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 Amendment
In response to amendments, filed August 18, 2025, claims 1, 3-6, and 9 have been amended. No claims have been cancelled or added. Claims 1-11 are pending.
Response to Arguments
Applicant’s arguments, see Remarks, filed August 18, 2025, with respect to the specification objection have been fully considered and are persuasive in view of the amendments. The objection to the specification has been withdrawn.
Applicant’s arguments with respect to the prior art claim(s) have been considered but are moot because the new ground of rejection does not rely on the same reference combination applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. A new ground(s) of rejection is made in view of the combinations of Rogers (US 20180165566 A1), Carter (US 20170181649 A1), Park (US 20170095171 A1), Ouzir (DOI: 10.1109/ULTSYM.2017.8092152), Connor (US 20190030230 A1), Zhou (US 20200085327 A1), and Kang (US 20190104997 A1). Any arguments still relevant based on the new grounds of rejection are addressed below.
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., multi-wavelength composite light; simultaneously processing MWPPG signals and accelerometer signals in models in parallel) 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). As the claims are currently written, “a multi-wavelength photoplethysmogram (MWPPG) sensor for detecting multi-wavelength photoplethysmogram (MWPPG) signals” may provide multiple wavelengths in a variety of ways, including using multiple light sources each emitting a different wavelength of light, or using a single light source emitting composite light with different wavelengths.
Regarding applicant’s arguments that Carter is silent on inputting MWPPG and accelerometry signals into blood pressure prediction model and physiological mathematical models to obtain an initial central tonoarteriogram signal and then processing multiple initial central tonoarteriogram signals to obtain a target central tonoarteriogram, Examiner respectfully disagrees. Carter describes a blood pressure prediction model in [0046] by modeling with machine learning to determine blood pressure based off of MWPPG and accelerometry as inputs. In [0058], Carter describes using a physiological mathematical model of a human pulse waveform and motion data to perform filtering of individual beats as part of the process of determining blood pressure. As described in [0082], the relationships between additional features and/or biometric features and known blood pressures in the iterative machine learning process allows for a predictive model for blood pressure, obtaining a target central tonoarteriogram.
In response to applicant's argument that Connor is nonanalogous art, it has been held that a prior art reference must either be in the field of the inventor’s endeavor or, if not, then be reasonably pertinent to the particular problem with which the inventor was concerned, in order to be relied upon as a basis for rejection of the claimed invention. See In re Oetiker, 977 F.2d 1443, 24 USPQ2d 1443 (Fed. Cir. 1992). In this case, like the present invention, Conner teaches a system for continuously collecting data on a biometric parameter concerning a person's body in real time.
In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
In response to applicant's argument that the examiner has combined an excessive number of references, reliance on a large number of references in a rejection does not, without more, weigh against the obviousness of the claimed invention. See In re Gorman, 933 F.2d 982, 18 USPQ2d 1885 (Fed. Cir. 1991).
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“processing module” in claim 1-5, 8, and 10 -- [0055] “the processing module is integrated on the chip as shown in FIG 8;” [0058] “when the wireless communication module is integrated on the chip and the processing module is separate and independent from the chip as shown in FIG. 9. The blood pressure prediction model and the physiological mathematical module are designed on an external display device, such as a cell phone”
“wireless communication module” in claim 10 – [0058] “the wireless communication module is integrated on the chip”
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2, 4, 6, 8, and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rogers (US 20180165566 A1) in view of Carter (US 20170181649 A1).
Regarding claim 1, Rogers teaches a nail sensing based, wireless multi-modal tonoarteriogram (TAG) monitoring apparatus (Fig. 10),
comprising a nail patch, a plurality of sensors and a processing module; wherein at least one first sensor of the plurality of sensors is arranged on the nail patch, with the plurality of sensors being used for obtaining a biological signal at fingernail ([0180] “The fingernail-mounted or tissue-mounted devices optionally provide additional bio-sensing modalities;” [0029] “the electronic device comprises one or more sensors or a component thereof, for example, sensors selected from the group consisting of an optical sensor, an electrochemical sensor, a chemical sensor, a mechanical sensor, a pressure sensor, an electrical sensor, a magnetic sensor, a strain sensor, a temperature sensor, a heat sensor, a humidity sensor, a motion sensor (e.g., accelerometer, gyroscope), ...” [0069] “FIG. 10 provides images and experimental results characterizing a fingernail mounted silicon CMOS device.”). However, Rogers fails to explicitly disclose a multi-wavelength photophethysmogram (MWPPG) or using MWPPG in combination with accelerometry signals to determine blood pressure.
