DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendments
This Office Action is responsive to the amendment filed on 14 August 2025. As directed by the amendment: claims 16, 23, and 28 have been amended, no claims have been added or cancelled, and claims 18-20 and 30-33 remain withdrawn. Thus, claims 16-17 and 21-29 are currently under consideration.
Response to Arguments
Objections to Drawings
The drawings replacement sheet filed 14 August 2025 has been acknowledged and has overcome the previously cited drawing objections in the Non-Final Rejection of 14 March 2025.
Response to Arguments Regarding 35 USC § 112
Applicant’s amendments to the claims have overcome the 112(a) and 112(b) rejection previously set forth in the Non-Final Office Action mailed 14 March 2025.
Response to Arguments Regarding 35 USC § 101
Applicant’s arguments, see pg. 14-17 of Remarks, filed 14 August 2025, with respect to 35 U.S.C. 101 rejection of claims 16-17 and 21-29 have been fully considered and are persuasive. The 35 U.S.C. 101 rejections of claims 16-17 and 21-29 has been withdrawn.
Response to Arguments Regarding 35 USC § 102/103
Applicant’s arguments, see pg. 17-20 of Remarks, filed 14 August 2025, with respect to the rejection(s) of claim(s) 16-17, 24, 25, and 27 under 35 USC 103 in view of Valys further in view of Lemay have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Chatham et al. (US 2023/0081751 A1, previously cited for claims 28-29).
Applicant argues Valys fails to teach PPG and ECG signals recorded semi-synchronously, no time-aligning of the PPG and ECG signals, and deriving annotations for PPG signal segments by copying annotations of time-corresponding ECG signal segments or by attributing annotations that differ from said time-corresponding ECG signal segments depending on how said ECG beats can be paired with said PPG beats and annotating said PPG signal segments using said annotations, thereby generating said annotated PPG signal (emphasis added).
Examiner agrees and has instead used Chatham to teach the limitations of recording signals semi-synchronously and time-aligning the PPG and ECG signals, as described in detail below.
Additionally, examiner has made a 112(b) rejection of the independent claims 16 and 28-29 for being indefinite as reciting “how said ECG beats can be paired with said PPG beats” is ambiguous and vague, as “can be” makes the pairing of the ECG and PPG beats to be optional and not necessarily a part of the claimed invention. There are multitude of ways an ECG beat “can be” paired with said PPG beats, thus a person of ordinary skill in the art would not be able to accurately interpret the metes and bounds of the claims so as to understand how to avoid infringement. Examiner noted that the applicant seems to be claiming subject matter present in the specification [0022] and withdrawn claims 18-20 as the “how ECG beats can be paired with said PPG beats”. Examiner has advised applicant to amend claims to specifically recite the nature of the ”how ECG beats can be paired with said PPG beats”, for example, “If no ECG beat is paired with a PPG beat for said segment, then annotate said PPG segment as insufficient quality”, “If an ECG beat is paired with a PPG segment, copying an annotation of an ECG segment onto a time-corresponding PPG segment”, etc. Thus, in view of the 112(b) rejection Examiner is interpreting the limitation of “how said ECG beats can be paired with said PPG beats” to be any form of pairing that occurs between an identified ECG beat and another identified PPG beat.
Additionally, Applicant further argues that Lemay does not teach pairing individual ECG beats with individual PPG beats. Examiner does not agree as Lemay teaches a “ECG- and PPG-based interbeat intervals were then computed from the R-waves and systolic downstrokes by taking the time difference of consecutive events. For each patient, beat-to-beat alignment of the two series of interbeat intervals was then performed”, where the “position of heartbeats on ECG signal was extracted from the R-wave detection” and “position of heartbeats in PPG signals was performed by detecting systolic downstroke”. Additionally, since it is noted that “how said ECG beats can be paired with said PPG beats” is interpreted to be any form of pairing that occurs between an identified ECG beat and another identified PPG beat, Lemay teaches the limitation of “deriving annotations for PPG signal segments by copying annotations of time-corresponding ECG signal segments or by attributing annotations that differ from said time-corresponding ECG signal segments depending on how said ECG beats can be paired with said PPG beats and annotating said PPG signal segments using said annotations, thereby generating said annotated PPG signal” (“Expert annotations of rhythm epochs were automatically projected into the same time base, leading to one annotation for each interbeat interval. Figure 1 illustrates typical examples of aligned ECG and PPG data, as well as calculated RR intervals.”).
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “the successful pairing or unsuccessful or a quality value assigned to pairing if the success of pairing is qualitatively assessed by an algorithm”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). The limitation of “how said ECG beat can be paired with PPG beat” is interpreted to be any form of pairing that occurs between an ECG beat and a PPG beat.
Thus, claim 16-17, 22, 24, 25, and 27 are rejected under 35 USC 103, as described in detail below.
