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 .
Claims 1-16 and 21-22 are pending. Claims 1-9 remain withdrawn. Claims 21-22 are new.
Response to Arguments
Applicant's arguments filed 12/8/25 have been fully considered but they are not persuasive.
According to MPEP 2111.01 “an inventor may define specific terms used to describe invention, but must do so “with reasonable clarity, deliberateness, and precision””. The examiner maintains that neither Applicant’s specification, nor their Remarks of 12/8/25 limit the terms “real time” with a special definition. Applicant argues (Remarks IV.A) that “the specification …readily renders the meaning of the terminology “real time” ascertainable by reference to the description in para. [0048]”. This is not persuasive, at least because:
a) Regarding special definitions, the correct test is whether the term is defined “with reasonable clarity, deliberateness, and precision”.
b) ¶ 48 states:
“According to various implementations, only a small latency is introduced in estimating the signal quality. In some examples, a latency of about 1.5 seconds is used, where 1.5. seconds is approximately the duration of two heart beats. Thus, signal quality is estimated in real time. In some examples, the latency is about 0.75 seconds, where 0.75 seconds is approximately the duration of one heartbeat. In various examples, the latency is one or two heartbeats, and in some examples, the latency varies based on heart rate.”
¶ 48 does in no way offer a deliberate or precise meaning for the terms “real time”. Applicant does not state that “small latency” (in terms of noise removal) is meant to limit what “real time” means or set limits to “real time”. One is a specific species parameter for a specific measurement and the other is a generic qualitative term, akin to “real fast”, that merely separates the macro (e.g. daily tests) with the micro, leaving the micro relative (be it seconds, minutes or even hours). Neither does Applicant set precise limits to the relevant “small latency”. In fact, if Applicant were to define “real time” according to ¶ 48, there would potentially be issues of indefiniteness, in terms of the relevant terms of ¶48. Furthermore, right above, Applicant discloses on ¶ 46 that “the average of last five good beat is used as the threshold” of “the average QRS amplitude”, which is used to identify and discard the noisy portion of the signal. If Applicant’s reasoning were correct, by the same reasoning, would that (the last five beats) not be part of the alleged special definition of “real time”? However, that is not the case. It is not persuasive that ¶ 48, or any other part of the disclosure and arguments reasonably provide a special definition of the terms “real time”. Furthermore, 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 plain and ordinary meaning of “real time” in the art includes, for example, “within minutes”, see US 2019/0336025 by Qu, ¶ 38. Gomez-Clapers discloses that “in less than 5 s” (e.g. abstract, and sections III.B, IV,V), the signal is sufficiently clear of noise so as to be stable. The 5 seconds are from touching the dry electrode of the wheel to a clean signal (section V). Figures 8 and 9, illustrate clearly how, even within the first second of recording, the ECG signal is clear and lacks any noise portions that would be confused with an ECG peak. Gomez-Clapers further discusses how this is achieved with an analog front-end and a continuous wavelet transform (e.g. abstract), and is “fast enough to be observed as continuous by human perception”. Thus, Gomez-Clapers clearly meets the limitation of “real time”.
Applicant further attempts to equate a signal buffer mentioned by Gomez-Clapers to “latency” of detecting signal corruption. This conclusion is not based on evidence or the scope of the claims. Applicant’s arguments do not take the place of evidence. In re Wiseman, 596 F.2d 1019, 201 USPQ 658 (CCPA 1979); In re Pearson, 494 F.2d 1399, 181 USPQ 641 (CCPA 1974). It is not clear at all, what the assumption behind the argument is. Gomez-Clapers clearly discloses that the signal’s quality is corrected and stable in under 5 seconds. Mentioning one buffer size is like mentioning the size of a computer’s hard drive memory, and does not limit processing speed or latency. It’s more likely that the signal buffer in question has to do with the display of the 10 s signal, as in Fig. 9, than anything else. In addition, as noted above, even a 10 second latency would read on “real-time”.
