DETAILED ACTION
Applicant’s arguments, filed on 09/17/2025, have been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Applicants have amended their claims, filed on 09/17/2025, and therefore rejections newly made in the instant office action have been necessitated by amendment.
Claims 1-20 are the current claims hereby under examination.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1, the claim recites the limitation “control the analysis device based on a result of the analysis” in lines 24-25. It is unclear what is meant by controlling the analysis device based on a result of the analysis, as the analysis device is what provides the result, therefore the analysis device has already finished its claimed steps. The broad and indefinite scope of the limitation fails to inform a person of ordinary skill in the art with reasonable certainty of the metes and bounds of the claimed invention, therefore the claim is rendered indefinite. For purposes of examination, any type of control of the device based on the result will teach on this limitation. Claims 2-16 are also rejected due to their dependency on claim 1.
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 1-2, 10-11, and 16-19 are rejected under 35 U.S.C. 103 as being unpatentable over Johns Hopkins (“Holter Monitor”) in further view of Schram (US 20210401349) and Dhawan (US 20130096447).
Regarding independent claim 1, Johns Hopkins teaches a system for diagnosing a progressive structural heart disease (Page 1: “The Holter monitor is a type of portable electrocardiogram (ECG). It records the electrical activity of the heart continuously over 24 hours or longer while you are away from the doctor's office”), comprising:
obtain first ECG data corresponding to a patient;
analyze first ECG data for signs of the progressive structural heart disease;
based on the first ECG data indicating the progressive structural heart disease:
obtain multiple sets of the second ECG data corresponding to the patient (Page 1: “Your healthcare provider may request a Holter monitor ECG if you have symptoms, such as dizziness, fainting, low blood pressure, ongoing fatigue (tiredness), and palpitations and a resting ECG doesn't show a clear cause”; Page 2: “Certain arrhythmias (abnormal heart rhythms) may occur only now and then. Or, they may occur only under certain conditions, such as stress or activity. Arrhythmias of this type are hard to record on an ECG done in the office. Because of this, the healthcare provider might request a Holter monitor to get a better chance of capturing any abnormal heartbeats or rhythms that may be causing the symptoms. Some Holter monitors also have an event monitor feature that you activate when you notice symptoms.”; “The Holter monitor is a type of portable electrocardiogram (ECG). It records the electrical activity of the heart continuously over 24 hours or longer while you are away from the doctor's office”).
John’s Hopkins states that the first ECG data obtained is obtained in a doctor’s office, however it does not state how many leads the resting ECG uses.
Schram discloses a mobile electrocardiogram sensor. Specifically, Schram teaches a 12-lead ECG being a conventional lead amount for use in a doctor’s office and a 12-lead ECG configured to generate 12-lead ECG data ([0030]: “While a conventional 12-lead electrocardiogram gives very useful information concerning the health and condition of an individual's heart, the conventional electrocardiograph equipment is expensive and the procedure is not normally available in areas other than hospitals and medical doctors' offices”). Johns Hopkins and Schram are analogous arts as they are both related to ECGs used for monitoring a user.
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 12-lead ECG from Schram into the system from Johns Hopkins, as Johns Hopkins is silent on the amount of leads used, and Schram discloses a suitable number of leads in an analogous device.
However, the Johns Hopkins/Schram combination does not teach the second ECG data obtained with a 6-lead ECG device.
Schram discloses a 6-lead electrocardiogram (ECG) configured to generate 6-lead ECG data ([0045]: “an ECG sensing device 500 is configured to sense the six leads V1, V2, V3, V4, V5, and V6 sequentially when a user, for example, contacts a first electrode 502A with a right upper extremity, a second electrode 502B with a left upper extremity, and a third electrode 502C with an area of his or her chest corresponding to a precordial lead position.”; [0033]: “device 500 is referred to as a mobile computing device herein, and includes all necessary components to sense, record, and display ECG signals and analysis”; Abstract: “Embodiments of the present disclosure provide a mobile electrocardiogram (ECG) sensor comprising an electrode assembly comprising electrodes, wherein the electrode assembly senses heart-related signals when in contact with a body of a user, and produces electrical signals representing the sensed heart-related signals.”).
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 6-lead ECG from Schram into the Johns Hopkins/Schram combination as the 6-lead ECG is a suitable device for mobile electrocardiogram monitoring, and would be a simple substitution into the combination.
However, the Johns Hopkins/Schram combination is silent on the components used to process, analyze, and store data.
Schram teaches an analysis device comprising; a memory storing instructions; and at least one processor configured to execute the instructions ([0036]: “FIG. 5B illustrates a hardware block diagram of ECG sensing device 500, which may include hardware such as processing device 505 (e.g., processors, central processing units (CPUs)), memory 510 (e.g., random access memory (RAM), storage devices (e.g., hard-disk drive (HDD)), solid-state drives (SSD), etc.), and other hardware devices (e.g., analog to digital converter (ADC) etc.)”; [0039]: “the computing device 550 may be used to provide instructions for operating the ECG sensing device 500”).
