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 .
Response to Arguments
Applicant’s arguments, see page 5, filed 07/30/2025, with respect to 35 U.S.C. 112(a), 112(b),and 112(d) have been fully considered and are persuasive. The amendments obviate the rejection of record. The rejections of the claims have been withdrawn.
Applicant's arguments, see pages 5-16, filed 07/30/2025, under 35 U.S.C. 101 have been fully considered but they are not persuasive. Applicant argues on pages 10-11 that “The present application describes improvements to medical alert systems for preventing falls, and, in particular, to a system for providing an alert of a fall risk based on “detecting abnormal blood pressure drops, and/or increase or decrease in pulse rate, in real-time using individualized criteria and providing actionable cues to mitigate a potential injurious fall.”… the system is configured to predict that the patient is at risk for experiencing symptoms of abnormal blood pressure and/or heart rate (and would thus be susceptible to dizziness and falling) using a trained machine learning system based on heart rate variability (HRV) data by determining that the HRV data does not include power spectral density peaks in the high frequency range.” Applicant, on page 13, then cites the claim language and further asserts that “claim 21 provides a specific means and method that improves medical alert system technology using certain predictive technology that is implemented by a trained machine learning system,” and further on page 14 that “specific limitations that make it clear that they focus on an improvement in computerized systems that collect heart rate and movement data from a patient as a medical alert system tool for preventing falls based on predictions that are made relating to both the intent of the patient to stand and the risk that the patient will experience abnormal blood pressure and or heart rate.” Examiner disagrees since the processing of data on a microcontroller unit is merely performing this process on a generic computer structure. The transmitting of signals is simply a generic computer function performed by a generic computer structure, wherein implementing the abstract idea with a generic computer is not enough to show integration into a practical application or significantly more than the abstract idea itself. The transmission of data to and from the sensor systems is merely data gathering, which is insignificant extra-solution activity.
Applicant then asserts on page 14 that “the claims require that the limitations be performed by a specially adapted processor arrangement that is structured and configured to implement a trained machine learning system. As a result, Applicant respectfully submits that claim 21, as amended, satisfies Step 2A-Prong One of the 2019 PEG as it is not directed to an abstract idea and therefore is not directed to a judicial exception to patent eligibility.” Applicant further cites on pages 14-15 multiple Ex Parte case laws citing mental processes that were overturned. Examiner notes that each case turns on its own facts and the instant cases mental process is the analyzing of motion data for predicting an intention for transition and analyzing HRV for OH blood pressure and heart rate abnormalities. Examiner notes that Applicant has failed to show that the processor is a special processor than a generic processor.
Applicant then asserts on page 15 that “the limitations of independent claim 21 taken as a whole represent an “unconventional” solution compared to the prior art that “involve more than performance of ‘well-understood, routine, [and] conventional activities previously known to the industry.’”” Applicant is asserting the abstract idea itself as the improvement. However, the abstract idea cannot be an “additional element” that shows integration into a practical application. The order of calculations and the particular calculations claimed do not make the abstract idea any less abstract. The claims are currently structured as simply using a generic computer to implement the abstract idea (mental process), which is not enough to show a practical application. Therefore, the rejection is maintained.
Applicant’s arguments, see pages 16-18, filed 07/30/2025, with respect to the rejection(s) of the claim(s) under 35 U.S.C. 102 and 103 have been fully considered and are persuasive. The amendments obviate the rejection of record. Therefore, the rejection has been withdrawn.
Claim Objections
Claim 33 is objected to because of the following informalities: Claim 33 is a newly added claim, which is unclear how there may be amendments to the newly added claim that was not previously presented in prosecution.
Claim 21 is objected to because of the following informalities: the phrases “the processor being structured” should be amended to recite “the processor configured to”.
Examiner notes that "configured to" is indicative of a state of the device that is capable of performing the steps. Appropriate correction is required.
Claims 22-32 is objected to because of the following informalities: the phrases “The system of claim 21” is missing a comma, and should recite “The system of claim 21,”.
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 the first paragraph of pre-AIA 35 U.S.C. 112:
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 of carrying out his invention.
Claims 21-33 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, fulfilling the written description requirement.