No additional specific arguments were presented with previous 35 USC 103 rejections of dependent claims 21, 23, and 26, nor specifically with respect to the previously cited Bouchakour, Rundo, and Fleming references.
Therefore, claims 21, 23, and 26 remain rejected as described in detail below.
Claim Rejections - 35 USC § 112
Claims 16-17 and 21-29 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 claims 16, 28, and 29, the phrase "can be" renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. See MPEP § 2173.05(d). The usage of “can be” presents the limitation as optional and not necessarily part of the claimed invention, additionally it appears that the Applicant is attempting to broadly claim the limitations present in dependent claims 18-20. However, the recitation of deriving annotations for PPG signal segments based on how ECG beats can be paired with PPG beats, is indefinite and ambiguous. If Applicant would like to claim this feature it is advised to amend the claim to positively recite the function by using contingent limitations. For example, “If no ECG beat can be paired with a PPG beat for said segment, then said PPG segment as insufficient quality”, etc.
For examination purposes, under the broadest reasonable interpretation “how ECG beats can be paired with PPG beats”, will be interpreted to be any form of pairing that occurs between an identified ECG beat and another identified PPG beat.
Claims 17 and 21-27 are rejected by virtue of its dependency on claim 16.
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.
Claim(s) 16-17, 22, 24, 25, and 27 is/are rejected under 35 U.S.C. 103 as being unpatentable over Valys et al. (US 2019/0104951 A1, previously cited), hereinafter Valys in view of Chatham et al. (US 2023/0081751 A1), hereinafter Chatham, and further in view of Lemay et al., "Wrist-located optical device for atrial fibrillation screening: A clinical study on twenty patient," 2016 Computing in Cardiology Conference (CinC), Vancouver, BC, Canada, 2016, pp. 681-684., hereinafter Lemay (previously cited).
Regarding claim 16, Valys discloses a computer-implemented method for generating an annotated photoplethysmography signal, abbreviated annotated PPG signal, (Abstract: “method…for continuously monitoring a user’s low-fidelity health-indicator data (for example and without limitation PPG signals)”, [0106] “some embodiments may be practiced in distributed computing environments”) said method comprising:
recording an electrocardiogram signal, abbreviated ECG signal, using an ECG monitoring system ([0090] “The high-fidelity measurement, in some embodiments, may be obtained directly by the user using a mobile monitoring system, such as ECG or blood pressure systems, which may be associated with the wearable device in some embodiments.”);
recording a photoplethysmography signal, abbreviated PPG signal, using a contact PPG sensor ([0088] “Some embodiments receive the user's health-indicator data from a wearable device (e.g., Apple Watch, smart watch, FitBit?, etc.) on the user, or from another mobile device (e.g., tablet, computer, etc.) in communication with a sensor on the user (e.g., Polar? strap, PPG sensor etc.), which is discussed throughout this description.”, [0098] “the labeled user data may be provided based on high-fidelity data (such as an ECG reading) taken at a time period when low-fidelity data (e.g., PPG, heart rate) and other data (e.g., activity level or steps) is also available”);
annotating segments in said ECG signal either algorithm-based or expert-based, resulting in ECG segment annotations ([0024] “The high-fidelity measurement, ECG in this embodiment, can be evaluated by algorithms and/or medical professionals to make a notification or diagnosis (collectively referred to herein as “diagnosis”, recognizing that only a physician can make a diagnosis). In the ECG example, the diagnosis may be AFib or any other number of well-known conditions diagnosed utilizing ECGs.”, [0091] “In step 912, the high-fidelity data is analyzed by an algorithm, a health professional or both and is described as normal or not normal, and if not normal some diagnosis may be assigned, e.g., AFib, tachycardia, bradycardia, atrial flutter, or high/low blood pressure depending on the high-fidelity measurement obtained”) ;
deriving annotations for PPG signal segments based on the nature of said ECG segment annotations; and annotating said PPG signal segments using said annotations, thereby generating said annotated PPG signal ([0025] “In further embodiments, a diagnosis is used to label a low-fidelity data sequence (e.g., heart rate or PPG), which may include the other-factor data sequence. This high-fidelity diagnosis-labeled low-fidelity data sequence is used to train a high-fidelity machine learning model.”, [0092] “The trained high-fidelity machine learning model, in some embodiments, has the capability to receive measured low-fidelity health-indicator data sequence (e.g., heart rate data or PPG data) and optionally other-factor data and give a probability or predict or diagnose or detect when a user is experiencing an event typically diagnosed or detected using high-fidelity data.”).
Valys fails to explicitly disclose the method comprising: recording a photoplethysmography signal, abbreviated PPG signal, semi-synchronously with said recording of said ECG signal, time-aligning said PPG signal and said ECG signal, detecting cardiac beats in said ECG signal, named ECG beats; detecting cardiac beats in said PPG signal, named PPG beats; pairing said ECG beats with said PPG beats, deriving annotations for PPG signals based on how said ECG beats can be paired with said PPG beats.