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 analysis device from Schram into the Johns Hopkins/Schram combination as the combination is silent on the components used to process and store data, and Schram discloses a suitable component in an analogous device.
The Johns Hopkins/Schram combination teaches monitoring the 6-lead ECG data over time, but does not teach the multiple sets of 6-lead ECG data being obtained during spaced apart time intervals to show changes over time.
Dhawan discloses systems and methods for serial analysis of electrocardiograms. Specifically, Dhawan teaches the multiple sets of 6-lead ECG data being obtained during spaced apart time intervals to show changes over time (Abstract: “Systems and methods for serial analysis of electrocardiograms are presented, wherein serial electrocardiographic (ECG) assessment is incorporated with three-dimensional vectorial analysis of the cardiac electrical signal, using changes in novel 3D-based vectorial markers over time to improve diagnostic sensitivity for acute coronary syndromes (ACS), and improve differentiation of ACS from the broad range of heart diseases that resemble ACS on ECG.”; [0049]: “Two ECGs were taken for each patient between 10-60 min apart, and were transformed to 3D ECGs”). Johns Hopkins, Schram, and Dhawan are analogous arts as they are all related to systems using ECG data to monitor a patient over 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 obtaining the sets of ECG data during spaced apart time intervals instead of continuously, as it allows the device to collect data and specified times instead of all the time, which can save memory space and processing capabilities of the device and only record measurements when needed, not all the time.
The Johns Hopkins/Schram/Dhawan combination teaches the step of perform serial analysis on the multiple sets of the 6-lead ECG data to validate the indicated progressive structural heart disease (Dhawan, Abstract: “Systems and methods for serial analysis of electrocardiograms are presented, wherein serial electrocardiographic (ECG) assessment is incorporated with three-dimensional vectorial analysis of the cardiac electrical signal, using changes in novel 3D-based vectorial markers over time to improve diagnostic sensitivity for acute coronary syndromes (ACS), and improve differentiation of ACS from the broad range of heart diseases that resemble ACS on ECG.”; [0049]: “Two ECGs were taken for each patient between 10-60 min apart, and were transformed to 3D ECGs”; Johns Hopkins, Page 2: “Some reasons for your healthcare provider to request a Holter monitor recording or event monitor recording include: … To identify irregular heartbeats or palpitations, To assess risk for future heart-related events in certain conditions, such as hypertrophic cardiomyopathy (thickened heart walls), after a heart attack that caused weakness of the left side of the heart, or Wolff-Parkinson-White syndrome (where an abnormal electrical conduction pathway exists within the heart)”).
However, the Johns Hopkins/Schram/Dhawan combination does not teach the step of control the analysis device based on a result of the analysis.
Schram teaches the step of control the analysis device based on a result of the analysis ([0029]: “The machine learning model may be trained using 12-lead ECG data corresponding to a population of individuals. The data, before being input into the machine learning model, may be pre-processed to filter the data in a manner suitable for the application. For example, data may be categorized according to height, gender, weight, nationality, etc. before being used to train one or more machine learning models, such that the resulting one or models are finely-tuned the specific types of individuals. In a further embodiment, the machine learning model may be further trained based on a user's own ECG data, to fine-tune and personalize the model even further to decrease any residual synthesis error.”).
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 control step from Schram into the Johns Hopkins/Schram/Dhawan combination as it allows the combination to use the result to train the analysis device, which can provide more information and a more accurate result.
Regarding claim 2, the Johns Hopkins/Schram/Dhawan combination teaches the system of claim 1.
However, the combination is silent on the steps used to analyze the ECH data.
Schram teaches wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease, determine one or more trends across the multiple sets the 6-lead ECG data ([0067]: “the ECG sensing device 500 may be used to predict the QT interval of a user. As discussed herein, Machine learning (ML) is well suited for continuous monitoring of one or multiple criteria to identify anomalies or trends, big and small, in input data as compared to training examples used to train the model”).
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 analysis step of determining trends of the ECG data from Schram into the Johns Hopkins/Schram/Dhawan combination as the combination is silent on the analysis steps, and Schram discloses suitable analysis steps in an analogous device.
Regarding claim 10, the Johns Hopkins/Schram/Dhawan combination teaches the system of claim 1.
However, the Johns Hopkins/Schram/Dhawan combination does not teach wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease, obtain a diagnosis by analyzing the results of the serial analysis for the progressive structural heart disease based on trends in 6-lead ECG data.
