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 .
Applicant cancelled claim 15.
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 1-14 and 16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
Under Step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance, the claims are directed to a process (claim 1, a method) or machine (claim 13, a calibration device, claim 14, a physiological measurement device), which are statutory categories.
3.1 However, evaluating claim 1, under Step 2A, Prong One, the claim is directed to the judicial exception of an abstract idea using the grouping of a mathematical relationship. The limitations include:
inputting at least one definition vector (vi) describing a linear combination of samples (ci) of at least two input channels; optimizing a metric calculated from at least one vector signal (y,), the vector signal being based on the samples (ci) of at least two of the received input signals and the definition vector (vi); and based on the optimizing, obtaining at least one set filter coefficients (xi) for at least one digital input filter associated with a specific input channel.
Next, Step 2A, Prong Two evaluates whether additional elements of the claim “integrate the abstract idea into a practical application” in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. The claim does not recite additional elements that integrate the judicial exception into a practical application.
Therefore, the claims are directed to an abstract idea.
At Step 2B, consideration is given to additional elements that may make the abstract idea significantly more. Under Step 2B, there are no additional elements that make the claim significantly more than the abstract idea.
The additional element of “receiving samples (ci) of multiple input signals (s) of the measurement device corresponding to a test signal (TS) applied to multiple input channels of the measurement device” are considered insignificant extra-solution activity of receiving data that is not sufficient to integrate the claim into a particular practical application. The input channels of the measurement device merely collect without adding anything novel or transformative to the system itself. The act of data gathering is considered insufficient to elevate the claim to a practical application.
The limitations have been considered individually and as a whole and do not amount to significantly more than the abstract idea itself.
Dependent claims 2-12 and 16 do not add anything which would render the claimed invention a patent eligible application of the abstract idea. The claim merely extends (or narrow) the abstract idea which do not amount for "significant more" because it merely adds details to the algorithm which forms the abstract idea as discussed above.
The additional element of “a computer program comprising program code means for causing a computer to carry out the steps of the method” (claim 12) amounts to no more than general purpose computer components programmed to perform the abstract ideas. As set forth in the 2019 Eligibility Guidance, 84 Fed. Reg. at 55 “merely include[ing] instructions to implement an abstract idea on a computer” is an example of when an abstract idea has not been integrated into a practical application.
The limitations have been considered individually and as a whole and do not amount to significantly more than the abstract idea itself.
3.2. Claims 13 and 14 are rejected 35 USC § 101 for the same rational as in claim 1.
This judicial exception is not integrated into a practical application because (claim 14) the remaining elements amount to no more than general purpose computer components programmed to perform the abstract ideas. As set forth in the 2019 Eligibility Guidance, 84 Fed. Reg. at 55 “merely include[ing] instructions to implement an abstract idea on a computer” is an example of when an abstract idea has not been integrated into a practical application.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created
doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement.
Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
Claims 1, 2, 13 and 14 are rejected under the judicially created doctrine of obviousness-type double patenting as being unpatentable over claim 3 of Patent No. US 11,147,517. An obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but an examined application claim is not patentably distinct from the reference claims because the examined claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985). Although the conflicting claims are not identical, they are not patentably distinct from each other because claim 1 is anticipated or fall entirely within the scope of claim 3 of Patent No. US 11,147,517.