However, Chatham teaches recording a photoplethysmography signal, abbreviated PPG signal, semi-synchronously with said recording of said ECG signal, using a contact PPG signal ([0041] “ECG and PPG data may be collected simultaneously”, time-aligning said PPG signal and said ECG signal ([0041] “post alignment/synchronization of the time series obtained from the reference ECG and the PPG signals”), detecting cardiac beats in said ECG signal, named ECG beats ([0044] “For the ECG data comprising a plurality of ECG signals, a different evaluation may be performed. The raw ECG signal may be analyzed with a variation on the Pan-Tompkins algorithms... The signal may be normalized...Single heart beats may be identified on this normalized signal as the peaks exceeding a threshold that in our case was identified as the 90th percentile of the data in the current window. Each heart beat crossing the threshold may be subsequently checked manually to make sure no erroneous beat was included in the analysis”, detecting cardiac beats in said PPG signal, named PPG beats ([0023] “The PPG may comprise a plurality of beats... The term may specifically may refer, without limitation to at least one local maximum of the PPG”, [0036] “The peaks on the filtered PPG signal may then be identified and/or determine and/or calculated”);
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Valys to incorporate the teachings of Chatham for recording a photoplethysmography signal, abbreviated PPG signal, semi-synchronously with said recording of said ECG signal, time-aligning said PPG signal and said ECG signal, detecting cardiac beats in said ECG signal, named ECG beats; detecting cardiac beats in said PPG signal, named PPG beats; pairing said ECG beats with said PPG beats, as these prior art references and the instant application are directed to analyzing ECG and PPG beats together. One would be motivated to do this because by pairing the ECG and PPG beats one can establish a relationship between these two separate signals which would make it easier to compare and project annotations of one signal onto the other.
Valys and Chatham, alone or in combination, fail to teach deriving annotations for PPG signal segments based on how said ECG beats can be paired; and annotating said PPG signal segments
However, Lemay teaches recording an ECG signal, using an ECG monitoring system; recording a PPG signal using a contact PPG sensor; annotating segments in said ECG signal either algorithm-based or expert-based, resulting in ECG segment annotations (“12-lead ECG signals were acquired at 2 kHz by a commercial electro-physiology system (Siemens Sensis), and PPG waveforms were acquired by a proprietary wrist-based device embedding reflective infrared sensors sampled at 21.33 Hz. ECG signals were further analyzed by clinical experts, providing annotations of sinus rhythm epochs (SR), regularly paced rhythm epochs, irregularly paced rhythm epochs, and AF epochs”), detecting cardiac beats in said ECG signals, named ECG beats (“position of heartbeats on ECG signals was extracted from R-wave detection as directly provided by the commercial electro-physiology system”), detecting cardiac beats in PPG signal, named PPG beats (“position of heartbeats in PPG signals was performed by detecting the systolic downstroke of each heart-beat waveform”) and then pairing said ECG beats with said PPG beats (“ECG- and PPG-based interbeat intervals were then computed from the R-waves and systolic downstrokes by taking the time difference of consecutive events. For each patient, beat-to-beat alignment of the two series of interbeat intervals was then performed”, Figure 1); deriving annotations for PPG signal segments by copying annotations of time-corresponding ECG signal segments or by attributing annotations that differ from said time-corresponding ECG signal segments depending on how said ECG beats can be paired with said PPG beats and annotating said PPG signal segments using said annotations, thereby generating said annotated PPG signal (“Expert annotations of rhythm epochs were automatically projected into the same time base, leading to one annotation for each interbeat interval. Figure 1 illustrates typical examples of aligned ECG and PPG data, as well as calculated RR intervals.”).
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Valys and Chatham to incorporate the teachings of Lemay for deriving annotations for PPG signal segments by copying annotations of time-corresponding ECG signal segments or by attributing annotations that differ from said time-corresponding ECG signal segments depending on how said ECG beats can be paired with said PPG beats; and annotating said PPG signal segments using said annotations, thereby generating said annotated PPG signal as these prior arts and the instant application are directed to the correlation between ECG and PPG signals. One would be motivated to do this because PPG signals are easily affected by external factors and therefore have more artifacts and noise being harder to analyze, whereas an ECG is easier to analyze and by deriving the annotations from an aligned ECG signal, the PPG can be easily marked and analyzed without hindrance from noise or artifacts.
Regarding claim 17, Valys in view of Chatham in view of Lemay teaches the computer-implemented method for generating an annotated PPG signal according to claim 16 (as shown above).