Schram teaches wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease, obtain a diagnosis by analyzing the results of the serial analysis for the progressive structural heart disease based on trends in 6-lead ECG data ([0083]: “software incorporated with any of the systems, devices, methods described herein may be used to determine a diagnosis or abnormality associated with an ECG”).
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 diagnosis from Schram into the Johns Hopkins/Schram/Dhawan combination as it allows the combination to not only monitor symptoms and potential diseases, but also provide the user with a diagnosis based on the measured ECG signals.
Regarding claim 11, the Johns Hopkins/Schram/Dhawan combination teaches the system of claim 1, wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease: obtain patient symptom data corresponding to each set of the multiple sets of the 6-lead ECG data (Johns Hopkins, Page 2: “Some Holter monitors also have an event monitor feature that you activate when you notice symptoms.”; Page 3: “You will be instructed to keep a diary of your activities while wearing the monitor. Write down the date and time of your activities, particularly if any symptoms, such as dizziness, palpitations, chest pain, or other previously experienced symptoms, occur.”).
Regarding claim 16, the Johns Hopkins/Schram/Dhawan combination teaches the system of claim 1.
However, the Johns Hopkins/Schram/Dhawan combination does not teach wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data not indicating the disease, output information indicating that no disease has been detected.
Schram teaches wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data not indicating the disease, output information indicating that no disease has been detected ([0083]: “software incorporated with any of the systems, devices, methods described herein may be used to determine a diagnosis or abnormality associated with an ECG”. If the diagnosis is that no disease is detected, this is what will be output.).
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 diagnosis information from Schram into the Johns Hopkins/Schram/Dhawan combination as it allows the combination to not only monitor symptoms and potential diseases, but also provide the user with a diagnosis based on the measured ECG signals.
Regarding independent claim 17, Johns Hopkins teaches a system for diagnosing a progressive structural heart disease (Page 1: “The Holter monitor is a type of portable electrocardiogram (ECG). It records the electrical activity of the heart continuously over 24 hours or longer while you are away from the doctor's office”), the system comprising:
obtain first electrocardiogram (ECG) data corresponding to a patient; the first ECG data being obtained based on a first amount of leads;
analyze the first ECG data for signs of the progressive structural heart disease; and
based on the first ECG data indicating the disease:
obtain multiple sets of the second ECG data corresponding to the patient, the second ECG data being obtained based on a second amount of leads, (Page 1: “Your healthcare provider may request a Holter monitor ECG if you have symptoms, such as dizziness, fainting, low blood pressure, ongoing fatigue (tiredness), and palpitations and a resting ECG doesn't show a clear cause”; Page 2: “Certain arrhythmias (abnormal heart rhythms) may occur only now and then. Or, they may occur only under certain conditions, such as stress or activity. Arrhythmias of this type are hard to record on an ECG done in the office. Because of this, the healthcare provider might request a Holter monitor to get a better chance of capturing any abnormal heartbeats or rhythms that may be causing the symptoms. Some Holter monitors also have an event monitor feature that you activate when you notice symptoms.”; “The Holter monitor is a type of portable electrocardiogram (ECG). It records the electrical activity of the heart continuously over 24 hours or longer while you are away from the doctor's office”).
John’s Hopkins states that the first ECG data obtained is obtained in a doctor’s office, however it does not state how many leads the resting ECG uses.
Schram discloses a mobile electrocardiogram sensor. Specifically, Schram teaches a 12-lead ECG being a conventional lead amount for use in a doctor’s office wherein the second amount of leads is less than the first amount of leads ([0030]: “While a conventional 12-lead electrocardiogram gives very useful information concerning the health and condition of an individual's heart, the conventional electrocardiograph equipment is expensive and the procedure is not normally available in areas other than hospitals and medical doctors' offices”). Johns Hopkins and Schram are analogous arts as they are both related to ECGs used for monitoring a user.
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 12-lead ECG from Schram into the system from Johns Hopkins, as Johns Hopkins is silent on the amount of leads used, and Schram discloses a suitable number of leads in an analogous device. Additionally, Johns Hopkins utilizes 5 leads (Fig. 1), therefore the first amount of leads is more than the second amount of leads.
However, the Johns Hopkins/Schram combination is silent on the components used to process, analyze, and store data.
Schram teaches a memory storing instructions; and at least one processor configured to execute the instructions ([0036]: “FIG. 5B illustrates a hardware block diagram of ECG sensing device 500, which may include hardware such as processing device 505 (e.g., processors, central processing units (CPUs)), memory 510 (e.g., random access memory (RAM), storage devices (e.g., hard-disk drive (HDD)), solid-state drives (SSD), etc.), and other hardware devices (e.g., analog to digital converter (ADC) etc.)”; [0039]: “the computing device 550 may be used to provide instructions for operating the ECG sensing device 500”).
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 analysis device from Schram into the Johns Hopkins/Schram combination as the combination is silent on the components used to process and store data, and Schram discloses a suitable component in an analogous device.
