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 .
Information Disclosure Statement
The Information Disclosure Statement (IDS) filed 02/26/2024 has been considered by the Examiner.
Response to Arguments
Rejections under 35 USC 112
The amended claims dated 04/03/2026 have overcome the rejections under 35 USC 112 as previously presented in the Office Action dated 01/14/2026. The rejections of the claims under 35 USC 112 have hereby been withdrawn.
Rejections under 35 USC 101
Applicant's arguments filed 04/03/2026 have been fully considered but they are not persuasive.
Applicant argues that the amended claims move beyond the judicial exception and are therefore directed to statutory subject matter. Applicant argues that the amended limitations of the claimed method being explicitly performed by a computer including a processor and a non-transitory memory device and the measurement data being acquired by acceleration sensors operatively coupled with the computer overcomes the rejection of the claimed invention under 35 USC 101 as being directed to non-statutory subject matter.
Examiner respectfully disagrees and argues that the amended claims do not amount to more than mere instructions to implement the abstract idea using a computer. MPEP 2106.05(f) states that ‘claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render the abstract idea eligible,’ see Alice Corp., 573 U.S. at 223. The newly amended claims do not integrate the abstract idea into a practical application or add significantly more than the abstract idea itself. With this in consideration, Examiner maintains the rejection of the claims under 35 USC 101.
Rejections under 35 USC 102/103
Applicant's arguments filed 04/03/2026 have been fully considered but they are not persuasive.
Applicant argues that the previously presented prior art of Ishikawa does not teach, suggest, or fairly disclose all of the limitations of the amended independent claims, namely that of informing a user via a user interface device operatively coupled with a computer whether the quality of a setup of an array of acceleration sensors on an anatomical body part is acceptable relative to a predetermined criterion.
Examiner respectfully disagrees and points to terminal apparatus 400 as taught by Ishikawa which may be used to output information to the user using a display 410 after data analysis is conducted by the analysis apparatus, which may be implemented in the sensor apparatus, server, or terminal apparatus (Ishikawa [0231-0233]). The information output to the user may be in the form of a notification (image display, speech display, etc.) that the sensor is not attached/not in contact with the user when the observation signal is determined to be less than a threshold value by the first sensor analysis unit (Ishikawa [0171]). It can be appreciated that the notifying of a user that the sensor is not attached/not in contact with the user fulfills the limitation of informing the user whether the quality of the setup of the sensor array on the anatomical body is acceptable relative to a predetermined criterion, as the first active state analysis unit informs the user that the quality of the setup of the sensor array is not acceptable relative to a predetermined criterion.
Applicant also argues with respect to independent claim 15 that Ishikawa does not teach, suggest, or fairly disclose all of the limitations of the claim, namely if the setup quality data associated with a specific point in time does not describe the predetermined quality of the setup of the array of acceleration sensors, saving an acceleration value associated with the specific point in time and marking the associated acceleration value that it shall not be used further. Applicant argues that Ishikawa teaches away from the claimed limitation and disregards signals not fulfilling a predetermined relation to a threshold value, pointing to Ishikawa paragraph [0123] stating: ‘in a case where it is determined in the third sensor analysis (pressing force analysis) that the pressing force signal of the third sensor information is smaller than the threshold value, the noise reduction processing unit 161 does not output a reference signal or outputs nonexistence of a reference signal.’
Examiner respectfully disagrees and argues that Ishikawa does indeed teach the limitations of the claim. The portion of paragraph [0123] as cited by Applicant only discusses the third sensor analysis unit (pressing force analysis). However, it can be appreciated that paragraph [0123] discloses the active state analysis unit 162 as a whole which performs active state analysis in the order of first sensor analysis (contact analysis), second sensor analysis (body motion analysis), and third sensor analysis (pressing force analysis). When the second sensor analysis determines that a body motion (acceleration) signal is less than a threshold value, therefore not meeting a threshold of predetermined setup quality, the third sensor analysis unit then compares the pressing force signal to a predetermined threshold. If the pressing force signal is equal to or above a threshold value, then the pressing force signal, associated with the same point in time as the body motion signal that was determined to be less than a threshold value, is output as a reference signal. This process does not wholly discard the body motion signal which was determined to be less than a threshold value at a specific time, and instead marks the acceleration value that it shall not be used further by proceeding with the sensor analysis process to the third sensor analysis unit which then outputs the pressing force signal as the reference signal rather than the body motion signal from the second sensor analysis unit.
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 1-18, 20, 21, and 26 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea/mental process without significantly more.
Step 1
Claims 1 and 15 recite a process and claims 20 and 21 recite a machine.
Step 2A, Prong 1
Claims 1, 15, 20, and 21 recite the limitations of:
determining signal noise data based on the acceleration measurement data, wherein the signal noise data describes a noise component contained in the acceleration measurement data;
determining movement indication data based on the acceleration measurement data, wherein the movement indication data describes whether the acceleration values indicate a gross movement of the patient's body; and
determining setup quality data based on the sensor contact data and data the signal noise data, and the movement indication data, wherein the setup quality data describes a quality of the setup of the array of acceleration sensors on the anatomical body part.
These steps, given their broadest reasonable interpretation, can be practically performed in the human mind and are thereby considered to be directed to an abstract idea/mental process. A person of ordinary skill in the art could analyze the setup of an array of acceleration sensors on an anatomical body part of a patient based on an observation of movement indication data and signal noise data based on acceleration measurement data and sensor contact data.
Dependent claims 2, 5, 6, 8, and 11-13 also introduce additional abstract ideas as follows:
Claim 2 recites the limitation of determining pressure change data based on the contact pressure data, wherein the pressure change data describes a first-order temporal derivative of the pressure values detected by each of the pressure sensors.
Claim 5 recites the limitation of determining pressure quality data based on the contact pressure data and the pressure threshold data by comparing the pressure values detected by each of the pressure sensors to the at least one threshold value of the pressure values, wherein the pressure quality data is determined to indicate a predetermined quality of the pressure values detected by each of the pressure sensors if the comparison results in that the pressure values detected by each of the pressure sensors have a predetermined relationship to the at least one threshold value of the pressure values.
Claim 6 recites the limitation of determining pressure change quality data based on the pressure change data and the pressure change threshold data by comparing the first-order temporal derivative of the pressure values detected by each of the pressure sensors to the at least one threshold value of the first-order temporal derivative of the pressure values, wherein the pressure change quality data is determined to indicate a predetermined quality of the first-order temporal derivative of the pressure values if the comparison results in that the first-order temporal derivative of the pressure values has a predetermined relationship to the at least one threshold value of the first-order temporal derivative of the pressure values.
Claim 8 recites the limitation of determining noise quality data based on the at least one of the signal noise data or the noise comparison data by comparing the noise to the predetermined quantity of the noise, wherein the noise quality data is determined to indicate a predetermined quality of the noise if the comparison results in that the noise has a predetermined relationship to the predetermined quantity of the noise.
