DETAILED ACTION
This action is pursuant to claims filed on 12/11/2025. Claims 1, 3-4, 7, 10, 12-15, 17-18, and 21-24 are pending. An action on the merits of claims 1, 3-4, 7, 10, 12-15, 17-18, and 21-24 is as follows.
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 .
Appeal
In view of the appeal brief filed on 03/27/2026, PROSECUTION IS HEREBY REOPENED. New grounds of rejection are set forth below.
To avoid abandonment of the application, appellant must exercise one of the following two options:
(1) file a reply under 37 CFR 1.111 (if this Office action is non-final) or a reply under 37 CFR 1.113 (if this Office action is final); or,
(2) initiate a new appeal by filing a notice of appeal under 37 CFR 41.31 followed by an appeal brief under 37 CFR 41.37. The previously paid notice of appeal fee and appeal brief fee can be applied to the new appeal. If, however, the appeal fees set forth in 37 CFR 41.20 have been increased since they were previously paid, then appellant must pay the difference between the increased fees and the amount previously paid.
A Supervisory Patent Examiner (SPE) has approved of reopening prosecution by signing below:
/JASON M SIMS/ Supervisory Patent Examiner, Art Unit 3791
Information Disclosure Statement
The information disclosure statement filed 06/01/2026 fails to comply with 37 CFR 1.98(a)(2), which requires a legible copy of each cited foreign patent document; each non-patent literature publication or that portion which caused it to be listed; and all other information or that portion which caused it to be listed. It has been placed in the application file, but the information referred to therein has not been considered. The IDS lists a non-patent literature document of an office action from counterpart Chinese Application, however no copy of this reference has been provided. Additionally, a Notice of Allowance for US application 18/651330 has been provided, however this reference is not listed on the IDS.
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, 3-4, 7, 10, 12-15, 17-18 and 21-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Under the two-step 101 analysis, the claims fail to satisfy the criteria for subject matter eligibility.
Regarding Step 1, claims 1-20 are all within at least one of the four statutory categories.
Claim 1 and its dependent claims disclose a method.
Claim 13 and its dependent claims disclose a system (machine).
Claim 24 discloses a non-transitory computer-readable media (machine).
Regarding Step 2A, Prong One, the independent claims 1, 13, and 24 recite an abstract idea. In particular, the claims generally recite the following:
Detecting a plurality of posture transitions of a subject based on an accelerometer signal from the accelerometer that varies as a function of movement and posture of the subject;
For each posture transition of the detected plurality of posture transitions, determining a respective response of a plurality of responses of the physiological parameter of the subject to the posture transition based on an electrocardiogram signal sensed via the plurality of electrodes, wherein the physiological parameter comprises one of heart rate, heart rate variability, or an electrocardiogram morphology parameter,
Wherein determining the respective response comprises determining a difference between a first value of the physiological parameter at or near a commencement of the posture transition and a second value of the physiological parameter at or near an end of the posture transition;
Determining that a current one or more responses of the plurality of responses crosses a threshold, the threshold determined based on a subset of the plurality of responses previous to the current one or more responses.
These elements recited in claims 1, 13, and 24 are drawn to abstract ideas since they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgement, and opinion and using pen and paper.
Detecting a plurality of posture transitions of a subject based on an accelerometer signal from the accelerometer that varies as a function of movement and posture of the subject is drawn to an abstract idea since it is a mental process that can be practically performed in the human mind, or with the aid of pen and paper. A person of ordinary skill in the art could reasonably receive the sensed signal on a piece of paper and determine when the posture transitions occur mentally. This technique is based on observation of the signal as well as calculations and mathematical principles, which can be performed by hand. The mathematics of determining if a posture transition has occurred is not overly complicated to perform mentally or using pen and paper given enough time, therefore this limitation is defined as an abstract idea. There is nothing to suggest an undue level of complexity in detecting a plurality of posture transitions of a subject based on an accelerometer signal from the accelerometer that varies as a function of movement and posture of the subject.
For each posture transition of the detected plurality of posture transitions, determining a respective response of a plurality of responses of the physiological parameter of the subject to the posture transition based on an electrocardiogram signal sensed via the plurality of electrodes, wherein the physiological parameter comprises one of heart rate, heart rate variability, or an electrocardiogram morphology parameter is drawn to an abstract idea since it is a mental process that can be practically performed in the human mind, or with the aid of pen and paper. A person of ordinary skill in the art could reasonably receive the electrocardiogram signal on a piece of paper and determine the response of a physiological parameter of the subject to the posture transition mentally. This technique is based on observation of the signal as well as calculations and mathematical principles, which can be performed by hand. The mathematics of determining a response of the physiological parameter is not overly complicated to perform mentally or using pen and paper given enough time, therefore this limitation is defined as an abstract idea. There is nothing to suggest an undue level of complexity in determining a response of the physiological parameter of the subject to the posture transition based on an electrocardiogram signal sensed via the plurality of electrodes, wherein the physiological parameter comprises one of heart rate, heart rate variability, or an electrocardiogram morphology parameter.
Determining the respective response comprises determining a difference between a first value of the physiological parameter at or near a commencement of the posture transition and a second value of the physiological parameter at or near an end of the posture transition is drawn to an abstract idea since it is a mental process that can be practically performed in the human mind, or with the aid of pen and paper. A person of ordinary skill in the art could reasonably determine the difference between two values mentally. This technique is based on observation, calculations, and mathematical principles, which can be performed by hand. The mathematics of determining a difference between two values is not overly complicated to perform mentally or using pen and paper given enough time, therefore this limitation is defined as an abstract idea. There is nothing to suggest an undue level of complexity in determining the response comprises determining a difference between a first value of the physiological parameter at or near a commencement of the posture transition and a second value of the physiological parameter at or near an end of the posture transition.
Determining that a current one or more responses of the plurality of responses crosses a threshold, the threshold determined based on a subset of the plurality of responses previous to the current one or more responses is drawn to an abstract idea since it is a mental process that can be practically performed in the human mind, or with the aid of pen and paper. A person of ordinary skill in the art could reasonably receive the responses on a piece of paper and determine if the responses crosse a threshold mentally by comparing the values and the threshold mentally through observation and comparison. There is nothing to suggest an undue level of complexity in determining that a current one or more responses crosses a threshold, the threshold determined based on a plurality of responses previous to the current one or more responses.
