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 .
Claim Objections
Claim 1 is objected to because of the following informalities: line 1 states “(400); this is objected to because the other instances in the claim have been removed.
Claim 2 is objected to because of the following informalities: lines 2-3 states “a bio adhesive which sticking said ECG skin patch with the skin” is non-idiomatic. Appropriate correction is required.
Claim 6 is objected to because of the following informalities: line 2 last word states “off”; this should be “of”. Appropriate correction is required.
Claim 21 states in line 6 “the said ECG skin patch”, only one of “the” or “said” is necessary.
Claim Interpretation
The examiner notes that claim 6 is interpreted as requiring at least one of Bluetooth, WI-FI and or SD card and a mobile data network 4G/LTE. This means the claim requires mobile data network and at least one of Bluetooth, WI-FI and SD card.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-25 are 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.
Claim 1 recites the limitation "the heart" in line 13. There is insufficient antecedent basis for this limitation in the claim. Dependent claims inherit the same deficiencies.
Claim 4 recites the limitation "the contact point" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 4 recites the limitation of “the signal”, line 4, it is unclear if this is the electrical signal or if this is part of the transmitted signal by the IOT or something else.
Claim 4 recites the limitation "the pathway" in line 5. There is insufficient antecedent basis for this limitation in the claim.
Claim 9 recites the limitation "said integrated circuit" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 11 recites the limitation "said PCB components" in lines 2-3. There is insufficient antecedent basis for this limitation in the claim.
Claim 12 recites the limitation "the battery level status" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 15 recites the limitation "the clock frequency" in line 1. There is insufficient antecedent basis for this limitation in the claim.
Claim 15 recites the limitation "the input channels" in line 6. There is insufficient antecedent basis for this limitation in the claim.
Claim 15 recites the limitation "the ECG female snap connector end" in lines 6-7. There is insufficient antecedent basis for this limitation in the claim.
Claim 15 recites the limitation "the battery" in line 7. There is insufficient antecedent basis for this limitation in the claim.
Claim 16 recites the limitation "the data" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 17 recites the limitation "said PCB assembly" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 17 recites the limitation "the male snap connectors" in line 4. There is insufficient antecedent basis for this limitation in the claim.
Claim 19 recites the limitation "said device" in lines 2, 3, and 7. There is insufficient antecedent basis for this limitation in the claim.
Claim 19 recites the limitation "said application" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 19 recites the limitation "said data" in lines 4, 6, 8 and 9. There is insufficient antecedent basis for this limitation in the claim.
Claim 19 recites the limitation "the mobile application" in line 6. There is insufficient antecedent basis for this limitation in the claim.
Claim 19 recites the limitation "the cloud servers" in line 8. There is insufficient antecedent basis for this limitation in the claim.
Claim 19 recites the limitation "the PC/laptop" in line 9. There is insufficient antecedent basis for this limitation in the claim.
Claim 19 recites the limitation "the USB connection" in lines 9-10. There is insufficient antecedent basis for this limitation in the claim.
Claim 20 requires “compared with available data through said AI engine”; it is unclear what this data is and how it is different from the stored data or is this the knowledge database.
Claim 21 recites the limitation "the underlying cardiovascular dynamics" in lines 3-4. There is insufficient antecedent basis for this limitation in the claim.
Claim 21 recites the limitation "the condition of the heart" in line 4. There is insufficient antecedent basis for this limitation in the claim.
Claim 21 recites the limitation "the complexity and irregularity of heart" in line 5. There is insufficient antecedent basis for this limitation in the claim.
Claim 21 recites the limitation "the intermittent cluster" in line 7. There is insufficient antecedent basis for this limitation in the claim.
Claim 23 recites the limitation “said pins” in line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 23 recites the limitation "the device" in line 2. There is insufficient antecedent basis for this limitation in the claim.
Regarding claim24, the phrase "such as" renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
Claim 25 recites the limitation "the data" in line 6. There is insufficient antecedent basis for this limitation in the claim.
Claim 25 recites the limitation "the circulation rhythm" in lines 6-7. There is insufficient antecedent basis for this limitation in the claim.