Claim 11 recites the limitations of determining, based on the heartbeat signal data, waveform correlation data describing a correlation of the waveform of the time series of the heartbeat and/or determining, based on the heartbeat signal data, heartbeat spectrum data describing an energy spectrum of the time series of the heartbeat.
Claim 12 recites the limitation of determining waveform quality data based on the waveform correlation data and the correlation threshold data by comparing the correlation of the waveform of the time series of the heartbeat to the at least one threshold value of the correlation of the waveform of the time series of the heartbeat, wherein the waveform quality data is determined to indicate a predetermined quality of the waveform of the time series of the heartbeat if the comparison results in that waveform of the time series of the heartbeat has a predetermined relationship to the at least one threshold value of the correlation of the waveform of the time series of the heartbeat.
Claim 13 recites the limitation of determining heartbeat spectrum quality data based on the heartbeat spectrum data and the spectrum comparison data by comparing the energy spectrum of the time series of the heartbeat to the predetermined energy spectrum of the time series of the heartbeat, wherein the heartbeat spectrum quality data is determined to indicate a predetermined quality of the first energy spectrum of the time series of the heartbeat if the comparison results in that the energy spectrum of the time series of the heartbeat has a predetermined relationship to the predetermined energy spectrum of the time series of the heartbeat.
Given their broadest reasonable interpretation, the additional abstract ideas introduced in the dependent claims can be practically performed in the human mind. One of ordinary skill in the art could determine pressure change data, pressure change quality data, noise quality data, waveform correlation data, waveform quality data, and/or heartbeat spectrum quality data given the appropriate acquired signal of contact pressure data, noise data, heartbeat waveform data, and/or heartbeat spectrum data.
Step 2A, Prong 2
Claims 1, 15, 20, and 21 do not include any additional elements that integrate the abstract idea into a practical application.
Claims 1, 15, 20, and 21 include the additional elements of acquiring acceleration measurement data from acceleration sensors operatively coupled with a computer and acquiring sensor contact data, then performing a method of analysis using a computer including a processor and non-transient memory device.
The limitations of:
acquiring acceleration measurement data and
acquiring acceleration sensor contact data
are pre-solution activity of data collection in the form of performing clinical tests to obtain input for an equation, in this case gathering acceleration measurement data and sensor contact data as an input to determine setup quality data. See MPEP 2106.05(g), In re Grams 888 F.2d 835.
The computer comprising at least one processor and a non-transient memory device are claimed such that they amount to generic computer implementation of the abstract idea. See MPEP 2106.05(f).
The additional elements do not amount to integrating the abstract idea into practical application.
Claim 2 and 5-6 include the additional elements of acquiring
contact pressure data;
pressure threshold data; and
pressure change threshold data.
These limitations amount to pre-solution activity of data collection in the form of performing clinical tests to obtain input for an equation, in this case gathering contact pressure data, pressure threshold data, and pressure change threshold data as an input to determine pressure change data, pressure quality data, and pressure change quality data. See MPEP 2106.05(g), In re Grams 888 F.2d 835.
Claim 8 includes the additional element of acquiring noise comparison data.
These limitations amount to pre-solution activity of data collection in the form of performing clinical tests to obtain input for an equation, in this case gathering noise comparison data as an input to determine noise quality data. See MPEP 2106.05(g), In re Grams 888 F.2d 835.
Claims 11-13 includes the additional element of acquiring correlation threshold data which describes at least one threshold value of the correlation of the waveform of the time series of the heartbeat; and/ or acquiring spectrum comparison data describing a predetermined energy spectrum of the time series of the heartbeat.
These limitations amount to pre-solution activity of data collection in the form of performing clinical tests to obtain input for an equation, in this case gathering correlation threshold data and or spectrum comparison data as an input to determine waveform correlation data, heartbeat spectrum data, waveform quality data, and/or heartbeat spectrum quality data. See MPEP 2106.05(g), In re Grams 888 F.2d 835.
The additional elements do not amount to integrating the abstract idea into practical application.
Step 2B
Claims 1, 15, 20, and 21 do not include any additional elements which amount to significantly more than the abstract idea itself.
See above in Step 2A, Prong 2 wherein the additional elements of claims 1, 15, 20, and 21 are determined to be pre-solution activity of data gathering and generic computer implementation of the abstract idea. None of these additional elements alone or in combination amount to significantly more than the abstract idea itself. Additionally, the additional elements of the sensor array comprising acceleration sensors and a computer comprising at least one processor and a non-transient memory device can be held to be well-understood, routine, and conventional in the art, and they are recited with a high level of generality which does not amount to significantly more than the abstract idea itself. Ishikawa (US 20210275103 A1) teaches a sensor array (150) comprising at least one accelerator sensor (152) a computer (400) comprising at least one processor and a non-transient memory (530).
Therefore, the additional elements do not amount to significantly more than the abstract idea itself.
Claims 2-14 and 16-18 further limit the extra-solution activity of data-gathering via an array of sensors.
Claim 26 amounts to extra-solution activity of generating a signal based on the fulfillment of a criteria.
Claim Rejections - 35 USC § 102
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 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 4, 7, 8, 15-18, 20, 21, and 26 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ishikawa (US 20210275103 A1).
