Detailed Correspondence
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of claims
This final office action on merits is in response to the communication received on 12/30/2025. Claims 2-3, 7-10, and 13 are cancelled. Amendments to claims 1, 4-6, 11-12, and 14-15 are acknowledged and have been carefully considered. Claims 1, 4-6, 11-12, and 14-15 are pending and considered below.
Claim Objections
Claim 6 is objected to because of the following informalities: “System according to claim 5” should read “System according to claim 4” in claim 6.
Specification and Drawings
The objections to the specification and drawings are withdrawn. It was indicated that the specification described an element “device 11,” while the drawings did not include such an element, creating an inconsistency between the written description and the drawings. Applicant identified device 11 in figure 1 so that the device element is consistently identified throughout the specification and drawings.
It was further indicated that the specification and drawings were objected to because the reference numerals “device (5, 7)” were used inconsistently between the claims and the specification. Applicant has addressed this issue by removing the reference signs from the claims, thereby eliminating the inconsistency. Accordingly, this objection is also withdrawn.
The objection to the specification regarding trademark usage is withdrawn. Applicant amended the specification to include the appropriate trademark designations for “Apple,” “iPhone,” and “Pro 13” where these terms appear.
Claim Rejections - 35 USC § 112
The rejection of the claims under 35 U.S.C. § 112(b) for indefiniteness has been overcome. Applicant amended the claims to remove the inconsistent reference numerals (“device (1),” “device (11),” and “device (5, 7)”) that created ambiguity regarding the identity and number of devices recited in the claims. By removing the reference numerals, the claims no longer contain inconsistent element designations and the scope of the claimed subject matter can now be reasonably ascertained. Accordingly, the rejection under 35 U.S.C. § 112(b) is withdrawn.
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, 4-6, 11-12, and 14-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Under step 1, the analysis is based on MPEP 2106.03, and claims 1, 4-6, 11-12 are drawn to a system and claim 14 is drawn to a method. Thus, each of these claims, on their face, is directed to one of the statutory categories (i.e., useful process, machine, manufacture, or composition of matter) of 35 U.S.C. §101.
Additionally, claim 15 is directed to non-statutory subject matter. Claim 15 does not fall within at least one of the four categories of patent eligible subject matter because the claim(s) are directed to a computer code per se. Applicant is advised that the claim may be amended to recite statutory subject matter by replacing the recitation of a “computer program” with “a non-transitory computer-readable storage medium storing instructions”, which would place the claim in a statutory category.
Step 2A Prong One
Claim 1 recites the limitations of determining the type of the smart phone running the application software; and determining the health state of the heart of the user based on the measurement signal and based on the mass of the smartphone and/or based on the moment of inertia of the smart phone. These limitations, as drafted, are processes that, under their broadest reasonable interpretations, cover performance of the limitations in the mind or by using a pen and paper. The claim encompasses a user observing the measurement signal and device information and evaluating that information to determine a health state of the heart in their mind or by using a pen and paper. Thus, the claim recites a mental process which is an abstract idea.
Claim 1 also recites the limitation of determining a mass of the smartphone and/or a moment of inertia of the smart phone based on the type of the device smartphone determined. This limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers mathematical relationships, mathematical formulas or equations, and mathematical calculations. Thus, the claim recites mathematical concepts which are abstract ideas.
The types of identified abstract ideas are considered together as a single abstract idea for analysis purposes.
Independent claims 14 and 15 recite identical or nearly identical steps with respect to claim 1 (and therefore also recite limitations that fall within this subject matter grouping of abstract ideas), and these claims are therefore determined to recite an abstract idea under the same analysis.
Under Step 2A Prong Two
The claimed limitations, as per claim 1, include:
a server with a server software,
a smartphone including an inertial measurement unit (IMU) and a processor, wherein an application program is running on the processor of the smartphone, wherein the application program is configured to connect with the server software of the server, wherein the application software is configured to cause the IMU of the smartphone to measure a measurement signal when the smartphone is placed on a body of the user,
a processing means realized by at least one of the processor of the smartphone and a processor of the server work as the processing means, wherein the processing means is configured to
determine the type of the smart phone running the application software,
determine a mass of the smartphone and/or a moment of inertia of the smart phone based on the type of the device smartphone determined;
determine the health state of the heart of the user based on the measurement signal and based on the mass of the smartphone and/or based on the moment of inertia of the smart phone, and
output on the smartphone an output information based on the determined health state.
Examiner Note: underlined elements indicate additional elements of the claimed invention identified as performing the steps of the claimed invention.
The judicial exception expressed in claim 1 is not integrated into a practical application. The claim as a whole merely describes how to generally “apply” the concept of evaluating measurement data to determine a health state of the heart in a computer environment. The claimed computer components (i.e., a server with a server software; a smartphone including a processor; wherein an application program is running on the processor, wherein the application program is configured to connect with the server software of the server; a processing means realized by at least one of the processor and a processor of the server work as the processing means, wherein the processing means is configured to) are recited at a high level of generality and are merely invoked as tools to perform an existing process of evaluating measurement information and determining a heart health state. Simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea. Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application.