The Johns Hopkins/Schram combination teaches monitoring the second ECG data over time, but does not teach the multiple sets of second ECG data being obtained during spaced apart time intervals to show changes over time.
Dhawan discloses systems and methods for serial analysis of electrocardiograms. Specifically, Dhawan teaches each of the sets being obtained during a time period that is spaced apart from time periods of the other sets (Abstract: “Systems and methods for serial analysis of electrocardiograms are presented, wherein serial electrocardiographic (ECG) assessment is incorporated with three-dimensional vectorial analysis of the cardiac electrical signal, using changes in novel 3D-based vectorial markers over time to improve diagnostic sensitivity for acute coronary syndromes (ACS), and improve differentiation of ACS from the broad range of heart diseases that resemble ACS on ECG.”; [0049]: “Two ECGs were taken for each patient between 10-60 min apart, and were transformed to 3D ECGs”). Johns Hopkins, Schram, and Dhawan are analogous arts as they are all related to systems using ECG data to monitor a patient over 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 obtaining the sets of ECG data during spaced apart time intervals instead of continuously, as it allows the device to collect data and specified times instead of all the time, which can save memory space and processing capabilities of the device and only record measurements when needed, not all the time.
The Johns Hopkins/Schram/Dhawan combination teaches the step of perform serial analysis on the multiple sets of the second ECG data to validate the indicated progressive structural heart disease; and output a result of the serial analysis (Dhawan, Abstract: “Systems and methods for serial analysis of electrocardiograms are presented, wherein serial electrocardiographic (ECG) assessment is incorporated with three-dimensional vectorial analysis of the cardiac electrical signal, using changes in novel 3D-based vectorial markers over time to improve diagnostic sensitivity for acute coronary syndromes (ACS), and improve differentiation of ACS from the broad range of heart diseases that resemble ACS on ECG.”; [0049]: “Two ECGs were taken for each patient between 10-60 min apart, and were transformed to 3D ECGs”; Johns Hopkins, Page 2: “Some reasons for your healthcare provider to request a Holter monitor recording or event monitor recording include: … To identify irregular heartbeats or palpitations, To assess risk for future heart-related events in certain conditions, such as hypertrophic cardiomyopathy (thickened heart walls), after a heart attack that caused weakness of the left side of the heart, or Wolff-Parkinson-White syndrome (where an abnormal electrical conduction pathway exists within the heart)”).
Regarding claim 18, the Johns Hopkins/Schram/Dhawan combination teaches the system of claim 17.
However, the combination is silent on the steps used to analyze the ECH data.
Schram teaches wherein the result of the serial analysis is information corresponding to a trend in the second ECG data ([0067]: “the ECG sensing device 500 may be used to predict the QT interval of a user. As discussed herein, Machine learning (ML) is well suited for continuous monitoring of one or multiple criteria to identify anomalies or trends, big and small, in input data as compared to training examples used to train the model”).
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 analysis step of determining trends of the ECG data from Schram into the Johns Hopkins/Schram/Dhawan combination as the combination is silent on the analysis steps, and Schram discloses suitable analysis steps in an analogous device.
Regarding claim 19, the Johns Hopkins/Schram/Dhawan combination teaches the system of claim 17.
However, the Johns Hopkins/Schram/Dhawan combination does not teach wherein the at least one processor is configured to execute the instructions to, based on the first ECG data not indicating the disease, end a process of analyzing ECG data.
Schram teaches wherein the at least one processor is configured to execute the instructions to, based on the first ECG data not indicating the disease, end a process of analyzing ECG data ([0083]: “software incorporated with any of the systems, devices, methods described herein may be used to determine a diagnosis or abnormality associated with an ECG”).
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 diagnosis information from Schram into the Johns Hopkins/Schram/Dhawan combination as it allows the combination to not only monitor symptoms and potential diseases, but also provide the user with a diagnosis based on the measured ECG signals.
Claims 3-5 are rejected under 35 U.S.C. 103 as being unpatentable over the Johns Hopkins/Schram/Dhawan combination as applied to claim 2 above, and further in view of Doomra (WO 2023026151).
Regarding claim 3, the Johns Hopkins/Schram/Dhawan combination teaches the system of claim 2.
However, the Johns Hopkins/Schram/Dhawan combination is silent on the analysis steps used to process the data.
Doomra discloses a system to analyze biological signals to diagnose diseases in a user. Specifically, Doomra teaches wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease: obtain a first cardiac vector for each set of the 6-lead ECG data; and record an angle of each of the first cardiac vectors ([0096]: “Module 500 can determine (i) the vector azimuth angle values and the elevation angle values for the 6 cardiac vectors and (ii) the elevation angles of the 8 PPG vectors of Table 6, e.g., to provide up to 28 features for the cardiac signal data”). Johns Hopkins, Schram, Dhawan, and Doomra are analogous arts as they are all related to measuring and analyzing ECG signals.
