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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/25/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 and 12 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 measurement point" in line 6. There is insufficient antecedent basis for this limitation in the claim.
Claim 12 recites the limitation "the anthropometric data" in line 12. There is insufficient antecedent basis for this limitation in the claim.
Claim 12 recites the limitation "based on bio-electrical impedance data of the body” in lines 11 and 12. It is unclear if the limitation is related to the limitation “configured to measure bio-electrical impedance data of the body” in lines 5 and 6. If the limitations are related, then the limitations at lines 11 and 12 should read “"based on the bio-electrical impedance data of the body.”
Claims 1 and 12 recite the limitation “in a body section in an abdominal region” in line 2, the limitation "into a body in an abdominal region" in line 3, the limitation “in a body section of the body” in line 6, the limitation “in the body section in the abdominal region” in line 9, and the limitation “in the body section” in line 10. It is unclear whether the limitations reference the same area of the body. For example, while radiation is emitted into a body in an abdominal region, the step to “determining the ASFA in a body section of the body” appears to include sections of the body not inclusive to the abdomen which does not corresponds to the measurement point at the abdominal region. Similarly, the step to “determining total fat are (TFA) in the body section in the abdominal region” appear to include a section of the body which is potentially outside of the region where the ASFA is determined. Finally, the AVFA is calculated in the body section without reference to the abdominal region.
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, 9, 10, and 12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claims 1 and 12 recite “calculating the AVFA in the body section from the determined TFA and the ASFA” wherein claim 10 provides an equation for determining the AVFA; thus, involving mathematical concept grouping which is an abstract idea. Claim 9 recites a formula for determining the TFA which is an abstract idea. This judicial exception is not integrated into a practical application because it is merely an implementation method of an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite only names of formulas and their corresponding variables for usage.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 7, 8, 12, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Chernokalov et al. (Pub. No.: US 2016/0143558, Applicant’s IDS filed 02/25/2025) in view of Valsan et al. (Pub. No.: US 20230065288) and further in view of Kasahara et al. (Pub. No.: US 2009/0093732).
Consider claim 1, Chernokalov discloses a method for determining an abdominal visceral fat area (AVFA) and an abdominal subcutaneous fat area (ASFA) in a body section in an abdominal region (paragraph [0187], subcutaneous fat measured by sensor and visceral fat can be estimated based on subtraction of subcutaneous fat amount from total body fat amount where visceral fat accumulates around the internal organs on the abdominal muscles, see paragraph [0006]), comprising:
using a device (Fig. 2B, smartphone) with ultra-wide band (UWB) radar (paragraph [0090], Fig. 2B, smartphone with an integrated UWB sensing module 220), emitting radiation into a body (paragraph [0092], Figs. 2A, 2B, transmitter block 224 generates microwave signals transmitted into the body 101) and measuring parameters of reflected radiation (paragraph [0093], Fig. 2A, CPU 221 receives parameters of the reflected signal and calculates structures of the body 101 tissues);
based on the measured parameters of the reflected radiation obtained by the UWB radar, determining the ASFA in the body section of the body corresponding to the measurement point (paragraph [0187], subcutaneous fat may be measured directly by sensor and displayed);
acquiring anthropometric data (paragraph [0187], acquiring weight and height);
based on the anthropometric data, determining total fat area (TFA) in the body (paragraph [0187], total body fat amount may be measured by common methods based on weight and height);
calculating the AVFA in the body section from the determined TFA and the ASFA (paragraph [0187], visceral fat can be estimated based on subtraction of subcutaneous fat amount from total body fat amount).
Chernokalov does not specifically discloses emitting radiation into a body in the abdominal region.
Valsan discloses emitting radiation into a body in the abdominal region (paragraph [0070], [0071], Figs. 10, 11, 12, using a depth sensor 36 (see paragraph [0067], Fig. 3) to capture images of user's torso only in order to track visceral and/or subcutaneous fat in the torso).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the emission of radiation into a body as disclosed by Chernokalov to include the emission of radiation into a body in the abdominal region as taught by Valsan to track visceral and/or subcutaneous fat in the torso (Valsan, paragraph [0070]).