The judicial exception expressed in claim 1 is not integrated into a practical application. The abstract idea is merely carried out in a technical environment or field (i.e., smartphone based physiological monitoring environment using an inertial measurement unit), however fails to contain meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment (see MPEP 2106.05(h)). The additional elements that are carried out in a technical environment includes the smart phone and a smartphone including an inertial measurement unit (IMU). Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application.
The judicial exception expressed in claim 1 is not integrated into a practical application. The claim recites the additional elements of wherein the application software is configured to cause the IMU of the smartphone to measure a measurement signal when the smartphone is placed on a body of the user, and output on the smartphone an output information based on the determined health state. These limitations are recited at a high level of generality (i.e., as a general means of collecting measurement data and presenting the results), and amounts to mere data gathering and displaying results, which are forms of insignificant extra-solution activities. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
Therefore, under step 2A, the claims are directed to the abstract idea, and require further analysis under Step 2B.
Under step 2B
Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A, the claim as a whole merely describes how to generally “apply” the concept of evaluating measurement data to determine a health state of the heart in a computer environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
Claim 1 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A, the abstract idea is merely carried out in a technical environment or field, however fails to contain meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
For claim 1, under step 2B, the additional elements of wherein the application software is configured to cause the IMU of the smartphone to measure a measurement signal when the smartphone is placed on a body of the user, and output on the smartphone an output information based on the determined health state have been evaluated. The system comprising at a processor performs a general function of receiving patient data for determining the health state of the heart of a user, which represents a well-understood, routine, and conventional activity in the field of physiological monitoring and medical data analysis. The specification discloses that the processor is used in its ordinary capacity as a data input device and does not describe any improvement to the computer itself or to the functioning of the overall computer system (see page 11). Also noted in Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016), merely collecting information for analysis without a technological improvement does not add significantly more to an abstract idea. The use of the system is no more than collecting information before analyzing the information to determine the health state of the heart and displaying the result does not integrate the abstract idea into a practical application. Therefore, the claim does not recite an inventive concept and is not patent eligible.
Claims 5-6 recite no further additional elements, and only further narrow the abstract idea. The previously identified additional elements, individually and as a combination, do not integrate the narrowed abstract idea into a practical application for reasons similar to those explained above, and do not amount to significantly more than the narrowed abstract idea for reasons similar to those explained above.
Claims 4 and 11-12 recite the additional element of the processing means (claim 4), the smartphone (claims 11, 12), and an operating system running on the smartphone (claim 12). However, these additional elements amount to implementing an abstract idea on a generic computing device or mere linking to a particular environment. As such, these additional elements, when considered individually or in combination with the prior devices, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Thus, as the dependent claims remain directed to a judicial exception, and as the additional elements of the claims do not amount to significantly more, the dependent claims are not patent eligible.
Therefore, the claims here fail to contain any additional element(s) or combination of additional elements that can be considered as significantly more and the claim is rejected under 35 U.S.C. 101 for lacking eligible 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, 4-6, 11-12, and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Migeotte et al. (U.S. Patent Publication 2018/0214030 A1), referred to hereinafter as Migeotte, in view of Yang et al. (Yang et al., Combined Seismo- and Gyro-Cardiography: A More Comprehensive Evaluation of Heart-Induced Chest Vibrations. (2018), IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 22, NO. 5, pg. 1466-1475 (Year: 2018)), referred to hereinafter as Yang.
Regarding claim 1, Migeotte teaches system for detecting a health state of a heart of a user comprising (Migeotte [0029] “By being able to generate kineticardiography signals in six dimensions or having six degrees of freedom and by applying appropriate calibration procedures, it is possible to provide accurate and detailed information relating to heart health.” and Migeotte [0127] “In FIG. 3, a portable ECG/MKCG system 200 in accordance with the present invention is shown in which connections are provided between the sensors and a mobile computing platform 230.”):
a server with a server software (Migeotte [0254] “As described above, a mobile computing platform (mobile unit) 1090 receives data from the combined computing and communication unit at main sensor position 1010 together with data from other sensors, for example, from sensors at sensor positions 1050, 1060, 1070 and 1080. Data from sensors at sensor positions 1020, 1030 and 1040 may be processed in the combined computing and communication unit at the main sensor position 1010 together with the acceleration measurements obtained from the sensor at that position. The mobile computing platform may be a smart-phone or a tablet or any other device capable of computation and data transmission (receiving data from the sensor unit(s) and transmitting the data over the Internet to a server unit in a remote location or to the “cloud”, as indicated by 1110). The mobile platform 1090 is configured to receive, process, store, display and send the data to a remote system or data server (or to the “cloud” 1110) whilst providing an automated data processing capability that allows the user to get an immediate self-assessment of his/her own cardiac function.”),