Regarding Step 2A, Prong Two, claims 1, 13, and 24 do not recite additional elements that integrate the exception into a practical application. Therefore, the claims are “directed to” the abstract idea. The additional elements merely:
Recite the words “apply it” or an equivalent with the judicial exception, or include instructions to implement the abstract idea on a computer, or merely use the computer as a tool to perform the abstract idea (e.g., “sensing circuitry” (claim 13), “processing circuitry” (claim 13), and “non-transitory computer-readable media” (claim 24)), and
Add insignificant extra-solution activity (the pre-solution activity of: using generic data-gathering components (e.g., “a medical device comprising an accelerometer and a plurality of electrodes”), insignificant post-solution activity (e.g., “generating an alert to a user based on the determination that the current one or more responses cross the threshold” (claims 1, 13, and 24))).
As a whole, the additional elements merely serve to gather information to be used by the abstract idea, while generically implementing it on a computer. There is no practical application because the abstract idea is not applied, relied on, or used in a meaningful way. The processing performed remains in the abstract realm, i.e., the result is not used for a treatment. No improvement to the technology is evident. Therefore, the additional elements, alone or in combination, do not integrate the abstract idea into a practical application.
Regarding Step 2B, claims 1, 13, and 24 do not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception (i.e., an inventive concept) for the same reasons as described above.
Claims 1, 13, and 24 do not recite additional elements that amount to significantly more than the judicial exception itself. In particular, “a medical device comprising an accelerometer and a plurality of electrodes” does not qualify as significantly more because this limitation merely describes generic and well-known data gathering devices. Moreover, the step of “generating an alert to a user based on the determination that the current one or more responses cross the threshold” is insignificant post-solution activity, as it is just providing the result to a user.
The data gathering step of “a medical device comprising an accelerometer and a plurality of electrodes” is nothing more than a conventional data gathering device. Such devices are evidenced by:
US Patent Application Publication No. 20170311830 (Korzinov) discloses electrodes and accelerometers being in medical devices as conventional (Korzinov, [0018]);
US Patent Application Publication No. 20120265029 (Fahey) discloses medical devices with well-known sensors such as electrodes and accelerometers (Fahey, [00796]);
US Patent Application Publication No. 20150099972 (Jacobson) discloses electrodes and accelerometers as conventional in medical devices (Jacobson, [0007]).
Further, the elements of sensing circuitry and processing circuitry in claim 13 and the non-transitory computer readable media in claim 24 do not qualify as significantly more because these limitations are simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l, 110USPQ2d 1976 (2014)) and/or a claim to an abstract idea requiring no more than being stored on a computer readable medium which is a well-understood, routine and conventional activity previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l, 110 USPQ2d 1976 (2014); SAP Am. v. InvestPic, 890 F.3d 1016 (Fed. Circ. 2018)).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above judicial exception. Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements 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, i.e., the computer is simply a tool to perform the process.
Regarding the dependent claims, claims 3-4, 7, 10, 12, and 21 depend on claim 1 and claims 14-15, 17-18, and 22-23 depend on claim 13. The dependent claims merely further define the abstract idea or are additional data output that is well-understood, routine, and previously known to the industry.
For example, the following are dependent claims reciting abstract ideas and can be performed in the human mind:
(Claim 3): “further comprising determining the threshold based on at least one of a mean, a median, or a range of variability of the subset of the plurality of responses” is drawn to an abstract idea as it can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in observing the recorded data and performing calculations to determine the desired results. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 4): “wherein determining the threshold comprises determining the threshold based on the range of variability, wherein the range of variability is based on a number of standard deviations from the mean or the median of the one or more plurality of responses” is drawn to an abstract idea as it can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in observing the recorded data and performing calculations to determine the desired results. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 7): “wherein each posture transition of the plurality of posture transitions comprises a sit-stand transition” further defines the abstract idea as it specifies the type of generic data gathering performed;
(Claim 10): “wherein the physiological parameter comprises heart rate” further defines the abstract idea as it specifies the type of generic data gathering performed;
(Claim 12): “wherein generating the alert to the user comprises transmitting a signal to an external device indicating the current one or more responses cross the threshold” is insignificant post-solution activity;
(Claim 14): “wherein the housing is configured for implantation in a human body, and wherein the accelerometer and the plurality of electrodes are one of on or within the housing” is insignificant pre-solution activity of generic data gathering, as evidenced by:
US Patent No. 6073049 (Alt) discloses a conventional implanted sensor including electrodes and an accelerometer places in a housing (Alt, Column 8, line 66 – Column 9, line 17);
WO Patent Application No. 2008105698 (Bjoerling) discloses conventional implants having a housing that includes electrodes and an accelerometer (Bjoerling, Page 11, line 26 – Page 13, line 23);
(Claim 15): “further comprising a memory configured to store the threshold and data indicating the current one or more responses and the subset of the plurality of responses previous to the current one or more responses” is drawn to an abstract idea since it is a claim to an abstract idea requiring no more than being stored on a computer readable medium which is a well-understood, routine and conventional activity previously known in the industry;
(Claim 17): “wherein the processing circuitry is configured to determine the threshold based on at least one of a mean, a median, or a range of variability of the subset of the plurality of responses” is drawn to an abstract idea as it can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in observing the recorded data and performing calculations to determine the desired results. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 18): “wherein the range of variability is based on a number of standard deviations from the mean or the median of the subset of the plurality of responses” is drawn to an abstract idea as it can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in observing the recorded data and performing calculations to determine the desired results. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 21): “wherein each posture transition of the plurality of detected posture transitions comprises a lay-sit transition” further defines the abstract idea as it specifies the type of generic data gathering performed;
(Claim 22): “wherein each posture transition of the plurality of detected posture transitions comprises a sit-stand transition” further defines the abstract idea as it specifies the type of generic data gathering performed;
(Claim 23): “wherein each posture transition of the plurality of detected posture transitions comprises a lay-sit transition” further defines the abstract idea as it specifies the type of generic data gathering performed.
The dependent claims do not recite significantly more than the abstract ideas. Therefore, claims 1, 3-4, 7, 10, 12-15, 17-18 and 21-24 are rejected as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-4, 7, 10, 12-13, 15, 17-18, and 21-24 are rejected under 35 U.S.C. 103 as being unpatentable over Lyons (US 20140358193) in view of Cho (US 7438686) and Castillo (US 20150161876).