The examiner notes that the limitation “receiving analog test signals at the input channels; generating response signals at the analog circuitry in response to receiving the analog test signals; converting each response signal into digital data samples; storing, in a memory of the physiological measurement system, the digital data samples in association with each of the input channels” of claim 1 of US 11,147,517 corresponds to the claimed limitation “receiving samples (ci) of multiple input signals (s) of the measurement device corresponding to a test signal (TS) applied to multiple input channels of the measurement device”, claim 2, of US 11,147,517, also specifies the test signal form: “analog test signals include a square wave that is superimposed with the sine wave”; the limitation “inputting at least one definition vector (vi) describing a linear combination of samples (ci) of at least two input channels”, the examiner notes that the method of claim 1, of US 11,147,517, forms and uses a difference to a reference channel and later even computes a differential signal and minimize time-domain differences between the reference input channel and each other input channel, the examiner notes that a difference operation is a linear combination of samples; the limitation “optimizing a metric calculated from at least one vector signal (yi), the vector signal being based on the samples (ci) of at least two of the received input signals and the definition vector (vi)” is anticipated by the limitation (claim 1 of US 11,147,517) “applying a filter…to minimize time-domain differences between the reference input channel and each input channel”; the limitation “obtaining at least one set filter coefficient (xi) for at least one digital input filter” is anticipated by the limitation (claim 1 of US 11,147,517) “ applying a filter to each input channel during operation of said physiological measurement system, wherein each filter operates according to a digital filter coefficient from the set of digital filter coefficients to minimize time-domain differences between the reference input channel and each input channel other than the reference input channel”.
Claims 1 and 13 are provisionally rejected on the ground of nonstatutory
obviousness-type double patenting as being unpatentable over claim 10 of copending application No. 18/717,512. An obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but an examined application claim not is patentably distinct from the reference claim(s) because the examined claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985). Although the conflicting claims are not identical, they are not patentably distinct from each other because claims 1 and 13 of the present application is anticipated by claim 10 of copending application No. 18/717,512. Specifically, since claim 10 of copending application No. 18/717,512 uses extra elements that are not required in claims 1 and 13 of the present application.
The examiner notes that the limitation “receiving samples (ci) of multiple input signals (si) of the measurement device corresponding to a test signal (TS) applied to multiple input channels” reads on the limitation “multiple input channels configured to obtain multiple measurement signals (si) acquired from a subject” (claim 1 of application No. 18/717,512); the limitation “inputting at least one definition vector (vi) describing a linear combination of samples (ci) of at least two input channels” reads on the limitation “input at least one definition vector (vi) describing a linear combination of samples (ci) of at least two input channels” (claim 8 of application No. 18/717,512); the limitation “optimizing a metric calculated from at least one vector signal (yi), the vector signal being based on the samples (ci) of at least two of the received input signals and the definition vector (vi) reads on the limitation “optimize a metric calculated from at least one vector signal (yj), the vector signal being based on the samples (ci) of the one or more stimulation signals and the definition vector (v,)” (claim 8 of application No. 18/717,512); and the limitation “based on the optimizing, obtaining at least one set filter coefficients (xi) for at least one digital input filter associated with a specific input channel” reads on the limitation “obtain, based on the optimizing, at least one set of filter coefficients (x) for at least one digital filter associated with a specific input channel” (claim 8 of application No. 18/717,512), including the case of multiple definition vectors claim 9 of application No. 18/717,512).
This is a provisional obviousness-type double patenting rejection because the conflicting claims have not in fact been patented.
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.
Claims 1-3 and 12-14 are rejected under 35 U.S.C. 103 as being unpatentable
over Levin et al. (Pub. No. US 2017/0143275) (hereinafter Levin) in view of Visser et al. (Pub. No. US 2009/0022336) (hereinafter Visser).
As per claims 1 and 12-14, Levin teaches receiving samples (ci) of multiple input signals (s) of the measurement device corresponding to a test signal (TS) applied to multiple input channels of the measurement device (¶¶ [0033]-[0045], i.e., physiological measurement system including multiple input electrodes, ¶¶ [0003]-[0006], [0050]-[0060], i.e., an injection electrode for introducing a known calibration signal, ¶¶ [0060]-[0062], i.e., receiving multiple input signals generated in response to the calibration/test signal and acquiring corresponding data samples from all electrodes).
While Levin teaches a processor that derives correction vectors and weighting factors based on the measured multi-channel signals (¶¶ [0073]-[0084]), which are applied to filter or correct the physiological signals (¶¶ [0073]-[0084], the examiner notes that Levin teaches receiving samples of multiple input signals corresponding to a test signal applied to multiple input channels, and determining coefficient (i.e., weights) applied to those channels), Levin fails to explicitly teach a definition vector describing a linear combination of two or more channels, an explicit optimization process for computing the coefficients; and a clear digital filter structure whose coefficients are obtained.