a smartphone including an inertial measurement unit (IMU) and a processor, wherein an application program is running on the processor of the smartphone, wherein the application program is configured to connect with the server software of the server, wherein the application software is configured to cause the IMU of the smartphone to measure a measurement signal when the smartphone is placed on a body of the user (Migeotte [0158] “The wearable MKCG device may be a smartphone or the like which includes accelerometers and gyroscopes to be able to measure the MKCG signals in at least 6-DOF which can be located at the centre of mass (or centre of gravity) of a subject for sufficient time to be able to obtain the MKCG 6-DOF measurements. Such a smartphone or the like, with appropriate software loaded thereon, be able to process the kineticardiography measurements and to provide a display of the results for the user. Additionally, the processed data can be uploaded via a suitable wireless connection to another mobile computing device.”, Migeotte [0141] “A sensor device 320 comprising three accelerometer/gyroscope modules 320X, 320Y and 320Z is also provided within the belt 310 for providing the three linear MKCG signals along respective x-, y- and z-axes and the three rotational MKCG signals around respective x-, y- and z-axes. As shown in FIG. 4, bi-directional connections 325X, 325Y and 325Z are provided between respective ones of the accelerometer/gyroscope modules 320X, 320Y, 320Z and the processor 335. As described above, depending on the particular embodiment of the portable wireless system, the bi-directional links may comprise one-way links which only pass signals from the modules to the processor 335.” and Migeotte [0241] “FIG. 11 illustrates a MKCG system 1000 in which MKCG sensors may be positioned at different locations on the body of a subject and which provide 6-DOF acceleration measurements at at least one of these locations. It will readily be appreciated that other types of sensors may also be used at one or more of the illustrated locations.”, and Migeotte [0254] “The mobile computing platform may be a smart-phone or a tablet or any other device capable of computation and data transmission (receiving data from the sensor unit(s) and transmitting the data over the Internet to a server unit in a remote location or to the “cloud”, as indicated by 1110). The mobile platform 1090 is configured to receive, process, store, display and send the data to a remote system or data server (or to the “cloud” 1110) whilst providing an automated data processing capability that allows the user to get an immediate self-assessment of his/her own cardiac function.”),
a processing means realized by at least one of the processor of the smartphone and a processor of the server work as the processing means, wherein the processing means is configured to (Migeotte [0158] “The wearable MKCG device may be a smartphone or the like which includes accelerometers and gyroscopes to be able to measure the MKCG signals in at least 6-DOF which can be located at the centre of mass (or centre of gravity) of a subject for sufficient time to be able to obtain the MKCG 6-DOF measurements. Such a smartphone or the like, with appropriate software loaded thereon, be able to process the kineticardiography measurements and to provide a display of the results for the user. Additionally, the processed data can be uploaded via a suitable wireless connection to another mobile computing device.”, and Migeotte [0254] “The mobile computing platform may be a smart-phone or a tablet or any other device capable of computation and data transmission (receiving data from the sensor unit(s) and transmitting the data over the Internet to a server unit in a remote location or to the “cloud”, as indicated by 1110). The mobile platform 1090 is configured to receive, process, store, display and send the data to a remote system or data server (or to the “cloud” 1110) whilst providing an automated data processing capability that allows the user to get an immediate self-assessment of his/her own cardiac function.”)
determine the type of the smart phone running the application software (Migeotte [0134] “FIG. 4 illustrates a schematic block diagram of a portable wireless system 300 in accordance with the present invention. The system 300 comprises a mobile computing platform 330, such as a tablet, laptop or smartphone, which forms a processing device, which is connected to sensor devices in a belt 310 by way of a Bluetooth wireless connection 350 having both a transmit path 350T and a receive path 350R. [Bluetooth is a trademark of the Bluetooth Special Interest Group (SIG)].”, Migeotte [0135] “It will be appreciated that the wireless connection 350 is not limited to Bluetooth and may comprise any suitable wireless connection that can provide a bi-directional (or one-way—transmitting only) communication link between the processor 335 and the mobile processing platform 330, for example, a suitable Wi-Fi or ZigBee link can be implemented.”)
the type of the device smartphone determined (Migeotte [0134] “FIG. 4 illustrates a schematic block diagram of a portable wireless system 300 in accordance with the present invention. The system 300 comprises a mobile computing platform 330, such as a tablet, laptop or smartphone, which forms a processing device, which is connected to sensor devices in a belt 310 by way of a Bluetooth wireless connection 350 having both a transmit path 350T and a receive path 350R. [Bluetooth is a trademark of the Bluetooth Special Interest Group (SIG)].”, Migeotte [0135] “It will be appreciated that the wireless connection 350 is not limited to Bluetooth and may comprise any suitable wireless connection that can provide a bi-directional (or one-way—transmitting only) communication link between the processor 335 and the mobile processing platform 330, for example, a suitable Wi-Fi or ZigBee link can be implemented.”)
