-defined inputs [0056 “…the urinary system data 20 stored in advance in the database 490 may be learned, the urinary system data 20 including the age, urination pattern (e.g. number of urinations, residual urine volume, number of urinary urgencies, and number of night urinations), uroflowmetry index, prostate symptom score, past medical history and voiding efficacy of the examinee”], but fails to explicitly teach the user-defined inputs comprises a survey identifying anxiety.
Kataria teaches the user-defined inputs comprises a survey identifying anxiety [par. 0055 “The time for the survey 414, the user response 408, and the user expression and anxiety 412 are all recorded in a user response storage 416”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and incorporate the teachings of Kataria to include the user-defined inputs comprises a survey identifying anxiety. Doing so configures the system to feed the acquired data “into an algorithm, which weighs respective elements of the user's stored data”, which provides for a more robust and accurate assessment of the acquired data, as recognized by Kataria par. 0055.
Claims 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Lee, Conner, and Liu as applied to claim 4 above, and further in view of Biswas (US 10557737 B2).
Regarding claim 10, Lee, Conner, and Liu teach the method of claim 4, wherein Lee teaches storing the user-defined inputs [Lee par. 0056 “…the urinary system data 20 stored in advance in the database 490 may be learned, the urinary system data 20 including the age, urination pattern (e.g. number of urinations, residual urine volume, number of urinary urgencies, and number of night urinations), uroflowmetry index, prostate symptom score, past medical history and voiding efficacy of the examinee”], but fails to explicitly teach the user-defined inputs comprises fluid intake volume.
Biswas teaches the user-defined inputs comprises fluid intake volume [col. 2 lns. 27-30 “…the user's fluid intake information may be stored at a centralized server allowing the user to access this information from several network-enabled devices in addition to the smart band”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee, Conner, and Liu and incorporate the teachings of Biswas to include the user-defined inputs comprises fluid intake volume. Doing so configures the system to incorporate additional data that provide for a more robust and accurate analysis of the patient’s condition.
Regarding claim 11, Lee, Conner, Liu, and Biswas teach the method of claim 10, wherein the combination further teaches determining a post-void residual volume [0056 “…the urinary system data 20 stored in advance in the database 490 may be learned, the urinary system data 20 including the age, urination pattern…, residual urine volume…”] with the machine learning algorithm [Lee 0012 “…learning the correlation between diagnosis result data and urinary system data acquired in advance and stored in a database, through a machine learning algorithm…”] based on the fluid intake volume [Biswas col. 2 lns. 27-30], the fluid volume of urine transferred during the catheterization process [Conner 0049 “The volume of urine entering the urine meter 14 from the catheter in communication with the patient may be determined by a fluid level assembly that can include a sensor 42, such as an ultrasound or capacitive sensor”], and data provided by the user and one or more monitoring device [Lee 0018 “…a result providing unit configured to provide the derived prediction result data to a user terminal”].
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Lee, Conner, Liu, and Biswas as applied to claim 10 above, and further in view of Seki (US 20230237546 A1).
Regarding claim 12, Lee, Conner, Liu, and Biswas teach the method of claim 10, wherein Lee teaches providing feedback [Lee 0018 “…a result providing unit configured to provide the derived prediction result data to a user terminal”], but fails to explicitly teach the feedback includes a predictive catheterization timeframe.
Seki teaches the feedback includes a predictive catheterization timeframe [0064 “An information processing device will be described that predicts for catheter treatment scheduled to be performed, a treatment time (working time) and a fee required for each of a plurality of procedures of the catheter treatment”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee, Conner, Liu, and Biswas and incorporate the teachings of Seki to include the feedback includes a predictive catheterization timeframe. Doing so configures the method to reduce infection risk by ensuring the catheter is replaced/removed at appropriate times, preventing bladder damage, and improving patient safety and comfort.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Lee as applied to claim 1 above, and further in view of Liu.
Regarding claim 13, Lee teaches the method of claim 1, wherein the user-defined inputs are stored [0056], but fails to explicitly teach the user-defined inputs comprises a device type.
Liu teaches the user-defined inputs comprises a device type [Liu 0039 “…the data stored in the repository 140 may have various attributes such as gender, age, ejection fraction, type of catheter used (e.g. Swan-Ganz)…”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and incorporate the teachings of Liu to include the user-defined inputs comprises a device type. Doing so configures the method to incorporate additional data that provide for a more robust and accurate analysis of the patient’s condition.
Claims 15 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Lee as applied to claim 1 above, and further in view of Lu (US 20190090756 A1).
Regarding claim 15, Lee teaches the method of claim 1, wherein Lee teaches gathering patient information and providing feedback [0018], but fails to teach gathering and storing heart rate data and considering the heart rate data with the machine learning algorithm before providing feedback.