Regarding independent claim 1, Lyons teaches a method ([0053]: “there is provided a method for monitoring a patient”) comprising, by processing circuitry of a medical device system ([0086]: “a system of the invention comprises sensors 101 of biomechanical and physiological events which can be related to the onset of a syncopal fall. A processor 102 is provided for analyzing sensed data, detecting risk of a syncopal fall, and tracking and reporting patient compliance and usage data”. The system of the invention is the medical device system, and the processor is the processing circuitry), the medical device system comprising a medical device ([0030]: “the bio-mechanical sensors include sensors arranged to allow the processor to detect a user posture.”. The set of biomechanical sensors is the medical device), the medical device comprising an accelerometer and a plurality of electrodes ([0033]: “the sensors comprise one or more selected from accelerometers, electrocardiography (ECG) sensors”; [0129]: “monitoring of heart rate using ECG electrodes placed on the chest is important for predicting a syncopal fall arising from these conditions”. The ECG electrodes are the plurality of electrodes):
detecting a plurality of posture transitions of a subject based on an accelerometer signal from the accelerometer that varies as a function of movement and posture of the subject (Abstract: “The bio-mechanical sensors include sensors arranged to allow the processor to detect a user postures and posture transitions”. The posture transition is determined based on the accelerometer signals (movement), therefore the posture transitions vary as a function of movement and posture.);
for each posture transition of the detected plurality of posture transitions, determining a respective response of a plurality of responses of a physiological parameter of the subject to the posture transition based on an electrocardiogram signal sensed via the plurality of electrodes, wherein the physiological parameter comprises one of heart rate, heart rate variability, or an electrocardiogram morphology parameter ([0088]: “the system of the invention detects combinations of intention to change posture, periods of prolonged standing, heart rate changes, and respiration rate changes that are precursor events to the start of a syncopal fall (a faint related fall)”. Fig. 9 shows determining heart rate values after a posture transition. Heart rate is measured from the ECG electrodes ([0131]: “heart rate is measured using an ECG patch”), and the heart rate is the physiological parameter), and wherein determining the respective response comprises determining a difference between a first value of the physiological parameter at or near a commencement of the posture transition and a second value of the physiological parameter at or near an end of the posture transition (Fig. 9; [0148]: “If a heart rate above 120 beats per minute is not detected (908) then the algorithm checks for an increase in heart rate of 30 beats per minute (909) above the pre-transition resting heart rate (910)”. The pre-transition heart rate is the first value and the detected heart rate after the transition is the second value.);
determining that a current one or more responses of the plurality of responses cross a threshold ([0148]: “If the timer value has not been reached (905) the algorithm checks for a sustained heart rate above 120 beats per minute (906) and applies NMES (904) if a heart rate above 120 beats per minute is detected (907). If a heart rate above 120 beats per minute is not detected (908) then the algorithm checks for an increase in heart rate of 30 beats per minute (909) above the pre-transition resting heart rate (910). If the heart rate increase is greater than 30 beats per minute (911) then NMES is applied (904). If the heart rate is not found to be greater than 30 beats per minute (912) than the algorithm returns back to the start of the timer checking step (913)”. The threshold is if the heart rate is over 120 beats per minute, or an increase of greater than 30 beats per minute. The threshold of greater than 30 beats per minute is determined relative to a previous response to the current measured heart rate.).
Lyons does not teach wherein the threshold is determined based on a subset of the plurality of responses previous to the current one or more responses, however this concept is suggested by the limitations of Lyons. Lyons involves determining the threshold based off of previous values of the heart rate, which suggests the use of a subset of the plurality of previous responses.
Cho discloses an apparatus and method for monitoring disordered breathing. While Cho is not directly related to the problem of preventing falls like Lyons, they both relate to a similar problem of evaluating heart rate data against a threshold to determine whether a user’s heart rate has exceeded normal values. Both references use similar evaluation techniques and methods to determine these thresholds, and therefore a person of ordinary skill in the art would look to Cho’s method for improvement on the method from Lyons. Specifically, Cho teaches wherein the threshold is determined based on a subset of the plurality of responses previous to the current one or more responses (Column 11, line 42 – Column 12, line 6: “At step 510 a dynamic threshold is calculated based on the sensed heart rate. In one embodiment, the dynamic threshold may be a range defined by upper and lower threshold boundaries that, when crossed, indicates a change in heart rate that may be associated with a disordered breathing cycle. In a preferred embodiment, a dynamic threshold may be calculated based on a function of the rolling mean of the sensed heart rate. A rolling mean heart rate may calculated from a given number of heart rate data points according to the following formula:
H
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+
x
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a
n
(
n
-
1
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N
wherein
H
R
m
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a
n
n
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1
is the rolling heart rate calculated on the previous heart rate data point; x(n) is the current heart rate data point; and N is the number of data points included in the rolling average. The upper and lower boundaries of the dynamic threshold range (DTR) may then be calculated according to equation (2):
D
T
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n
=
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m
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a
n
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±
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(
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wherein K(n) may be a fixed value including 0, a fraction of the mean heart rate from equation (1), proportional to the standard deviation of the mean heart rate, or other predefined value. When K(n) is 0, the dynamic threshold is a single curve rather than a range defined by an upper boundary curve and a lower boundary curve. In alternative embodiments, a threshold value or threshold range may be fixed value(s) that are programmable, rather than dynamically calculated values.”). Lyons and Cho are analogous art as they are directed towards solving a similar problem of determining when a measured heart rate has increased a significant amount.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the dynamic threshold determination from Cho into the method from Lyons as it allows for a changing, dynamic threshold relative to the previous heart rate values rather than a set threshold number. This allows for a threshold that can automatically adapt and evolve based on real-time data, allowing for a more refined and personal value instead of a singular static value.
The Lyons/Cho combination does not teach generating an alert to a user based on the determination that the current one or more responses cross the threshold, wherein the user comprises the subject or another user, however the concept of notifying the user when there is an abnormal condition is suggested by Lyons. Lyons discloses a system to prevent falling, which revolves around the concept of determining an abnormal condition and notifying a user when there is a risk of fall. While the specific limitation of alerting the user when a value crosses a threshold is not explicitly recited in Lyons, the concept is suggested through the main goal of the system to prevent a fall.