determine the health state of the heart of the user based on the measurement signal (Migeotte [0301] “From FIG. 15, it can clearly be seen that by having 6-DOF measurements and deriving at least the kinetic energy values for both linear and angular (rotational) movement due to contraction of the heart, it is possible to determine an important measure of cardiac health.”, Migeotte [0158] “The wearable MKCG device may be a smartphone or the like which includes accelerometers and gyroscopes to be able to measure the MKCG signals in at least 6-DOF which can be located at the centre of mass (or centre of gravity) of a subject for sufficient time to be able to obtain the MKCG 6-DOF measurements. Such a smartphone or the like, with appropriate software loaded thereon, be able to process the kineticardiography measurements and to provide a display of the results for the user. Additionally, the processed data can be uploaded via a suitable wireless connection to another mobile computing device.”); and
output on the smartphone an output information based on the determined health state (Migeotte [0115] “Turning now to FIG. 2, a MKCG system 100 in accordance with the present invention is shown. The system 100 comprises a belt 110 in which a sensor device 120 is mounted, and a mobile computing platform 130 which displays processed waveforms 140 obtained from the sensor device 120.” and Migeotte [0302] “It will readily be appreciated that by making use of all 6-DOF measurements at the same time to provide scalar signals representing the transfer of energy or the work from a cardiac contraction and ejection of blood into the body of a subject during a cardiac cycle, a robust indication of cardiac function or health can be obtained.” and Migeotte [0254] “The mobile computing platform may be a smart-phone or a tablet or any other device capable of computation and data transmission (receiving data from the sensor unit(s) and transmitting the data over the Internet to a server unit in a remote location or to the “cloud”, as indicated by 1110). The mobile platform 1090 is configured to receive, process, store, display and send the data to a remote system or data server (or to the “cloud” 1110) whilst providing an automated data processing capability that allows the user to get an immediate self-assessment of his/her own cardiac function.”).
Migeotte fails to explicitly teach determine a mass and/or a moment of inertia.
Yang teaches determine a mass and/or a moment of inertia (Yang, page 1468-1469, “In this work, we propose a model composed of two separate spring-damping couplings on the two ends of the sensor platform as an approximation of the continuous deformation of the chest wall. This single-axis rotation model is projected in two dimensions for the consideration of GCG_X and GCG_Y components in the y-z and x-z planes respectively. As illustrated in Fig. 3, the sensor platform has been rotated by an angle of θ. The spring is considered linear with a coefficient of K. Denoting the mass of the sensor platform by M, its linear motion by Z, its moment of inertia by I, and the damping coefficient by C, the expressions of energy can be written as follows… where Ki is the kinetic energy, P is the potential energy, and D is the dissipation energy.”).
It would have been obvious to a person having ordinary skill in the art (PHOSITA), before the effective filing date of the claimed invention, to modify the IMU cardiac monitoring system of Migeotte to account for device characteristics such as mass or moment of inertia as taught by Yang. Migeotte teaches a system for detecting cardiac health using motion signals obtained from accelerometers and gyroscopes, including implementations using a smartphone platform that measures chest vibrations and processes those measurements to determine cardiac health indicators. Yang teaches that the physical properties of the sensor platform, including its mass and moment of inertia, influence the mechanical behavior of the sensor during seismo- and gyro-cardiography measurements and therefore affect the interpretation of chest vibration signals.
A PHOSITA would have recognized that when implementing the cardiac monitoring system of Migeotte on different sensing platforms, including consumer devices such as smartphones, the physical characteristics of the sensing device may vary and can influence the measured motion signals. Accordingly, it would have been obvious to determine or account for the mass or moment of inertia of the sensing device when processing the measurement signals in order to improve the accuracy and reliability of the cardiac health determination. This modification represents the predictable application of known physical modeling techniques to improve sensor physiological measurement systems, and therefore would have been obvious to try with a reasonable expectation of success.
Regarding claim 4, Migeotte and Yang teach the invention in claim 1, as discussed above, and further teach wherein the processing means is configured to (Migeotte [0157] “In one embodiment of the present invention (as shown in FIG. 2), a miniaturised wearable MKCG device, intended for use by the general public, records only 6-DOF MKCG data. The device includes three accelerometer/gyroscope modules, as described above with reference to FIG. 4, and a processor similar to the processor 335 described above with reference to FIG. 4.”) compute at least one feature based on the measurement signal and based on the characteristic of the smartphone (Migeotte [0093] “The terms “total kinetic energy”, “total (cardiac) work” and “total (cardiac) power” as used herein refer respectively to kinetic energy, work and power of the heart derived from both linear acceleration measurements and angular (or rotational) acceleration measurements. The mass of the subject is used directly for linear measurements, and, for the determination of moment of inertia values for the angular (or rotational) measurements.” and Migeotte [0254] “The mobile computing platform may be a smart-phone or a tablet or any other device capable of computation and data transmission (receiving data from the sensor unit(s) and transmitting the data over the Internet to a server unit in a remote location or to the “cloud”, as indicated by 1110). The mobile platform 1090 is configured to receive, process, store, display and send the data to a remote system or data server (or to the “cloud” 1110) whilst providing an automated data processing capability that allows the user to get an immediate self-assessment of his/her own cardiac function.” and Yang, page 1468-1469, “In this work, we propose a model composed of two separate spring-damping couplings on the two ends of the sensor platform as an approximation of the continuous deformation of the chest wall. This single-axis rotation model is projected in two dimensions for the consideration of GCG_X and GCG_Y components in the y-z and x-z planes respectively. As illustrated in Fig. 3, the sensor platform has been rotated by an angle of θ. The spring is considered linear with a coefficient of K. Denoting the mass of the sensor platform by M, its linear motion by Z, its moment of inertia by I, and the damping coefficient by C, the expressions of energy can be written as follows… where Ki is the kinetic energy, P is the potential energy, and D is the dissipation energy.”), wherein the processing means is configured to determine the health state based on the at least one feature computed (Migeotte [0301] “From FIG. 15, it can clearly be seen that by having 6-DOF measurements and deriving at least the kinetic energy values for both linear and angular (rotational) movement due to contraction of the heart, it is possible to determine an important measure of cardiac health.”).
