DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 03/02/2026 has been entered.
Election/Restrictions
Claims 6-10 and 14 withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 07/07/2025.
Response to Amendment
This action is in response to the amendments filed on 11/18/2025. Claims 1 and 13 have been amended, claims 6-10 and 14 have been withdrawn, and claim 15 has been previously cancelled. Claims 1-5, and 11-13 are examined below.
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 1-5, and 11-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claim 1 recites (additional limitations crossed out):
A method for supporting a patient's health control,
transmitting,
receiving from the implanted medical device, the first data set of data values of the first physiological measure,
transmitting, by the implanted medical device, at least one second data set of data values of the second physiological measure different from the first physiological measure;
receiving from the implanted medical device, the at least one second data set of data values of the second physiological measure different from the first physiological measure,
assessing each data item of the first data set whether its respective value lies within or outside a first reference range;
correcting those data value/values of the at least one second data set by means of a pre-defined correction factor determined for the respective second data set whose corresponding data value/values of the first data set lies outside the first reference range
storing the corrected data value/values of the at least one second data set with the respective second data set
wherein the pre-defined correction factor of the respective second data set is previously determined for the respective second data set using a correction factor determining AI algorithm, wherein the processor of the remote device adapts the pre-defined correction factor at pre-defined time intervals.
The above limitations, as drafted, are processes that, under their broadest reasonable interpretation, is a process that, under its broadest reasonable interpretation covers managing personal behavior or relationships or interactions between people, as well as performance of limitations by the human mind or with pen and paper. That is, other than reciting the claims as being performed by a “remote device comprising a receiver, a processor and a memory” and a “medical device comprising a sender”, nothing in the claims precludes the steps as being described as managing personal behavior or relationships or interactions between people, or performance of limitations by the human mind or with pen and paper. The claims, as written describe receiving a first and second data set, determining if data from the first data set is within or outside of a reference range, correcting data from the second data set whose corresponding data from the first data set lies outside of the reference range using a correction factor, and storing the corrected data. If a claim limitation, under its broadest reasonable interpretation, describes managing personal behavior or relationships or interactions between people, then it falls within the “Certain Methods of Organizing Human Activities” grouping of abstract ideas. Further, if a claim limitation, under its broadest reasonable interpretation, describes steps that may be performed mentally or with pen and paper, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of a “remote device comprising a receiver, a processor, and a memory” to perform the steps. This additional element is recited at a high level of generality (see at least page 5, Lines 17-23) such that it amounts to no more than mere instructions to apply the exception using generic computing components. The claim also recites a “medical device comprising a sender”, however said medical device contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) and does not integrate the judicial exception or provide significantly more. Further, the claims recite an “AI algorithm”. However, the functionality performed by the AI algorithm is not positively recited. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are therefore still directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of a “remote device comprising a receiver, a processor and a memory” to perform the claimed steps amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Therefore, the claims are not found to be patent eligible.
Claims 11 and 12 feature limitations similar to those of claim 1, but for the recitation of a “computer program product” and a “computer readable data carrier”, respectively, to perform the steps. Claims 11 and 12 are also found to be directed to an abstract idea without significantly more.
Claim 14 features limitations similar to those of claim 1. However, the use of the additional element “AI algorithm” is positively recited. In regards to said “AI algorithm”, it is considered to be generic computer function and/or field-of-use/”general link” implementations and does not meaningfully limit the claim (See Accenture, 728 F.3d 1336, 108 U.S.P.Q.2d 1173 (Fed. Cir. 2013), citing Cf. Diamond v. Diehr, 450 U.S. 175, 191-192 (1981) ("[I]nsignificant post-solution activity will not transform an unpatentable principle in to a patentable process.”). Moreover, the functionality intended to be performed by the AI algorithm appears to be based on very rudimentary constraints (e.g., correction factor, data sets). Without some prohibition in the claims regarding scalability, computation load, etc., the functions performed by this AI algorithm could reasonably be considered an additional abstract idea in the “mental process” category, but for which is simply automated (i.e., “apply it”). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Claim 14 is therefore also directed to an abstract idea without significantly more.