Regarding claim 1, Ishikawa teaches a method performed by a computer including a processor (530) and a non-transient memory device for analyzing the setup of an array of acceleration sensors (152) on an anatomical body part of a patient (see [0115-0118]; processing unit 160 comprising active state analysis unit 162 can determine an attachment status of the biological information processing system), the method comprising:
acquiring by acceleration sensors operatively coupled with the computer (see [0230]; the analysis apparatus executes analysis based on sensor array 100 and is implemented as the server 300, terminal apparatus 400, or the sensor apparatus 100, the analysis apparatus including a receiving unit 510, a transmission unit 520, and a processing unit 530) acceleration measurement data (see [0089]; output from sensor unit 152 in the form of body motion change information) that describes acceleration values (see [0089-0091]; second sensor 152 may be an acceleration sensor to acquire body motion change information);
acquiring by the processor of the computer sensor contact data (see [0171]; observation signal from sweat sensor 151) that describes a quality of a contact between at least one of the acceleration sensors comprised in the array of acceleration sensors and the anatomical body part of the patient (see [0171]; first sensor analysis unit 61 determines a contact state of a biological sensor, if the observed signal is above a threshold which indicates that the sensor is attached, a signal will be sent to the body motion analysis unit 62);
determining by the processor of the computer signal noise data (see [0160]; body motion noise) based on the acceleration measurement data, wherein the signal noise data describes a noise component contained in the acceleration measurement data (see [0160]; noise reduction processing unit 161 is configured to regard body motion signal as a reference signal and calculate error signal by subtracting body motion noise from the observation signal using the reference signal, [0161]; bandpass filter unit 155 extracts fluctuation components from a body motion signal);
determining by the processor of the computer movement indication data (see [0172]; active state determination) based on the acceleration measurement data, wherein the movement indication data describes whether the acceleration values indicate a gross movement of the patient's body (see [0172]; second sensor analysis unit 62 processes body motion signal from the IMU sensor and determines if the user is in an active state based on a comparison to a motion threshold); and
determining by the processor of the computer setup quality data (see [0171]; contact state of biological sensor) based on the sensor contact data, the signal noise data, and the movement indication data (see [0170-0174]; sensor contact data determines if the sensor is attached to the user and triggers second sensor analysis unit 62 to process a body motion signal where the signal is passed through a bandpass filter, and sent to a noise reduction processing unit 161 to be used as a reference signal),
wherein the setup quality data describes a quality of the setup of the array of acceleration sensors on the anatomical body part (see [0173]; biological information is output from the output signal quality calculation unit 163 to which the observation signal is input, [0162]; an output signal quality calculation unit 163 that determines a reduction state of body motion noise on the basis of a relationship between observation signal power calculated from the observation signal and error signal power calculated from the error signal is further included); and
informing a user via a user interface device (400/410) operatively coupled with the computer whether the quality of the setup of the array of acceleration sensors on the anatomical body part is acceptable relative to a predetermined criterion (see [0233]; information is output by the terminal apparatus 400 using the display 410, [0171]; when it is determined that the observation signal is smaller than a threshold value, it is determined that the sensor is not attached/not in contact, and therefore the quality of the setup of the sensor array is not acceptable relative to a predetermined criterion, the first active state analysis unit notifies the user of this via image display, speech display, etc.)
Regarding claim 4, Ishikawa teaches the method according to claim 1, wherein the sensor contact data is acquired based on the acceleration measurement data by skin resistance measurement (see [0150-0151]; contact analysis unit 61 is configured to determine that the biological processing apparatus is in contact with the user, using skin conductance measured by sweat sensor 151).
Regarding claim 7, Ishikawa teaches the method according to claim 1 further comprising acquiring, using at least one of at least one of the acceleration sensors or an auxiliary sensor comprising a pressure level sensor, background noise data that describes background noise (see [0170-0174]; sensor contact data determines if the sensor is attached to the user and triggers second sensor analysis unit 62 to process a body motion signal where the signal is passed through a bandpass filter, and sent to a noise reduction processing unit 161 to be used as a reference signal),
wherein the setup quality data is determined based on the background noise data (see [0173]; biological information is output from the output signal quality calculation unit 163 to which the observation signal is input, [0162]; an output signal quality calculation unit 163 that determines a reduction state of body motion noise on the basis of a relationship between observation signal power calculated from the observation signal and error signal power calculated from the error signal is further included).
Regarding claim 8, Ishikawa teaches the method according to claim 1, further comprising:
acquiring noise comparison data that describes a predetermined quantity of the noise contained in at least one of the signal noise data or the background noise data (see [0120]; active state analysis unit 162 is configured to have a function of determining body motion noise); and
determining noise quality data based on the at least one of the signal noise data or the noise comparison data by comparing the noise to the predetermined quantity of the noise (see [0120]; when active state analysis unit 162 determines that a user is in an active state, the body motion signal may be determined as noise, when active state analysis unit 162 determines that a user is in an rest state, the body motion noise is not included),
wherein the noise quality data is determined to indicate a predetermined quality of the noise if the comparison results in that the noise has a predetermined relationship to the predetermined quantity of the noise (see [0123]; when active state analysis unit 162 determines that second sensor information is equal to or greater than a threshold value, unit 162 outputs the motion signal to the noise reduction processing unit 161 as a reference signal).
Regarding claim 15, Ishikawa teaches a method performed by a computer including a processor (530) and a non-transient memory device for determining the validity of acceleration values sampled using an array of acceleration sensors (152) placed on an anatomical body part of a patient (see [0115-0118]; processing unit 160 comprising active state analysis unit 162 can determine an attachment status of the biological information processing system), the method comprising:
acquiring by acceleration sensors operatively coupled with the computer (see [0230]; the analysis apparatus executes analysis based on sensor array 100 and is implemented as the server 300, terminal apparatus 400, or the sensor apparatus 100, the analysis apparatus including a receiving unit 510, a transmission unit 520, and a processing unit 530), acceleration measurement data (see [0089]; output from sensor unit 152 in the form of body motion change information) that describes acceleration values (see [0089-0091]; second sensor 152 may be an acceleration sensor to acquire body motion change information);
acquiring sensor contact data (see [0171]; observation signal from sweat sensor 151) that describes a quality of a contact between at least one of the acceleration sensors comprised in the array of acceleration sensors and the anatomical body part of the patient (see [0171]; first sensor analysis unit 61 determines a contact state of a biological sensor, if the observed signal is above a threshold which indicates that the sensor is attached, a signal will be sent to the body motion analysis unit 62);
determining signal noise data (see [0160]; body motion noise) based on the acceleration measurement data, wherein the signal noise data describes a noise component contained in the acceleration measurement data (see [0160]; noise reduction processing unit 161 is configured to regard body motion signal as a reference signal and calculate error signal by subtracting body motion noise from the observation signal using the reference signal, [0161]; bandpass filter unit 155 extracts fluctuation components from a body motion signal);
determining movement indication data (see [0172]; active state determination) based on the acceleration measurement data, wherein the movement indication data describes whether the acceleration values indicate a gross movement of the patient's body (see [0172]; second sensor analysis unit 62 processes body motion signal from the IMU sensor and determines if the user is in an active state based on a comparison to a motion threshold);
determining setup quality data (see [0171]; contact state of biological sensor) based on the sensor contact data, the signal noise data, and the movement indication data (see [0170-0174]; sensor contact data determines if the sensor is attached to the user and triggers second sensor analysis unit 62 to process a body motion signal where the signal is passed through a bandpass filter, and sent to a noise reduction processing unit 161 to be used as a reference signal),
wherein the setup quality data describes a quality of the setup of the array of acceleration sensors on the anatomical body part (see [0173]; biological information is output from the output signal quality calculation unit 163 to which the observation signal is input, [0162]; an output signal quality calculation unit 163 that determines a reduction state of body motion noise on the basis of a relationship between observation signal power calculated from the observation signal and error signal power calculated from the error signal is further included);