Migeotte teaches computing cardiac features such as kinetic energy from IMU measurement signals and using those features to determine cardiac health. Yang teaches that the physical characteristics of the sensor platform, including mass and moment of inertia, influence the energy calculations derived from seismo- and gyro-cardiographic measurements. A PHOSITA would have recognized that when implementing the IMU cardiac monitoring system of Migeotte on different sensing platforms such as smartphones, the physical characteristics of the device affect the measured signals and derived features. Therefore, it would have been obvious to compute the cardiac features based not only on the measurement signals but also on the physical characteristics of the sensing device in order to improve the accuracy of the health state determination.
Regarding claim 5, Migeotte and Yang teach the invention in claim 4, as discussed above, and further teach wherein the at least one feature computed comprises or is based on at least one of cardiac force or torque, cardiac kinetic energy, cardiac work and cardiac power computed based on the mass of the smartphone (Migeotte [0093] “The terms “total kinetic energy”, “total (cardiac) work” and “total (cardiac) power” as used herein refer respectively to kinetic energy, work and power of the heart derived from both linear acceleration measurements and angular (or rotational) acceleration measurements. The mass of the subject is used directly for linear measurements, and, for the determination of moment of inertia values for the angular (or rotational) measurements.” and Migeotte [0158] “The wearable MKCG device may be a smartphone or the like which includes accelerometers and gyroscopes to be able to measure the MKCG signals in at least 6-DOF which can be located at the centre of mass (or centre of gravity) of a subject for sufficient time to be able to obtain the MKCG 6-DOF measurements. Such a smartphone or the like, with appropriate software loaded thereon, be able to process the kineticardiography measurements and to provide a display of the results for the user. Additionally, the processed data can be uploaded via a suitable wireless connection to another mobile computing device.” and Yang, page 1468-1469, “In this work, we propose a model composed of two separate spring-damping couplings on the two ends of the sensor platform as an approximation of the continuous deformation of the chest wall. This single-axis rotation model is projected in two dimensions for the consideration of GCG_X and GCG_Y components in the y-z and x-z planes respectively. As illustrated in Fig. 3, the sensor platform has been rotated by an angle of θ. The spring is considered linear with a coefficient of K. Denoting the mass of the sensor platform by M, its linear motion by Z, its moment of inertia by I, and the damping coefficient by C, the expressions of energy can be written as follows… where Ki is the kinetic energy, P is the potential energy, and D is the dissipation energy.”).
It would have been obvious to a person having ordinary skill in the art (PHOSITA), before the effective filing date of the claimed invention, to modify the cardiac motion analysis system of Migeotte to compute cardiac features based on the mass of the sensing device as taught by Yang. Migeotte teaches computing cardiac kinetic features such as cardiac kinetic energy, work, and power from linear and rotational accelerations obtained from IMU measurements and further teaches that the sensing platform may be implemented as a smartphone containing accelerometers and gyroscopes with software configured to process the measurements. Yang teaches that the physical characteristics of the sensor platform, including the mass and moment of inertia of the sensing device, influence the mechanical response of the device during seismo- and gyro-cardiography measurements and therefore affect the energy calculations derived from those signals. A PHOSITA implementing the IMU cardiac monitoring system of Migeotte on different sensing platforms, including consumer smartphones with varying physical properties, would have recognized that the mass of the sensing device influences the derived kinetic energy and related cardiac features. Accordingly, it would have been obvious to incorporate the mass of the sensing device into the computation of cardiac features such as force, torque, kinetic energy, work, or power in order to improve the accuracy and reliability of the cardiac health determination. Such modification represents the predictable application of known physical modeling techniques to improve sensor physiological measurement systems and therefore would have been obvious to try with a reasonable expectation of success.