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 analysis steps from Doomra into the Johns Hopkins/Schram/Dhawan combination as the combination is silent on the analysis steps, and Doomra provides suitable analysis steps in an analogous device.
Regarding claim 4, the Johns Hopkins/Schram/Dhawan/Doomra combination teaches the system of claim 3, wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease: obtain a first diagnosis based on the angles of the first cardiac vectors trending in a first direction; and obtain a second diagnosis based on the angles of the first cardiac vectors trending in a second direction (Doomra, [0095]: “Module 500 can calculate the magnitude of the projection of a given vector in the 3 orthogonal planes, e.g., as the square root of the sum of orthogonal components of the projection. Module 500 can thus determine the 2dAmplitude values for the 6 cardiac vectors and 8 PPG vectors of Table 6 for the 3 orthogonal planes, e.g., to provide up to 66 features for the cardiac signal data and the 2 PPG signal data.”; Abstract: “The visual features or parameters can be used in a model or classifier (e.g., a machine-learned classifier) to estimate metrics associated with the physiological state of a patient, including for the presence or non-presence of a disease, medical condition, or an indication of either. The estimated metric may be used to assist a physician or other healthcare provider in diagnosing the presence or non-presence and/or severity and/or localization of diseases or conditions or in the treatment of said diseases or conditions.”).
Regarding claim 5, the Johns Hopkins/Schram/Dhawan/Doomra combination teaches the system of claim 3, wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease: obtain, for each set of the 6-lead ECG data, a second cardiac vector; obtain, for each set of the 6-lead ECG data, an angular relationship between the first vector and the second vector (Doomra, [0095]: “Module 500 can calculate the magnitude of the projection of a given vector in the 3 orthogonal planes, e.g., as the square root of the sum of orthogonal components of the projection. Module 500 can thus determine the 2dAmplitude values for the 6 cardiac vectors and 8 PPG vectors of Table 6 for the 3 orthogonal planes, e.g., to provide up to 66 features for the cardiac signal data and the 2 PPG signal data.”; Abstract: “The visual features or parameters can be used in a model or classifier (e.g., a machine-learned classifier) to estimate metrics associated with the physiological state of a patient, including for the presence or non-presence of a disease, medical condition, or an indication of either. The estimated metric may be used to assist a physician or other healthcare provider in diagnosing the presence or non-presence and/or severity and/or localization of diseases or conditions or in the treatment of said diseases or conditions.”); and detect a trend in the angular relationships (Schram, [0067]: “the ECG sensing device 500 may be used to predict the QT interval of a user. As discussed herein, Machine learning (ML) is well suited for continuous monitoring of one or multiple criteria to identify anomalies or trends, big and small, in input data as compared to training examples used to train the model”).
Claims 6-9 are rejected under 35 U.S.C. 103 as being unpatentable over the Johns Hopkins/Schram/Dhawan combination as applied to claim 1 above, and further in view of Toth (US Patent 12310760).
Regarding claim 6, the Johns Hopkins/Schram/Dhawan combination teaches the system of claim 1.
However, the Johns Hopkins/Schram/Dhawan combination is silent on the analysis steps used to analyze the ECG data.
Toth discloses a system to monitor and process physiological systems. Specifically, Toth teaches wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease: obtain, from each set of the multiple sets of 6-lead ECG data, a first value corresponding to a first quantifiable metric; obtain a first trend value based on a trend in the first values; and generate a value indicating a degree of a disease based on the first trend value (Column 6, lines 49-57: “determine groups of similarly classified cardiac cycles of the electrocardiogram signals which fall within the parsed regions based on a time synchronization of each cardiac cycle within the respiratory cycles and the torso posture of the individual, (iii) extract waveform features in each group of similarly classified cardiac cycles in each of the parsed regions, (iv) determine a trend in changes of the extracted waveform feature of each group of similarly classified cardiac cycles (v) compare the determined trends to known trends in changes of the extracted waveform feature for developing a heart dysfunction as determined from a cohort patient population, and (vi) predict a risk level of the individual developing the heart dysfunction based on a result of comparing the determined trends to the known trends.”). Johns Hopkins, Schram, Dhawan, and Toth are analogous arts as they are all related to measuring and analyzing ECG signals.
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 analysis steps from Toth into the Johns Hopkins/Schram/Dhawan combination as the combination is silent on the analysis steps, and Toth discloses suitable steps in an analogous device.