informing a user via a user interface device (400/410) operatively coupled with the computer whether the quality of the setup of the array of acceleration sensors on the anatomical body part is acceptable relative to a predetermined criterion (see [0233]; information is output by the terminal apparatus 400 using the display 410, [0171]; when it is determined that the observation signal is smaller than a threshold value, it is determined that the sensor is not attached/not in contact, and therefore the quality of the setup of the sensor array is not acceptable relative to a predetermined criterion, the first active state analysis unit notifies the user of this via image display, speech display, etc.); and
determining time-correlated measurement data describing a time-correlation of the acceleration measurement data with the setup quality data and (see [0171-0174]; first active state analysis unit causes the first sensor analysis unit 61 to determine the contact state of a sensor at a specific time, and if the sensor is in contact then the body motion analysis unit is activated to determine if the user is in an active state),
if the setup quality data associated with a specific point in time does not describe the predetermined quality of the setup of the array of acceleration sensors, saving an acceleration value associated with the specific point in time and marking the associated acceleration value that it shall not be used further (see [0123]; active state analysis unit 161 performs active state analysis in order of first sensor analysis unit (contact analysis), second sensor analysis unit (body motion analysis), and third sensor analysis unit (pressing force analysis), when it is determined that the body motion signal from the second sensor analysis unit is less than a predetermined threshold value, therefore not describing a predetermined quality of the setup of the sensor array, the analysis unit 161 moves to the third sensor analysis unit and if the pressing force signal is equal to or greater than a predetermined threshold value, the pressing force signal is used as the reference signal; thereby marking that the acceleration value shall not be used further by proceeding with the sensor analysis process to the third sensor analysis unit which then outputs the pressing force signal as the reference signal rather than the body motion signal from the second sensor analysis unit, wherein the first, second, and third sensor signals are all associated with the same time, [0176-0177]; when the first sensor analysis unit determines that the sensor unit is in contact with a user and the second sensor analysis unit determines the user to be in an inactive state with the first active state analysis unit, the third sensor analysis unit with the second active state analysis unit determines if the user is in a quasi-rest state and the acceleration/body motion noise should be discarded and a pressure signal noise should be correlated with the first sensor signal at a specific time),
otherwise saving the acceleration value associated with the specific point in time (see [0172]; when the sensor is in contact and the second acceleration/body motion sensors have determined the user to be in an active state, sending the body motion signal to further processing with regard to the first sensor signal measured at the same time).
Regarding claim 16, Ishikawa teaches the method according to claim 15, further comprising:
acquiring movement acceleration threshold data describing at least one threshold of the acceleration values indicating a gross movement of the patient's body (see [0122]; body motion analysis threshold may be set by active state analysis unit 162 analyzing sensor information and setting a threshold value as a result of the analysis); and
determining the movement indication data based on the acceleration measurement data and the movement acceleration threshold data (see [0172]; second sensor analysis unit 62 processes body motion signal from the IMU sensor and determines if the user is in an active state based on a comparison to a motion threshold).
Regarding claim 17, Ishikawa teaches the method according to claim 15, further comprising,
determining the movement indication data by comparing the acceleration values to the at least one threshold of the acceleration values indicating a gross movement of the patient's body (see [0172]; second sensor analysis unit 62 processes body motion signal from the IMU sensor and determines if the user is in an active state based on a comparison to a motion threshold), and
determining that the movement indication data describes that an acceleration value indicates a gross movement of the patient's body if the acceleration value has a predetermined relationship to the at least one threshold of the acceleration values indicating a gross movement of the patient's body (see [0172]; in a case where the processed signal is equal to or larger than a threshold value it is determined that the user is in an active state).
Regarding claim 18, Ishikawa teaches the method according to claim 15, further comprising determining time-correlated measurement data describing a time-correlation of the acceleration measurement data with the setup quality data (see [0171-0174]; first active state analysis unit causes the first sensor analysis unit 61 to determine the contact state of a sensor at a specific time, and if the sensor is in contact then the body motion analysis unit is activated to determine if the user is in an active state), and
determining whether the data set comprising the time-correlated measurement data has a predetermined length of acceleration values which are associated with points in time at which the correlated setup quality data describes the predetermined quality of the setup of the array of acceleration sensors (see [0112]; the second sensor information includes a time from the start to the end of the movement, [0171-0172]; the second sensor information is used by the first active state analysis unit to determine if the user is in an active state).
Regarding claim 20, Ishikawa teaches a non-transient computer-readable storage medium on which a program is stored and that is executable by a processor (530) of a computer (see [0230]; biological information analysis apparatus has processing unit 530, which is implemented by a processor operating in accordance with a program stored in memory or storage, to execute analysis that is based on data from sensor apparatus 100) to carry out a method comprising:
acquiring by acceleration sensors (152) operatively coupled with the computer (see [0230]; the analysis apparatus executes analysis based on sensor array 100 and is implemented as the server 300, terminal apparatus 400, or the sensor apparatus 100, the analysis apparatus including a receiving unit 510, a transmission unit 520, and a processing unit 530), acceleration measurement data (see [0089]; output from sensor unit 152 in the form of body motion change information) that describes acceleration values (see [0089-0091]; second sensor 152 may be an acceleration sensor to acquire body motion change information);
acquiring by the processor of the computer sensor contact data (see [0171]; observation signal from sweat sensor 151) that describes a quality of a contact between at least one of the acceleration sensors comprised in the array of acceleration sensors and the anatomical body part of the patient (see [0171]; first sensor analysis unit 61 determines a contact state of a biological sensor, if the observed signal is above a threshold which indicates that the sensor is attached, a signal will be sent to the body motion analysis unit 62);
determining by the processor of the computer signal noise data (see [0160]; body motion noise) based on the acceleration measurement data, wherein the signal noise data describes a noise component contained in the acceleration measurement data (see [0160]; noise reduction processing unit 161 is configured to regard body motion signal as a reference signal and calculate error signal by subtracting body motion noise from the observation signal using the reference signal, [0161]; bandpass filter unit 155 extracts fluctuation components from a body motion signal);
determining by the processor of the computer movement indication data (see [0172]; active state determination) based on the acceleration measurement data, wherein the movement indication data describes whether the acceleration values indicate a gross movement of the patient's body (see [0172]; second sensor analysis unit 62 processes body motion signal from the IMU sensor and determines if the user is in an active state based on a comparison to a motion threshold); and
determining by the processor of the computer setup quality data (see [0171]; contact state of biological sensor) based on the sensor contact data, the signal noise data, and the movement indication data (see [0170-0174]; sensor contact data determines if the sensor is attached to the user and triggers second sensor analysis unit 62 to process a body motion signal where the signal is passed through a bandpass filter, and sent to a noise reduction processing unit 161 to be used as a reference signal),
wherein the setup quality data describes a quality of the setup of the array of acceleration sensors on the anatomical body part (see [0173]; biological information is output from the output signal quality calculation unit 163 to which the observation signal is input, [0162]; an output signal quality calculation unit 163 that determines a reduction state of body motion noise on the basis of a relationship between observation signal power calculated from the observation signal and error signal power calculated from the error signal is further included);
informing a user via a user interface device (400/410) operatively coupled with the computer whether the quality of the setup of the array of acceleration sensors on the anatomical body part is acceptable relative to a predetermined criterion (see [0233]; information is output by the terminal apparatus 400 using the display 410, [0171]; when it is determined that the observation signal is smaller than a threshold value, it is determined that the sensor is not attached/not in contact, and therefore the quality of the setup of the sensor array is not acceptable relative to a predetermined criterion, the first active state analysis unit notifies the user of this via image display, speech display, etc.).