Regarding claim 6, Migeotte and Yang teach the invention in claim 5, as discussed above, and further teach wherein the at least one feature computed comprises or is based on at least one of cardiac torque, cardiac rotational kinetic energy, cardiac rotational work and cardiac rotational power computed based on the moment of inertia of the smartphone (Migeotte [0093] “The terms “total kinetic energy”, “total (cardiac) work” and “total (cardiac) power” as used herein refer respectively to kinetic energy, work and power of the heart derived from both linear acceleration measurements and angular (or rotational) acceleration measurements. The mass of the subject is used directly for linear measurements, and, for the determination of moment of inertia values for the angular (or rotational) measurements.” and Migeotte [0158] “The wearable MKCG device may be a smartphone or the like which includes accelerometers and gyroscopes to be able to measure the MKCG signals in at least 6-DOF which can be located at the centre of mass (or centre of gravity) of a subject for sufficient time to be able to obtain the MKCG 6-DOF measurements. Such a smartphone or the like, with appropriate software loaded thereon, be able to process the kineticardiography measurements and to provide a display of the results for the user. Additionally, the processed data can be uploaded via a suitable wireless connection to another mobile computing device.” and Yang, page 1468-1469, “In this work, we propose a model composed of two separate spring-damping couplings on the two ends of the sensor platform as an approximation of the continuous deformation of the chest wall. This single-axis rotation model is projected in two dimensions for the consideration of GCG_X and GCG_Y components in the y-z and x-z planes respectively. As illustrated in Fig. 3, the sensor platform has been rotated by an angle of θ. The spring is considered linear with a coefficient of K. Denoting the mass of the sensor platform by M, its linear motion by Z, its moment of inertia by I, and the damping coefficient by C, the expressions of energy can be written as follows… where Ki is the kinetic energy, P is the potential energy, and D is the dissipation energy.”).
It would have been obvious to a person having ordinary skill in the art (PHOSITA), before the effective filing date of the claimed invention, to modify the cardiac motion analysis system of Migeotte to compute rotational cardiac features based on the moment of inertia of the sensing device as taught by Yang. Migeotte teaches computing cardiac features such as cardiac kinetic energy, work, and power from both linear and rotational accelerations obtained from IMU measurements and further teaches that moment of inertia is used in the determination of rotational energy quantities derived from angular motion. Migeotte also teaches implementations in which the sensing platform may be a smartphone including accelerometers and gyroscopes configured to measure cardiac motion signals. Yang teaches that the physical characteristics of the sensor platform, including its mass and moment of inertia, influence the mechanical response of the sensing device during seismo- and gyro-cardiographic measurements and therefore affect the energy calculations derived from those measurements. A PHOSITA implementing the IMU cardiac monitoring system of Migeotte on sensing platforms such as smartphones would recognize that the physical characteristics of the sensing device, including its moment of inertia, influence the rotational motion measurements and the derived rotational energy quantities. Accordingly, it would have been obvious to incorporate the moment of inertia of the sensing device when computing rotational cardiac features such as torque, rotational kinetic energy, rotational work, or rotational power in order to improve the accuracy and reliability of the cardiac health assessment. Such modification represents the predictable application of known physical modeling techniques to improve sensor physiological measurement systems and would have been obvious to try with a reasonable expectation of success.
Regarding claim 11, Migeotte and Yang teach the invention in claim 1, as discussed above, and further teach wherein the type of the smartphone is received from a user input (Migeotte [0157] “In one embodiment of the present invention (as shown in FIG. 2), a miniaturised wearable MKCG device, intended for use by the general public, records only 6-DOF MKCG data. The device includes three accelerometer/gyroscope modules, as described above with reference to FIG. 4, and a processor similar to the processor 335 described above with reference to FIG. 4. The device may include a removable SD card for storing data for subsequent processing and/or the data may be transmitted to a mobile computing platform such as a smartphone, tablet computer, laptop etc. In the case where data is to be transmitted from the device, the processor also includes a communication link, preferably a Bluetooth link. It will readily be understood that other communication links may be used as described above. All components of the MKCG device are included on a single system on a chip (SOC) which is small and can readily be incorporated into a belt as described above with reference to FIG. 2, or any other suitable support that locates the MKCG device at the L5/S1 joint or centre of mass (or gravity) of a user of the device.”).
Migeotte teaches a cardiac motion sensing system in which sensor measurements are transmitted to and processed by a mobile computing platform such as a smartphone. In implementing this a system on a smartphone platform, a person having ordinary skill in the art (PHOSITA) would recognize that different smartphones may have different hardware characteristics or configurations and that such information may need to be provided to the application software in order to properly configure the system. One well-known approach for providing device configuration information to an application is through user input during setup or configuration of the application. Accordingly, it would have been obvious to a PHOSITA to allow the user to input the type of smartphone so that the application can obtain device specific parameters or configure the software appropriately. Incorporating such a user input step represents a predictable implementation detail involving the use of known user-interface techniques to configure software operating on a smartphone platform.