In terms of the claimed “defined latency” of Claim 10, it is noted that: a) it is actually not defined and bound in the claim by any specific limits, b) it does not need to be a hardwired, preprogramed or preset parameter, c) it does not preclude ranges, as evidenced by Claim 22, which is taken as further limiting Claim 10, d) it does not preclude reliance on the user and signal itself as it arrives, as evidenced by Claims 21 and 22, which are taken as further limiting Claim 10, and d) it would be met, so long as one would be able to measure and define it at any point. Latency is inherent in any electrical recording, and in any processing and it is a parameter capable of being measured. Gomez-Clapers clearly disclose that the signal is processed to a clean and stable signal from the time of touching the wheel in under 5 seconds, and any latency within those bounds is a measurable, definable and definite parameter, which, as noted above, would include ranges. After all, the reason it is supported by Applicant’s disclosure is that it is supported as an output performance attribute (an intended result), not as a preset parameter. Applicant does not disclose presetting or setting the latency at any point in the system. The latency in question is the measurable result of a series of other, largely unclaimed, structural and algorithmic configurations (e.g. Daubechies D8 wavelet, adaptive thresholding, specific filtering, inter alia).
In terms of new claims 21 and 22, it is noted that Applicant’s specification does not disclose a system where one would set a parameter called latency. Rather, latency is a measurable result of the configurations of the system which are not claimed. See, for example ¶ 48, where heart beats are used as an equivalent to time in seconds (1.5 seconds). Thus, “latency based on heart beat” is read consistent with the specification to mean a time measurable in heart beats or seconds. While the total latency of Gomez-Clapers is within the range of “less than 5 seconds”, making the time of noise detection to be within that range, Brockman teaches ECG denoising in less than 100 ms. Thus, their combination teaches denoising with noise detection in less than 100 ms, which is less than 1.5 seconds and less than 2 heart beats, consistent with the specification.
It is also important to note that: a) the claims make no mention of a raw ECG signal (e.g. as in ¶ 64 of the disclosure), and b) the claimed latencies are limited to the detection of corruption of the signal, and do not necessarily limit the other parts of processing, such as discarding the noise, detecting potential QRS and updating the ECG.
Thus, overall, the measurable total delay of Gomez-Clapers of less than 5 seconds from touching the electrode to getting a clear ECG, and the continuous to human perception are sufficient to meet the claimed “real time” and “defined latency”.
Claim 14 remains allowable, as noted in the respective section of this action. Another potential way forward would be to limit the application to steering wheel ECG detection, in combination with specifics of the algorithm (e.g. db4 wavelet, raw signal directly to peak detection) that makes the total latency (from wheel to clean ECG) less than two heart beats (always provided sufficient support exists for any amendments).
Claim Objections
Claims 10-16 and 21-22 objected to because of the following informalities: 1) the latencies in Claims 1 and 14 and 21 are not the same latencies [one is for noise detection (Claim 10), the other is the total latency (Claims 14 and 21)], and should include a label, such as “first” and “second”. After that is corrected, then the latency of Claim 22 should also include the “first” label, 2) In Claim 13, “sign” should be “signal”. Appropriate correction is required.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 10-13, 15-16, and 21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by NPL by Gomez-Clapers et al., A Fast and Easy-to-Use ECG Acquisition and Heart Rate Monitoring System Using a Wireless Steering Wheel, IEEE SENSORS JOURNAL, VOL. 12, NO. 3, MARCH 2012 [submitted by Applicant on 5/19/23, 8 pages], as evidenced by US 2019/0336025 by Qu.