Valys and Chatham, alone or in combination, fail to teach wherein deriving annotations for PPG signal segments comprises: copying an annotation of an ECG segment onto a time-corresponding PPG segment when an ECG beat can be paired with a PPG beat for said segment.
However, Lemay further teaches wherein deriving annotations for PPG signal segments comprises: copying an annotation of an ECG segment onto a time-corresponding PPG segment when an ECG beat can be paired with a PPG beat for said segment (section 2.1: “ECG signals were further analyzed by clinical experts, providing annotations of sinus rhythm epochs (SR), regularly paced rhythm epochs, irregularly paced rhythm epochs, and AF epochs”; p. 682, col. 2: after the synchronization, “Expert annotations of rhythm epochs were automatically projected into the same time base, leading to one annotation for each interbeat interval” so each annotation would be associated with a PPG signal interval after the PPG and ECG signals have been synchronized; see also section 2.4: “[the algorithm] created...a set of four PPG-related features for each annotated epoch”).
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Valys and Chatham to incorporate the teachings of Lemay to have deriving annotations for PPG signal segments comprises: copying an annotation of an ECG segment onto a time-corresponding PPG segment when an ECG beat can be paired with a PPG beat for said segment. One would be motivated to do this to determine the accuracy of PPG to substitute ECG-based solutions (Introduction) since the PPG technology is noninvasive and extremely reduced in cost (Discussion), as recognized by Lemay.
Regarding claim 22, Valys in view of Chatham in view of Lemay teaches the computer-implemented method for generating an annotated PPG signal according to claim 16 (as shown above). Lemay further teaches detecting said PPG beats by “by detecting the systolic downstroke of each heart-beat waveform”. Valys and Lemay, alone or in combination, fail to teach wherein detecting PPG beats comprises detecting local maxima in said PPG signal.
However, Chatham teaches a computer-implemented method for determining accuracy of heart rate variability by obtaining a PPG signal, detecting a signal feature, and determining the accuracy by comparing with a true value derived from an ECG signal wherein “the PPG may comprise a plurality of beats. The term “beat” of the PPG…specifically may refer, without limitation to at least one local maximum of the PPG” [0023].
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Valys in view of Lemay to incorporate the teachings of Chatham to detect said PPG beats by detecting local maxima in said PPG signal. One would be motivated to do this because finding the local maxima is a faster and more efficient way to detect PPG beats.
Regarding claim 24, Valys in view of Chatham in view of Lemay teaches the computer-implemented method for generating an annotated PPG signal according to claim 16 (as shown above).
Valys discloses wherein the method further comprises storing said annotated PPG signal in a database of training data used for training in machine learning ([0025] “This high-fidelity diagnosis-labeled low-fidelity data sequence is used to train a high-fidelity machine learning model”).
Valys does not explicitly state that the signal is stored in a database for training data used for training in machine learning, however, Valys teaches “the training of the high-fidelity model can take place on the user's mobile device, remote from the user's mobile device, a combination of the two, or in a distributed network. For example and not by way of limitation, the user's health-indicator data could be stored in a cloud system, and this data can be labeled in the cloud using the diagnosis from step 914. The skilled artisan will readily appreciate any number of ways and manners to store, label and access this information.” ([0092]), therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have stored the annotated PPG signal in a database to be accessed to be used to train machine learning.
Regarding claim 25, Valys in view of Chatham in view of Lemay teaches the computer-implemented method for generating an annotated PPG signal according to claim 16 (as shown above).
Valys discloses wherein the method further comprises training a neural network with said annotated PPG signal ([0094] “As the skilled artisan will appreciate, the description herein relating to machine learning algorithms (e.g., … neural network algorithms) apply equally to all embodiments described herein.”, [0025] “This high-fidelity diagnosis-labeled low-fidelity data sequence is used to train a high-fidelity machine learning model”).
Regarding claim 27, Valys in view of Chatham in view of Lemay teaches the computer-implemented method for generating an annotated PPG signal according to claim 16 (as shown above). Valys further discloses wherein said annotations comprise one or more of the following ([0024-0025] “The high-fidelity measurement, ECG in this embodiment, can be evaluated by algorithms and/or medical professionals to make a notification or diagnosis (collectively referred to herein as “diagnosis”, recognizing that only a physician can make a diagnosis). In the ECG example, the diagnosis may be AFib or any other number of well-known conditions diagnosed utilizing ECGs. In further embodiments, a diagnosis is used to label a low-fidelity data sequence (e.g., heart rate or PPG)”):Irregular rhythm annotations comprising (Valys, [0091] “if not normal some diagnosis may be assigned”):
Atrial fibrillation; atrial flutter; supraventricular tachycardia; ventricular tachycardia; sinus tachycardia; bradycardia (Valys, [0091] “diagnosis may be assigned, e.g., AFib, tachycardia, bradycardia, atrial flutter”)
Claim(s) 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Valys in view of Chatham in view of Lemay as applied to claim 16 above, and further in view of Bouchakour et al. (WO 2018/002541 A1, citations below are from attached NPL translation, previously cited), hereinafter Bouchakour.