The combination of Chernokalov and Valsan does not specifically disclose acquiring anthropometric data and bio-electrical impedance data of the body;
based on the bio-electrical impedance data of the body and the anthropometric data, determining total fat area (TFA) in the body section in the abdominal region.
Kasahara discloses acquiring anthropometric data (paragraph [0038], acquiring height, weight, age, sex, BMI (body mass index)) and bio-electrical impedance data of the body (paragraph [0038], bioelectrical impedance of the abdomen);
based on the bio-electrical impedance data of the body and the anthropometric data, determining total fat area (TFA) in the body section in the abdominal region (paragraph [0038], height, weight, age, sex, BMI (body mass index) may be used in conjunction with the bioelectrical impedance for calculating the body composition indexes X, wherein body composition indexes X includes total fat area of the abdomen).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to replace the method as disclosed by the combination of Chernokalov and Valsan with the method to include acquiring bio-electrical impedance data as taught by Kasahara to provide a correlation between the bioelectrical impedance of the abdomen, height, weight, age, sex, and BMI (body mass index) and measured values of the body composition index (Kasahara, paragraph [0038]).
Consider claim 12, Chernokalov discloses a system configured to determine an abdominal subcutaneous fat area (ASFA) and an abdominal visceral fat area (AVFA) (paragraph [0187], subcutaneous fat measured by sensor and visceral fat can be estimated based on subtraction of subcutaneous fat amount from total body fat amount where visceral fat accumulates around the internal organs on the abdominal muscles, see paragraph [0006]), comprising:
a device (Fig. 2B, smartphone) comprising ultra wide-band (UWB) radar circuitry (paragraph [0090], Fig. 2B, smartphone with an integrated UWB sensing module 220), configured to emit radiation into a body (paragraph [0092], Figs. 2A, 2B, transmitter block 224 generates microwave signals transmitted into the body 101) and measure parameters of reflected radiation (paragraph [0093], Fig. 2A, CPU 221 receives parameters of the reflected signal and calculates structures of the body 101 tissues);
a processing unit comprising at least one processor (paragraph [0093], Fig. 2A, CPU 221), comprising processing circuitry, individually and/or collectively, configured to:
determine the ASFA in a body section of the body based on the measured parameters of the reflected radiation obtained by the UWB radar (paragraph [0187], subcutaneous fat may be measured directly by sensor and displayed);
determine total fat area (TFA) in the body section based on the anthropometric data (paragraph [0187], total body fat amount may be measured by common methods based on weight and height), and
calculate the AVFA in the body section from the determined TFA and the ASFA (paragraph [0187], visceral fat can be estimated based on subtraction of subcutaneous fat amount from total body fat amount).
Chernokalov does not specifically discloses emitting radiation into a body in the abdominal region.
Valsan discloses emitting radiation into a body in the abdominal region (paragraph [0070], [0071], Figs. 10, 11, 12, using a depth sensor 36 (see paragraph [0067], Fig. 3) to capture images of user's torso only in order to track visceral and/or subcutaneous fat in the torso).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the emission of radiation into a body as disclosed by Chernokalov to include the emission of radiation into a body in the abdominal region as taught by Valsan to track visceral and/or subcutaneous fat in the torso (Valsan, paragraph [0070]).
The combination of Chernokalov and Valsan does not specifically disclose a bio-electrical impedance analysis device comprising circuitry configured to measure bio-electrical impedance data of the body;
determine total fat area (TFA) in the body section in the abdominal region based on bio- electrical impedance data of the body and the anthropometric data.