Carter teaches systems and methods for determining a blood pressure of a subject from a photoplethysmogram and accelerometry. Carter discloses:
wherein the plurality of sensors comprise at least a multi-wavelength photoplethysmogram (MWPPG) sensor for detecting multi-wavelength photoplethysmogram (MWPPG) signals ([0051] “Light sensor 202 is positioned adjacent LEDs 201a, 201b so as to be able to capture light (i.e., both red light and infrared waves) that is emitted by LEDs 201a, 201b and reflected from the wearer's body. … Accordingly, the present invention extends to wearable sensor devices that include one or more LEDs and one or more light sensors for sensing light that is either transmitted through or reflected by the wearer's skin. Light sensor 202 acquires a raw PPG representing the intensity of light that it receives over time. A PPG can be generated for each of LEDs 201a, 201b”), and an accelerometer sensor for detecting an accelerometer signal ([0052] “The motion sensor 203 can comprise one or more accelerometers or other suitable component to acquire raw motion data.”);
wherein the processing module comprises a blood pressure prediction model and a physiological mathematical model; each of the blood pressure prediction model and the physiological mathematical model is adapted to process both of the detected MWPPG signals and the accelerometer signal to obtain a respective initial central tonoarteriogram signal (Fig. 4, a red light emitting diode (LED) 201a and an infrared (IR) LED 201b; [0038] “While the methods and systems can comprise any suitable component or step, in some cases, they can include collecting raw photoplethysmogram (PPG) and accelerometer data, processing the raw data with a biometric engine configured to perform signal processing to generate scaled beats and biometric features, processing the scaled beats and biometric features with a blood pressure engine configure to perform beat shape analysis, measure additional shape features, and model with machine learning to determine blood pressure.” [0046] “In some embodiments of the described methods and systems for determining blood pressure with beat shape analysis, the methods comprise one or more steps to acquire raw data (e.g., raw PPG data and/or raw motion data) and/or one or more steps to process the raw data to determine blood pressure. While these methods and systems can comprise any suitable step, suitable process, suitable component or characteristic, FIG. 2 illustrates, that at least in some embodiments, they can comprise a method 100 configured to acquire raw data and/or to process raw data to determine blood pressure. In some embodiments, method 100 comprises one or more of providing a wearable device 104, collecting raw data 108, identifying individual beats 112, filtering individual beats 116, measuring biometric features 120, scaling individual beats 124, analyzing beat shape 128, measuring additional shape features 132, modeling with machine learning to determine blood pressure 136, and correlating blood pressure with hypotension, hypertension, and/or normotension 140.” [0058] “This filtering can be performed by using a model of a human pulse waveform and/or motion data collected by the motion sensor 203. In some embodiments, filtering of individual beats can be performed using a model of a human pulse waveform that is matched to individual beats. Those individual beats that are not similar to the model can be filtered out. Any suitable statistical processes can be used to match the individual beats to the model and to determine which individual beats can be excluded.” [0082]);
the multiple initial central tonoarteriogram signals obtained from the blood pressure prediction model and the physiological mathematical model are processed to obtain a target physiological parameter comprising a target central tonoarteriogram signal ([0082] “modeling with machine learning to determine blood pressure 136 comprises using machine learning with one or more biometric features 36 and/or one or more additional shape features 44 and/or ground truth blood pressure data to develop a predictive model for blood pressure.” [0075] “The known blood pressures (e.g., ground truth blood pressure data) can be collected with conventional inflatable cuff devices at the same time as the raw data is collected. The strength of the linear relationship established between the additional features and/or biometric features and known blood pressures can be measured by a Pearson correlation coefficient (denoted by k). In other embodiments, the relationships between these additional features and/or biometric features and known blood pressures can be used to determine cardiovascular values such as blood pressure. For example, FIGS. 10-24 show relationships between some additional features and biometric features and known blood pressures.” Table 3).
