DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 12-16 and 18-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent 11,439,344 to Zhang et al. in view of “Improving Sleep Quality Assessment Using Wearable Sensors by Including Information From Postural/Sleep Position Changes and Body Acceleration: A Comparison of Chest-Worn Sensors, Wrist Actigraphy, and Polysomnography” by Razjouyan et al.
As to claim 12, 22, and 23, Zhang discloses a sleep and arousal determination system, comprising at least one processor configured to execute a program to cause each of following steps to be performed:
an acquisition step of acquiring a signal indicating acceleration of at least a part of body of a user (Zhang column 25 lines 57-67 and column 26 lines 1-55 see “The characteristics and/or STI (e.g. motion information) may comprise: … acceleration” and “the object may be a person” column 27 lines 29-33 also column 52 lines 10-37 where sleep related motions are monitored);
a determination step of determining sleep and arousal of the user based on a specific frequency component included in the signal indicating the acceleration and preset reference information (Zhang column 25 lines 57-67 and column 26 lines 1-55 see “The characteristics and/or STI (e.g. motion information) may comprise: … acceleration”; column 52 lines 60-67 and column 53 lines 1-67 where “A sleep stage may be classified as "awake" if at least one of: the motion ratio is greater than a second threshold, and/or the breathing ratio is less than a third threshold. The sleep stage may be classified as "asleep" if at least one of: the motion ratio is less than the second threshold” (where thresholds are preset information); and column 15 lines 3-58 see signal strength processing).
However, Zhang does not explicitly teach acquiring a three-dimensional acceleration vector from an acceleration vector attached to the body of a user and determining sleep/arousal based on the corresponding three dimensional acceleration vector. Razjouyan discloses acquiring a three-dimensional acceleration vector from an acceleration vector attached to the body of a user and determining sleep/arousal based on the corresponding three dimensional acceleration vector (Razjouyan see An algorithm for analyzing the accelerations data from the chest sensor was developed using the following steps: PREPROCESSING: The raw three-dimensional acceleration data were processed with a band-pass filter at cutoff frequencies of 0.1953 Hz and 12.5 Hz to remove the gravity component and high-frequency noise that was not originated from human body movements, a vector magnitude (VM) of the filtered acceleration data, and see classifying sleep/wake epochs in “Statistical Analysis” section).
It would have been obvious to one of ordinary skill in the art before the effective filing date to utilize a wearable sensor to reduce costs and improve accuracy.
As to claim 13, see the discussion of claim 12, additionally, Zhang discloses the sleep and arousal determination system, the processor configured to execute the program further to cause each of following steps to be performed:
a bandwidth limitation step of limiting a frequency component included in the signal indicating the acceleration to the specific frequency component (Zhang column 25 lines 57-67 and column 23 lines 1-26),
a transform step of Fourier transforming a signal configured of the specific frequency component to generate data for determination (Zhang column 38 lines 1-39), and
the determination step of determining sleep and arousal of the user based on the data for determination and preset reference information column 63 lines 51-67).
Razjouyan disclose a bandwidth limitation step including the signal corresponding to the three-dimensional acceleration vector (Razjouyan see preprocessing)
As to claim 14, see the discussion of claim 12, additionally, Razjouyan discloses the sleep and arousal determination system, the processor configured to execute the program to cause following step to be performed:
the bandwidth limitation step of limiting the frequency component included in the information including the signal to the specific frequency component using a band-pass filter (Razjouyan see preprocessing step).
As to claim 15, see the discussion of claim 13, additionally, Zhang discloses the sleep and arousal determination system, the processor configured to execute the program further to cause following step to be performed:
a correction step of standardizing and correcting distribution of frequency component of the data for determination (Zhang column 60 lines 1-51).
As to claim 16, see the discussion of claim 13, additionally, Zhang discloses the sleep and arousal determination system, the processor configured to execute the program further to cause each of following steps to be performed:
a correction step of standardizing and correcting distribution of frequency component of the signal in the acquired infomration (Zhang column 60 lines 1-51), and
the bandwidth limitation step of limiting the standardized frequency component to the specific frequency component (Zhang column 25 lines 57-67 and column 23 lines 1-26).
As to claim 18, see the discussion of claim 12, additionally, Zhang discloses the sleep and arousal determination system, wherein:
the preset reference information is a learned model that is allowed to learn correlation between the specific frequency component and the sleep and arousal (Zhang figure 11 1116).
As to claim 19, see the discussion of claim 18, additionally, Zhang discloses the sleep and arousal determination system, wherein:
The correlation between the specific frequency component and the sleep and arousal in the learned model is learned by acquiring the signal at a sampling frequency of 5 Hz or higher (Zhang column 55 lines 50-55).
As to claim 20, see the discussion of claim 19, additionally, Zhang discloses the sleep and arousal determination system, wherein:
the learned model is a learned model in which correlation between the specific frequency component and the sleep and arousal is learned by acquiring the signal at a sampling frequency of 25 Hz or higher (Zhang column 55 lines 50-55).
As to claim 21, see the discussion of claim 12, additionally, Razjouyan discloses the sleep and arousal determination system, the processor configured to execute the program to cause following step to be performed:
discloses the determination step of specifying a feature quantity for each epoch of a plurality of epochs defined by a predetermined time period in a time series manner based on the based on the specific frequency component, the plurality of epochs including a desired epoch and a recent epoch earlier than the desired epoch in the time series manner (Razjouyan see “Algorithm”);
determining sleep and arousal of the user based on, among the epoch, the feature quantity of a desired epoch, the feature quantity of a recent epoch past the desired epoch in time series, and the reference information (Razjouyan see “Algorithm”).
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent 11,439,344 to Zhang et al. in view of “Improving Sleep Quality Assessment Using Wearable Sensors by Including Information From Postural/Sleep Position Changes and Body Acceleration: A Comparison of Chest-Worn Sensors, Wrist Actigraphy, and Polysomnography” by Razjouyan et al. in view of OFFICIAL NOTICE
As to claim 17, see the discussion of claim 12, however, Zhang does not explicitly teach acquiring the signal by analog-to-digital conversion of the acceleration with a bit rate of 8 bits or more. Examiner takes OFFICIAL NOTICE that performing analog-to-digital conversions of acceleration data at a bit rate of 8 bits or more is exceedingly well known in the art. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize this technology to allow for near real time analysis of user health data.
Response to Arguments
Applicant’s arguments with respect to the claims have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ELIZA A LAM/Primary Examiner, Art Unit 3681