Kasahara discloses a bio-electrical impedance analysis device (paragraph [0023], Fig. 1, body composition determining apparatus 100) comprising circuitry configured to measure bio-electrical impedance data of the body (paragraph [0023], Fig. 1, body composition determining apparatus 100 is a device for measuring bioelectrical impedance of the abdomen of a human subject);
determine total fat area (TFA) in the body section in the abdominal region based on bio- electrical impedance data of the body and the anthropometric data (paragraph [0038], height, weight, age, sex, BMI (body mass index) may be used in conjunction with the bioelectrical impedance for calculating the body composition indexes X, wherein body composition indexes X includes total fat area of the abdomen).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to replace the system as disclosed by the combination of Chernokalov and Valsan with the system including a bio-electrical impedance analysis device as taught by Kasahara to provide a correlation between the bioelectrical impedance of the abdomen, height, weight, age, sex, and BMI (body mass index) and measured values of the body composition index (Kasahara, paragraph [0038]).
Consider claim 7, the combination of Chernokalov, Valsan, and Kasahara discloses wherein the measured parameters of reflected radiation include amplitude and/or phase of a signal (paragraph [0153], receiver block 225 detects amplitude and phase frequency characteristics of the reflected signal).
Consider claim 8, the combination of Chernokalov and Kasahara does not specifically disclose wherein the measured parameters of the reflected radiation are processed by a neural network trained on a dataset corresponding to a reference sample of people and including values of the thickness of the abdominal subcutaneous fat and ASFA, obtained using a reference method and respective values of the measured parameters of reflected radiation.
Valsan discloses wherein the measured parameters of the reflected radiation are processed by a neural network (paragraph [0063], body composition analysis circuitry 58 uses an autoencoder (e.g., an artificial neural network, see paragraph [0052])) trained on a dataset corresponding to a reference sample of people (paragraph [0062], body composition analysis circuitry 58 stores a model that is trained using data collected from a group of participants) and including values of the thickness of the abdominal subcutaneous fat and ASFA (paragraphs [0059], use a three-compartment model and estimate an amount of subcutaneous fat located in a user's torso), obtained using a reference method (paragraph [0062], body composition measured using magnetic resonance imaging) and respective values of the measured parameters of reflected radiation (paragraph [0067], body image data 60 captured using a depth sensor 36 may include an array of data points representing the depth to different locations across the user's body).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the device as disclosed by the combination of Chernokalov and Kasahara with the device including a neural network as taught by Valsan to compensate for effects of breathing and body pose by using the identity latent space only to output an estimated body composition of the subject (Valsan, paragraph [0063]).
Consider claim 15, the combination of Chernokalov, Valsan, and Kasahara discloses a non-transitory computer-readable medium that stores instructions causing at least one processor, individually and/or collectively to perform operations of the method of claim 1 when executed (paragraph [0193], computer readable storage medium).
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Chernokalov, Valsan, and Kasahara in view of Raskin (Pub. No.: US 2014/0121564).
Consider claim 2, the combination of Chernokalov, Valsan, and Kasahara does not specifically disclose wherein determining the ASFA comprises:
comparing the measured parameters of the reflected radiation with specified threshold values corresponding to a specified thickness of abdominal subcutaneous fat, and
based on the comparison, obtaining data on the thickness of the abdominal subcutaneous fat at the measurement point and data on the ASFA in the body section corresponding to the measurement point.
Raskin discloses wherein determining the ASFA comprises: comparing the measured parameters of the reflected radiation with specified threshold values corresponding to a specified thickness of abdominal subcutaneous fat (paragraph [0039], frequency-domain impulse response of the user may be compared with frequency-domain template impulse responses of template users, wherein frequency-domain power spectral density data of the impulse response may be matched to template frequency-domain power spectral density data of a template user of known body fat value within the frequency band of subcutaneous fat, see paragraph [0036]), and
based on the comparison, obtaining data on the thickness of the abdominal subcutaneous fat at the measurement point and data on the ASFA in the body section corresponding to the measurement point (paragraph [0036], the amplitude of a particular frequency in a frequency-domain plot of the impulse response of the body at some time after the impact may be correlated with a mass, volume, or density of the subcutaneous fat portion of the body).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to replace the determining of the ASFA as disclosed by the combination of Chernokalov, Valsan, and Kasahara with the determining of the ASFA as taught by Raskin to account for any one or more of age, gender, medical history, medication, diet, diet plan, recent food or water consumption, exercise regimen, average activity level, physical body dimension, physical condition, and/or body weight of the user and template user (Raskin, paragraph [0039]).