Regarding claim 21, Valys in view of Chatham in view of Lemay teaches the computer-implemented method for generating an annotated PPG signal according to claim 16 (as shown above). Valys, Chatham and Lemay, alone or in combination, fail to explicitly teach wherein pairing said ECG beats with said PPG beats comprises: selecting an ECG beat; determining an ECG signal portion comprising said ECG beat and no other ECG beats; determining a PPG signal portion time-aligned with said ECG signal portion; identifying a PPG beat lying within said PPG signal portion; associating said PPG beat with said ECG beat.
However Bouchakour teaches detecting cardiac rhythm disturbance in a subject by using two signals: a photoplethysmographic (PPG) signal (S1) and a electrocardiographic (ECG) signal (S2) wherein “the R peak is considered as a marker of ventricular systole, that is, of the heartbeat. The R wave is the thinnest and highest amplitude peak of the ECG signal, and is generally used to mark the instant of the heartbeat with very good accuracy.” ([0007]) and “The detection of R peaks in fact makes it possible to form time series whose constituent element is the RR interval, i.e. the time between two successive R peaks. To construct a time series of RR intervals, the ECG signal is sampled, digitized and then analyzed to detect R waves. A time series of RR intervals is thus made up of a plurality of successive RR intervals (... RRi-1, RRi, RRi+1 ...) as illustrated in Figure 3, each RR interval corresponding to the time interval separating two successive R waves of the ECG signal.” ([0009]) additionally “The PPG signal has a roughly sinusoidal appearance and presents peaks noted "R" by analogy with the electrocardiographic signal, the occurrence of which is representative of the subject's cardiac activity. At each heartbeat, the time of occurrence of an "R" peak of the PPG signal is correlated, with a slight phase shift, to the time of occurrence of the R peak of the ECG signal” (Figure 3 and 4, [0050]).
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Valys in view of Chatham in view of Lemay to incorporate the teachings of Bouchakour selecting an ECG beat; determining an ECG signal portion comprising said ECG beat and no other ECG beats; determining a PPG signal portion time-aligned with said ECG signal portion; identifying a PPG beat lying within said PPG signal portion; associating said PPG beat with said ECG beat. One would be motivated to do this because ECG heartbeats can be detected with great accuracy therefore when aligned with the peaks from PPG beat one can align cardiac activity so that the signals are detecting the same activity and can be related to each other, as recognized by Bouchakour ([0050]).
Claim(s) 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Valys in view of Chatham in view of Lemay in view of Bouchakour and further in view of Rundo et al. (US 2019/0021615 A1, previously cited), hereinafter Rundo.
Regarding claim 23, Valys in view of Chatham in view of Lemay and further in view of Bouchakour teaches the computer-implemented method for generating an annotated PPG signal according to claim 21 (as shown above).
Valys, Chatham, Lemay, and Bouchakour, alone or in combination fail to teach the method further comprising: verifying if said PPG beat represents the highest local maximum within a time interval ranging from an ECG beat preceding said ECG beat in said ECG signal to an ECG beat following said ECG beat in said ECG signal; and associating said PPG beat with said ECG beat only when said PPG beat represents the highest local maximum.
However, Rundo teaches the processing of electrophysiological signals such as e.g., ElectroCardioGraphy (ECG) and/or PhotoPlethysmoGraphy (PPG) ([0039]) wherein: verifying if said PPG beat represents the highest local maximum ([0081] “a mathematical analysis of the PPG signal can be performed in order to detect certain relative extremes, i.e., systolic peak (maximum), notch, diastolic peak, and minimum of the PPG waveform”) within a time interval ranging from an ECG beat preceding said ECG beat in said ECG signal to an ECG beat following said ECG beat in said ECG signal (view Figure 15A and 15B, the maximum peak of the PPG signal is found between two peaks of the ECG signal) ; and associating said PPG beat with said ECG beat only when said PPG beat represents the highest local maximum ([0208] ““translating” (shifting in time) the sampled ECG waveforms to be analyzed by causing their peaks (maxima) to correspond with the peaks in the first-derivative PPG signal and the peak of the ECG reference signal”).
It would have been prima facia obvious for one of ordinary skill in the art to have modified Valys in view of Chatham in view of Lemay to incorporate the teachings of Rundo to verify if PPG beat represents the highest local maximum within a time interval ranging from an ECG beat preceding said ECG beat in said ECG signal to an ECG beat following said ECG beat in said ECG signal; and associating said PPG beat with said ECG beat only when said PPG beat represents the highest local maximum. One would be motivated to do this to time-align the peaks of the various signals ([0199]) and where these coupled signals can facilitate obtaining robust and proper medical measures, by dealing with various factors such as, e.g., electronic noise, body movements, motion artifacts, body tissue issues, and breath and heart activity during the measuring session, which may corrupt both PPG and ECG signals ([0079]), as recognized by Rundo.