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 modified the apparatus of Rogers to include MWPPG and determining blood pressure using MWPPG and accelerometry as disclosed in Carter to accurately and continuously measure blood pressure based on biometric features that do not involve a cumbersome inflatable cuff (Carter [0004, 0043]).
Regarding claim 2, the combination of Rogers/Carter discloses the nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus according to claim 1, further comprising a chip, wherein the processing module is optionally integrated at the chip (Rogers: [0069] “FIG. 10 provides images and experimental results characterizing a fingernail mounted silicon CMOS device.” [0054] “communicating a signal indicative of the digital content from the tissue mounted electronic system to an external device;” [0051] “the external device may be a computer, a phone”).
Regarding claim 4, the combination of Rogers/Carter teaches the nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus according to claim 1, the blood pressure prediction model is pre-trained by taking the MWPPG signals and the accelerometer signal as samples and referencing a central tonoarteriogram signal as a label (Carter: [0038] “collecting raw photoplethysmogram (PPG) and accelerometer data, processing the raw data with a biometric engine configured to perform signal processing to generate scaled beats and biometric features, processing the scaled beats and biometric features with a blood pressure engine configure to perform beat shape analysis, measure additional shape features, and model with machine learning to determine blood pressure;” [0082] “modeling with machine learning to determine blood pressure 136 comprises using machine learning with one or more biometric features 36 and/or one or more additional shape features 44 and/or ground truth blood pressure data to develop a predictive model for blood pressure.” [0075] “The known blood pressures (e.g., ground truth blood pressure data) can be collected with conventional inflatable cuff devices at the same time as the raw data is collected. The strength of the linear relationship established between the additional features and/or biometric features and known blood pressures can be measured by a Pearson correlation coefficient (denoted by k). In other embodiments, the relationships between these additional features and/or biometric features and known blood pressures can be used to determine cardiovascular values such as blood pressure. For example, FIGS. 10-24 show relationships between some additional features and biometric features and known blood pressures.” Table 3).
Regarding claim 6, the combination of Rogers/Carter discloses the nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus according to claim 1, wherein the biological signal further comprises at least a pressure signal; the plurality of sensors further comprise a pressure sensor for obtaining the pressure signal (Rogers: [0029] “the electronic device comprises one or more sensors or a component thereof, for example, sensors selected from the group consisting of an optical sensor, … a pressure sensor;” Fig. 31).
Regarding claim 8, the combination of Rogers/Carter discloses the nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus according to claim 1, wherein the nail patch comprises a substrate layer and a protective layer layered in sequence; the substrate layer is adhered onto a nail and the substrate layer is made of a transparent material (Rogers: [0024] "The invention includes substrates having functionality as an electrical insulator, an optically transparent layer, an optical filter and/or a mechanically supporting layer"; Fig. 1B); the first sensor is arranged on the substrate layer, the processing module is optionally arranged on the substrate layer; the protective layer is made of a waterproof material (Rogers: [0029] “the electronic device comprises one or more sensors;” [0069] “FIG. 10 provides images and experimental results characterizing a fingernail mounted silicon CMOS device.” [0017] "In some embodiments, the present systems are waterproof, for example, by encapsulation or packaging, with a biopolymer, a thermoset polymer, a rubber, an adhesive tape, plastic or any combination of these. For example, in embodiments, the system comprises an encapsulation layer or other waterproofing structure comprising polyimide, conformal Q, vinyl, acrylic, polydimethylsiloxane (PDMS), polyurethane, vinyl, polystyrene, polymethyl methacrylate (PMMA) or polycarbonate.").