Claims 2-5 are dependent on claim 1, and include all the limitations of claim 1. Therefore, they are also found to be directed to an abstract idea. Claim 2 states “the correction factor determining AI algorithm is a linear regression or a deep learning algorithm”. However, as stated above, the functionality performed by the AI algorithm is not positively recited. Claim 4 states “wherein the pre- defined correction factor of the respective second data set is determined by training the correction factor determining AI algorithm using data from a first learning period of the respective single patient or using data from a second learning period of a group of at least two different patients”. However said “training” is recited at a high level of generality and may reasonably be considered an additional abstract idea in the “mental process” category. Claim 5 states “wherein the at least one second data set comprising the corrected data value/values is displayed on a display unit of the remote device or on a display unit connected to the remote device”. However, the display of data is merely insignificant extra-solution activity. Claim 3 has not been found to integrate the judicial exception into a practical application, or provide significantly more than the abstract idea since it merely further narrows the abstract idea. Therefore, the dependent claims are found to be directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-5, 11-13, and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gutfinger (US 2011/0208083) in view of Chung (US 2015/0106020) and Kraetschmer (US 2018/0168449)
Regarding claim 1, Gutfinger discloses A method for supporting a patient's health control, using an implanted medical device comprising a sender for transmitting data of a first physiological measure and data of at least one second physiological measure and an at least partially extracorporeally located remote device comprising a receiver for receiving the data of the first physiological measure and the data of the at least one second physiological measure, the at least partially extracorporeally located remote device further comprising a processor and a memory connected to the processor, wherein the method comprises the following steps: (See at least Para. [0060] – “The external device 558 may be utilized in a hospital setting, a physician's office, or even the patient's home to communicate with the IMD 100 to change a variety of operational parameters regarding the therapy provided by the IMD 100 as well as to select among physiological parameters to be monitored and recorded by the IMD 100.)
transmitting, by the implanted medical device, a first set of data values of the first physiological measure;
receiving from the implanted medical device the first data set of data values of a first physiological measure by the remote device
(See at least Para. [0058] – “For example, with respect to posture, the sensor 13 6 may be used to determine if the patient is in one or more of the following positions: (i) upright, or standing upright, (ii) supine, or laying on his or her back, (iii) prone, or laying on his or her stomach, (iv) right side down, or laying on his or her right side or arm, (v) left side down, or laying on his or her left side or arm, or (vi) a combination of any of the previously listed positions.”)
transmitting, by the implanted medical device, at least one second data set of data values of the second physiological measure different from the first physiological measure;
receiving from the implanted medical device the at least one second data set of data values of a second physiological measure different from the first physiological measure by the remote device
(See at least Para. [0032] – “The supine chronic admittance As may be measured as the smallest impedance vector between the predetermined combination of electrodes 104, 116, 118, 120, 122, 124, 126, 128, 130, 132, 134 (shown in FIG. 1) that is measured over a time window. The IMD 100 (shown in FIG. 1) may periodically measure the impedance vector between the predetermined combination of electrodes 104, 116, 118, 120, 122, 124,126,128,130,132,134 throughout the day and night. By way of example only, the IMD 100 may measure the impedance vector every two hours throughout the day and night.”