Regarding claim 7, the Johns Hopkins/Schram/Dhawan/Toth combination teaches the system of claim 6, wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease: compare the first trend value to a predefined threshold; and based on the first trend value exceeding the predefined threshold, output the first trend value (Toth, Column 6, lines 49-57: “determine groups of similarly classified cardiac cycles of the electrocardiogram signals which fall within the parsed regions based on a time synchronization of each cardiac cycle within the respiratory cycles and the torso posture of the individual, (iii) extract waveform features in each group of similarly classified cardiac cycles in each of the parsed regions, (iv) determine a trend in changes of the extracted waveform feature of each group of similarly classified cardiac cycles (v) compare the determined trends to known trends in changes of the extracted waveform feature for developing a heart dysfunction as determined from a cohort patient population, and (vi) predict a risk level of the individual developing the heart dysfunction based on a result of comparing the determined trends to the known trends.”. The known trends are the predefined threshold, and the risk level is the output of the first trend value.).
Regarding claim 8, the Johns Hopkins/Schram/Dhawan/Toth combination teaches the system of claim 7, wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease: obtain, from each set of the multiple sets of the 6-lead ECG data, a second value indicating a second quantifiable metric; detect a second trend in the obtained second values; and generate a value indicating the degree of the disease based on the detected first trend and the detected second trend (Toth, Column 6, lines 49-57: “determine groups of similarly classified cardiac cycles of the electrocardiogram signals which fall within the parsed regions based on a time synchronization of each cardiac cycle within the respiratory cycles and the torso posture of the individual, (iii) extract waveform features in each group of similarly classified cardiac cycles in each of the parsed regions, (iv) determine a trend in changes of the extracted waveform feature of each group of similarly classified cardiac cycles (v) compare the determined trends to known trends in changes of the extracted waveform feature for developing a heart dysfunction as determined from a cohort patient population, and (vi) predict a risk level of the individual developing the heart dysfunction based on a result of comparing the determined trends to the known trends.” Different waveform features can be used to determine the second trend.).
Regarding claim 9, the Johns Hopkins/Schram/Dhawan/Toth combination teaches the system of claim 8, wherein the first trend value is based on a first feature in the multiple sets of 6-lead ECG data and the second trend value is based on a second feature in the multiple sets of 6-lead ECG data (Toth, Column 6, lines 49-57: “determine groups of similarly classified cardiac cycles of the electrocardiogram signals which fall within the parsed regions based on a time synchronization of each cardiac cycle within the respiratory cycles and the torso posture of the individual, (iii) extract waveform features in each group of similarly classified cardiac cycles in each of the parsed regions, (iv) determine a trend in changes of the extracted waveform feature of each group of similarly classified cardiac cycles (v) compare the determined trends to known trends in changes of the extracted waveform feature for developing a heart dysfunction as determined from a cohort patient population, and (vi) predict a risk level of the individual developing the heart dysfunction based on a result of comparing the determined trends to the known trends.” Different waveform features can be used to determine the second trend.).
Claims 12-15 are rejected under 35 U.S.C. 103 as being unpatentable over the Johns Hopkins/Schram/Dhawan combination as applied to claim 11 above, and further in view of Bardy (EP 2438848).
Regarding claim 12, the Johns Hopkins/Schram/Dhawan combination teaches the system of claim 11, wherein the patient symptom data includes: one or more symptoms (Johns Hopkins, Page 2: “Some Holter monitors also have an event monitor feature that you activate when you notice symptoms.”; Page 3: “You will be instructed to keep a diary of your activities while wearing the monitor. Write down the date and time of your activities, particularly if any symptoms, such as dizziness, palpitations, chest pain, or other previously experienced symptoms, occur.”).
However, the Johns Hopkins/Schram/Dhawan combination does not teach the patient symptom data including a severity value corresponding to a severity of each of the one or more symptoms.
Bardy discloses a method for evaluating ECG signals. Specifically, Bardy teaches the patient symptom data including a severity value corresponding to a severity of each of the one or more symptoms ([0035]: “A complete patient history 55 indicates how frequent the patients presumed arrhythmia arises, its duration, the severity of symptoms, heart rate, drug and dietary history, systematic illnesses, and family history of rhythm disturbances. The patient history 55 elicits major cardiovascular symptoms and how they may have varied over time. Classic cardiovascular symptoms can include chest discomfort, dyspnea, fatigue, edema, palpitations, syncope, coughing, hemoptysis, and cyanosis.”). Johns Hopkins, Schram, Dhawan, and Bardy are analogous arts as they are all related to measuring and analyzing ECG signals.
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 severity of symptoms from Brady into the Johns Hopkins/Schram/Dhawan combination as it allows the system to evaluate not only the symptoms, but also the severity, which can allow for a more comprehensive analysis of the user’s health state and the ECG signals.
Regarding claim 13, the Johns Hopkins/Schram/Dhawan combination teaches the system of claim 11.
However, the Johns Hopkins/Schram/Dhawan combination is silent on the analysis steps for processing the ECG data.