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 1-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the mental process of data pre-processing, feature extraction, feature selection, training, validation and testing, and performance evaluation; peak detector algorithm. This judicial exception is not integrated into a practical application because the additional elements of a wearable ECG skin patch, IoT connected signal transmission unit comprising a microcontroller unit, flexible dry electrodes having TPU substrate (claim 3); a snap connector and a conducting channel (claim 5); rechargeable battery (claim 8); voltage regulators with diodes (claim 9); LED indicator (claim 12) are pre-solution activities necessary for obtaining data. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the microcontroller is recited with a high level of generality as the disclosure indicates in published paragraph [0101] states the Microcontroller unit (MCU) (201) is shown, which is an 80 MHz, dual core processor with inbuilt Bluetooth (311) and Wi-Fi (312) module; flexible dry electrodes having TPU substrate; a snap connector and a conducting channel; rechargeable battery; and LED indicator are well understood, routine, and conventional as shown by Trapero Martin et al (US Patent 11,207,025) and flexible dry electrodes having TPU substrate; a snap connector and a conducting channel are well understood, routine, and conventional as evidenced by Pernu (US Publication 2022/0192571 (e.g. Paragraphs [0015], and [0040]-[0048]) and Uy et al (US Patent 10,993,635 (e.g. Column 3 lines 56-67); rechargeable battery (claim 8); and LED indicator are well understood, routine, and conventional as shown by Murphy (US Patent 6,409,661)(e.g. Column 10 lines 26-45); and Gibson et al (US Publication 2008/0281168) (e.g. Paragraphs [0097] and [0100]); in addition, voltage regulators with diodes (claim 9) is well understood, routine, and conventional as shown by Cocatre-Zilgien (US Patent 5,844,862) (e.g. Column 8 lines 56-58) and Trenkler et al (US Patent 4,150,284 (e.g. Column 5 lines 4-11).
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.
Claim(s) 1, 3, 5-6, 8, 10-15, 17-20, and 22-25 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Trapero Martin et al (US Patent 11,207,025).
Referring to Claim 1, Trapero Martin et al teaches an artificial intelligence enabled wearable ECG skin patch (e.g. Figures 7-9, Elements 700, 800 and 960) to detect sudden cardiac arrest, the skin patch comprising an loT connected signal transmission unit and an artificial intelligence engine (e.g. electronics module 802 and Figure 18 communications module 1851 and microcontroller 1870 and Column 30 lines 59-52); wherein, said wearable ECG skin patch comprises a flexible printed electronic technology based biocompatible polymer ECG skin patch that is capable of capturing an electrical signal (e.g. Column 24 lines 12-20 discloses the flexible patch extending from the PCB and Column 19 lines 3-8 discloses the patch made of a flexible biocompatible polymer and Column 20 lines 44-Column 21 line 52 discloses capturing electrical signals); said loT connected signal transmission unit comprising a microcontroller unit that is capable of controlling signal transmission using a wireless interface (e.g. Figure 18 and Column 32 lines 25-28); said artificial intelligence engine comprising an artificial intelligence (Al) and Machine Learning (ML) pipeline that is arranged to perform a sequence of steps comprising: a data pre-processing step, a feature extraction step, a feature selection step, a training step, a validation and testing step, and a performance evaluation step (e.g. Column 30 lines 46- line 66; and Column 33 lines 18-56 discloses machine learning and artificial intelligence which necessarily require the sequence of steps in order to take the data and convert it to diagnose medical conditions); wherein, said wearable ECG skin patch is capable of capturing the entire span of the heart to detect the sudden cardiac arrest (e.g. Figure 7); in that a sudden cardiac arrest is predicted through said Al and ML pipeline (e.g. Column 30 lines 46- Column 31 line 60); wherein the Al and ML pipeline is trained using a knowledge database and is thereafter arranged to automate the process of cardiac disease prediction (e.g. Column 40 lines 18-41); wherein a peak detector algorithm of the artificial intelligence engine is capable of capturing the instantaneous heart rate from the R-peaks of the ECG so as to obtain a measure of Heart Rate Variability (HRV), preferably by plotting an R-R interval time series (e.g. Column 38 lines 52-67).
Referring to Claim 3, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claim 1, further comprising a conductive part having flexible dry electrodes which are conducting ink printed over a TPU substrate, preferably wherein said flexible dry electrodes comprise Ag/AgCl ink printed over said Thermoplastic Polyurethane (TPU) substrate (e.g. Column 19-lines 3-7 and Column 24 lines 27-34 and Column 25 lines 14-26).
Referring to Claim 5, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, further comprising one or more of a snap connector provides the contact point with a PCB assembly box being capable to sensing the signal (e.g. Column 20 lines 44-62); a conducting channel which provides the pathway for the signal to said ECG patch (e.g. Column 20 lines 44-62).
Referring to Claim 6, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein the wireless interface is arranged to communicate using one or more off Bluetooth, WI-FI and/or SD card, and a mobile data network 4G/LTE (e.g. Column 32 lines 15-57).
Referring to Claim 8, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, comprising, and being powered through, a rechargeable battery (e.g. Column 14 lines 50-51 and lines 59-67 and Column 30 lines 31-32).
Referring to Claim 10, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein said loT connected signal transmission unit further comprises a PCB which houses specific circuit combinations for ECG signal sensing, amplification, sampling, storing and transmitting (e.g. Figure 16 and Column 29 lines 12-16 and lines 25-35).
Referring to Claim 11, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein said microcontroller unit is capable of driving said PCB components (e.g. Figure 16 and Column 29 lines 12-16 and lines 25-35).