Castillo discloses methods and systems for emergency alerts. While Castillo is not directly related to preventing falls of a user like Lyons, both references are directed to a similar problem of notifying a user of an abnormal condition to prevent a medical event from occurring. Therefore, when looking to improve the alert system from Lyons, a person of ordinary skill in the art would look to Castillo for a specific alert method. Specifically, Castillo teaches generating an alert to a user based on the determination that the current one or more responses cross the threshold ([0061]: “Alert module 178 may be a hardware device configured to determine if an emergency situation has occurred responsive to receiving sensor data from wearable computing device 110 as determined by modules 119, 160, 162, 164, 166, 168, 170. Alert module 178 may set threshold values or change thresholds associated with received data from modules 119, 160, 162, 164, 166, 168, or 170. The threshold ranges or change threshold may be associated with if an emergency situation has occurred or if a quality check is desired to determine the cause of the emergency situation. The threshold ranges may set values associated with the wearer's biometric data, and the change thresholds may be associated with a change in values over a period of time. In embodiments, the threshold ranges may include a lower threshold and/or an upper threshold”; [0065]: “Responsive to alert module 178 determining that the heart rate of the wearer wearing wearable computing device 110 is increased or decreased based on data received from pulse oximeter 162 to levels greater than a heart rate change threshold and/or outside of a threshold range, alert module 178 may begin a quality check for a possible cause of the increase or decrease of the wearer's heart rate”; [0062]: “When alert module 178 determines an emergency situation has occurred, alert module 178 may transmit an emergency alert signal to a third party computing device 140”. The alert module generates an alert when the heart rate has increased over a certain threshold, which can be incorporated into the threshold from Lyons.), wherein the user comprises the subject or another user ([0098]: “At operation 350, the emergency alert signal may be transmitted to users within a group, wherein the group may be determined based on the timestamp and the user's schedule. Responsive to determining an emergency alert signal should be transmitted, groups that the user is part of having a schedule associated with the time of day corresponding to the timestamp may be determined. Furthermore, the emergency alert signal may be transmitted to the users within the group(s) with a schedule corresponding to the timestamp. Operation 350 may be performed by an alert module that is the same as or similar to alert module 178, in accordance with one or more implementation”. The group that the emergency alert is transmitted to can be the subject or other users.). Lyons and Castillo are analogous art as they are directed towards solving a similar problem of monitoring a user’s heart rate over a period of time.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the alert generation from Castillo into the method from the Lyons/Cho combination as it allows the method to alert the user if there is a large change in their heart rate, as it keeps them informed of a health event that can/will occur, ensuring they are able to take proper action to prepare themselves.
Regarding claim 3, the Lyons/Cho/Castillo combination teaches the method of claim 1, further comprising determining the threshold based on at least one of a mean, a median, or a range of variability of the subset of the plurality of responses (Cho, Column 11, line 42 – Column 12, line 6: “At step 510 a dynamic threshold is calculated based on the sensed heart rate. In one embodiment, the dynamic threshold may be a range defined by upper and lower threshold boundaries that, when crossed, indicates a change in heart rate that may be associated with a disordered breathing cycle. In a preferred embodiment, a dynamic threshold may be calculated based on a function of the rolling mean of the sensed heart rate. A rolling mean heart rate may calculated from a given number of heart rate data points according to the following formula:
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wherein
H
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is the rolling heart rate calculated on the previous heart rate data point; x(n) is the current heart rate data point; and N is the number of data points included in the rolling average. The upper and lower boundaries of the dynamic threshold range (DTR) may then be calculated according to equation (2):
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=
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wherein K(n) may be a fixed value including 0, a fraction of the mean heart rate from equation (1), proportional to the standard deviation of the mean heart rate, or other predefined value. When K(n) is 0, the dynamic threshold is a single curve rather than a range defined by an upper boundary curve and a lower boundary curve. In alternative embodiments, a threshold value or threshold range may be fixed value(s) that are programmable, rather than dynamically calculated values.”).
Regarding claim 4, the Lyons/Cho/Castillo combination teaches the method of claim 3, wherein determining the threshold comprises determining the threshold based on the range of variability, wherein the range of variability is based on a number of standard deviations from the mean or the median of the subset of the plurality of responses (Cho, Column 11, line 42 – Column 12, line 6: “At step 510 a dynamic threshold is calculated based on the sensed heart rate. In one embodiment, the dynamic threshold may be a range defined by upper and lower threshold boundaries that, when crossed, indicates a change in heart rate that may be associated with a disordered breathing cycle. In a preferred embodiment, a dynamic threshold may be calculated based on a function of the rolling mean of the sensed heart rate. A rolling mean heart rate may calculated from a given number of heart rate data points according to the following formula:
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wherein
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is the rolling heart rate calculated on the previous heart rate data point; x(n) is the current heart rate data point; and N is the number of data points included in the rolling average. The upper and lower boundaries of the dynamic threshold range (DTR) may then be calculated according to equation (2):
D
T
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n
=
H
R
m
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n
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±
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(
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wherein K(n) may be a fixed value including 0, a fraction of the mean heart rate from equation (1), proportional to the standard deviation of the mean heart rate, or other predefined value. When K(n) is 0, the dynamic threshold is a single curve rather than a range defined by an upper boundary curve and a lower boundary curve. In alternative embodiments, a threshold value or threshold range may be fixed value(s) that are programmable, rather than dynamically calculated values.”).
Regarding claim 7, the Lyons/Cho/Castillo combination teaches the method of claim 1, wherein each posture transition of the plurality of posture transitions comprises a sit-stand transition (Lyons, [0051]: “Preferably, the states include … a sit-to-stand transition state”).
Regarding claim 10, the Lyons/Cho/Castillo combination teaches the method of claim 1, wherein the physiological parameter comprises heart rate (Lyons, [0088]: “the system of the invention detects combinations of intention to change posture, periods of prolonged standing, heart rate changes, and respiration rate changes that are precursor events to the start of a syncopal fall (a faint related fall)”. Fig. 9 shows determining heart rate values after a posture transition.).
Regarding claim 12, the Lyons/Cho/Castillo combination teaches the method of claim 1, wherein generating the alert to the user comprises transmitting a signal to an external device indicating the current one or more responses cross the threshold (Castillo, [0061]: “Alert module 178 may be a hardware device configured to determine if an emergency situation has occurred responsive to receiving sensor data from wearable computing device 110 as determined by modules 119, 160, 162, 164, 166, 168, 170. Alert module 178 may set threshold values or change thresholds associated with received data from modules 119, 160, 162, 164, 166, 168, or 170. The threshold ranges or change threshold may be associated with if an emergency situation has occurred or if a quality check is desired to determine the cause of the emergency situation. The threshold ranges may set values associated with the wearer's biometric data, and the change thresholds may be associated with a change in values over a period of time. In embodiments, the threshold ranges may include a lower threshold and/or an upper threshold”; [0065]: “Responsive to alert module 178 determining that the heart rate of the wearer wearing wearable computing device 110 is increased or decreased based on data received from pulse oximeter 162 to levels greater than a heart rate change threshold and/or outside of a threshold range, alert module 178 may begin a quality check for a possible cause of the increase or decrease of the wearer's heart rate”; [0062]: “When alert module 178 determines an emergency situation has occurred, alert module 178 may transmit an emergency alert signal to a third party computing device 140”. The third party computing device is the external device).