Regarding claim 21, Ishikawa teaches a computer comprising at least one processor (see [0230]; biological information analysis apparatus which may be implemented by terminal apparatus 400 has processing unit 530 which is implemented by a processor, to execute analysis that is based on data from sensor apparatus 100);
a non-transient memory device operatively coupled with the processor and storing a program thereon (see [0230]; processing unit 530 may be implemented by a processor operating in accordance with a program stored in memory or storage),
wherein the processor is configured to execute the program to analyze the setup of an array of acceleration sensors (152) on an anatomical body part of a patient to:
acquire by acceleration sensors operatively coupled with the computer (see [0230]; the analysis apparatus executes analysis based on sensor array 100 and is implemented as the server 300, terminal apparatus 400, or the sensor apparatus 100, the analysis apparatus including a receiving unit 510, a transmission unit 520, and a processing unit 530) acceleration measurement data (see [0089]; output from sensor unit 152 in the form of body motion change information) that describes acceleration values (see [0089-0091]; second sensor 152 may be an acceleration sensor to acquire body motion change information);
acquire by the processor of the computer sensor contact data (see [0171]; observation signal from sweat sensor 151) that describes a quality of a contact between at least one of the acceleration sensors comprised in the array of acceleration sensors and the anatomical body part of the patient (see [0171]; first sensor analysis unit 61 determines a contact state of a biological sensor, if the observed signal is above a threshold which indicates that the sensor is attached, a signal will be sent to the body motion analysis unit 62);
determine by the processor of the computer signal noise data (see [0160]; body motion noise) based on the acceleration measurement data, wherein the signal noise data describes a noise component contained in the acceleration measurement data (see [0160]; noise reduction processing unit 161 is configured to regard body motion signal as a reference signal and calculate error signal by subtracting body motion noise from the observation signal using the reference signal, [0161]; bandpass filter unit 155 extracts fluctuation components from a body motion signal);
determine by the processor of the computer movement indication data (see [0172]; active state determination) based on the acceleration measurement data, wherein the movement indication data describes whether the acceleration values indicate a gross movement of the patient's body (see [0172]; second sensor analysis unit 62 processes body motion signal from the IMU sensor and determines if the user is in an active state based on a comparison to a motion threshold); and
determine by the processor of the computer setup quality data (see [0171]; contact state of biological sensor) based on the sensor contact data, the signal noise data, and the movement indication data (see [0170-0174]; sensor contact data determines if the sensor is attached to the user and triggers second sensor analysis unit 62 to process a body motion signal where the signal is passed through a bandpass filter, and sent to a noise reduction processing unit 161 to be used as a reference signal),
wherein the setup quality data describes a quality of the setup of the array of acceleration sensors on the anatomical body part (see [0173]; biological information is output from the output signal quality calculation unit 163 to which the observation signal is input, [0162]; an output signal quality calculation unit 163 that determines a reduction state of body motion noise on the basis of a relationship between observation signal power calculated from the observation signal and error signal power calculated from the error signal is further included); and
inform a user via a user interface device (400/410) operatively coupled with the computer whether the quality of the setup of the array of acceleration sensors on the anatomical body part is acceptable relative to a predetermined criterion (see [0233]; information is output by the terminal apparatus 400 using the display 410, [0171]; when it is determined that the observation signal is smaller than a threshold value, it is determined that the sensor is not attached/not in contact, and therefore the quality of the setup of the sensor array is not acceptable relative to a predetermined criterion, the first active state analysis unit notifies the user of this via image display, speech display, etc.).
Regarding claim 26, Ishikawa teaches the method according to claim 1 wherein the informing the user comprises generating a signal that indicates to the user whether the quality of the setup fulfills the predetermined criterion (see [0115]; noise reduction processing unit 161 can notify the user that the biological information processing system is not attached and may perform such a user notification).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 2, 3, 5, 6, and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ishikawa (US 20210275103 A1) in view of Coakley et al (US 20230270387 A1) and Kuang (US 20220338748 A1).
Regarding claim 2, Ishikawa teaches the method according to claim 1. However, Ishikawa is silent regarding wherein the determining the sensor contact data comprises:
acquiring contact pressure data that describes pressure values detected by each of pressure sensors comprised in an array of pressure sensors after positioning each of the pressure sensors on the anatomical body part;
acquiring pressure threshold data that describes at least one threshold value of the pressure values detected by each of the pressure sensors;
determining pressure change data based on the contact pressure data, wherein the pressure change data describes a first-order temporal derivative of the pressure values detected by each of the pressure sensors; and
acquiring pressure change threshold data that describes at least one threshold value of the first-order temporal derivative of the contact pressure data.
Coakley teaches a system for determining the accuracy of physiological data measured through contact with a skin surface of a user by determining sensor contact data comprising a fit score which indicates the quality of the interface between a wearable sensor unit and a user (Coakley [0046]), wherein the determining the sensor contact data (see Coakley [0035]; wearable device having one or more fit sensors to characterize the fit of a wearable device) comprises:
acquiring contact pressure data that describes pressure values detected by each of pressure sensors comprised in an array of pressure sensors after positioning each of the pressure sensors on the anatomical body part (see Coakley [0035]; a fit sensor can be a pressure-based sensor that can characterize the interface between a user's skin and the sensor);
acquiring pressure threshold data that describes at least one threshold value of the pressure values detected by each of the pressure sensors (see Coakley Fig. 4, [0036]; a range of pressures between pressure values P1 and P2 where skin sensors can accurately and reliably record biometric data).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Ishikawa’s method for determining the accuracy of an array of sensors on a patient with the pressure sensor contact data as taught by Coakley. One of ordinary skill in the art would have been motivated to make this modification in order to characterize the fit of a wearable biometric device by the quality of the interface between the wearable device and a user and validate the biometric measurements provided by the associated sensors (Coakley [0043-0046]).
Coakley is silent regarding determining pressure change data based on the contact pressure data, wherein the pressure change data describes a first-order temporal derivative of the pressure values detected by each of the pressure sensors; and
acquiring pressure change threshold data that describes at least one threshold value of the first-order temporal derivative of the contact pressure data.