Claims 3, 4, and 11 are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Chernokalov, Valsan, Kasahara, and Raskin in view of Li et al. (Pub. No.: US 2024/0395408).
Consider claim 3, the combination of Chernokalov, Valsan, Kasahara, and Raskin disclose wherein the specified threshold values are determined based on a plurality of measurements taken on a reference sample of people (Raskin, paragraph [0039], template impulse response in a library of template impulse responses of template users),
The combination of Chernokalov, Valsan, Kasahara, and Raskin does not specifically disclose wherein to match the specified threshold values, the thickness of the abdominal subcutaneous fat and the ASFA are determined by a reference method.
Li discloses wherein to match the specified threshold values, the thickness of the abdominal subcutaneous fat and the ASFA are determined by a reference method (paragraph [0048], area of the region of the subcutaneous fat is calculated according to the CT HU values. Specifically, the area between boundary 1 and boundary 2 is the location of subcutaneous fat, wherein the HU value, which is a CT value, is a measurement unit to measure the density of a local tissue or organ in a human body, see paragraph [0038]).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to replace the specified threshold as disclosed by the combination of Chernokalov, Valsan, Kasahara, and Raskin with the specified threshold as taught by Li to extract the subcutaneous adipose tissue region SAT (Li, paragraph [0048]).
Consider claim 4, the combination of Chernokalov, Valsan, Kasahara, and Raskin does average not specifically disclose determining a specified threshold value to which each of the measured parameters of the reflected radiation is closer among the specified threshold values, and determining a respective thickness value of the abdominal subcutaneous fat.
Li discloses determining a specified threshold value to which each of the measured parameters of the reflected radiation is closer among the specified threshold values, and determining a respective thickness value of the abdominal subcutaneous fat (paragraph [0048], According to the HU value range of the adipose tissue, a threshold is set to extract the subcutaneous adipose tissue region SAT).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to replace the specified threshold as disclosed by the combination of Chernokalov, Valsan, Kasahara, and Raskin with the specified threshold as taught by Li to calculate the total fat area (paragraph [0048]).
Consider claim 11, the combination of Chernokalov, Valsan, Kasahara, Raskin, and Li discloses wherein the reference method is selected from magnetic resonance imaging and computer-assisted tomography (Li, paragraph [0048], area of the region of the subcutaneous fat is calculated according to the CT (Computed Tomography) HU values).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Chernokalov, Valsan, Kasahara, Raskin, and Li in view of Payne (Pub. No.: US 2013/0281820).
Consider claim 5, the combination of Chernokalov, Valsan, Kasahara, Raskin, and Li does not specifically disclose wherein based on multiple measurements, the thickness value of the abdominal subcutaneous fat is determined by averaging all obtained thickness values of the abdominal subcutaneous fat based on the measured parameters of the reflected radiation.
Payne discloses wherein based on multiple measurements, the thickness value of the abdominal subcutaneous fat is determined by averaging all obtained thickness values of the abdominal subcutaneous fat based on the measured parameters of the reflected radiation (paragraph [0050], composition of the subcutaneous region is calculated from the average of the values between the left and right subcutaneous regions 110 shown in FIG. 8).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the determining of ASFA as disclosed by the combination of Chernokalov, Valsan, Kasahara, Raskin, and Li to include the calculation of the subcutaneous region as taught by Payne to provide for a subcutaneous fat fraction (Payne, paragraph [0050]).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Chernokalov, Valsan, Kasahara, Raskin, and Li in view of Choi et al. (Pub. No.: US 2016/0249857).
Consider claim 6, the combination of Chernokalov, Valsan, Kasahara, Raskin, and Li does not specifically disclose wherein based on multiple measurements, the thickness value of the abdominal subcutaneous fat is determined by determining the thickness value of the abdominal subcutaneous fat occurring more often than other values based on the measured parameters of the reflected radiation, and discarding the other values.