Similarly, original claims may lack written description when the claims define the invention in functional language specifying a desired result but the specification does not sufficiently describe how the function is performed or the result is achieved. For software, this can occur when the algorithm or steps/procedure for performing the computer function are not explained at all or are not explained in sufficient detail (simply restating the function recited in the claim is not necessarily sufficient). In other words, the algorithm or steps/procedure taken to perform the function must be described with sufficient detail so that one of ordinary skill in the art would understand how the inventor intended the function to be performed. See MPEP §§ 2163.02 and 2181, subsection IV.
When examining computer-implemented functional claims, examiners should determine whether the specification discloses the computer and the algorithm (e.g., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor possessed the claimed subject matter at the time of filing. An algorithm is defined, for example, as "a finite sequence of steps for solving a logical or mathematical problem or performing a task." Microsoft Computer Dictionary (5th ed., 2002). Applicant may “express that algorithm in any understandable terms including as a mathematical formula, in prose, or as a flow chart, or in any other manner that provides sufficient structure." Finisar Corp. v. DirecTV Grp., Inc., 523 F.3d 1323, 1340 (Fed. Cir. 2008) (internal citation omitted).It is not enough that one skilled in the art could write a program to achieve the claimed function because the specification must explain how the inventor intends to achieve the claimed function to satisfy the written description requirement. See, e.g., Vasudevan Software, Inc. v. MicroStrategy, Inc., 782 F.3d 671, 681-683, 114 USPQ2d 1349, 1356, 1357 (Fed. Cir. 2015).
Applicant’s algorithm for 1) predicting the intention to transition from lying to sitting to sitting to standing and 2) predicting a risk of experiencing symptoms of abnormal blood pressure and heart rate (claim 21) lacks written description support. The mere statement and recitation of a machine learning model used to predict the intention of transition (claim 21) and the nominal recitation of training of an AI model using motion sensors for predicting the transition, specifically from one axis to determine a tilt ([0103] and [0109] of PG Pub US 20210219923 and US 20240350098) and the generic recitation of features of ECG ([0057]) used in an AI algorithm for predicting the risk of OH ([0068]). The instant specification provides insufficient disclosure of the details of the algorithm for predicting the intention for transition and the risk of experiencing symptoms of abnormal blood pressure and heart rate (OH risk). Specifically, the instant specification fails to the type of data that is used to train the model and the inputs and outputs of the models to predict the intention of a transition and OH. Moreover, the instant specification fails to disclose what within the motion data is identified, whether it be features or a specific calculation done to the motion data, HRV, and blood pressure, that is used to identify the intention of transition and OH, which would be used to train the model. For example, if the RR intervals were used to make the determination of risk of OH, what type of classifications would be made based on the RR interval result. Further, the instant specification fails to detail the way in which each of the machine learning models is used in their distinctive manner. Moreover, the instant specification fails to disclose how one would classify a fall risk based on the results of the outputted abnormal blood pressure and heart rate. Ultimately, the specification is written generically such that it only defines the invention in functional language specifying a desired result but does not sufficiently identify how the function is performed or the result is achieved, thereby failing the written description requirement (see MPEP §2161.01).
Claims 21-33 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, because the specification does not reasonably provide enablement for predicting that the patient has an intention to transition to the sitting position from the lying position and/or to transition to the standing position from the sitting position. The specification does not enable any person skilled in the art to which it pertains, or with which it is most nearly connected, for calculating and predicting, using motion data, to predict an intention of a transition to the sitting position from the lying position and/or to transition to the standing position from the sitting position as the invention commensurate in scope with these claims.
In making a determination as to whether an application has met the requirements for enablement under 35 U.S.C. 112(a), the following factors enumerated In re Wands, 8 USPQ2d 1400, at 1404 (CAFC 1988) are considered:
(1) the breadth of the claims,
(2) the amount of direction or guidance presented, (3) the presence or absence of working examples,
(4) the nature of the invention,
(5) the state of the prior art,
(6) the relative skill of those in the art,
(7) the predictability or unpredictability of the art, &
(8) the quantity of experimentation necessary.
While it is not essential that every factor be examined in detail, those factors deemed most relevant should be considered.
The claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention. Taking into account the factors discussed in MPEP 2164.01 (a), there is insufficient guidance and direction for one of ordinary skill in the art to make and use a processor where the predict an intention. Predicting an intention is oxymoronic because an intention may be unpredictable. The nature of the invention is highly technical, and the level of predictability in the art is low, as the prediction of an intent to change positions lacks sufficient working examples in the instant specification.