Kuang teaches a wearable device (200) having an array of sensors, comprising at least one pressure sensor (205) to acquire sensor contact data that describes the quality of the contact between a sensor array and a user (see Kuang [0008]; the device determines the tightness of the wristband worn by the user based on a first pressure signal), wherein the determining the sensor contact data comprises:
determining pressure change data based on the contact pressure data, wherein the pressure change data describes a first-order temporal derivative of the pressure values detected by each of the pressure sensors (see Kuang [0018-0019]; obtaining a first pressure signal which indicates that the pressure of the airbag changes with time and determining a pressurization slope of the first pressure signal to indicate the tightness of wearing the wristband by the user); and
acquiring pressure change threshold data that describes at least one threshold value of the first-order temporal derivative of the contact pressure data (see Kuang [0116-0118]; quantifying the tightness of the wristband based on the pressurization slope is only accurate within a certain interval which may be denoted with threshold values consisting of a minimum first slope and a maximum second slope, the first and second slope may be determined based on sample data or may be set by the user based on an actual situation).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Coakley’s method of determining pressure sensor contact data with Huang’s pressure change data. One of ordinary skill in the art would have been motivated to make this modification in order to provide compensation in measured biometric data, for example, blood pressure data, based on the rate of pressurization described as a first-order temporal derivative of the pressure values (Hoang [0010]).
Regarding claim 3, Ishikawa, Coakley, and Huang teach the method according to claim 2. Ishikawa further teaches wherein the array of pressure sensors and the array of acceleration sensors are comprised in the same device and for example have a predetermined, for example at least one of fixed or known, spatial relationship to each other (see Ishikawa Fig. 5, [0136-0139]; second sensor unit/accelerometer unit 152 may be in the sensor module 140; biological sensors 151 are disposed at equal intervals across the wristband 141, the third sensor unit/pressure unit 153 is provided between the exposed surface of the biological sensor and the wristband 141).
Regarding claim 5, Ishikawa, Coakley, and Huang teach the method according to claim 2. Ishikawa is silent regarding determining pressure quality data based on the contact pressure data and the pressure threshold data by comparing the pressure values detected by each of the pressure sensors to the at least one threshold value of the pressure values,
wherein the pressure quality data is determined to indicate a predetermined quality of the pressure values detected by each of the pressure sensors if the comparison results in that the pressure values detected by each of the pressure sensors have a predetermined relationship to the at least one threshold value of the pressure values.
Coakley teaches determining pressure quality data based on the contact pressure data and the pressure threshold data (see Coakley Fig. 4, [0036]; relationship between the signal quality provided by a biometric sensor in contact with the skin and the pressure which the sensor is pressed against the surface of the skin) by comparing the pressure values detected by each of the pressure sensors to the at least one threshold value of the pressure values (see Coakley Fig. 4, [0036]; a range of pressures between P1 and P2 where skin sensors can accurately and reliably record biometric data),
wherein the pressure quality data is determined to indicate a predetermined quality of the pressure values detected by each of the pressure sensors if the comparison results in that the pressure values detected by each of the pressure sensors have a predetermined relationship to the at least one threshold value of the pressure values (see Coakley [0036]; a range of pressures between P1 and P2 where skin sensors can accurately and reliably record biometric data, the pressure at which a sensor is applied to the skin can be related to a confidence value in the measured biometric data).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Ishikawa’s method for determining the accuracy of an array of sensors on a patient with the pressure sensor contact data and threshold as taught by Coakley. One of ordinary skill in the art would have been motivated to make this modification in order to validate the biometric measurements provided by the associated sensors (Coakley [0043-0046]), by determining that the pressure which the sensor is pressed against the skin is within an expected range at which the skin sensors can reliably and accurately record data (Coakley [0036]).
Regarding claim 6, Ishikawa, Coakley, and Huang teach the method according to claim 2. Ishikawa is silent regarding determining pressure change quality data based on the pressure change data and the pressure change threshold data by comparing the first-order temporal derivative of the pressure values detected by each of the pressure sensors to the at least one threshold value of the first-order temporal derivative of the pressure values,
wherein the pressure change quality data is determined to indicate a predetermined quality of the first-order temporal derivative of the pressure values if the comparison results in that the first-order temporal derivative of the pressure values has a predetermined relationship to the at least one threshold value of the first-order temporal derivative of the pressure values.
Huang teaches determining pressure change quality data based on the pressure change data and the pressure change threshold data by comparing the first-order temporal derivative of the pressure values detected by each of the pressure sensors to the at least one threshold value of the first-order temporal derivative of the pressure values (see Huang [0116-0118]; quantifying the tightness of the wristband based on the pressurization slope is only accurate within a certain interval which may be denoted with threshold values consisting of a minimum first slope and a maximum second slope, the first and second slope may be determined based on sample data or may be set by the user based on an actual situation),
wherein the pressure change quality data is determined to indicate a predetermined quality of the first-order temporal derivative of the pressure values if the comparison results in that the first-order temporal derivative of the pressure values has a predetermined relationship to the at least one threshold value of the first-order temporal derivative of the pressure values (see Huang [0118]; if the pressurization slope is greater than the first slope and less than the second slope it indicates that the wearing tightness may be quantized based on the pressurization slope).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Ishikawa’s method for determining the accuracy of an array of sensors on a patient using the pressure sensor contact data and threshold as taught by Coakley with the pressure change quality data as taught by Kuang. One of ordinary skill in the art would have been motivated to make this modification in order to compensate for changing pressure over time in measured biometric data (Huang [0010]).
Regarding claim 9, Ishikawa teaches the method according to claim 7. In addition, Coakley teaches the method according to claim 7 comprising acquiring, using an auxiliary sensor comprising a pressure level sensor (169), background noise data that describes background noise, wherein the setup quality data is determined based on the background noise data (see Coakley [0036]; the confidence value may depend on signal to noise ratio).
Ishikawa is silent regarding wherein the setup quality data is determined to describe a predetermined quality of the positioning of the array of pressure sensors on the anatomical body part if the pressure quality data has been determined to indicate the predetermined quality of the pressure values detected by each of the pressure sensors and
the pressure change quality data has been determined to indicate the predetermined quality of the first-order temporal derivative of the pressure values and the noise quality data has been determined to indicate the predetermined quality of the noise component.
Coakley teaches wherein the setup quality data is determined to describe a predetermined quality of the positioning of the array of pressure sensors on the anatomical body part if the pressure quality data has been determined to indicate the predetermined quality of the pressure values detected by each of the pressure sensors (see Coakley Fig. 4, [0036]; a range of pressures between P1 and P2 where skin sensors can accurately and reliably record biometric data).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Ishikawa’s method for determining the setup quality data with the pressure sensor contact data as taught by Coakley. One of ordinary skill in the art would have been motivated to make this modification in order to characterize the fit of a wearable biometric device by the quality of the interface between the wearable device and a user and validate the biometric measurements provided by the associated sensors (Coakley [0043-0046]).