However, Visser teaches a multi-channel adaptive filter and source separation system employing unmixing matrices and directivity matrices (W(ω), D(ω)) that define linear combinations (vectors) of signals across multiple channels (¶¶ [0113]-[0119]). Visser further teaches iterative, sample-based optimization of filter coefficients using adaptive learning rules (e.g., ICA/IVA algorithms) that minimize mutual information or maximize independence between output vectors, thereby implementing an explicit optimization target function (¶¶ [0098]-[0101], [0113]-[0121]). The coefficients are updated on a per-sample or block basis within well-defined digital filter structures (¶¶ [0099]-[0103]). Visser also describes training the filters using known reference or test signals such as white noise, pink noise, or other calibration sources (¶¶ [0066]-[0077], [0130]-[0133]) and explicitly states that the techniques apply to physiological and medical signals such as ECG or EEG (¶ [0052]). It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to incorporate Visser’s teaching into Levin’s invention because it would optimize the physiological measurement device. Therefore, the accuracy of the physiological measurement device would be improved and stability and common-mode rejection would be achieved.
As per claim 2, the combination of Levin and Visser teaches the system as stated above.
Levin further teaches a physiological measurement system that receives analog test signals at multiple input channels, generates response signals, converts each response into digital samples, and analyzes samples to determine digital filter coefficients for each channel in order to minimize differences between a reference channel and the other channels (¶¶ [0001]-[0005], [0010], [0014] and [0044]-[0046]). (the examiner notes that the calibration process therefore teaches receiving and processing samples of multiple input signals corresponding to an applied test signal (TS) and determining per-channel filter coefficients xi based on a measured response. However, the calibration reference employs only a single reference channel, that is, it effectively uses a single definition vector describing the time-domain difference between one reference and the others).
Levin fails to teach inputting multiple definition vectors (vi).
However, Visser teaches multi-channel signals X(ω, I) can be separated into independent components Y(ω, I) by applying an un-mixing matrix W(ω). (the examiner notes that the ICA process describes therein therefore, provides multiple definition vectors, the rows of the un-mixing matrix W(ω), where Y(ω,I) = W(ω) X(ω,I) (¶ [0113]). The coefficients of W(ω) are iteratively updated according to stochastic gradient rule (Eq. (6)) to minimize mutual information and achieve statistical independence among the separated components. Visser further describes a time-domain embodiment using adaptive filters with outputs y1(t) and y2(t) and per-sample coefficient updates Δh12k, Δh21k (¶¶ [0098]-[0101]). Accordingly, the ICA process in Visser provides multiple separation vectors (the rows of W(ω)), and produces a distinct set of optimized coefficients for each vector). It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to incorporate Visser’s teaching into Levin’s invention because during calibration, multiple definition vectors (vi) could be input, each describing a linear combination of channels to be equalized, and for each vector vi the system would derive an optimized set of filter coefficients (xi) using the test responses. Therefore, calibration accuracy and cross channel compensation would be improved yielding common-mode rejection and orthogonalized signal output.
As per claim 3, the combination of Levin and Visser teaches the system as stated above. Visser further teaches that optimizing the metric comprises multiple optimizing steps, a set of filter coefficient obtained by one step being kept as constant for a subsequent optimizing step (¶ [0096], i.e., “Convergence may be determined based on the coefficient values of the component filters. For example, it may be decided that the filter has converged when the filter coefficient values no longer change, or when the total change in the filter coefficient values over some time interval is less than (alternatively, not greater than) a threshold value. Convergence may be determined independently for each cross filter, such that the updating operation for one cross filter may terminate while the updating operation for another cross filter continues”).
Claims 4, 6, 7, 9-11 and 16 are rejected under 35 U.S.C. 103 as being
unpatentable over Levin in view of Visser and further in view of Haykin et al. (Pub. No. US 2009/0304203) (hereinafter Haykin).
As per claim 4, the combination of Levin and Visser teaches the system as stated above. The combination of Levin and Visser fails to teach that the optimizing is subject to at least one linear equality constraint with respect to a filter coefficient (xi).