Referring to Claim 12, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein said loT connected signal transmission unit further comprises an LED indicator capable of showing the battery level status as well as a critical situation status when abnormal heart activity is sensed (e.g. Column 34 lines 30-46).
Referring to Claim 13, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein said loT connected signal transmission unit further comprises one or more of connector pins being capable of flashing the microcontroller through USB to UART conversion integrated circuit (e.g. Column 32 lines 61-Column 33 line 3); a low power, channel analog front end (AFE) sensing unit for ECG signal (e.g. Figure 16, Element 1617 and Column 29 lines 25-35 and Column 35 lines 10-23).
Referring to Claim 14, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 13, wherein said AFE is capable of capturing low amplitude multi resolution signals through said wearable skin patch (e.g. Figure 16, Element 1617 and Column 29 lines 25-35 and Column 35 lines 10-23).
Referring to Claim 15, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein said loT connected signal transmission unit further comprises one or more of a crystal oscillator capable of providing the clock frequency for dataflow synchronisation; female connector audio jacks for connecting the input channels from the ECG female snap connector end; a battery charging circuit IC capable of charging the battery (e.g. Column 15 lines 35-44).
Referring to Claim 17, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein: said PCB assembly is covered with laminated box; and/or said ECG skin patch comprises four ECG female snap connector points for connecting with the male snap connectors attached to said ECG patch (e.g. Figure 12 and Column 24 lines 12-25 disclose mating electrode pads with electrode contacts and Column 10 lines 41-50 discloses six or fewer electrode contacts).
Referring to Claim 18, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein said artificial intelligence engine is capable of observing de-noising by discrete wavelet Transforms (DWT) (e.g. Paragraph [0143]-[0149]).
Referring to Claim 19, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein said device further comprises an loT system architecture capable of providing interconnection between said device and said application, preferably wherein the data is stored into the memory via Bluetooth mode, Wi-Fi mode, or SD card mode (e.g. Column 32 lines 16-41); said Bluetooth mode being capable to activate the mobile application to store the data; said Wi-Fi mode being capable to connect said device to local gateway through which said data being transmitted and stored into the cloud servers; said SD card mode being capable to store said data into the PC/laptop through the USB connection (e.g. Column 32 lines 58-66 and Column 40 lines 7-29).
Referring to Claim 20, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 19, wherein said stored data is analysed and compared with available data through said Al engine (e.g. Column 33 lines 21-56).
Referring to Claim 22, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein said ECG skin patch can be operated in single channel and/or 3 channel according to patient requirements (e.g. Column 21 lines 45-47 and Column 35 lines 10-23).
Referring to Claim 23, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein said pins through the device are capable of reuse with provision for further firmware updates for up-gradation via offline and online modes (e.g. Column 32 lines 58-Column 33 line 3).
Referring to Claim 24, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein said artificial intelligence engine is capable of being trained through Deep Learning models such as ID Convolutional Neural Network (CNN) for real time SCA prediction (e.g. Column 41 lines 1-15).
Referring to Claim 25, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein: said ECG skin patch is an integrated expert system that can work in assisting the patient's physician or cardiologist for secondary level of diagnosis and treatment planning; and/or said ECG skin patch is capable of automatically plotting the data in sync with the circadian rhythm; and/or said ECG skin patch is arranged to capture the entire span of the heart in accordance with the principles of Einthoven Triangle (e.g. Column 30 lines 46- line 66; and Column 33 lines 18-56).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 2 and 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Trapero Martin et al (US Patent 11,207,025) in view of Kumar et al (US Publication 2017/0056682).
Referring to Claim 2, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, except further comprising a circular Area containing a bio adhesive which sticking said ECG skin patch with the skin. Kumar et al teaches that it is known to use a circular Area containing a bio adhesive which sticking said ECG skin patch with the skin as set forth in Figure 7 and Paragraph [0107] to provide improved ability to maintain constant contact across different anatomical configurations. It would have been obvious before the effective filing date of the claimed invention to one having ordinary skill in the art to modify the system as taught by Trapero Martin et al, with a circular Area containing a bio adhesive which sticking said ECG skin patch with the skin as taught by Kumar et al, since such a modification would provide the predictable results of improved ability to maintain constant contact across different anatomical configurations.
Referring to Claim 4, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 3, except wherein said TPU Substrate is laminated with textile material in order to provide form and shape to said ECG skin patch. Kumar et al teaches that it is known to use TPU Substrate is laminated with textile material as set forth in Paragraphs [0107]-[0109] to provide a water resistance surface which reduces water from entering the housing. It would have been obvious before the effective filing date of the claimed invention to one having ordinary skill in the art to modify the system as taught by Trapero Martin et al, with TPU Substrate is laminated with textile material as taught by Kumar et al, since such a modification would provide the predictable results of a water resistance surface which reduces water from entering the housing.