Regarding independent claim 13, Lyons teaches a medical device system ([0086]: “a system of the invention comprises sensors 101 of biomechanical and physiological events which can be related to the onset of a syncopal fall. A processor 102 is provided for analyzing sensed data, detecting risk of a syncopal fall, and tracking and reporting patient compliance and usage data”) comprising:
a medical device comprising: an accelerometer configured to generate an accelerometer signal that varies as a function of movement and posture of a subject; and a plurality of electrodes configured to sense an electrocardiogram signal that varies as a function of a physiological parameter of the subject, wherein the physiological parameter comprises one of heart rate, heart rate variability, or an electrocardiogram morphology parameter ([0033]: “the sensors comprise one or more selected from accelerometers, electrocardiography (ECG) sensors”; [0129]: “monitoring of heart rate using ECG electrodes placed on the chest is important for predicting a syncopal fall arising from these conditions”. The ECG electrodes are the plurality of electrodes. Accelerometers measure movement and in turn posture as movement changes relative to the posture, therefore the accelerometer signal varies as a function of movement and posture of a subject. Similarly, if the physiological parameter is heart rate and the ECG signal measures heart rate, then the ECG signal varies as a function of the physiological parameter of the subject.); and
processing circuitry ([0086]: “a system of the invention comprises sensors 101 of biomechanical and physiological events which can be related to the onset of a syncopal fall. A processor 102 is provided for analyzing sensed data, detecting risk of a syncopal fall, and tracking and reporting patient compliance and usage data”. The processor is the processing circuitry) configured to:
detect a plurality of posture transitions of the subject based on the accelerometer signal (Abstract: “The bio-mechanical sensors include sensors arranged to allow the processor to detect a user postures and posture transitions”. The posture transition is determined based on the accelerometer signals.);
for each posture transition of the detected plurality of posture transitions, determine a respective response of a plurality of responses of the physiological parameter of the subject to the posture transition based on the electrocardiogram signal ([0088]: “the system of the invention detects combinations of intention to change posture, periods of prolonged standing, heart rate changes, and respiration rate changes that are precursor events to the start of a syncopal fall (a faint related fall)”. Fig. 9 shows determining heart rate values after a posture transition. Heart rate is measured from the ECG electrodes ([0131]: “heart rate is measured using an ECG patch”), and the heart rate is the physiological parameter), wherein to determine the respective response the processing circuitry is configured to determine a difference between a first value of the physiological parameter at or near a commencement of the posture transition and a second value of the physiological parameter at or near an end of the posture transition (Fig. 9; [0148]: “If a heart rate above 120 beats per minute is not detected (908) then the algorithm checks for an increase in heart rate of 30 beats per minute (909) above the pre-transition resting heart rate (910)”. The pre-transition heart rate is the first value and the detected heart rate after the transition is the second value.);
determine that a current one or more responses of the plurality of responses cross a threshold ([0148]: “If the timer value has not been reached (905) the algorithm checks for a sustained heart rate above 120 beats per minute (906) and applies NMES (904) if a heart rate above 120 beats per minute is detected (907). If a heart rate above 120 beats per minute is not detected (908) then the algorithm checks for an increase in heart rate of 30 beats per minute (909) above the pre-transition resting heart rate (910). If the heart rate increase is greater than 30 beats per minute (911) then NMES is applied (904). If the heart rate is not found to be greater than 30 beats per minute (912) than the algorithm returns back to the start of the timer checking step (913)”. The threshold is if the heart rate is over 120 beats per minute, or an increase of greater than 30 beats per minute. The threshold of greater than 30 beats per minute is determined relative to a previous response to the current measured heart rate.).
Lyons does not teach wherein the threshold is determined based on a subset of the plurality of responses previous to the current one or more responses, however this concept is suggested by the limitations of Lyons. Lyons involves determining the threshold based off of previous values of the heart rate, which suggests the use of a subset of the plurality of previous responses.
Cho discloses an apparatus and method for monitoring disordered breathing. While Cho is not directly related to the problem of preventing falls like Lyons, they both relate to a similar problem of evaluating heart rate data against a threshold to determine whether a user’s heart rate has exceeded normal values. Both references use similar evaluation techniques and methods to determine these thresholds, and therefore a person of ordinary skill in the art would look to Cho’s method for improvement on the method from Lyons. Specifically, Cho teaches wherein the threshold is determined based on a subset of the plurality of responses previous to the current one or more responses (Column 11, line 42 – Column 12, line 6: “At step 510 a dynamic threshold is calculated based on the sensed heart rate. In one embodiment, the dynamic threshold may be a range defined by upper and lower threshold boundaries that, when crossed, indicates a change in heart rate that may be associated with a disordered breathing cycle. In a preferred embodiment, a dynamic threshold may be calculated based on a function of the rolling mean of the sensed heart rate. A rolling mean heart rate may calculated from a given number of heart rate data points according to the following formula:
H
R
m
e
a
n
n
=
H
R
m
e
a
n
n
-
1
+
x
n
-
H
R
m
e
a
n
(
n
-
1
)
N
wherein
H
R
m
e
a
n
n
-
1
is the rolling heart rate calculated on the previous heart rate data point; x(n) is the current heart rate data point; and N is the number of data points included in the rolling average. The upper and lower boundaries of the dynamic threshold range (DTR) may then be calculated according to equation (2):
D
T
R
n
=
H
R
m
e
a
n
(
n
)
±
K
(
n
)
wherein K(n) may be a fixed value including 0, a fraction of the mean heart rate from equation (1), proportional to the standard deviation of the mean heart rate, or other predefined value. When K(n) is 0, the dynamic threshold is a single curve rather than a range defined by an upper boundary curve and a lower boundary curve. In alternative embodiments, a threshold value or threshold range may be fixed value(s) that are programmable, rather than dynamically calculated values.”). Lyons and Cho are analogous art as they are directed towards solving a similar problem of determining when a measured heart rate has increased a significant amount.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the dynamic threshold determination from Cho into the system from Lyons as it allows for a changing, dynamic threshold relative to the previous heart rate values rather than a set threshold number. This allows for a threshold that can automatically adapt and evolve based on real-time data, allowing for a more refined and personal value instead of a singular static value.
The Lyons/Cho combination does not teach generating an alert to a user based on the determination that the current one or more responses cross the threshold, wherein the user comprises the subject or another user, however the concept of notifying the user when there is an abnormal condition is suggested by Lyons. Lyons discloses a system to prevent falling, which revolves around the concept of determining an abnormal condition and notifying a user when there is a risk of fall. While the specific limitation of alerting the user when a value crosses a threshold is not explicitly recited in Lyons, the concept is suggested through the main goal of the system to prevent a fall.