Regarding claim 10, the combination of Rogers/Carter discloses the nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus according to claim 1, further comprising a wireless communication module, the wireless communication module being arranged on the nail patch, wherein when the processing module is arranged on the nail patch, the wireless communication module is used for transmitting the biological signal to the processing module, and the wireless communication module is used for outputting the physiological parameter obtained by the processing module (Rogers: [0032] “In embodiments, the electronic device comprises one or more communication systems or a component thereof, for example, communication systems or components thereof selected from the group consisting of a transmitter, a receiver, a transceiver, an antenna, and a near field communication device.” [0069] “FIG. 10 provides images and experimental results characterizing a fingernail mounted silicon CMOS device.”); wherein when the processing module is arranged to separate from the nail patch, the wireless communication module is used for transmitting the biological signal to the processing module (Rogers: [0054] “communicating a signal indicative of the digital content from the tissue mounted electronic system to an external device;” [0051] “the external device may be a computer, a phone”).
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rogers (US 20180165566 A1) in view of Carter (US 20170181649 A1) and Park (US 20170095171 A1).
Regarding claim 3, the combination of Rogers/Carter discloses the nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus according to claim 1, wherein the processing module (Rogers: [0069] “CMOS device;” [0180] “The fingernail-mounted or tissue-mounted devices optionally provide additional bio-sensing modalities;” Fig. 31).
However, the combination of Rogers/Carter fails to disclose channel estimation. Park teaches an apparatus and a method of measuring bioinformation and extracting cardiovascular features of a user.
Park discloses is adapted to:
perform a channel estimation against the MWPPG signals according to the multiple initial central tonoarteriogram signals to obtain a channel estimation result ([0060] “the bioinformation estimator 130 may select a reference PPG signal to be used to estimate the bioinformation from among PPG signals to be transferred through a plurality of channels, and estimate the bioinformation based on the selected reference PPG signal. For example, the bioinformation estimator 130 may select, as the reference PPG signal, a PPG signal having a best signal quality, for example, a highest signal-to-noise ratio (SNR).”);
obtain the target central tonoarteriogram signal according to the channel estimation result ([0061] “bioinformation estimator 130 may estimate, for example, an arterial stiffness, a vascular age, a blood pressure”).
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 modified the combination of Rogers/Carter to include channel estimation as disclosed in Park to obtain more accurate blood pressure estimations based on the selection of the best quality PPG signals (Park [0060]).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rogers (US 20180165566 A1) in view of Carter (US 20170181649 A1) and Park (US 20170095171 A1), and in further view of Ouzir (DOI: 10.1109/ULTSYM.2017.8092152).
Regarding claim 5, the combination of Rogers/Carter/Park discloses the nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus according to claim 3, wherein the processing module is adapted to input the channel estimation result into an aortic pressure estimation model (Rogers: [0069] “silicon CMOS device”; Park: [0061] “bioinformation estimator 130 may estimate, for example, an arterial stiffness, a vascular age, a blood pressure”). However, the combination of Rogers/Carter/Park fails to disclose model estimation based on dictionary learning.
Ouzir teaches cardiac motion estimation method based on dictionary learning. The combination of Rogers/Carter/Park/Ouzir discloses estimation model based on dictionary learning to obtain the central tonoarteriogram signal (Park: [0061] “bioinformation estimator 130 may estimate a blood pressure;” “modeling with machine learning to determine blood pressure 136 comprises using machine learning to develop a predictive model for blood pressure;” Ouzir: [Abstract] “evaluate a recently proposed cardiac motion estimation method based on dictionary learning;” Pg 3 [2] “a simulated cardiac motion field (horizontal component of the motion vectors) used in the offline dictionary learning process and the resulting atoms for the horizontal dictionary.”).
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 modified the combination of Rogers/Carter/Park to include an estimation model based on dictionary learning as disclosed because a sparsity-based regularization through trained dictionaries containing patterns of cardiac motion improves estimation accuracy compared to several state-of-the-art methods (Ouzir Pg 2 [3]).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rogers (US 20180165566 A1) in view of Carter (US 20170181649 A1), and in further view of Connor (US 20190030230 A1).
Regarding claim 7, the combination of Rogers/Carter discloses the nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus according to claim 1, wherein the target physiological parameter further comprises a heart rate, a blood oxygen saturation level, a blood glucose level (Rogers: [0011] “a measured physiological property of the tissue or subject (e.g., temperature, pH level, glucose, pulse oximetry, heart rate, respiratory rate, blood pressure, peripheral capillary oxygen saturation (SpO2)) or measured ambient property (e.g., temperature, electromagnetic radiation, etc.)”). However, the combination of Rogers/Carter fails to disclose a heart rate variability, a lactic acid value and a sleep parameter.