Coakley is silent regarding the pressure change quality data has been determined to indicate the predetermined quality of the first-order temporal derivative of the pressure values and the noise quality data has been determined to indicate the predetermined quality of the noise component.
Huang teaches wherein the pressure change quality data has been determined to indicate the predetermined quality of the first-order temporal derivative of the pressure values and the noise quality data has been determined to indicate the predetermined quality of the noise component (see Huang [0116-0118]; quantifying the tightness of the wristband based on the pressurization slope is only accurate within a certain interval which may be denoted with threshold values consisting of a minimum first slope and a maximum second slope, the first and second slope may be determined based on sample data or may be set by the user based on an actual situation).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Coakley’s method of determining setup quality data with Huang’s pressure change data. One of ordinary skill in the art would have been motivated to make this modification in order to provide compensation in measured biometric data, for example, blood pressure data, based on the rate of pressurization described as a first-order temporal derivative of the pressure values (Hoang [0010]).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ishikawa (US 20210275103 A1) in view of Coakley et al (US 20230270387 A1).
Regarding claim 7, Ishikawa teaches the method according to claim 1 further comprising acquiring, using at least one of at least one of the acceleration sensors or an auxiliary sensor comprising a pressure level sensor, background noise data that describes background noise, wherein the setup quality data is determined based on the background noise data (see rejection above).
In addition, Coakley teaches acquiring, using an auxiliary sensor comprising a pressure level sensor (169), background noise data that describes background noise, wherein the setup quality data is determined based on the background noise data (see Coakley [0036]; the confidence value may depend on signal to noise ratio).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Ishikawa’s method for determining the accuracy of an array of sensors on a patient with background noise data in conjunction with the pressure sensor contact data as taught by Coakley. One of ordinary skill in the art would have been motivated to make this modification in order to determine a confidence value of the measured biometric data that takes metrics including pressure sensor contact and signal to noise ratio into consideration (Coakley [0036]).
Claim(s) 10-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ishikawa (US 20210275103 A1) in view of Chahine et al (US 20220007986 A1).
Regarding claim 10, Ishikawa teaches the method according to claim 1. Ishikawa is silent regarding acquiring heartbeat signal data that describes a time series of the heartbeat of the patient, wherein an additional setup quality data point is determined based on the heartbeat signal data.
Chahine teaches a multi-sensor system which measures a heartbeat signal in the form of an ECG signal having a desired resolution from an array of different electrode locations to facilitate measurements of an appropriate quality when firm skin contact is not possible for all electrodes simultaneously (Chahine [0006]), comprising acquiring heartbeat signal data that describes a time series of the heartbeat of the patient, wherein the setup quality data is determined based on the heartbeat signal data (see Chahine [0025-0026]; collected ECG signals 6b can be examined by controller 14 for signal quality and real time change in potential direct contact between the sensors and the user, where it can be deemed that signals of poor quality can be due to the contact of the sensor and the user being below a contact threshold).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Ishikawa’s method for determining the quality of a sensor setup with the heartbeat signal quality determination as made by Chahine. One of ordinary skill in the art would have been motivated to make this modification in order to collect a signal having the appropriate quality where the quality is determined by the contact of the sensors with the user, and there are a plurality of sensors to select from, so the sensors having the best contact/signal quality can be used (Chahine [0025-0026]).
Regarding claims 11 and 12, Ishikawa and Chahine teach the method according to claim 10. Ishikawa is silent regarding the method further comprising one or more of:
determining, based on the heartbeat signal data, waveform correlation data describing a correlation of the waveform of the time series of the heartbeat;
acquiring correlation threshold data which describes at least one threshold value of the correlation of the waveform of the time series of the heartbeat;
determining, based on the heartbeat signal data, heartbeat spectrum data describing an energy spectrum of the time series of the heartbeat; and/or
acquiring spectrum comparison data describing a predetermined energy spectrum of the time series of the heartbeat,
wherein the setup quality data describes the quality of the positioning of a heartbeat detector on the anatomical body part and is determined based on the at least one of the waveform correlation data or the correlation threshold data and the heartbeat spectrum data or the spectrum comparison data; and
determining waveform quality data based on the waveform correlation data and the correlation threshold data by comparing the correlation of the waveform of the time series of the heartbeat to the at least one threshold value of the correlation of the waveform of the time series of the heartbeat,
wherein the waveform quality data is determined to indicate a predetermined quality of the waveform of the time series of the heartbeat if the comparison results in that waveform of the time series of the heartbeat has a predetermined relationship to the at least one threshold value of the correlation of the waveform of the time series of the heartbeat, and
wherein the setup quality data is determined based on the waveform quality data.
Chahine teaches determining, based on the heartbeat signal data, waveform correlation data describing a correlation of the waveform of the time series of the heartbeat; acquiring correlation threshold data which describes at least one threshold value of the correlation of the waveform of the time series of the heartbeat (see Chahine [0037]; if a sensor was active at a specific time then the processor can determine the magnitude of the signal at that time as well as if the signal contains the necessary ECG features);
determining waveform quality data based on the waveform correlation data and the correlation threshold data by comparing the correlation of the waveform of the time series of the heartbeat to the at least one threshold value of the correlation of the waveform of the time series of the heartbeat (see Chahine [0025-0026]; examine collected signals for appropriate signal quality, where it is assumed that signals of poor/unacceptable quality can be due to direct skin contact of a sensor below a contact threshold),
wherein the waveform quality data is determined to indicate a predetermined quality of the waveform of the time series of the heartbeat if the comparison results in that waveform of the time series of the heartbeat has a predetermined relationship to the at least one threshold value of the correlation of the waveform of the time series of the heartbeat (see Chahine [0025]; signals are examined for quality based by the controller 14 where signals may be of unacceptable quality for waveform features including signal amplitude below a set amplitude minimum, signal detail such as below a set number of desired signal characteristics/features present such as peaks, intervals and other ECG indicators), and
wherein the setup quality data is determined based on the waveform quality data; wherein the setup quality data describes the quality of the positioning of a heartbeat detector on the anatomical body part and is determined based on the at least one of the waveform correlation data or the correlation threshold data (see Chahine [0025-0026]; the signal quality is determined by the contact between the sensor and the user, signals are examined for quality and may be deemed of an unacceptable quality due to feature measurements which may be a result of poor sensor contact, in which case the setup quality it deemed to be poor and a new sensor pairing may be selected instead).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Ishikawa’s method for determining the quality of a sensor setup with the heartbeat signal quality determination as made by Chahine. One of ordinary skill in the art would have been motivated to make this modification in order to collect a signal having the appropriate quality where the quality is determined by the contact of the sensors with the user, and there are a plurality of sensors to select from, so the sensors having the best contact/signal quality can be used (Chahine [0025-0026]).
Claim(s) 11, 13, and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ishikawa (US 20210275103 A1) in view of Chahine et al (US 20220007986 A1) and Bhushan et al (US 20170347899 A1).