Castillo discloses methods and systems for emergency alerts. While Castillo is not directly related to preventing falls of a user like Lyons, both references are directed to a similar problem of notifying a user of an abnormal condition to prevent a medical event from occurring. Therefore, when looking to improve the alert system from Lyons, a person of ordinary skill in the art would look to Castillo for a specific alert method. Specifically, Castillo teaches generating an alert to a user in response to the determination that the current one or more responses cross the threshold ([0061]: “Alert module 178 may be a hardware device configured to determine if an emergency situation has occurred responsive to receiving sensor data from wearable computing device 110 as determined by modules 119, 160, 162, 164, 166, 168, 170. Alert module 178 may set threshold values or change thresholds associated with received data from modules 119, 160, 162, 164, 166, 168, or 170. The threshold ranges or change threshold may be associated with if an emergency situation has occurred or if a quality check is desired to determine the cause of the emergency situation. The threshold ranges may set values associated with the wearer's biometric data, and the change thresholds may be associated with a change in values over a period of time. In embodiments, the threshold ranges may include a lower threshold and/or an upper threshold”; [0065]: “Responsive to alert module 178 determining that the heart rate of the wearer wearing wearable computing device 110 is increased or decreased based on data received from pulse oximeter 162 to levels greater than a heart rate change threshold and/or outside of a threshold range, alert module 178 may begin a quality check for a possible cause of the increase or decrease of the wearer's heart rate”; [0062]: “When alert module 178 determines an emergency situation has occurred, alert module 178 may transmit an emergency alert signal to a third party computing device 140”. The alert module generates an alert when the heart rate has increased over a certain threshold, which can be incorporated into the threshold from Lyons.), wherein the user comprises the subject or another user ([0098]: “At operation 350, the emergency alert signal may be transmitted to users within a group, wherein the group may be determined based on the timestamp and the user's schedule. Responsive to determining an emergency alert signal should be transmitted, groups that the user is part of having a schedule associated with the time of day corresponding to the timestamp may be determined. Furthermore, the emergency alert signal may be transmitted to the users within the group(s) with a schedule corresponding to the timestamp. Operation 350 may be performed by an alert module that is the same as or similar to alert module 178, in accordance with one or more implementation”. The group that the emergency alert is transmitted to can be the subject or other users.). Lyons and Castillo are analogous art as they are directed towards solving a similar problem of monitoring a user’s heart rate over a period of time.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the alert generation from Castillo into the method from the Lyons/Cho combination as it allows the system to alert the user if there is a large change in their heart rate, as it keeps them informed of a health event that can/will occur, ensuring they are able to take proper action to prepare themselves.
Regarding claim 15, the Lyons/Cho/Castillo combination teaches the medical device system of claim 13, further comprising a memory configured to store the threshold and data indicating the current one or more responses and the subset of the plurality of responses previous to the current one or more responses (Lyons, [0105]: “a memory block for storing programmed parameters, usage data and any other recorded data”).
Regarding claim 17, the Lyons/Cho/Castillo combination teaches the medical device system of claim 13, wherein the processing circuitry is configured to determine the threshold based on at least one of a mean, a median, or a range of variability of the subset of the plurality of responses (Castillo, Column 11, line 42 – Column 12, line 6: “At step 510 a dynamic threshold is calculated based on the sensed heart rate. In one embodiment, the dynamic threshold may be a range defined by upper and lower threshold boundaries that, when crossed, indicates a change in heart rate that may be associated with a disordered breathing cycle. In a preferred embodiment, a dynamic threshold may be calculated based on a function of the rolling mean of the sensed heart rate. A rolling mean heart rate may calculated from a given number of heart rate data points according to the following formula:
H
R
m
e
a
n
n
=
H
R
m
e
a
n
n
-
1
+
x
n
-
H
R
m
e
a
n
(
n
-
1
)
N
wherein
H
R
m
e
a
n
n
-
1
is the rolling heart rate calculated on the previous heart rate data point; x(n) is the current heart rate data point; and N is the number of data points included in the rolling average. The upper and lower boundaries of the dynamic threshold range (DTR) may then be calculated according to equation (2):
D
T
R
n
=
H
R
m
e
a
n
(
n
)
±
K
(
n
)
wherein K(n) may be a fixed value including 0, a fraction of the mean heart rate from equation (1), proportional to the standard deviation of the mean heart rate, or other predefined value. When K(n) is 0, the dynamic threshold is a single curve rather than a range defined by an upper boundary curve and a lower boundary curve. In alternative embodiments, a threshold value or threshold range may be fixed value(s) that are programmable, rather than dynamically calculated values.”).
Regarding claim 18, the Lyons/Cho/Castillo combination teaches the medical device system of claim 17, wherein the range of variability is based on a number of standard deviations from the mean or the median of the subset of the plurality of responses (Castillo, Column 11, line 42 – Column 12, line 6: “At step 510 a dynamic threshold is calculated based on the sensed heart rate. In one embodiment, the dynamic threshold may be a range defined by upper and lower threshold boundaries that, when crossed, indicates a change in heart rate that may be associated with a disordered breathing cycle. In a preferred embodiment, a dynamic threshold may be calculated based on a function of the rolling mean of the sensed heart rate. A rolling mean heart rate may calculated from a given number of heart rate data points according to the following formula:
H
R
m
e
a
n
n
=
H
R
m
e
a
n
n
-
1
+
x
n
-
H
R
m
e
a
n
(
n
-
1
)
N
wherein
H
R
m
e
a
n
n
-
1
is the rolling heart rate calculated on the previous heart rate data point; x(n) is the current heart rate data point; and N is the number of data points included in the rolling average. The upper and lower boundaries of the dynamic threshold range (DTR) may then be calculated according to equation (2):
D
T
R
n
=
H
R
m
e
a
n
(
n
)
±
K
(
n
)
wherein K(n) may be a fixed value including 0, a fraction of the mean heart rate from equation (1), proportional to the standard deviation of the mean heart rate, or other predefined value. When K(n) is 0, the dynamic threshold is a single curve rather than a range defined by an upper boundary curve and a lower boundary curve. In alternative embodiments, a threshold value or threshold range may be fixed value(s) that are programmable, rather than dynamically calculated values.”).
Regarding claim 21, the Lyons/Cho/Castillo combination teaches the method of claim 1, wherein each posture transition of the plurality of detected posture transitions comprises a lay-sit transition (Lyons, [0051]: “Preferably, the states include a lying state, a lie-to-sit transition state”).
Regarding claim 22, the Lyons/Cho/Castillo combination teaches the system of claim 13, wherein each posture transition of the plurality of detected posture transitions comprises a sit-stand transition (Lyons, [0051]: “Preferably, the states include … a sit-to-stand transition state”).