Choi wherein based on multiple measurements, the thickness value of the abdominal subcutaneous fat is determined by determining the thickness value of the abdominal subcutaneous fat occurring more often than other values based on the measured parameters of the reflected radiation, and discarding the other values (paragraph [0151], comparing a subcutaneous fat thickness of the plurality of detected body fat measurement information with a body part-specific subcutaneous fat thickness standard range among the plurality of pre-stored body part-specific body fat-based standard ranges and selecting at least one second measurement body part having the detected subcutaneous fat thickness).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the determining of ASFA as disclosed by the combination of Chernokalov, Valsan, Kasahara, Raskin, and Li to include the subcutaneous fat thickness determination as taught by Choi to determine a subcutaneous fat thickness which corresponds to the pre-stored body part-specific subcutaneous fat thickness standard range (Choi, paragraph [0151]).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Chernokalov, Valsan, and Kasahara in view of Jung et al. (Pub. No.: EP 3505050).
Consider claim 9, the combination of Chernokalov, Valsan, and Kasahara does not specifically disclose wherein the TFA in the body section in the abdominal region is determined by the equation:
TFA= α ∙ BII + β ∙ W + γ ∙ G + δ ∙ E,
where, BII is a body impedance index of the body, W is a weight, G is a gender, E is an age, α, β, γ, δ are coefficients, wherein:
BII = H2/Zbody, where H is a height, and Zbody is the bio-electrical impedance value.
Jung discloses wherein the TFA in the body section in the abdominal region is determined by the equation of claimed invention (paragraphs [0118] to [0119], calculation of body fat according to Equation 1 to include the abdomen, see paragraph [0058], Fig. 4A).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to replace the processor as disclosed by the combination of Chernokalov, Valsan, and Kasahara with the processor as taught by Jung to analyze body composition based on user information including the converted impedance, sex, age, height, and weight (Jung, paragraph [0118]).
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Chernokalov, Valsan, and Kasahara in view of Choi et al. (Pub. No.: US 2016/0249857).
Consider claim 14, the combination of Chernokalov, Valsan, and Kasahara discloses wherein the device (Fig. 2A, device 210) including the UWB radar circuitry (paragraph [0090], Fig. 2B, device 210 with an integrated UWB sensing module 220) is implemented in a smartphone (paragraph [0090], FIG. 2B illustrates the device 210 - a smartphone which includes the sensing module (sensor) 220).
The combination of Chernokalov, Valsan, and Kasahara does not specifically disclose wherein the device including the UWB radar circuitry and the bio-electrical impedance analysis device are implemented in a single device, comprising a smartphone.
Choi discloses wherein the device (paragraph [0065], Fig. 2, electronic device 200) including the UWB radar circuitry (paragraph [0092], Fig. 5, subcutaneous fat measurement module 504 may apply an RF signal having a frequency of about 0.1 to 200 GHz (inclusive to the range of 3.1 GHz to 10.6 GHz defined for UWB as known in the art) and the bio-electrical impedance analysis device (paragraph [0090], Fig. 5, body resistance measurement module 502 may detect an impedance value) are implemented in a single device, comprising a smartphone (paragraph [0045], Figs. 2, 5, electronic device 200 includes a smart phone wherein the partial body fat measurement unit 220 may include a body resistance measurement module 502 and a subcutaneous fat measurement module 504, see paragraph [0089]).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the smartphone as disclosed by the combination of Chernokalov, Valsan, and Kasahara to include the body resistance measurement module as taught by Choi to analyze a partial body composition of the corresponding measurement body part by using the impedance value (Choi, paragraph [0090]).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Chernokalov, Valsan, and Kasahara in view of Li et al. (Pub. No.: US 2024/0395408) and Garff et al. (Pub. No.: US 2022/0117509).
Consider claim 10, the combination of Chernokalov and Kasahara discloses wherein the AVFA is determined by the equation:
AVFA = TFA – ASFA (paragraph [0187], visceral fat can be estimated based on subtraction of subcutaneous fat amount from total body fat amount).