Regarding claim 11 and 13, Ishikawa and Chahine teach the method according to claim 10. Ishikawa is silent regarding the method further comprising one or more of:
determining, based on the heartbeat signal data, waveform correlation data describing a correlation of the waveform of the time series of the heartbeat;
acquiring correlation threshold data which describes at least one threshold value of the correlation of the waveform of the time series of the heartbeat;
determining, based on the heartbeat signal data, heartbeat spectrum data describing an energy spectrum of the time series of the heartbeat; and/or
acquiring spectrum comparison data describing a predetermined energy spectrum of the time series of the heartbeat,
wherein the setup quality data describes the quality of the positioning of a heartbeat detector on the anatomical body part and is determined based on the at least one of the waveform correlation data or the correlation threshold data and the heartbeat spectrum data or the spectrum comparison data; and
determining heartbeat spectrum quality data based on the heartbeat spectrum data and the spectrum comparison data by comparing the energy spectrum of the time series of the heartbeat to the predetermined energy spectrum of the time series of the heartbeat,
wherein the heartbeat spectrum quality data is determined to indicate a predetermined quality of the first energy spectrum of the time series of the heartbeat if the comparison results in that the energy spectrum of the time series of the heartbeat has a predetermined relationship to the predetermined energy spectrum of the time series of the heartbeat,
wherein the setup quality data is determined based on the heartbeat spectrum quality data.
Regarding claim 11 and 13, Bhushan teaches a method for measuring a heartbeat signal of a user using sensors in contact with the user’s skin, wherein acquiring the signal comprises determining a signal quality comprising (Bhushan [0025], [0072-0073])
acquiring spectrum comparison data describing a predetermined energy spectrum of the time series of the heartbeat (see Bhushan [0072-0073]; calculate the FFT of a measured ECG and the FFT of the ideal signal which may be compared to one another),
determining heartbeat spectrum quality data based on the heartbeat spectrum data and the spectrum comparison data by comparing the energy spectrum of the time series of the heartbeat to the predetermined energy spectrum of the time series of the heartbeat (see Bhushan [0072]; signal quality assessed by comparison of FFTs of the measured and ideal signals),
wherein the heartbeat spectrum quality data is determined to indicate a predetermined quality of the first energy spectrum of the time series of the heartbeat if the comparison results in that the energy spectrum of the time series of the heartbeat has a predetermined relationship to the predetermined energy spectrum of the time series of the heartbeat (see Bhushan [0072]; signal quality of each sensor is assessed, which may include comparison of FFTs of measured vs ideal signals, in order to calculate a confidence interval for the heartbeat signal), and
wherein the setup quality data is determined based on the waveform quality data (Bhushan [0072-0073]; signal quality has a threshold of 20 which assumes that a chi-squared value of more than 20 means that the signal is pure noise, it can be appreciated that this therefore indicates the setup quality).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Ishikawa’s method for determining the quality of a sensor setup with Bhushan’s signal quality measurement based on the heartbeat spectrum data. One of ordinary skill in the art would have been motivated to make this modification in order to determine the difference between the measured signal and an ideal signal to ensure the measured signal is falling within an acceptable range (Bhushan [0072-0073]).
Bhushan is silent regarding wherein the setup quality data describes the quality of the positioning of a heartbeat detector on the anatomical body part.
Chahine teaches wherein the setup quality data describes the quality of the positioning of a heartbeat detector on the anatomical body part (see Chahine [0025-0026]; the signal quality is determined by the contact between the sensor and the user, signals are examined for quality and may be deemed of an unacceptable quality due to feature measurements which may be a result of poor sensor contact, in which case the setup quality it deemed to be poor and a new sensor pairing may be selected instead).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to use Bhushan’s spectral quality data as an input to determine setup quality data as taught by Chahine. One of ordinary skill in the art would have been motivated to make this modification in order to collect a signal having the appropriate quality where the quality is determined by the contact of the sensors with the user, and there are a plurality of sensors to select from, so the sensors having the best contact/signal quality can be used (Chahine [0025-0026]).
Regarding claim 14, Ishikawa and Chahine teach the method according to claim 10. Ishikawa is silent regarding determining the setup quality data to describe a predetermined quality of the positioning, on the anatomical body part, of a heartbeat detector used to acquire the heartbeat of the patient if the waveform quality data has been determined to indicate the predetermined quality of the waveform of the time series of the heartbeat and the heartbeat spectrum quality data has been determined to indicate the predetermined quality of the first energy spectrum of the time series of the heartbeat.
Chahine teaches determining the setup quality data to describe a predetermined quality of the positioning, on the anatomical body part, of a heartbeat detector used to acquire the heartbeat of the patient if the waveform quality data has been determined to indicate the predetermined quality of the waveform of the time series of the heartbeat (see Chahine [0025-0026]; collected ECG signals 6b can be examined by controller 14 for signal quality and real time change in potential direct contact between the sensors and the user, where it can be deemed that signals of poor quality can be due to the contact of the sensor and the user being below a contact threshold).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Ishikawa’s method for determining the quality of a sensor setup with the heartbeat signal quality determination as made by Chahine. One of ordinary skill in the art would have been motivated to make this modification in order to collect a signal having the appropriate quality where the quality is determined by the contact of the sensors with the user, and there are a plurality of sensors to select from, so the sensors having the best contact/signal quality can be used (Chahine [0025-0026]).
Chahine is silent regarding determining the setup quality data to describe a predetermined quality of the positioning, on the anatomical body part, of a heartbeat detector used to acquire the heartbeat of the patient if the heartbeat spectrum quality data has been determined to indicate the predetermined quality of the first energy spectrum of the time series of the heartbeat.
Bhushan teaches wherein the heartbeat spectrum quality data is determined to indicate a predetermined quality of the first energy spectrum of the time series of the heartbeat if the comparison results in that the energy spectrum of the time series of the heartbeat has a predetermined relationship to the predetermined energy spectrum of the time series of the heartbeat (see Bhushan [0072]; signal quality of each sensor is assessed, which may include comparison of FFTs of measured vs ideal signals, in order to calculate a confidence interval for the heartbeat signal).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to use Bhushan’s spectral quality data as an input to determine setup quality data as taught by Chahine. One of ordinary skill in the art would have been motivated to make this modification in order to determine the difference between the measured signal and an ideal signal to ensure the measured signal is falling within an acceptable range (Bhushan [0072-0073]).
Conclusion
THIS ACTION IS MADE FINAL. 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 ALISHA J SIRCAR whose telephone number is (571)272-0450. The examiner can normally be reached Monday - Thursday 9-6:30, Friday 9-5:30 CT.
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/A.J.S./Examiner, Art Unit 3792
/ALLEN PORTER/ Primary Examiner, Art Unit 3796
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