Haykin teaches “Processing the first and second sets of input signals to produce the first and second noise-reduced signals can comprise minimizing the energy of the first and second noise-reduced signals under the constraints that the speech component of the first noise-reduced signal is similar to the speech component of one of the input signals in the first set of input signals, the speech component of the second noise-reduced signal is similar to the speech component of one of the input signals in the second set of input signals and that the one or more binaural cues for the noise component in the input signal sets is preserved in the first and second noise-reduced signals” (¶ [0049]) and “Minimizing can comprise performing the TF-LCMV method extended with a cost function based on one of: an Interaural Time Difference (ITD) cost function, an Interaural Intensity Difference (IID) cost function, an Interaural Transfer function cost (ITF) and a combination thereof” (¶ [0050]). (the examiner notes that Haykin introduces the linearly constrained minimum-variance (LCMV) method that optimizes filter weights under linear equality constraints to preserve desired signal components (speech cues, binaural cues, etc,) (see also ¶¶ [0051]-[0055]). Since Haykin models physiological (auditory) signal behavior using linear constraints and adaptive filters (¶¶ [0179]-[0180]). It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to incorporate Haykin’s teaching into the combination of Levin and Visser’s teaching because the LCMV method maintains linear equality constraints that preserve both a defined relationship between channels and the statistical relationship among channels. Accordingly, integrating such constrained optimization into the calibration process would predictably yield more accurate and stable system calibration by ensuring that channel equalization is achieved without distorting reference relationships.
As per claims 6 and 7, the combination of Levin and Visser teaches the system as stated above. The combination of Levin and Visser fails to teach that the optimizing is subject to at least one nonlinear inequality constraint for limiting a gain of a certain input filter at a given frequency.
Haykin teaches that, in adaptive beamforming and TF-LCMV processing, “additional constraint, e.g., a quadratic inequality constraint, can be imposed on the update formula of the adaptive filter” (¶ [0125]) to control distortion and maintain stability. (The examiner notes that ¶ [0125] cites “Robust adaptive beamforming” (Cox et al., IEEE Trans.. Acoust. Speech and Signal Processing vol. 35, no. 10, pp. 1365-1376 (1987); U.S. Pat. 5,627,799) that impose quadratic inequality constraints on the adaptive weights to bound filter response magnitude in specified directions or frequencies. When read together with the time-frequency LCMV formulation of ¶¶ [0049]-[0050], these teachings clearly describe inequality constraints that limit the gain of a filter within given frequency bins. It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to incorporate Haykin’s teaching into the combination of Levin and Visser’s teaching because it would provide filters whose frequency-domain gain remains bounded. Therefore, the desired minimization of interference or common-mode components would be achieved.
As per claim 9, the combination of Levin and Visser teaches the system as stated above. The combination of Levin and Visser fails to explicitly teach that optimizing the metric comprises minimizing a penalty function of output samples (yi), the output samples corresponding to at least one vector signal (yi) calculated from the input signal filtered according to the filter coefficients (xi) and from the definition vector (vi).
Haykin teaches optimizing by minimizing a penalty function (i.e., the minimum-variance cost JMV) of the output samples Zi (corresponding to yi), where those outputs are vector signals derived by filtering the input signal vector X using filter coefficients Wi (corresponding to xi) and constrained by linear definition vectors Hi (corresponding to vi) (¶¶ [0120]-[0122]). It would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to incorporate Haykin’s teaching into the combination of Levin and Visser’s teaching because it would it would lower residual output energy (noise/interference) while maintaining the desired inter-channel relationships (linear or statistical dependencies among channels). Therefore, the desired minimization of interference or common-mode components would be achieved.
As per claim 10, the combination of Levin, Visser and Haykin teaches the system as stated above. Haykin further teaches that optimizing comprises minimizing multiple different penalty functions of the output samples (y,) simultaneously or minimizing a scalar target function of different penalty functions (¶¶ [0120]-[0122], equations (18)-(19)), the examiner notes that equation (18) explicitly minimizes two distinct penalty functions, JMv,0 for the left output and JMV,1 for the right output, at the same time. The same equation defines a scalar target function JMV(W) = JMV,0 + αJMV,1, i.e., a single scalar objective combining multiple penalty terms, where α sets their relative contribution and because both outputs (left and right) are optimized jointly within the same matrix formulation (equations (20)-(26), the minimization is simultaneous across multiple outputs).