The combination of Chernokalov and Kasahara does not specifically disclose:
a neural network trained on a dataset corresponding to a reference sample of people and including the ASFA and the TFA in the abdominal region, obtained from the measured parameters of the reflected radiation, and the anthropometric data, and the AVFA, determined by a reference.
Valsan discloses a neural network (paragraph [0063], body composition analysis circuitry 58 uses an autoencoder (e.g., an artificial neural network, see paragraph [0052])) trained on a dataset corresponding to a reference sample of people (paragraph [0062], body composition analysis circuitry 58 stores a model that is trained using data collected from a group of participants) and including the ASFA and the TFA in the abdominal region (paragraph [0059], use a three-compartment model and estimate an amount of visceral fat and subcutaneous fat (hence, total body fat) located in a user's torso), obtained from the measured parameters of the reflected radiation (paragraph [0067], body image data 60 captured using a depth sensor 36 may include an array of data points representing the depth to different locations across the user's body), and the anthropometric data (paragraph [0062], anthropometric measurements), and the AVFA (paragraph [0059], estimate an amount of visceral fat located in a user's torso), determined by a reference method (paragraph [0062], body composition measured using magnetic resonance imaging).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the device as disclosed by the combination of Chernokalov and Kasahara with the device including a neural network as taught by Valsan to compensate for effects of breathing and body pose by using the identity latent space only to output an estimated body composition of the subject (Valsan, paragraph [0063]).
The combination of Chernokalov, Kasahara, and Valsan does not specifically disclose where υ and θ are coefficients determined by a neural network.
Li discloses clinical information to include abdominal fat is established clinical feature of a neural network (paragraph [0036]) and a total fat area SAT = SVAT + SSAT is calculated (Hence, where SVAT = SAT - SSAT) (paragraphs [0048], [0051]).
Li further discloses where υ and θ are coefficients determined by a neural network (paragraph [0064], parameters of network structure and model are set based on a grid search method to include regularization coefficient γ1 and γ2).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to replace the device as disclosed by the combination of Chernokalov, Kasahara, and Valsan with the device as taught by Li to use the training set and verification set of the neural network (Li, paragraph [0064]).
The combination of Chernokalov, Kasahara, Valsan, and Li does not specifically disclose the neural network including bio-electrical impedance data.
Garff discloses the neural network including bio-electrical impedance data (paragraph [0085], [0087], artificial intelligence/machine learning algorithms 128 (to include neural networks, see paragraph [0088]) processes the measured signals from specific locations on the patient 124 against a database 116 of signals to include patient bio-electrical impedance metrics).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to replace the device as disclosed by the combination of Chernokalov, Kasahara, Valsan, and Li with the device as taught by Garff to provide higher confidence diagnostic scoring (Garff, paragraph [0087]).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over the combination of Chernokalov, Valsan, and Kasahara in view of Panneer (Pub. No.: US 2020/0367816).
Consider claim 13, the combination of Chernokalov, Valsan, and Kasahara wherein the device including the UWB radar circuitry includes a smartphone (Fig. 2B, smartphone) with embedded UWB radar (paragraph [0090], Fig. 2B, smartphone with an integrated UWB sensing module 220).
The combination of Chernokalov, Valsan, and Kasahara does not specifically disclose the bio-electrical impedance analysis device includes a smart watch capable of measuring bio-electrical impedance of the body.
Panneer discloses the bio-electrical impedance analysis device includes a smart watch capable of measuring bio-electrical impedance of the body (paragraph [0074], [0183], bioelectrical impedance analysis (BIA) may be performed by the smartwatch).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to replace the bio-electrical impedance analysis device as disclosed by the combination of Chernokalov, Valsan, and Kasahara with the smartwatch as taught by Panneer in order to perform alert generation (Panneer, paragraph [0074]).
Conclusion
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/Gerald Johnson/
Primary Examiner, Art Unit 3797