Bardy teaches wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease: obtain a symptom trend value based on a serial analysis of one or more patient symptoms corresponding to the multiple sets of 6-lead ECG data to detect a trend in the patient symptoms over time ([0034]: “a series of ambulatory ECG monitors 52 can be used over the course of several months to establish a trending analysis for a patient 12 with particularly sporadic symptoms, such as episodic paroxysmal atrial fibrillation.”).
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 analysis steps from Bardy into the Johns Hopkins/Schram/Dhawan combination as the combination is silent on the analysis steps and Bardy discloses suitable analysis steps in an analogous device.
Regarding claim 14, the Johns Hopkins/Schram/Dhawan/Bardy combination teaches the system of claim 13.
However, the Johns Hopkins/Schram/Dhawan/Bardy combination does not teach wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease, perform the serial analysis of the one or more patient symptoms by quantifying a severity of each of the one or more symptoms.
Bardy teaches wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease, perform the serial analysis of the one or more patient symptoms by quantifying a severity of each of the one or more symptoms ([0035]: “A complete patient history 55 indicates how frequent the patients presumed arrhythmia arises, its duration, the severity of symptoms, heart rate, drug and dietary history, systematic illnesses, and family history of rhythm disturbances. The patient history 55 elicits major cardiovascular symptoms and how they may have varied over time. Classic cardiovascular symptoms can include chest discomfort, dyspnea, fatigue, edema, palpitations, syncope, coughing, hemoptysis, and cyanosis.”).
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 performing serial analysis on the patient symptoms from Bardy into the Johns Hopkins/Schram/Dhawan/Bardy combination as it allows the system to analyze the symptoms over time and allow for more information to aid the analysis of the user’s ECG data and health information, which can provide a more comprehensive analysis.
Regarding claim 15, the Johns Hopkins/Schram/Dhawan/Bardy combination teaches the system of claim 13.
However, the Johns Hopkins/Schram/Dhawan/Bardy combination does not teach wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease, obtain a diagnosis by analyzing the results of the serial analysis of the 6-lead ECG data and a result of the serial analysis of the patient symptom data for the progressive structural heart disease based on a trend in 6-lead ECG data and a trend in the patient symptoms.
Schram and Bardy teach wherein the at least one processor is configured to execute the instructions to, based on the 12-lead ECG data indicating the disease, obtain a diagnosis by analyzing the results of the serial analysis of the 6-lead ECG data and a result of the serial analysis of the patient symptom data for the progressive structural heart disease based on a trend in 6-lead ECG data and a trend in the patient symptoms (Bardy, [0034]: “a series of ambulatory ECG monitors 52 can be used over the course of several months to establish a trending analysis for a patient 12 with particularly sporadic symptoms, such as episodic paroxysmal atrial fibrillation.”; Schram, [0083]: “software incorporated with any of the systems, devices, methods described herein may be used to determine a diagnosis or abnormality associated with an ECG”).
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 analysis steps from Schram and Bardy into the Johns Hopkins/Schram/Dhawan/Bardy combination as the combination is silent on the analysis steps used to process the ECG signals, and Schram and Brody disclose suitable analysis steps in an analogous device.
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Johns Hopkins in further view of Schram, Dhawan, and Toth.
Regarding independent claim 20, Johns Hopkins teaches a system for determining a degree of a progressive structural heart disease (Page 1: “The Holter monitor is a type of portable electrocardiogram (ECG). It records the electrical activity of the heart continuously over
24 hours or longer while you are away from the doctor's office”), the system comprising:
obtain first electrocardiogram (ECG) data corresponding to a patient;
analyze the first ECG data for signs of the progressive structural heart disease; and
based on the first ECG data indicating the disease:
obtain multiple sets of the second ECG data corresponding to the patient (Page 1: “Your healthcare provider may request a Holter monitor ECG if you have symptoms, such as dizziness, fainting, low blood pressure, ongoing fatigue (tiredness), and palpitations and a resting ECG doesn't show a clear cause”; Page 2: “Certain arrhythmias (abnormal heart rhythms) may occur only now and then. Or, they may occur only under certain conditions, such as stress or activity. Arrhythmias of this type are hard to record on an ECG done in the office. Because of this, the healthcare provider might request a Holter monitor to get a better chance of capturing any abnormal heartbeats or rhythms that may be causing the symptoms. Some Holter monitors also have an event monitor feature that you activate when you notice symptoms.”; “The Holter monitor is a type of portable electrocardiogram (ECG). It records the electrical activity of the heart continuously over 24 hours or longer while you are away from the doctor's office”).
John’s Hopkins states that the first ECG data obtained is obtained in a doctor’s office, however it does not state how many leads the resting ECG uses.