Regarding claim 12, Migeotte and Yang teach the invention in claim 1, as discussed above, and further teach wherein the type of the smartphone is received from an operating system running on the smartphone (Migeotte [0157] “In one embodiment of the present invention (as shown in FIG. 2), a miniaturised wearable MKCG device, intended for use by the general public, records only 6-DOF MKCG data. The device includes three accelerometer/gyroscope modules, as described above with reference to FIG. 4, and a processor similar to the processor 335 described above with reference to FIG. 4. The device may include a removable SD card for storing data for subsequent processing and/or the data may be transmitted to a mobile computing platform such as a smartphone, tablet computer, laptop etc. In the case where data is to be transmitted from the device, the processor also includes a communication link, preferably a Bluetooth link. It will readily be understood that other communication links may be used as described above. All components of the MKCG device are included on a single system on a chip (SOC) which is small and can readily be incorporated into a belt as described above with reference to FIG. 2, or any other suitable support that locates the MKCG device at the L5/S1 joint or centre of mass (or gravity) of a user of the device.”, and Migeotte [0158] “The wearable MKCG device may be a smartphone or the like which includes accelerometers and gyroscopes to be able to measure the MKCG signals in at least 6-DOF which can be located at the centre of mass (or centre of gravity) of a subject for sufficient time to be able to obtain the MKCG 6-DOF measurements. Such a smartphone or the like, with appropriate software loaded thereon, be able to process the kineticardiography measurements and to provide a display of the results for the user. Additionally, the processed data can be uploaded via a suitable wireless connection to another mobile computing device.”).
It would have been obvious to a person having ordinary skill in the art (PHOSITA), before the effective filing date of the claimed invention, to modify the cardiac motion analysis system of Migeotte to compute rotational cardiac features based on the moment of inertia of the sensing device as taught by Yang. Migeotte teaches computing cardiac features such as cardiac kinetic energy, work, and power from both linear and rotational accelerations obtained from IMU measurements and further teaches that moment of inertia is used in the determination of rotational energy quantities derived from angular motion. Migeotte also teaches implementations in which the sensing platform may be a smartphone including accelerometers and gyroscopes configured to measure cardiac motion signals. Yang teaches that the physical characteristics of the sensor platform, including its mass and moment of inertia, influence the mechanical response of the sensing device during seismo- and gyro-cardiographic measurements and therefore affect the energy calculations derived from those measurements. A PHOSITA implementing the IMU cardiac monitoring system of Migeotte on sensing platforms such as smartphones would recognize that the physical characteristics of the sensing device, including its moment of inertia, influence the rotational motion measurements and the derived rotational energy quantities. Accordingly, it would have been obvious to incorporate the moment of inertia of the sensing device when computing rotational cardiac features such as torque, rotational kinetic energy, rotational work, or rotational power in order to improve the accuracy and reliability of the cardiac health assessment. Such modification represents the predictable application of known physical modeling techniques to improve sensor physiological measurement systems and would have been obvious to try with a reasonable expectation of success.
Claims 14 and 15 are analogous to claim 1, thus claims 14 and 15 similarly analyzed and rejected in a manner consistent with the rejection of claim 1.
Response to Arguments
Applicant’s arguments and amendments, see Remarks/Amendments submitted on 12/25/2025 with respect to the rejection of the claims have been carefully considered and is addressed below.
Claim Objections
Claim 6 is objected to for containing an informal dependency error. Claim 6 should be corrected to properly reflect the intended dependency.
Specification and Drawings
The objections to the specification and drawings are withdrawn. It was indicated that the specification described an element “device 11,” while the drawings did not include such an element, creating an inconsistency between the written description and the drawings. Applicant identified device 11 in figure 1 so that the device element is consistently identified throughout the specification and drawings.
It was further indicated that the specification and drawings were objected to because the reference numerals “device (5, 7)” were used inconsistently between the claims and the specification. Applicant has addressed this issue by removing the reference signs from the claims, thereby eliminating the inconsistency. Accordingly, this objection is also withdrawn.
The objection to the specification regarding trademark usage is withdrawn. Applicant amended the specification to include the appropriate trademark designations for “Apple,” “iPhone,” and “Pro 13” where these terms appear.
Claim Rejections - 35 USC § 112
Applicant amended the claims to remove the reference signs from the claims, as suggested in the Office Action. Accordingly, the issues under 35 U.S.C. § 112(b) relating to the lack of clarity caused by the reference signs in the claims has been overcome, and the rejection is withdrawn.
Claim Rejections - 35 USC § 101
Applicant states that the claims cannot be performed in the human mind because they require operation of a smartphone inertial measurement unit (IMU) to obtain a chest vibration signal and therefore do not recite a mental process. The argument is not persuasive. While the claims recite acquiring a measurement signal using an IMU, the abstract idea identified in the rejection is not only the act of collecting the signal itself but instead in the subsequent analysis and evaluation of the information to determine a health state of the heart. The steps of determining device characteristics (mass or moment of inertia) and evaluating measurement information to determine a heart health state describe processes that, under their broadest reasonable interpretation, encompass mental evaluation of data and mathematical relationships applied to that data. Courts have repeatedly recognized that collecting data and analyzing it to reach a conclusion constitutes an abstract idea, even when the data originates from physical sensors. See Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1353-54 (Fed. Cir. 2016).
Applicant also states that the determination of the smartphone mass or moment of inertia involves real-world mechanical properties and therefore cannot be performed mentally. However, the claims do not require physically measuring these parameters. Instead, the claims merely require determining such values based on the device type, which may be accomplished through stored data or mathematical relationships associated with the device. Such determinations constitute mathematical relationships or calculations applied to information, which fall within the mathematical concepts grouping of abstract ideas. Accordingly, the claim continues to recite abstract ideas in the form of mathematical relationships and data evaluation.