Regarding claim 23, the Lyons/Cho/Castillo combination teaches the system of claim 13, wherein each posture transition of the plurality of detected posture transitions comprises a lay-sit transition (Lyons, [0051]: “Preferably, the states include a lying state, a lie-to-sit transition state”).
Regarding independent claim 24, Lyons teaches non-transitory computer-readable media comprising program instructions that, when executed by processing circuitry of a medical device system, the medical device system comprising a medical device ([0069]: “the invention provides a computer readable medium comprising software code adapted to be executed by a digital processor to perform the processor steps of a method as defined in any embodiment above”; [0030]: “the bio-mechanical sensors include sensors arranged to allow the processor to detect a user posture.”. The set of biomechanical sensors is the medical device), the medical device comprising an accelerometer and a plurality of electrodes ([0033]: “the sensors comprise one or more selected from accelerometers, electrocardiography (ECG) sensors”; [0129]: “monitoring of heart rate using ECG electrodes placed on the chest is important for predicting a syncopal fall arising from these conditions”. The ECG electrodes are the plurality of electrodes), cause the processing circuitry to:
detect a plurality of posture transitions of a subject based on an accelerometer signal from the accelerometer that varies as a function of movement and posture of the subject (Abstract: “The bio-mechanical sensors include sensors arranged to allow the processor to detect a user postures and posture transitions”. The posture transition is determined based on the accelerometer signals (movement), therefore the posture transitions vary as a function of movement and posture.); for each posture transition of the detected plurality of posture transitions, determine a respective response of a plurality of responses of a physiological parameter of the subject to the posture transition based on an electrocardiogram signal sensed via the plurality of electrodes, wherein the physiological parameter comprises one of heart rate, heart rate variability, or an electrocardiogram morphology parameter ([0088]: “the system of the invention detects combinations of intention to change posture, periods of prolonged standing, heart rate changes, and respiration rate changes that are precursor events to the start of a syncopal fall (a faint related fall)”. Fig. 9 shows determining heart rate values after a posture transition. Heart rate is measured from the ECG electrodes ([0131]: “heart rate is measured using an ECG patch”), and the heart rate is the physiological parameter), and wherein determining the respective response comprises determining a difference between a first value of the physiological parameter at or near a commencement of the posture transition and a second value of the physiological parameter at or near an end of the posture transition (Fig. 9; [0148]: “If a heart rate above 120 beats per minute is not detected (908) then the algorithm checks for an increase in heart rate of 30 beats per minute (909) above the pre-transition resting heart rate (910)”. The pre-transition heart rate is the first value and the detected heart rate after the transition is the second value.);
determine that a current one or more responses of the plurality of responses cross a threshold ([0148]: “If the timer value has not been reached (905) the algorithm checks for a sustained heart rate above 120 beats per minute (906) and applies NMES (904) if a heart rate above 120 beats per minute is detected (907). If a heart rate above 120 beats per minute is not detected (908) then the algorithm checks for an increase in heart rate of 30 beats per minute (909) above the pre-transition resting heart rate (910). If the heart rate increase is greater than 30 beats per minute (911) then NMES is applied (904). If the heart rate is not found to be greater than 30 beats per minute (912) than the algorithm returns back to the start of the timer checking step (913)”. The threshold is if the heart rate is over 120 beats per minute, or an increase of greater than 30 beats per minute. The threshold of greater than 30 beats per minute is determined relative to a previous response to the current measured heart rate.).
Lyons does not teach wherein the threshold is determined based on a subset of the plurality of responses previous to the current one or more responses , however this concept is suggested by the limitations of Lyons. Lyons involves determining the threshold based off of previous values of the heart rate, which suggests the use of a subset of the plurality of previous responses.
Cho discloses an apparatus and method for monitoring disordered breathing. While Cho is not directly related to the problem of preventing falls like Lyons, they both relate to a similar problem of evaluating heart rate data against a threshold to determine whether a user’s heart rate has exceeded normal values. Both references use similar evaluation techniques and methods to determine these thresholds, and therefore a person of ordinary skill in the art would look to Cho’s method for improvement on the method from Lyons. Specifically, Cho teaches wherein the threshold is determined based on a subset of the plurality of responses previous to the current one or more responses (Column 11, line 42 – Column 12, line 6: “At step 510 a dynamic threshold is calculated based on the sensed heart rate. In one embodiment, the dynamic threshold may be a range defined by upper and lower threshold boundaries that, when crossed, indicates a change in heart rate that may be associated with a disordered breathing cycle. In a preferred embodiment, a dynamic threshold may be calculated based on a function of the rolling mean of the sensed heart rate. A rolling mean heart rate may calculated from a given number of heart rate data points according to the following formula:
H
R
m
e
a
n
n
=
H
R
m
e
a
n
n
-
1
+
x
n
-
H
R
m
e
a
n
(
n
-
1
)
N
wherein
H
R
m
e
a
n
n
-
1
is the rolling heart rate calculated on the previous heart rate data point; x(n) is the current heart rate data point; and N is the number of data points included in the rolling average. The upper and lower boundaries of the dynamic threshold range (DTR) may then be calculated according to equation (2):
D
T
R
n
=
H
R
m
e
a
n
(
n
)
±
K
(
n
)
wherein K(n) may be a fixed value including 0, a fraction of the mean heart rate from equation (1), proportional to the standard deviation of the mean heart rate, or other predefined value. When K(n) is 0, the dynamic threshold is a single curve rather than a range defined by an upper boundary curve and a lower boundary curve. In alternative embodiments, a threshold value or threshold range may be fixed value(s) that are programmable, rather than dynamically calculated values.”). Lyons and Cho are analogous art as they are directed towards solving a similar problem of determining when a measured heart rate has increased a significant amount.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the dynamic threshold determination from Cho into the system from Lyons as it allows for a changing, dynamic threshold relative to the previous heart rate values rather than a set threshold number. This allows for a threshold that can automatically adapt and evolve based on real-time data, allowing for a more refined and personal value instead of a singular static value.
The Lyons/Cho combination does not teach generating an alert to a user based on the determination that the current one or more responses cross the threshold, wherein the user comprises the subject or another user, however the concept of notifying the user when there is an abnormal condition is suggested by Lyons. Lyons discloses a system to prevent falling, which revolves around the concept of determining an abnormal condition and notifying a user when there is a risk of fall. While the specific limitation of alerting the user when a value crosses a threshold is not explicitly recited in Lyons, the concept is suggested through the main goal of the system to prevent a fall.