Gutfinger partially discloses performing the following by the processor of the remote device:
assessing each data item of the first data set whether its respective value lies within or outside a first reference range (See at least Para. [0033] – “At 404, an upright chronic admittance (Au) is measured between the predetermined combination of electrodes 104,116,118,120,122,124,126,128,130,132,134(shown in FIG. 1) when the patient is in the position of a second posture that differs from the first posture. The upright chronic admittance Au may be obtained by measuring the impedance vector between the predetermined combination of electrodes 104, 116, 118, 120, 122, 124, 126, 128, 130, 132, 134 after the patient has moved to the second posture for a sufficiently long time period that fluids within the patient's body have reached a steady state.”, and Para. [0058] – “For example, with respect to posture, the sensor 13 6 may be used to determine if the patient is in one or more of the following positions: (i) upright, or standing upright, (ii) supine, or laying on his or her back, (iii) prone, or laying on his or her stomach, (iv) right side down, or laying on his or her right side or arm, (v) left side down, or laying on his or her left side or arm, or (vi) a combination of any of the previously listed positions.”)
correcting those data value/values of the at least one second data set by means of a pre-defined correction factor determined for the respective second data set whose corresponding data value/values of the first data set lies outside the first reference range by the processor, and (See at least Para. [0028] – “In order to compensate for the change in the spacing or geometry between the electrode 202 and the IMD 100 and the shift in the impedance vector 200 to the vector 300, the IMD 100 may apply an offset factor~ to impedance measurements obtained along the impedance vector 200 or 300. The offset factor ~ is applied to impedance vectors 200, 300 in order to reduce or eliminate the impact of a changing posture of the patient on the impedance vectors 200, 300.”
storing the corrected data value/values of the at least one second data set with the respective second data set in the memory (See at least Para. [0066] – “The server 702 interfaces with the communication system 712, such as the internet, Internet, or a local POTS based telephone system, to transfer information between the programmer 706, the local RF transceiver 708, the user workstation 710 (as well as other components and devices) to the database 704 for storage/retrieval of records of information. By way of example only, these other components and devices may include a cell phone 714 and/or a personal data assistant (PDA) 716. The server 702 may download, via a wireless connection 720, to the cell phone 714 or the PDA 716 the results of processed cardiac signals, offset factors ~' postures, impedance vectors, admittances, or a patient's physiological state based on previously recorded cardiac information, impedance vectors, postures, and the like.”)
Gutfinger does not explicitly disclose wherein the pre-defined correction factor of the respective second data set is previously determined for the respective second data set using a correction factor determining an Al algorithm. (See Chung, Para. [0062] – “While this variability is often present between patients, much of the variation is consistent within a patient and can be corrected for by use of empiric data from past measurements. For example, a baseline heart rate across individuals may vary from 55-75 beats per minute, but will likely have a smaller variance within each individual, especially when corrected for activity level. To account for such variability in the sensed quantities 412, the preferred embodiment contains modules 410 to correct for these variations in constructing attributes for classification, as represented in FIG. 4. The personalization factors of sensed quantities to form attributes 414 can be learned during an initialization period 404 in which an individual or caregiver informs the sensing system 420 to the individual's current state.”, Para. [0064] – “FIG. 4 represents an embodiment that uses the questionnaire ability of the smartphone 406 to directly ask the patient questions to ascertain patient state and use the response to personalize sensor data in the form of training attribute modules 410 with 420. An example of the utility of this method is in slow fluctuations of baseline measures that may occur after the initialization period or if an initialization period is unavailable. Such personalization or correction of thresholds may be derived from regression models or other online learning methods, such as the perceptron algorithm.”, and Para. [0068] – “A further example of personalized corrections relate to patient posture, such as supine, prone, or angle of inclination, at time of sensing. Some physiological quantities, such as impedance or EKG, are known to be sensitive to posture because of physiological reflexes that may differ between individuals but remain consistent within an individual. Measurements can either be classified by position or otherwise corrected for by empiric learning.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Gutfinger to utilize the teachings of Chung since they are in the same field of endeavor (i.e., health monitoring), and all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions and the combination would have yielded predictable results to one of ordinary skill in the art at the time of the invention. The Examiner also notes that the language “wherein the pre-defined correction factor of the respective second data set is previously determined for the respective second data set using a correction factor determining an Al algorithm” is simply a label for the correction factor and adds little, if anything, to the claimed acts or steps and thus does not serve to distinguish over the prior art. Any differences related merely to the meaning and information conveyed through labels (i.e., how the correction factor is determined) which does not explicitly alter or impact the steps of the method (i.e., correcting data values using the correction factor) does not patentably distinguish the claimed invention from the prior art in terms of patentability. Therefore, it would have been obvious to a person of ordinary skill in the art at the time of invention to have the offset factor (i.e., correction factor) of Gutfinger be determined using a correction factor determining an AI algorithm because the manner in which the correction factor is determined does not functionally alter or relate to the steps of the method and merely labeling the correction factor differently from that of the prior art does not patentably distinguish the claimed invention.