Regarding Claim 1, Gomez-Clapers discloses a system, comprising:
a dry electrode configured to receive an electrocardiogram input signal (page 610, col. 2, par. 3: “The system uses dry electrodes placed on a plastic steering wheel, so that the Lead I ECG signal is acquired in monitor mode simply by placing the hands on it”); and
a processor (page 611, col. 1, par. 1: “The PC is in charge of processing and displaying the ECG with the possibility of transmitting it through Internet to a medical center. In order to obtain the heart rate from the ECG signal, the system implements a novel algorithm based on the continuous wavelet transform (CWT), which has been designed and tested to offer a robust performance against electromyografic (EMG) noise and baseline wandering, which are the most common noise and interference sources when acquiring the EGC in the hands.”) configured to:
identify peaks in a first portion of the electrocardiogram input signal as the electrocardiogram input signal is received, with the identified peaks potentially corresponding to respective QRS complexes within the electrocardiogram input signal (e.g. see annotated Fig. 4: the algorithm identifies QRS peaks; page 613, col. 1, par. 2: “First, Mexican Hat based CWT at scales 1 and 25 are applied to a 10 s signal buffer. Scale 1, where only QRS complexes and EMG noise remain, is used to eliminate low frequency baseline wandering, so that a simple peak detection algorithm can be applied to detect all the peaks of the obtained signal. Then, the peaks with amplitude equal or higher than 2/3 of the maximum peak amplitude are classified as QRS complexes. Next, the algorithm also classifies as QRS complexes the peaks with amplitude between 2/3 and 1/3 of the maximum peak amplitude only if they are followed by a peak in the scale 25, delayed between 150 and 350 ms, which indicates a T wave.”),
detect corruption in a second portion of the electrocardiogram input signal as the electrocardiogram input signal is received, with the corruption detected in real time (The plain and ordinary meaning of “real time” in the art includes, for example, “within minutes”, see US 2019/0336025 by Qu, ¶ 38) within a defined latency (again, it is noted that in Applicant’s specification the latency is a result that is measurable not a preset parameter, and this is how “defined latency” is taken under the broadest reasonable interpretation consistent with the specification) from receiving the electrocardiogram input signal, and the second portion being part of the first portion [e.g. page 612-613: “The new algorithm proposed is specially suited to the particularities of acquired signal in the wireless steering wheel, which are an EMG noise and baseline wander levels higher than in traditional systems. These increased levels of noise and interference are produced by changes in the strength with which the wheel is hold and by movements of the user, especially if he or she presses the electrodes with excessive strength. The proposed algorithm takes profit on the fact that the different scales of a CWT show different features of the signal, and uses two different scales to detect separately the QRS complex of the ECG overlapped with electromyographic noise at one scale, and the T wave of the ECG in the other. Fig. 3 shows a Lead I ECG signal acquired with the system and its associated Mexican Hat based CWT for scales 1 and 25. As it can be observed from the figure, at scale 1, all the low frequency components of the ECG are filtered and only the QRS complexes and the EMG noise remain. Oppositely, as only low frequency components of the ECG are present at scale 25, the resulting wave has a cosine-like behavior, which has the peaks where the original signal has T waves. Mexican Hat mother wavelet has been chosen for the presented algorithm because it was the one having the best performance after many tests with different ECG recordings and different mother wavelets. Fig. 4 shows the flowchart of the proposed algorithm. First, Mexican Hat based CWT at scales 1 and 25 are applied to a 10 s signal buffer. Scale 1, where only QRS complexes and EMG noise remain, is used to eliminate low frequency baseline wandering, so that a simple peak detection algorithm can be applied to detect all the peaks of the obtained signal. Then, the peaks with amplitude equal or higher than 2/3 of the maximum peak amplitude are classified as QRS complexes. Next, the algorithm also classifies as QRS complexes the peaks with amplitude between 2/3 and 1/3 of the maximum peak amplitude only if they are followed by a peak in the scale 25, delayed between 150 and 350 ms, which indicates a T wave. The remaining detected peaks at the scale 1 signal are discarded. Finally, if a detected peak has another higher QRS complex closer than 200 ms, it is also discarded because it is probably produced by noise, typically from the EMG”. Thus, the algorithm detects and discards corrupted peaks. In relation to “as the electrocardiogram input signal is received” and as noted in the claim interpretations section: As shown in Fig. 4, as the ECG signal is received it is sent to the algorithm that detects and discards corrupt QRS peaks. In addition, as disclosed on page 611, col.2, par.2, the abstract and shown in Fig. 