Schram discloses a mobile electrocardiogram sensor. Specifically, Schram teaches a 12-lead ECG being a conventional lead amount for use in a doctor’s office ([0030]: “While a conventional 12-lead electrocardiogram gives very useful information concerning the health and condition of an individual's heart, the conventional electrocardiograph equipment is expensive and the procedure is not normally available in areas other than hospitals and medical doctors' offices”). Johns Hopkins and Schram are analogous arts as they are both related to ECGs used for monitoring a user.
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 12-lead ECG from Schram into the system from Johns Hopkins, as Johns Hopkins is silent on the amount of leads used, and Schram discloses a suitable number of leads in an analogous device. Additionally, Johns Hopkins utilizes 5 leads (Fig. 1), therefore the first amount of leads is more than the second amount of leads.
However, the Johns Hopkins/Schram combination is silent on the components used to process, analyze, and store data.
Schram teaches a memory storing instructions; and at least one processor configured to execute the instructions ([0036]: “FIG. 5B illustrates a hardware block diagram of ECG sensing device 500, which may include hardware such as processing device 505 (e.g., processors, central processing units (CPUs)), memory 510 (e.g., random access memory (RAM), storage devices (e.g., hard-disk drive (HDD)), solid-state drives (SSD), etc.), and other hardware devices (e.g., analog to digital converter (ADC) etc.)”; [0039]: “the computing device 550 may be used to provide instructions for operating the ECG sensing device 500”).
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 analysis device from Schram into the Johns Hopkins/Schram combination as the combination is silent on the components used to process and store data, and Schram discloses a suitable component in an analogous device.
The Johns Hopkins/Schram combination teaches monitoring the second ECG data over time, but does not teach the multiple sets of second ECG data being obtained during spaced apart time intervals to show changes over time.
Dhawan discloses systems and methods for serial analysis of electrocardiograms. Specifically, Dhawan teaches the less-lead ECG data being obtained during spaced apart time intervals (Abstract: “Systems and methods for serial analysis of electrocardiograms are presented, wherein serial electrocardiographic (ECG) assessment is incorporated with three-dimensional vectorial analysis of the cardiac electrical signal, using changes in novel 3D-based vectorial markers over time to improve diagnostic sensitivity for acute coronary syndromes (ACS), and improve differentiation of ACS from the broad range of heart diseases that resemble ACS on ECG.”; [0049]: “Two ECGs were taken for each patient between 10-60 min apart, and were transformed to 3D ECGs”). Johns Hopkins, Schram, and Dhawan are analogous arts as they are all related to systems using ECG data to monitor a patient over 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 obtaining the sets of ECG data during spaced apart time intervals instead of continuously, as it allows the device to collect data and specified times instead of all the time, which can save memory space and processing capabilities of the device and only record measurements when needed, not all the time.
However, the Johns Hopkins/Schram/Dhawan combination does not teach the steps of obtain, from each set of the multiple sets of less-lead ECG data, a first value corresponding to a first quantifiable feature, obtain a first trend value based on a first trend in the obtained first values; and obtain a degree score based on the first trend value, the degree score indicating a degree of the progressive structural heart disease.
Toth discloses a system to monitor and process physiological systems. Specifically, Toth teaches the steps of obtain, from each set of the multiple sets of less-lead ECG data, a first value corresponding to a first quantifiable feature; obtain a first trend value based on a first trend in the obtained first values; and obtain a degree score based on the first trend value, the degree score indicating a degree of the progressive structural heart disease (Column 6, lines 49-57: “determine groups of similarly classified cardiac cycles of the electrocardiogram signals which fall within the parsed regions based on a time synchronization of each cardiac cycle within the respiratory cycles and the torso posture of the individual, (iii) extract waveform features in each group of similarly classified cardiac cycles in each of the parsed regions, (iv) determine a trend in changes of the extracted waveform feature of each group of similarly classified cardiac cycles (v) compare the determined trends to known trends in changes of the extracted waveform feature for developing a heart dysfunction as determined from a cohort patient population, and (vi) predict a risk level of the individual developing the heart dysfunction based on a result of comparing the determined trends to the known trends.”). Johns Hopkins, Schram, Dhawan, and Toth are analogous arts as they are all related to measuring and analyzing ECG signals.
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 analysis of trends from Toth into the system from the Johns Hopkins/Schram/Dhawan combination as it allows the system to analyze the ECG signals over time and determine further analysis of the health condition of the user, which can provide the user with more information about their health and how it is progressing.
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 claims 1-20 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.
Conclusion
Applicant's submission of an information disclosure statement under 37 CFR 1.97(c) with the timing fee set forth in 37 CFR 1.17(p) on 08/28/2025 prompted the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 609.04(b). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/E.K.M./Examiner, Art Unit 3791
/RENE T TOWA/Primary Examiner, Art Unit 3791