Connor teaches a system that collects data on a biometric parameter concerning a person's body in real time. Connor discloses a heart rate variability, a lactic acid value and a sleep parameter ([0088] “In an example, the biometric parameter which is measured and managed by this system can be selected from the group consisting of: oxygenation level, carbon dioxide level, lactate or lactic acid level, blood pressure, heart rate variability, pulsatile blood volume, pulsatile blood lag, hydration level, respiration rate, exhaled gas composition, body glucose level, troponin level, body motion or exercise level, and sleep status or stage”).
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 modified the combination of Rogers/Carter to include a heart rate variability, a lactic acid value and a sleep parameter as disclosed in Connor to assist in management of the person's cardiac rhythm and/or assist in pumping the person's blood based on the analysis of the biometric parameters in real time, which can prevent tissue degradation, can promote wound healing, and may even help to avoid amputation (Connor [0014]).
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rogers (US 20180165566 A1) in view of Carter (US 20170181649 A1), and in further view of Zhou (US 20200085327 A1).
Regarding claim 9, Rogers teaches the nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus according to claim 6. However, the combination of Rogers/Carter fails to disclose an adjustable finger ring.
Zhou teaches an expandable multi-physiological parameter monitoring ring. The combination of Rogers/Carter/Zhou discloses further comprises a finger ring adjustable in expansion size; wherein the pressure sensor is comprise a pressure sensor arranged on the finger ring (Rogers: [0180] “The fingernail-mounted or tissue-mounted devices;” [0014] “Tissue mounted systems of the invention may be provided in indirect conformal integration, wherein the system is provided on an intermediate structure provided in conformal contact with the tissue surface, such as a … jewelry (e.g., rings, bracelets, necklaces, wrist watches, piercings, etc.).” [0029] “the electronic device comprises one or more sensors or a component thereof, for example, … a pressure sensor;” Zhou: [0019] “FIG. 2 is a schematic diagram of function modules of an expandable multi-physiological parameter monitoring ring”).
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 modified the combination of Rogers/Carter to include an adjustable finger ring as disclosed in Zhou to improve the reliability of blood pressure readings while maintaining portability and comfort (Zhou [0003 0015]).
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rogers (US 20180165566 A1) in view of Carter (US 20170181649 A1), and in further view of Kang (US 20190104997 A1).
Regarding claim 11, the combination of Rogers/Carter discloses a tonoarteriogram monitoring system, comprising the nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus according to claim 1. However, the combination of Rogers/Carter fails to disclose a display screen with pressure alert information.
Kang teaches an apparatus for measuring bio-information of the object based on the pulse wave signal and the contact pressure signal. The combination of Rogers/Carter/Kang discloses and a wearable apparatus having a display screen (Kang: Fig. 9, touch screen panel 850); wherein, the wearable apparatus is used for displaying a pressure alert information at the display screen, the pressure alert information is used for indicating a strength of a target finger pressing on the display screen (Kang: [0068] “the outputter 210 may output guidance information regarding the contact pressure … when a request for measuring bio-information is received, the outputter 210 may display an area to be in contact with the second region and also display reference pressure information in a predetermined area of the touch screen panel, or when the second region is in contact with the touch screen, the outputter 210 may display information regarding an actual contact pressure along with information regarding a reference pressure to be applied (or desired to be applied) by the second region.”); the target finger being a finger wearing the nail sensing based, wireless multi-modal tonoarteriogram monitoring apparatus according to claim 1 (Rogers: Fig. 10; Kang: [0011] “region being in contact with the touch screen”).
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 modified the combination of Rogers/Carter to include a display screen with contact pressure information as disclosed in Kang to indicate whether a contact pressure between the biometric information detecting apparatus and a skin of the target object is an acceptable level (Kang [0012]).
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOLLY HALPRIN whose telephone number is (703)756-1520. The examiner can normally be reached 12PM-8PM ET.
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/M.H./Examiner, Art Unit 3791
/DEVIN B HENSON/Primary Examiner, Art Unit 3791