Gutfinger does disclose wherein the processor of the remote device adapts the pre-defined correction factor at pre-defined time intervals. (See at least Claim 8 – “…the correction module continues to adjust impedance values measured by the impedance measurement module between the predetermined combination of electrodes by applying an offset factor to the impedance measurements for a predetermined time period after the patient changes from a previous posture to the current posture.”, Para. [0029] – “FIG. 4 is a flowchart of a method 400 for adjusting impedance vectors based on changing postures of a patient in accordance with one embodiment. The method 400 determines an offset factor ~ that can be applied to impedance vectors that are measured between a predetermined combination of electrodes 104, 116, 118, 120, 122, 124, 126, 128, 130, 132, 134 (shown in FIG. 1) for a change in the patient's position from a first posture to a second posture. The method 400 may be repeated several times to determine additional offset factors ~ for different combinations of electrodes 104, 116, 118, 120, 122, 124, 126, 128, 130, 132, 134 and/or different changes in position.”, and Fig. 4)
While the combination of Gutfinger and Chung disclose the performance of the above functions, they do not explicitly disclose them being performed by the remote device. See Kraetschmer, Para. [0027] – “One skilled in the art will appreciate that the processor 2 and the non-transitory memory 3 can be part of the IMD 8. Alternatively, or in addition, the processor 2 and the non-transitory memory 3 can be part of an external computing device. Embodiments including use of an external device can receive data from a transceiver or other type of transmitter operatively associated with the IMD 8. The data received can then be manipulated by the external device, which can be done automatically via algorithms and/or manually via a user of the external device.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Gutfinger and Chung to utilize an external device to perform the functions as taught by Kraetschmer since they are all in the same field of endeavor (i.e., health monitoring), and all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions and the combination would have yielded predictable results to one of ordinary skill in the art at the time of the invention.
Regarding claim 2, Gutfinger does not explicitly disclose The method of claim 1, wherein the correction factor determining the AI algorithm is a linear regression or a deep learning algorithm. (See Para. [0064] – “FIG. 4 represents an embodiment that uses the questionnaire ability of the smartphone 406 to directly ask the patient questions to ascertain patient state and use the response to personalize sensor data in the form of training attribute modules 410 with 420. An example of the utility of this method is in slow fluctuations of baseline measures that may occur after the initialization period or if an initialization period is unavailable. Such personalization or correction of thresholds may be derived from regression models or other online learning methods, such as the perceptron algorithm.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Gutfinger to utilize the teachings of Chung since they are in the same field of endeavor (i.e., health monitoring), and all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions and the combination would have yielded predictable results to one of ordinary skill in the art at the time of the invention.)
Regarding claim 3, Gutfinger discloses The method of claim 1, wherein the pre- defined correction factor of the respective second data set is a single value and/or represents a mathematical function, wherein the single value is patient-specific or specific for a pre-determined group of patients or a general value for all patients, wherein the mathematical function is patient-specific or specific for a pre-determined group of patients or a general function for all patients. (See at least claim 2, “wherein the correction module adjusts the impedance value by applying an offset factor to the impedance value, the offset factor having a value that varies based on the at least one of the posture and the activity level of the patient.”