Claim(s) 26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Valys in view of Chatham in view of Lemay as applied to claim 16 above, and further in view of Fleming, Susannah & Tarassenko, L.. (2007). A Comparison of signal processing techniques for the extraction of breathing rate from the photoplethysmogram. Int J Biol Med Sci. 2., hereinafter Fleming (previously cited) .
Regarding claim 26, Valys in view of Chatham in view of Lemay discloses the computer-implemented method for generating an annotated PPG signal according to claim 16 (as shown above). Valys, Chatham, and Lemay, alone or in combination, fail to teach the method further comprising: recording a PPG signal, similarly to recording said PPG signal; pre-processing said PPG signal differently to obtain plural PPG signal versions; annotating said plural PPG signal versions, similarly to annotating said PPG signal, thereby generating plural annotated PPG signals; comparing said plural annotated PPG signals and deriving an optimal pre-processing for PPG signals based on the amount of insufficient quality annotations in said PPG signals.
However, Fleming teaches recording a PPG signal, similarly to recording said PPG signal (II. Materials and Methods: “Seven records from the MIMIC database in the Physiobank archive [1] were identified for use in assessing the accuracy of the algorithms for the extraction of breathing rate”); pre-processing said PPG signal differently to obtain plural PPG signal versions (Figure 2 and 3: PPG derived respiratory waveforms from two digital filtering methods and a wavelet method); annotating said plural PPG signal, similarly to annotating said PPG signal, thereby generating plural annotated PPG signals (Figure 2 and 3: detected breaths marked by circles); comparing said plural annotated PPG signals and deriving an optimal pre-processing for PPG signals based on the amount of insufficient quality annotations in said PPG signals (Table 1: errors between predicted breathing rate from the PPG and the reference respiratory rate, III. Results and Discussion: Table I shows that the novel AR method presented in this paper performs better than both the digital filtering and wavelet decomposition methods for extracting the breathing rate from a PPG waveform on most signals).
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Valys in view of Chatham in view of Lemay to incorporate the teachings of Fleming to recording a PPG signal, similarly to recording said PPG signal; pre-processing said PPG signal differently to obtain plural PPG signal versions; annotating said plural PPG signal versions, similarly to annotating said PPG signal, thereby generating plural annotated PPG signals; comparing said plural annotated PPG signals and deriving an optimal pre-processing for PPG signals based on the amount of insufficient quality annotations in said PPG signals, as these prior art references are directed to analyzing and annotating a PPG signal. One would be motivated to do this to determine the best method for extracting features from a PPG signal, as recognized by Fleming.
Claim(s) 28-29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chatham et al. (US 2023/0081751 A1, previously cited), hereinafter Chatham in view of Lemay et al., "Wrist-located optical device for atrial fibrillation screening: A clinical study on twenty patient," 2016 Computing in Cardiology Conference (CinC), Vancouver, BC, Canada, 2016, pp. 681-684, hereinafter Lemay (previously cited) .
Regarding claim 28, Chatham teaches a controller comprising at least one processor ([0092] “device further comprising at least one processing unit configured for determining the at least one signal feature”, [0070] “the processing unit may be a multi-core processor”)and at least one memory including computer program code ([0074] “The computer program may also be embodied as a computer program product. As used herein, a computer program product may refer to the program as a tradable product. The product may generally exist in an arbitrary format, such as in a paper format, or on a computer-readable data carrier and/or on a computer-readable storage medium”, [0073] “The computer-readable data carrier or storage medium specifically may be or may comprise a storage medium such as a random-access memory (RAM) and/or a read-only memory (ROM)”, the at least one memory and computer program code being configured, with the at least one processor cause the controller to perform ([0071] “the computer program comprising instructions which, when the program is executed by the portable photoplethysmogram device according to the present invention, such as according to any one of the embodiments disclosed above and/or according to any one of the embodiments disclosed in further detail below, cause the portable photoplethysmogram device to carry out steps a) to c) of the method according to the present invention… For the steps which are not computer-implemented or computer-implementable, the computer program may imply a prompting of the user to perform specific acts”):
recording an electrocardiogram signal, abbreviated ECG signal, using an ECG monitoring system ([0123] “ECG device 116 with sampling frequency 1kHz”);
recording a photoplethysmography signal, abbreviated PPG signal, semi-synchronously with said recording of said ECG signal, using a contact PPG sensor ([0041] “ECG and PPG data may be collected simultaneously”, [0123] “PPG device 110 a smart watch on the wrist equipped with LEDs and photodiode for measuring PPG”);
time-aligning said PPG signal and said ECG signal ([0041] “post alignment/synchronization of the time series obtained from the reference ECG and the PPG signals”);
detecting cardiac beats in said ECG signal, named ECG beats ([0044] “For the ECG data comprising a plurality of ECG signals, a different evaluation may be performed. The raw ECG signal may be analyzed with a variation on the Pan-Tompkins algorithms… The signal may be normalized…Single heart beats may be identified on this normalized signal as the peaks exceeding a threshold that in our case was identified as the 90th percentile of the data in the current window. Each heart beat crossing the threshold may be subsequently checked manually to make sure no erroneous beat was included in the analysis”);
detecting cardiac beats in said PPG signal, named PPG beats ([0023] “The PPG may comprise a plurality of beats…The term may specifically may refer, without limitation to at least one local maximum of the PPG”, [0036] “The peaks on the filtered PPG signal may then be identified and/or determine and/or calculated”);
Chatham fails to teach annotating segments in said ECG signal either algorithm-based or expert-based, resulting in ECG segment annotations; pairing said ECG beats with said PPG beats; deriving annotations for PPG signal segments by copying annotations of time-corresponding ECG signal segments or by attributing annotations that differ from said time-corresponding ECG signal segments depending on how said ECG beats can be paired with said PPG beats and annotating said PPG signal segments using said annotations, thereby generating said annotated PPG signal. .