Applicant also states that the claims provide a technological improvement by normalizing IMU cardiac measurements across different consumer devices. This argument is not persuasive because the claims do not recite a specific technological improvement to the operation of the smartphone, the IMU sensor, or the computer system itself. Instead, the claims broadly state that device parameters such as mass or moment of inertia are used when determining the heart health state. Applying mathematical relationships or evaluating data using generic computing components does not constitute a technological improvement to computer functionality. See Electric Power Group, 830 F.3d at 1354. The recited server and processor are described at a high level of generality and perform their ordinary functions of collecting data, processing data, and displaying results. These elements therefore represent generic computing components used as tools to implement the abstract idea.
When considered as an ordered combination, the claim simply gathers physiological measurement data, performs mathematical and evaluative analysis on the data to determine a heart health state, and outputs the result. Such data collection and analysis, implemented on generic computing devices, does not integrate the abstract idea into a practical application and does not amount to significantly more than the abstract idea itself. Therefore, the rejection under 35 U.S.C. §101 is maintained.
Claim Rejections - 35 USC § 103
Applicant argues that Migeotte does not disclose determining the type of a smartphone, determining the mass or moment of inertia of the smartphone based on the determined type, or determining the health state of the heart based on both the measurement signal and the mass or moment of inertia of the smartphone. The examiner agrees that Migeotte does not explicitly disclose these specific limitations. However, the rejection is based on the combination of Migeotte and Yang, not on Migeotte alone. Migeotte teaches a system for detecting cardiac health using IMU measurements obtained from accelerometers and gyroscopes and further teaches that such measurements may be implemented on a smartphone platform with appropriate software for processing the measurements and presenting results to the user. Migeotte also teaches that cardiac kinetic energy, work, and power are derived from linear and rotational acceleration measurements and that moment of inertia is used in the determination of rotational measurements. Therfore, Migeotte establishes the use of IMU-based measurements and derived kinetic features for determining cardiac health.
Applicant further argues that Yang merely introduces symbolic variables representing mass and moment of inertia in a theoretical model and does not explicitly determine the mass or moment of inertia of a device or apply such parameters in a smartphone-based system. While Yang may not explicitly determine these parameters from a smartphone type, Yang teaches that the physical characteristics of the sensing platform, including the mass and moment of inertia of the sensor platform, influence the mechanical response of the sensor during seismo- and gyro-cardiography measurements and affect the energy calculations derived from those measurements. Accordingly, Yang teaches that the physical properties of the sensing device are relevant parameters in modeling and interpreting cardiac vibration measurements.
A person having ordinary skill in the art (PHOSITA) implementing the IMU-based cardiac monitoring system of Migeotte on different sensing platforms, including consumer devices such as smartphones, would have recognized that different smartphones possess different physical characteristics, including mass and moment of inertia, which influence the measured motion signals and derived kinetic features. In view of Yang’s teaching that these physical parameters affect the interpretation of SCG/GCG signals, it would have been obvious to account for such parameters when implementing Migeotte’s system on smartphones in order to improve the accuracy and reliability of the cardiac health determination. Determining the type of the smartphone and obtaining corresponding physical parameters (mass or moment of inertia) represents a predictable implementation step that allows the system to apply the appropriate parameters for the specific device used. The modification applies known physical modeling principles to the known smartphone-based cardiac monitoring system of Migeotte and would have yielded predictable improvements in measurement accuracy. This modification represents the predictable use of prior art elements according to known methods and therefore would have been obvious to try with a reasonable expectation of success.
Applicant also states that Yang uses proprietary measurement devices rather than smartphones and this is also not persuasive. The rejection does not rely on Yang for teaching a smartphone platform. Instead, Migeotte teaches implementing the cardiac monitoring system on a smartphone device. Yang is relied upon for teaching that the mass and moment of inertia of the sensing platform affect the interpretation of cardiac vibration signals. A PHOSITA would reasonably apply this teaching to the smartphone implementation of Migeotte in order to account for the physical properties of the sensing device.
Accordingly, when considered together, Migeotte and Yang teach or render obvious the claimed limitations, and the rejection under 35 U.S.C. §103 is maintained.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure.
Jung et al. (International Publication No. WO 2021/107727A1) teaches a smart band and cardiac arrest management system that determines cardiac arrest by analyzing motion noise extracted from heart rate sensor data, allowing improved detection reliability without requiring additional sensors, and transmitting alerts to connected devices when cardiac arrest is identified.
D′Mello et al. (U.S. Publication 2023/0277071 A1) teaches a method and device for non-invasive hemodynamic measurement by analyzing vibrational cardiography (VCG) signals from chest surface vibrations to identify cardiac pulses, extract vibrations features, and determine hemodynamic parameters.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/K.R.L./Examiner, Art Unit 3685
/KAMBIZ ABDI/Supervisory Patent Examiner, Art Unit 3685