3, the ECG is obtained in “monitor mode”, thus is acquired, denoised and displayed continuously, in “real-time”. More broadly, the limitations is met by processing the signal in the order it is received, and/or the processor being capable of receiving signals from the electrode while corruption in a previously received signal is detected, which are clearly true in Gomez-Clapers. Furthermore, as noted in the Reply to Arguments section: Gomez-Clapers discloses that “in less than 5 s” (e.g. abstract, and sections III.B, IV,V), the signal is sufficiently clear of noise so as to be stable. The 5 seconds are from touching the dry electrode of the wheel to a clean signal (section V). Figures 8 and 9, illustrate clearly how, even within the first second of recording, the ECG signal is clear and lacks any noise portions that would be confused with an ECG peak. Gomez-Clapers further discusses how this is achieved with an analog front-end and a continuous wavelet transform (e.g. abstract), and is “fast enough to be observed as continuous by human perception”. Thus, Gomez-Clapers clearly meets the limitation of “real time”.],
discard at least one peak of the identified peaks present in the second portion of the electrocardiogram input signal including the corruption, with the at least one peak incorrectly representing respective QRS complexes (e.g. see annotated Fig. 4: the peaks not classified as QRS or QRS peaks too close to each other are discarded; page 613, col. 1, par. 2: “The remaining detected peaks at the scale 1 signal are discarded. Finally, if a detected peak has another higher QRS complex closer than 200 ms, it is also discarded”), and
update an electrocardiogram in real time based on remaining ones of the identified peaks after discarding at least one peak (e.g. page 611, col. 1, par. 1: “displaying the ECG”; As seen in Fig. 3, the ECG is a continuous for at least 10 seconds; also see title, abstract, page 610, col. 2, par. 3: fast, continuous, short-term, stable ECG in less than 5 s).
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Figure 1Annotated Fig. 1 from Gomez-Claper
In addition to the foregoing (detection and discarding of corrupted QRS peaks), all other methods of noise removal in Gomez-Clapers, meet the capability of detecting corruption in a portion of the signal and discarding the corrupted portion (e.g. band-pass filtering, high-pass filtering, square filtering etc.).
Regarding Claim 11, Gomez-Clapers, as evidenced by Qu, discloses the system of claim 10, further comprising an electrocardiogram lead coupled to the dry electrode and configured to receive electrical activity (e.g. page 611, col. 2, par. 1: ECG Lead I).
Regarding Claim 12, Gomez-Clapers, as evidenced by Qu, discloses the system of claim 11, wherein the electrocardiogram lead is attached to a steering wheel (e.g. Fig. 1: steering wheel with “[f]our dry stainless steel electrode”).
Regarding Claim 13, Gomez-Clapers, as evidenced by Qu, discloses the system of claim 10 any of claims 10, wherein the processor is further configured to adaptively determine a threshold based on an amplitude of the identified peaks in the first portion of the electrocardiogram input signal and wherein the corruption includes sign[al] noise exceeding the threshold (page 613, col. 1, par. 2: “Scale 1, where only QRS complexes and EMG noise remain, is used to eliminate low frequency baseline wandering, so that a simple peak detection algorithm can be applied to detect all the peaks of the obtained signal. Then, the peaks with amplitude equal or higher than 2/3 of the maximum peak amplitude are classified as QRS complexes. Next, the algorithm also classifies as QRS complexes the peaks with amplitude between 2/3 and 1/3 of the maximum peak amplitude only if they are followed by a peak in the scale 25, delayed between 150 and 350 ms, which indicates a T wave.” Thus, the thresholds are determined on the basis of the “maximum peak amplitude”, which is variable, and thus the thresholds are adaptive).
Regarding Claim 15, Gomez-Clapers, as evidenced by Qu, teaches the system of claim 10, wherein to detect corruption, the processor is configured to detect low frequency noise in the electrocardiogram input signal and determine when the low frequency noise exceeds a threshold (page 613, col. 1, par. 2:” Scale 1, where only QRS complexes and EMG noise remain, is used to eliminate low frequency baseline wandering, so that a simple peak detection algorithm can be applied to detect all the peaks of the obtained signal. Then, the peaks with amplitude equal or higher than 2/3 of the maximum peak amplitude are classified as QRS complexes. Next, the algorithm also classifies as QRS complexes the peaks with amplitude between 2/3 and 1/3 of the maximum peak amplitude only if they are followed by a peak in the scale 25, delayed between 150 and 350 ms, which indicates a T wave. The remaining detected peaks at the scale 1 signal are discarded. Finally, if a detected peak has another higher QRS complex closer than 200 ms, it is also discarded because it is probably produced by noise, typically from the EMG.” Thus, baseline wandering noise is eliminated based on the scale thresholds of the algorithm. Also see “high-pass differential filter” on page 611, col. 2, par. 2).