However, Lemay teaches recording an ECG signal, using an ECG monitoring system; recording a PPG signal using a contact PPG sensor (“12-lead ECG signals were acquired at 2 kHz by a commercial electro-physiology system (Siemens Sensis), and PPG waveforms were acquired by a proprietary wrist-based device embedding reflective infrared sensors sampled at 21.33 Hz”); annotating segments in said ECG signal either algorithm-based or by expert-based, resulting in ECG segment annotations. (“ECG signals were further analyzed by clinical experts, providing annotations of sinus rhythm epochs (SR), regularly paced rhythm epochs, irregularly paced rhythm epochs, and AF epochs”), detecting cardiac beats in said ECG signals, named ECG beats (“position of heartbeats on ECG signals was extracted from R-wave detection as directly provided by the commercial electro-physiology system”), detecting cardiac beats in PPG signal, named PPG beats (“position of heartbeats in PPG signals was performed by detecting the systolic downstroke of each heart-beat waveform”); pairing said ECG beats with said PPG beats (“ECG- and PPG-based interbeat intervals were then computed from the R-waves and systolic downstrokes by taking the time difference of consecutive events. For each patient, beat-to-beat alignment of the two series of interbeat intervals was then performed”, Figure 1); deriving annotations for PPG signal segments by copying annotations of time-corresponding ECG signal segments or by attributing annotations that differ from said time-corresponding ECG signal segments depending on how said ECG beats can be paired with said PPG beats and annotating said PPG signal segments using said annotations, thereby generating said annotated PPG signal (“Expert annotations of rhythm epochs were automatically projected into the same time base, leading to one annotation for each interbeat interval. Figure 1 illustrates typical examples of aligned ECG and PPG data, as well as calculated RR intervals.”).
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Chatham to incorporate the teachings of Lemay to pair said ECG beats with said PPG beats as these prior arts and the instant application are directed to the correlation between ECG and PPG signals. One would be motivated to do this because PPG signals are easily affected by external factors and therefore have more artifacts and noise being harder to analyze, whereas an ECG is easier to analyze and by deriving the annotations from an aligned ECG signal, the PPG can be easily marked and analyzed without hindrance from noise or artifacts.