Claim(s) 7 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Trapero Martin et al (US Patent 11,207,025).
Referring to Claim 7, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, comprising three conducting channels (e.g. Column 21 lines 45-47 discloses using fewer than 6 electrodes).
However, Trapero Martin et al does not explicitly disclose three conducting channels. It would have been obvious to one having ordinary skill in the art at the time the invention was made to modify the system as taught by Trapero Martin et al with three conducting channels, since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or workable ranges involves only routine skill in the art [In re Aller, 105 USPQ 233] and/or since it has been held that a prima facie case of obviousness exists where the claimed ranges and prior art ranges do not overlap but are close enough that one skilled in the art would have expected them to have the same properties. Titanium Metals Corp. of America v. Banner, 778 F.2d 775, 227 USPQ (Please see MPEP 2144.05).
Referring to Claim 16, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, wherein said loT connected signal transmission is capable of one or more of storing the data, and processing and analytics, wherein a cloud computing infrastructure is realised with virtual servers and databases (e.g. Column 42 lines 56-63 and Column 44 lines 39-44), However, Trapero Martin et al does not explicitly discloses wherein a cloud computing infrastructure is realised with virtual servers and databases with Hypertext Transfer Protocol Secure (https) and Message Queuing Telemetry Transport (mqtt) based communication protocols.
Since Trapero Martin et al discloses the use of a cloud-based healthcare server, it would have been obvious to try, by one of ordinary skill in the art before effective filing date of the invention, to perform Trapero Martin et al and to incorporate it into the system of Trapero Martin et al since there are a finite number of identified, predictable potential solutions (i.e., communication protocols) and one of ordinary skill in the art would have pursued the known potential solutions with a reasonable expectation of success.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Trapero Martin et al (US Patent 11,207,025) in view of Cocatre-Zilgien (US Patent 5,844,862).
Referring to Claim 9, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, except comprising a plurality of voltage regulators having a diode capable of providing a supply voltage to said integrated circuit. Cocatre-Zilgien teaches that it is known to use a plurality of voltage regulators having a diode capable of providing a supply voltage to said integrated circuit as set forth in Column 8 lines 56-58 to provide protection against accidental battery polarity reversals. It would have been obvious before the effective filing date of the claimed invention to one having ordinary skill in the art to modify the system as taught by Trapero Martin et al, with voltage regulators having a diode capable of providing a supply voltage to said integrated circuit as taught by Cocatre-Zilgien, since such a modification would provide the predictable results of protection against accidental battery polarity reversals.
Claim(s) 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Trapero Martin et al (US Patent 11,207,025) in view of Lee (US Patent 5,645,069).
Referring to Claim 21, Trapero Martin et al teaches the artificial intelligence enabled wearable ECG skin patch as claimed in claim 1, except wherein said machine learning pipeline uses one or more of a nonlinear discrete dynamical system theory (ND-DST) capable of quantifying the underlying cardiovascular dynamics for effective monitoring of the condition of the heart; a fractal dimension being capable to indicate the complexity and irregularity of heart beats from the said ECG skin patch profile, preferably wherein said fractal dimension is capable of identifying the intermittent cluster of PQRST arising during the sudden cardiac arrest.
Lee teaches that it is known to use a nonlinear discrete dynamical system theory (ND-DST) capable of quantifying the underlying cardiovascular dynamics for effective monitoring of the condition of the heart as set forth in Column 1 lines 9-40 and a fractal dimension being capable to indicate the complexity and irregularity of heart beats from the said ECG skin patch profile, preferably wherein said fractal dimension is capable of identifying the intermittent cluster of PQRST arising during the sudden cardiac arrest as set forth in Column 3 lines 34- Column 4 line 12 to provide improved robustness such as because of variations in positioning. It would have been obvious before the effective filing date of the claimed invention to one having ordinary skill in the art to modify the system as taught by Trapero Martin et al, with a nonlinear discrete dynamical system theory (ND-DST) capable of quantifying the underlying cardiovascular dynamics for effective monitoring of the condition of the heart; and a fractal dimension being capable to indicate the complexity and irregularity of heart beats from the said ECG skin patch profile, preferably wherein said fractal dimension is capable of identifying the intermittent cluster of PQRST arising during the sudden cardiac arrest as taught by Lee, since such a modification would provide the predictable results of improved robustness such as because of variations in positioning.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Bardy et al (US Publication 2019/0231210) teaches a wearable cardiac diagnostic device which uses a CNN to learn features during a training process and uses R-wave peaks.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to William J Levicky whose telephone number is (571)270-3983. The examiner can normally be reached Monday-Thursday 8AM-5PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, David Hamaoui can be reached at (571)270-5625. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/William J Levicky/Primary Examiner, Art Unit 3796
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