Absence of Working Examples/The Amount of Direction
In view of the absence of a specific and detailed description in Applicant’s specification of how to effectively use the method as claimed, and absence of working examples providing evidence which is reasonably predictive that the claims 21-33 would work, and the lack of predictability in the art at the time the invention was made, an undue amount of experimentation would be required to practice the claimed methods with a reasonable expectation of success. Although the claims merely state that “predicting that the patient has an intention to transition to the sitting position from the lying position and/or to transition to the standing position from the sitting position” (claim 21), with no guidance from the instant specification as to how an intention is identified and determined, it is simply unpredictable to predict an intention. Datta (“Human-Augmented Design - Reconciling Unpredictable Human Behaviour with Digital Transformation” LinkedIn, 03/31/2025) discloses that “We often act in ways that contradict our stated intentions, creating what behavioural scientists call the "intention-action gap." This unpredictability creates significant challenges when implementing digital systems that assume rational, consistent user behavior.” The prediction of an intention is simply unpredictable because it assumes consistent and rational behavior of a user. The Applicant has provided no direction whatsoever with regards to how to determine how to predict, using motion data, the intention of a sit to stand, as claimed, and the instant specification fails to provide any working example. As such, the Examiner believes the quantity of experimentation needed to make and use the invention based on the lack of content in the disclosure would be high.
The State of the Prior Art
In the instant field of endeavor, the prior art fails to show predicting that the patient has an intention to transition to the sitting position from the lying position and/or to transition to the standing position from the sitting position. There is insufficient working examples in the prior art that predicts the intention. Thus, the state of the art contradicts the instantly claimed method.
Taking all of the factors into consideration leads to a conclusion that there is no enablement for the limitations discussed above. The dependent claims also lack enablement based on their association with claims 21-33.
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.
Claims 21-33 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 21 recites the limitation "the same time" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 21 recites the limitation "the high frequency range" in line 23. There is insufficient antecedent basis for this limitation in the claim.
Regarding claim 21, it is unclear and indefinite as to how one can predict an intention when an intention is unpredictable. Examiner notes that predicting something that is unpredictable (i.e. the intentions of someone) is oxymoronic as it would be impossible for a conclusive prediction to be made, thereby being indefinite.
Claim 33 recites the limitation "the low frequency range" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 33 recites the limitation "the high frequency range" in line 3. There is insufficient antecedent basis for this limitation in the claim.
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 21-33 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Each of independent claim 21 recites a step analyzing transmitted movement data in the trained machine learning system to predict that the patient has an intention to transition to the sitting position from the lying position and/or to transition to the standing position from the sitting position, and (ii) analyzing the transmitted heart rate data in the trained machine learning system to predict that the patient is at risk of experiencing symptoms of abnormal blood pressure and/or heart rate based on a determination of an absence of power spectral density peaks in the HRV data in the high frequency range of 0.15 to 0.4 Hz, which is a mental process. This judicial exception is not integrated into a practical application because the generically recited computer elements (ie. a body mounted device, processor), determining values, and identifying susceptibility to dizziness do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations are to receiving data, processing data, and susceptibility to dizziness, which are all well-understood, routine, and conventional computer functions. See MPEP § 2106.05(d).
MPEP 2106(III) outlines steps for determining whether a claim is directed to statutory subject
matter. The stepwise analysis for the instant claim is provided here.
Step 1 – Statutory categories
Claim 21 is directed to a system (i.e. machine) and thus meets the step 1 requirements.
Step 2A – Prong 1 – Judicial exception (j.e.)
Regarding claim 21, the following step is an abstract idea:
“analyzing transmitted movement data in the trained machine learning system to predict that the patient has an intention to transition to the sitting position from the lying position and/or to transition to the standing position from the sitting position, and (ii) analyzing the transmitted heart rate data in the trained machine learning system to predict that the patient is at risk of experiencing symptoms of abnormal blood pressure and/or heart rate based on”, which is a mental process when given its broadest reasonable interpretation. As discussed in MPEP 2106.04(a)(2)(II), the mental process grouping includes observations, evaluations, judgements, and opinions. In this case, a human could analyze motion data to predict a transition and HRV for OH.