Regarding claim 29, Chatham teaches a computer readable storage medium comprising computer-executable instructions ([0073] “the term “computer-readable storage medium” specifically may refer to a non-transitory data storage means, such as a hardware storage medium having stored there-on computer-executable instructions”) of a program for performing the following steps when the program is run on a computer ([0074] “The computer program may also be embodied as a computer program product. As used herein, a computer program product may refer to the program as a tradable product. The product may generally exist in an arbitrary format, such as in a paper format, or on a computer-readable data carrier and/or on a computer-readable storage medium”, [0071] “the computer program comprising instructions which, when the program is executed by the portable photoplethysmogram device according to the present invention, such as according to any one of the embodiments disclosed above and/or according to any one of the embodiments disclosed in further detail below, cause the portable photoplethysmogram device to carry out steps a) to c) of the method according to the present invention… For the steps which are not computer-implemented or computer-implementable, the computer program may imply a prompting of the user to perform specific acts”) :
recording an electrocardiogram signal, abbreviated ECG signal, using an ECG monitoring system ([0123] “ECG device 116 with sampling frequency 1kHz”);
recording a photoplethysmography signal, abbreviated PPG signal, semi-synchronously with said recording of said ECG signal, using a contact PPG sensor ([0041] “ECG and PPG data may be collected simultaneously”) , using a contact PPG sensor ([0123] “PPG device 110 a smart watch on the wrist equipped with LEDs and photodiode for measuring PPG”);
time-aligning said PPG signal and said ECG signal ([0041] “post alignment/synchronization of the time series obtained from the reference ECG and the PPG signals”);
detecting cardiac beats in said ECG signal, named ECG beats ([0044] “For the ECG data comprising a plurality of ECG signals, a different evaluation may be performed. The raw ECG signal may be analyzed with a variation on the Pan-Tompkins algorithms… The signal may be normalized…Single heart beats may be identified on this normalized signal as the peaks exceeding a threshold that in our case was identified as the 90th percentile of the data in the current window. Each heart beat crossing the threshold may be subsequently checked manually to make sure no erroneous beat was included in the analysis”);
detecting cardiac beats in said PPG signal, named PPG beats ([0023] “The PPG may comprise a plurality of beats…The term may specifically may refer, without limitation to at least one local maximum of the PPG”, [0036] “The peaks on the filtered PPG signal may then be identified and/or determine and/or calculated”);
Chatham fails to teach annotating segments in said ECG signal either algorithm-based or expert-based, resulting in ECG segment annotations; pairing said ECG beats with said PPG beats; deriving annotations for PPG signal segments by copying annotations of time-corresponding ECG signal segments or by attributing annotations that differ from said time-corresponding ECG signal segments depending on how said ECG beats can be paired with said PPG beats and annotating said PPG signal segments using said annotations, thereby generating said annotated PPG signal.
However, Lemay teaches recording an ECG signal, using an ECG monitoring system; recording a PPG signal using a contact PPG sensor (“12-lead ECG signals were acquired at 2 kHz by a commercial electro-physiology system (Siemens Sensis), and PPG waveforms were acquired by a proprietary wrist-based device embedding reflective infrared sensors sampled at 21.33 Hz”); annotating segments in said ECG signal either algorithm-based or by expert-based, resulting in ECG segment annotations. (“ECG signals were further analyzed by clinical experts, providing annotations of sinus rhythm epochs (SR), regularly paced rhythm epochs, irregularly paced rhythm epochs, and AF epochs”), detecting cardiac beats in said ECG signals, named ECG beats (“position of heartbeats on ECG signals was extracted from R-wave detection as directly provided by the commercial electro-physiology system”), detecting cardiac beats in PPG signal, named PPG beats (“position of heartbeats in PPG signals was performed by detecting the systolic downstroke of each heart-beat waveform”); pairing said ECG beats with said PPG beats (“ECG- and PPG-based interbeat intervals were then computed from the R-waves and systolic downstrokes by taking the time difference of consecutive events. For each patient, beat-to-beat alignment of the two series of interbeat intervals was then performed”, Figure 1); deriving annotations for PPG signal segments by copying annotations of time-corresponding ECG signal segments or by attributing annotations that differ from said time-corresponding ECG signal segments depending on how said ECG beats can be paired with said PPG beats and annotating said PPG signal segments using said annotations, thereby generating said annotated PPG signal (“Expert annotations of rhythm epochs were automatically projected into the same time base, leading to one annotation for each interbeat interval. Figure 1 illustrates typical examples of aligned ECG and PPG data, as well as calculated RR intervals.”).
It would have been prima facia obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Chatham to incorporate the teachings of Lemay annotating segments in said ECG signal either algorithm-based or expert-based, resulting in ECG segment annotations; pairing said ECG beats with said PPG beats; deriving annotations for PPG signal segments by copying annotations of time-corresponding ECG signal segments or by attributing annotations that differ from said time-corresponding ECG signal segments depending on how said ECG beats can be paired with said PPG beats and annotating said PPG signal segments using said annotations, thereby generating said annotated PPG signal as these prior arts and the instant application are directed to the correlation between ECG and PPG signals. One would be motivated to do this because PPG signals are easily affected by external factors and therefore have more artifacts and noise being harder to analyze, whereas an ECG is easier to analyze and by deriving the annotations from an aligned ECG signal, the PPG can be easily marked and analyzed without hindrance from noise or artifacts.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
ALAM et al. (US 2019/0133533 A1), hereinafter ALAM teaches a system and method for PPG signal quality assessment ([0004],[0080]).
Pan et al. (US 2021/0100465 A1) teaches a heart-rhythm signal processing method which states that the bad signals of PPG results in misjudgement when an ECG is used as ground truth to label the PPG signal for detecting arrhythmias ([0004]) and labeling the quality of the PPG signals ([0024])
Persen et al. (US 201/0298272 A1) teaches flagging PPG signals for noise ([0061])
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/ATTIYA SAYYADA HUSSAINI/ Examiner, Art Unit 3792