Castillo discloses methods and systems for emergency alerts. While Castillo is not directly related to preventing falls of a user like Lyons, both references are directed to a similar problem of notifying a user of an abnormal condition to prevent a medical event from occurring. Therefore, when looking to improve the alert system from Lyons, a person of ordinary skill in the art would look to Castillo for a specific alert method. Specifically, Castillo teaches generating an alert to a user in response to the determination that the current one or more responses cross the threshold ([0061]: “Alert module 178 may be a hardware device configured to determine if an emergency situation has occurred responsive to receiving sensor data from wearable computing device 110 as determined by modules 119, 160, 162, 164, 166, 168, 170. Alert module 178 may set threshold values or change thresholds associated with received data from modules 119, 160, 162, 164, 166, 168, or 170. The threshold ranges or change threshold may be associated with if an emergency situation has occurred or if a quality check is desired to determine the cause of the emergency situation. The threshold ranges may set values associated with the wearer's biometric data, and the change thresholds may be associated with a change in values over a period of time. In embodiments, the threshold ranges may include a lower threshold and/or an upper threshold”; [0065]: “Responsive to alert module 178 determining that the heart rate of the wearer wearing wearable computing device 110 is increased or decreased based on data received from pulse oximeter 162 to levels greater than a heart rate change threshold and/or outside of a threshold range, alert module 178 may begin a quality check for a possible cause of the increase or decrease of the wearer's heart rate”; [0062]: “When alert module 178 determines an emergency situation has occurred, alert module 178 may transmit an emergency alert signal to a third party computing device 140”. The alert module generates an alert when the heart rate has increased over a certain threshold, which can be incorporated into the threshold from Lyons.), wherein the user comprises the subject or another user ([0098]: “At operation 350, the emergency alert signal may be transmitted to users within a group, wherein the group may be determined based on the timestamp and the user's schedule. Responsive to determining an emergency alert signal should be transmitted, groups that the user is part of having a schedule associated with the time of day corresponding to the timestamp may be determined. Furthermore, the emergency alert signal may be transmitted to the users within the group(s) with a schedule corresponding to the timestamp. Operation 350 may be performed by an alert module that is the same as or similar to alert module 178, in accordance with one or more implementation”. The group that the emergency alert is transmitted to can be the subject or other users.). Lyons and Castillo are analogous art as they are directed towards solving a similar problem of monitoring a user’s heart rate over a period of time.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the alert generation from Castillo into the method from the Lyons/Cho combination as it allows the system to alert the user if there is a large change in their heart rate, as it keeps them informed of a health event that can/will occur, ensuring they are able to take proper action to prepare themselves.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over the Lyons/Cho/Castillo combination as applied to claim 13 above, and further in view of Lee (US 20040167416).
Regarding claim 14, the Lyons/Cho/Castillo combination teaches the medical device system of claim 13.
However, the Lyons/Cho/Castillo combination does not teach the system further comprising a housing, wherein the housing is configured for implantation in a human body, and wherein the accelerometer and the plurality of electrodes are one of on or within the housing.
Lee discloses a method and apparatus for monitoring heart function. Specifically, Lee teaches the system further comprising a housing, wherein the housing is configured for implantation in a human body, and wherein the accelerometer and the plurality of electrodes are one of on or within the housing ([0012]: “An implantable hemodynamic monitoring device in accordance with the present invention is equipped with an acoustic sensor, ECG electrodes, a memory for storing acoustic and ECG data, and a microprocessor based controller for processing data and controlling device functions. An acoustic sensor may be provided as a passive sensor that does not require a power supply such as an accelerometer or piezoelectric sensor. An additional or alternative acoustic sensor may be provided as an active sensor requiring a power supply, such as a miniaturized microphone or an ultrasound transmitter and receiver. The acoustic sensor may be mounted within the device housing or header block, on the external surface of the housing or header block, or on a subcutaneous lead extending from the device.”). Lyons and Lee are analogous art as they are in the same field of endeavor as they both monitor heart function.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the housing for implantation from Lee into the system from the Lyons/Cho/Castillo combination as it is a known configuration and device for measuring ECG signals from a heart, and therefore would be a simple substitution to use the implantable device instead of an outside attachment of the sensors to the user.
Response to Arguments
All of applicant’s argument regarding the rejections and objections previously set forth have been fully considered and are persuasive unless directly addressed subsequently.
Applicant’s arguments with respect to the 103 rejections of claims 1, 3-4, 7, 10, 12-15, 17-18, and 21-24 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Applicant's arguments with respect to the 101 rejection have been fully considered but they are not persuasive. Applicant argues that the step of detecting posture transitions and determining respective responses of a physiological parameter to the posture transitions is not a mental process, specifically referencing the limitations of “wherein determining the respective response comprises determining a difference between a first value of the physiological parameter at or near a commencement of the posture transition and a second value of the physiological parameter at or near an end of the posture transition” and “the threshold determined based on a subset of the plurality of responses previous to the current one or more responses” as not being able to be practically performed in the human mind. Examiner disagrees, as determining a difference between two values can very easily be performed in the human mind. Additionally, determining a threshold based on previously recorded values can also easily be performed in the human mind or with the aid of pen and paper, as this can be based on a simple calculation or even basic observation to determine a threshold based on measured values. Applicant points to the use of implantable medical devices in the specification as evidence that the method cannot be performed in the human mind, however as stated previously in the 101 rejections, the use of an implantable device is generic data gathering, not a mental process, as evidenced by the cited references in the 101 rejection above. Applicant also argues that the claims integrate the abstract idea into a practical application. Applicant states that there is an improvement to the accuracy or timeliness of the output of a medical condition being monitored, and therefore is a practical application. However, the calculations and observations performed in the claims are already previously known and would have been obvious, as stated in the 103 rejection above, therefore this argument is not persuasive, and the claims do not reflect an improvement of the technology or technical field. Applicant also argues that the claims do not recite using the element of a medical device comprising an accelerometer and electrodes in a generic, well-understood, or routine manner. Applicant argues that the limitations of the claim cite using the accelerometer and electrodes to perform specific tasks, however the accelerometer is only claimed to provide an accelerometer signal, and the electrodes are only claimed to provide an electrocardiogram signal, both of which are generic and well-known functions of an accelerometer and a plurality of electrodes. The Applicant cites limitations that are not performed by either the accelerometer or the electrodes, but the processing circuitry, all of which are also mental processes being performed by a generic computer, and therefore do not add significantly more.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ERIN K MCCORMACK whose telephone number is (703)756-1886. The examiner can normally be reached Mon-Fri 7:30-5.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jason Sims can be reached at 5712727540. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/E.K.M./Examiner, Art Unit 3791
/JASON M SIMS/Supervisory Patent Examiner, Art Unit 3791
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