Regarding claim 4, Gutfinger does not explicitly disclose The method of claim 1, wherein the pre- defined correction factor of the respective second data set is determined by training the correction factor determining AI algorithm using data from a first learning period of the respective single patient or using data from a second learning period of a group of at least two different patients. (See at least Chung, Para. [0144] – “While general impedance measures are often taken between 1-100 KHz, individual differences may be learned as in FIG. 4 with an online or batch learning algorithm for personalization of impedance reading to reduce power and memory consumption by avoiding wide frequency range impedance sweeps. Maximally sensitive frequency ranges may be learned empirically in an initialization period 404, from a caregiver report 408, or from smartphone questionnaires 406, as an individual may self-report edema to validate impedance changes in their learned maximally sensitive frequency range.” It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Gutfinger to utilize the teachings of Chung since they are both in the same field of endeavor (i.e., health monitoring), and all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions and the combination would have yielded predictable results to one of ordinary skill in the art at the time of the invention.)
Regarding claim 5, Gutfinger discloses The method of claim1, wherein the at least one second data set comprising the corrected data value/values is displayed on a display unit of the remote device or on a display unit connected to the remote device (See at least Para. [0063] – “The display 622 (for example, may be connected to a video display 632) and the touch screen 624 display text, alphanumeric information, data and graphic information via a series of menu choices to be selected by the user relating to the IMD 100 (shown in FIG. 1), such as for example, status information, operating parameters, therapy parameters, patient status, access settings, software programming version, offset factors ~' impedance vectors, admittances, thresholds, and the like.”
Claims 11-13 feature limitations similar to claim 1, and are therefore rejected using the same rationale.
Response to Arguments
Applicant's arguments regarding claims rejected under 35 U.S.C. 101 have been fully considered but they are not persuasive. Applicant argues with substance:
Applicant argues that the claims are not directed to an abstract idea due to the operations being carried out by specific components of the system. The Examiner respectfully disagrees. As stated in the body of the rejection above, the recitation of the “remote device comprising a receiver, a processor, and a memory” amounts to no more than mere instructions to apply the exception using generic computing components, while the “medical device comprising a sender” contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) and does not integrate the judicial exception or provide significantly more.
Applicants arguments concerning the use of a “pre-defined correction factor” in the claims to address technical problems associated with device longevity, inaccuracies related to processing independent processing of physiological data, and information overload is not persuasive. First, the Examiner notes that the specification is silent in regards to how the pre-defined correction factor affects device longevity. The Examiner points to paragraph [0017] of the Applicant’s publication which states, in part, “According to the present invention the data of the first physiological measure and the at least one second physiological measure are received, assessed and corrected in a remote device (rather than by the medical device) thereby increasing the longevity of the medical device if the battery size is kept constant or allowing to reduce the size of the medical device or to incorporate more sensors if the battery size is reduced.” (emphasis added) The processing being performed at a remote device rather than a medical device does not provide an improvement to the longevity of the medical device. Not performing processing inherently results in less processing power being required. The actual battery efficiency of the medical device remains unchanged. Further, even if the claims addressed inaccuracies and information overload, these problems are not technical in nature. If anything, the claims merely provide an improvement to data itself, and not any involved computing components.
Applicant's arguments regarding claims rejected under 35 U.S.C. 103 have been fully considered but they are not persuasive. Applicant argues with substance:
Applicant argues that neither Gutfinger does not disclose “wherein the remote device is further configured to adapt the pre-defined correction factor at pre-defined time intervals”. The Examiner respectfully disagrees. Paragraph [0029] and Fig. 4 disclose that the determination (i.e., adapting) of the offset factor (i.e., pre-defined correction factor) is repeated several times based on the changes in posture (i.e., pre-defined time intervals) of the patient.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KYLE G ROBINSON whose telephone number is (571)272-9261. The examiner can normally be reached Monday - Thursday, 7:00 - 4:30 EST; Friday 7:00-11:00 EST.
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/KYLE G ROBINSON/Examiner, Art Unit 3685
/KAMBIZ ABDI/Supervisory Patent Examiner, Art Unit 3685
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