“a determination of an absence of power spectral density peaks in the HRV data in the high frequency range of 0.15 to 0.4 Hz” , which is a mathematical concept when given its broadest reasonable interpretation. As discussed in MPEP 2106.04(a)(2)(I), the mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. In this case, the spectral density analysis requires a fast Fourier Transform (FFT), which is a mathematical concept for converting HRV to isolate spectral frequencies.
Step 2A – Prong 2 – additional elements to integrate j.e. into a practical application
Regarding claim 21, the abstract idea is not integrated into a practical application.
The following claim elements do not add any meaningful limitation to the abstract idea:
- “a body mountable device”, “transmitter”, “a mounting device”, and “a processor” are recited at a high level of generality amounting to generic computer components for implementing abstract idea [MPEP 2106.05(b)];
It is noted that the trained machine learning system are by definition automating the human thinking process with a computer.
- “heart rate sensor”, “physical motion sensor” are data gathering structures for the insignificant extra-solution activity of data gathering [MPEP 2106.05(b)];
- “heart rate data”, “accelerometer/movement data”, “transition”, “abnormal blood pressure”, “HRV”, “abnormal heart rate”, “movement data”, “sitting, lying, and standing positions”, “risk”, “spectral density peaks”, and “warning” are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)].
Step 2B – significantly more/inventive concept
The following claim elements do not add any meaningful limitation to the abstract idea:
- “a body mountable device”, “transmitter”, “a mounting device”, and “a processor” are recited at a high level of generality amounting to generic computer components for implementing abstract idea [MPEP 2106.05(b)];
It is noted that the trained machine learning system are by definition automating the human thinking process with a computer.
- “heart rate sensor”, “physical motion sensor” are data gathering structures for the insignificant extra-solution activity of data gathering [MPEP 2106.05(b)];
- “heart rate data”, “accelerometer/movement data”, “abnormal blood pressure”, “HRV”, “abnormal heart rate”, “movement data”, “sitting, lying, and standing positions”, “transition”, “risk”, “spectral density peaks”, and “warning” are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)].
The additional elements of claim 21, when considered separately and in combination, do not add significantly more (ie. an inventive concept) to the abstract idea. As discussed above with respect to the integration of the abstract idea into a practical application, the body mounted device, and processor, along with their associated functions, are recited at a high level of generality and simply amount to implementing the abstract idea on a computer. The ECG sensor/EKG sensor and, accelerometer are claimed very generically and are used only to gather the data they are designed for. These are well-understood, routine and conventional structure since the diagnostic art in Zhao et al (US 20170258356) teaches the use of ECG/EKG sensors to collect ECG signals ([0006]), and Roovers et al (US 20170007166) teaches an accelerometer for detecting motion signals ([0008]).
Dependent claims 22-33 do not integrate the abstract idea into a practical application
and do not add significantly more to the abstract idea of claim 21. The dependent claim limitations are directed to well-understood, routine, and conventional structure (claims 22-23, 25-27, and 29) and to extra-solution activity (claims 24, 28, 30-33), which are insignificant extra-solution activity and do not amount to more than what is well-understood, routine, and conventional.
In summary, claims 21-33 are directed to an abstract idea without significantly more and, therefore, are patent ineligible.
Conclusion
Claims 21-33 overcome the prior art but are still rejected under claim objections, 35 U.S.C. 112(b), 35 U.S.C. 112(a), and 35 U.S.C. 101.
The following is a statement of reasons for the indication of the claims overcoming the prior art:
The analyzing, using a machine learning model, of motion data for predicting the intention to transition from sitting to standing or lying to standing and the analyzing to predict the risk of experiencing symptoms of abnormal blood pressure and heart rate based on absence of power spectral density in HRV data in the high frequency range and warning a care taker when each occurs are not conventionally relied upon in alerting a fall risk and are therefore overcomes the prior art.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Trimnell (US 11688262) is directed to fall detection using motion data for a change in position.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOUSSA M HADDAD whose telephone number is (571)272-6341. The examiner can normally be reached M-TH 8:00-6:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer McDonald can be reached at (571) 270-3061. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOUSSA HADDAD/Examiner, Art Unit 3796
/Jennifer Pitrak McDonald/Supervisory Patent Examiner, Art Unit 3796