Lu teaches gathering and storing heart rate data and considering the heart rate data with the machine learning algorithm [0039 “…the wearable compute device 102 may store and maintain different heart rate estimation models 236 for different users. In the illustrative embodiment, the heart rate estimation model 236 is initially embodied as a user-generic model that is customized or personalized to the user over time using a machine learning algorithm”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and incorporate the teachings of Lu to include gathering and storing heart rate data and considering the heart rate data with the machine learning algorithm. Doing so configures the method to incorporate additional data that provide for a more robust and accurate analysis of the patient’s condition.
Regarding claim 19, Lee teaches method of claim 1, wherein Lee teaches identifying and considering patient data with a machine learning algorithm, but fails to explicitly teach identifying and considering one or more of blood oxygen saturation, blood pressure, heart-rate variability, body temperature, and heart rate with the machine learning algorithm.
Lu teaches identifying and considering heart rate with the machine learning algorithm [0044 “…one or more machine learning algorithms to update the heart rate estimation model 236 based on the sensor data produced by the heart rate sensor(s) 120”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and incorporate the teachings of Lu to include identifying and considering heart rate with the machine learning algorithm. Doing so configures the system to “better estimate the user's heart rate over time and respond to changes in the user's biometrics”, as recognized by Lu par. 0044.
Regarding claim 20, Lee teaches the method of claim 1, wherein the method comprises storing information, but fails to explicitly teach storing sensor measurements providing a state of the user, wherein the sensor measurements include one or more of blood pressure, heart rate, and blood oxygen saturation.
Lu teaches storing sensor measurements providing a state of the user [par. 0046 “…the wearable compute device 102 may retrieve the biometric data from other applications on the wearable compute device 102 that may store the biometric data…”], wherein the sensor measurements include one or more of blood pressure, heart rate [0044 “…sensor data produced by the heart rate sensor(s) 120”], and blood oxygen saturation.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and incorporate the teachings of Lu to include storing sensor measurements providing a state of the user, wherein the sensor measurements include one or more of blood pressure, heart rate, and blood oxygen saturation. Doing so configures the system to acquire additional information from the patient that can be used to provide for a more robust and accurate assessment of the patient’s condition.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Lee as applied to claim 1 above, and further in view of Bechtel (US 20140200486 A1).
Regarding claim 16, Lee teaches method of claim 1, wherein feedback is output [0018], but fails to explicitly teach the feedback comprises a recommendation for device use frequency.
Bechtel teaches a recommendation for device use frequency [0018 “…a continuous-monitoring device with recommendation of constant use as well as a periodic-monitoring device performing more complex measurements with recommendation of once or twice daily use”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and incorporate the teachings of Bechtel to include a recommendation for device use frequency. Doing so configures the method to inform a user when to use a device to maximize acquired data and patient comfort while minimizing risk of harm/discomfort to a patient.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Lee as applied to claim 1 above, and further in view of Kuenzler (US 20090234240 A1).
Regarding claim 17, Lee teaches method of claim 1, wherein feedback is output [0018], but fails to explicitly teach the feedback is a recommendation for device type.
Kuenzler teaches a recommendation for device type [0012 “…a recommended change in a type of cardiac device used to treat the patient”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and incorporate the teachings of Kuenzler to include the feedback is a recommendation for device type. Doing so configures the system to “optimize” treatment/device parameters to a particular patient’s needs, maximizing the efficiency of acquiring and analyzing data from a patient, as recognized by Kuenzler par. 0012.
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Lee as applied to claim 1 above, and further in view of Sheldon (US 20140316220 A1).
Regarding claim 18, Lee teaches the method of claim 1, wherein feedback is output [0018], but fails to explicitly teach the feedback is a medical recommendation.
Sheldon teaches the feedback is a medical recommendation [0059 “…the output block 160 may display or otherwise provide the prediction, diagnosis, or recommendation(s) to the user via an output device (e.g., a display screen, a text message, an e-mail, a voice system, etc.) Still further, as indicated above, the block 160 may provide the diagnosis or predicted health issue or even the recommended action to a doctor, therapist, pharmacy, etc. as set up or specified by the user”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Lee and incorporate the teachings of Sheldon to include the feedback is a medical recommendation. Doing so configures the system to improve health outcomes by providing guidance on necessary treatment/action that need to be taken.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN M HANEY whose telephone number is (571)272-0985. The examiner can normally be reached Monday through Friday, 0730-1630 ET.
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/JONATHAN M HANEY/Examiner, Art Unit 3791
/JUSTIN XU/Primary Examiner, Art Unit 3791
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