As per claim 11, the combination of Levin, Visser and Haykin teaches the system as stated above. Haykin further teaches that at least one penalty function is a convex or quasi-convex penalty function (¶¶ [0120]-[0122], equations (11), (15), and (18)). (The examiner notes that each JMV(Wi) =
W
i
H
Ry
W
i
is convex quadratic cost function (since Ry is non negative) (The examiner also notes that a theorem from convex optimization and quadratic from theory states that “A function f(W)=
W
H
R
W
is convex if and only if the matrix R is positive semidefinite”).
As per claim 16, the combination of Levin, Visser and Haykin teaches the system as stated above. Haykin further teaches that the penalty function is a norm (¶[0120]. Equation (11)). (The examiner notes that E{
Z
2
}
is a squared 2-norm (specifically, the squared weighted L2-norm of the output signal).
Examiners Notes
Claims 5 and 8 distinguish over the prior art of record.
Regarding claim 5, none of the prior art of record teaches or fairly suggests a method for minimizing common mode interference in a physiological measurement device, the method including the steps of: inputting a DC gain value of at least one input channel and determining a corresponding linear equality constraint based on the DC gain value (DCi), in combination with the rest of the claim limitations as claimed and defined by the applicant.
Regarding claim 8, none of the prior art of record teaches or fairly suggests a method for minimizing common mode interference in a physiological measurement device, the method including the steps of: wherein the samples (ci) are received with a calibration sampling rate (fsamp) that is increased compared to an operating sampling rate applied to perform physiological measurements by the measurement device and/or wherein a calibration resolution (res) of the received samples (ci) differs from a measurement resolution of samples received to perform the physiological measurements, in combination with the rest of the claim limitations as claimed and defined by the applicant.
Prior art
The prior art made record and not relied upon is considered pertinent to applicant’s
disclosure:
Welch et al. [‘886] discloses a cardiac information dynamic display system comprises: one or more electrodes configured to record sets of electric potential data representing cardiac activity at a plurality of time intervals; and a cardiac information console, comprising: a signal processor configured to: calculate sets of cardiac activity data at the plurality of time intervals using the recorded sets of electric potential data, wherein the cardiac activity data is associated with surface locations of one or more cardiac chambers; and a user interface module configured to display a series of images, each image comprising: a graphical representation of the cardiac activity.
Mehrotra et al. [‘777] discloses a device and method for filtering impulsive noise and channel switching noise at ADC in an ECG device with multiplexed ESCs. The filtering is based on an implementation of Burst Sampling technique also a method for correcting errors in derived leads caused by time delays due to sequential sampling of different ECG signals is also provided. Real time digital FIR filters are used for removing other types of noise in ECG signals. The ECG device is compact and light weight and includes features of self-calibration, clip detection and drawing of power from USB port of a PC, batteries or an external power source. The ECG monitoring device of the present invention measures real time ECG signals with automated data recording, data storage and retrieval, data transmission/transfer to an external system, along with parameter extraction for ECG analysis in an efficient manner for quick and reliable ECG measurement, in an extremely cost-effective manner.
Causevic et al. [‘021] discloses an apparatus for monitoring bioelectric signals of a patient which includes a processing system and an interface for receiving external electrical signals representative of a condition of the patient. The interface is configured to convey a representation of the received external signals to the processing system, and includes a common mode cancellation amplifier circuit which is adapted to reduce common mode signal noise present in the external signals.
Contact information
Any inquiry concerning this communication or earlier communications from the
examiner should be directed to MOHAMED CHARIOUI whose telephone number is (571)272-2213. The examiner can normally be reached Monday through Friday, from 9 am to 6 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Schechter can be reached on (571) 272-2302. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
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Mohamed Charioui
/MOHAMED CHARIOUI/Primary Examiner, Art Unit 2857