Regarding Claim 16, Gomez-Clapers, as evidenced by Qu, teaches the system of claim 10, wherein to detect corruption, the processor is configured to detect narrowband powerline noise in the electrocardiogram input signal and determine when the narrowband powerline noise exceeds a threshold (e.g. page 611, col. 1, par. 2-3: band-pass filter lowers 50/60 Hz, ie. mains, interference).
Regarding Claim 21, Gomez-Clapers, as evidenced by Qu, teaches the system of claim 10, wherein to update the electrocardiogram, the processor generates the electrocardiogram with a latency that is based on a heart rate from the received electrocardiogram input signal [noting here that in Applicant’s specification there is no setting per se for a parameter of latency in the system, rather it being a performance outcome measurable in terms of heart beats or seconds (e.g. ¶ 48, where 1.5 seconds is equated to two heart beats). Consistent with the specification, the latency in Gomez-Clapers is measurable in either seconds or heart beats, and the “less than 5s” taught for the measurement would correspond to less than about 7 heart beats].
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 22 is rejected under 35 U.S.C. 103 as being unpatentable over Gomez-Clapers, as evidenced by Qu, as applied to Claim 10, in view of US 2022/0054090 by Brockway, as evidenced by Applicant Admitted Prior Art (AAPA).
Regarding Claim 22, Gomez-Clapers, as evidenced by Qu, discloses the system of claim 10, yet does not explicitly disclose the latency not exceeding the duration of two heartbeats.
However, Brockway teaches an analogous ECG monitoring system, wherein a noise portion of the ECG is removed in real time with a latency of less than 100 ms (e.g. abstract, ¶17). A latency of 100 ms is less than two heartbeats (AAPA, ¶ 48: “a latency of about 1.5 seconds is used, where 1.5 seconds is approximately the duration of two heart beats”). It would have been prima facie obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to denoise the ECG signal with a latency of less than 100 ms (not exceeding the duration of two heart beats) in a system according to the teachings of Gomez-Clapers, as taught by Brockway, as: a) this would amount to a selection within the working range of “less than 5 s” taught by Gomez-Clapers, and according to MPEP 2144.05, in the case where the claimed ranges “overlap or lie inside ranges disclosed by the prior art” a prima facie case of obviousness exists. In re Wertheim, 541 F.2d 257, 191 USPQ 90 (CCPA 1976); In re Woodruff, 919 F.2d 1575, 16 USPQ2d 1934 (Fed. Cir. 1990), b) this would predictably denoise the ECG signal in real time, as is desirable by both Gomez-Clapers and Brockway.
Allowable Subject Matter
Claim 14 is allowed.
The following is a statement of reasons for the indication of allowable subject matter:
The prior art does not reasonably teach, suggest or render obvious, either alone or in combination, claim 14 taken as a whole. The closest prior art is Gomez-Lopez, yet it fails to teach wherein to update the electrocardiogram, the processor generates the electrocardiogram with a latency in a range from one heartbeat to two heartbeats from the received electrocardiogram input signal, in addition to the other limitations of Claim 10. The latency claimed in Claim 14 is the total latency from reception of the signal from the dry electrode to the updated and denoised clean QRS peaks, and the respective latency is less than 5 seconds. A 5 second heartbeat would correspond to a pulse rate of 12 hb/s, and a 2.5 second heartbeat would correspond to a pulse rate of 24 hb/s, neither of which is a realistic heart rate for real-world ECG applications (presumed under 112 and 101 for the claims). Brockman is specific on the denoising part latency, thus would not remedy the deficiency of Gomez-Clapers.
Conclusion
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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/MANOLIS PAHAKIS/Examiner, Art Unit 3796