DETAILED ACTION
Non-Final Rejection
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) submitted on 06/26/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Election/Restriction
Applicants’ election with traverse of Species I, Claim(s) 1-35, as illustrated in Figure(s) 1, and further disclosed in [0039]-[0051] in the reply filed on 07/23/2026 is acknowledged. The traversal is on the ground(s) that Claims 1-35 are readable at least (e.g., not only) on the allegedly patentably distinct Species I. Assignee's representative traverses on the grounds that 1) it has not been demonstrated that the allegedly patentably distinct Species I-IX are independent or distinct as alleged, or that the allegedly patentably distinct Species recite mutually exclusive characteristics; that 2) Independent claims 1 and 19 are generic to claims dependent claims 2-18 and 20-35, respectively, each of which read on the allegedly patentably distinct Species I; and that 3) the burden of search and examination of the species is not unduly cumbersome. It is nevertheless noted that rejoinder opportunities may exist in subsequent prosecution. The requirement is still deemed proper and is therefore made FINAL.
Specification
The lengthy specification (more than 20 pages) has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant's cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The Claim(s) in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “liveness detection classifier component”, “determination component”, and “power management component” in Claim(s) 1.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 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.
Claim(s) 1-13 and 19-30 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by SUN (MEMS ultrasonic transducers for safe, low-power and portable eye-blinking monitoring, 2022, Microsystems & Nanoengineering, Vol. 8, No. 63, Pages 1-14), hereinafter “Sun”.
Referring to Claim 1, SUN teaches an apparatus (Abstract), comprising:
a processor that executes computer-executable components stored in a computer-readable memory, the computer-executable components comprising (the “PC” in Fig. 5.):
a liveness detection classifier component that generates a classification of ultrasonic information (Fig. 8c on page 11, four state classifications of the eye based on signals from ultrasonic transducer arrays in Fig. 5.) as indicative of proximity or liveness of a user of a wearable device comprising the apparatus via a liveness classification algorithm (Fig. 6, the depicted blink states meet the claimed single “eye blink”, “predetermined set of eye blinks”, and “predetermined blinking pattern” (one eye open, one eye closed); and wherein it is the Examiners’ broadest reasonable interpretation that liveness of a user of a wearable device corresponds to “eye blink”, “predetermined set of eye blinks”, and “predetermined blinking pattern” );
a determination component that generates a determination of the at least one of the proximity or the liveness of the user of the wearable device based at least in part on the classification (See page 12, left column: “The first 100 sets of data at the beginning of the experiment are divided into two clusters, which are regarded as labeled data. The midpoint of the two cluster centers is used as the criterion to classify the subsequent data. After that, the classified data are added to the cluster, the cluster center is recalculated, and the criteria are updated.”); and
a power management component configured to select at least one of a power state or an operating mode of the wearable device based at least in part on the determination of the at least one of the proximity or the liveness of the user of the wearable device (See page 12, right column: “I In the current detection system, the driving voltage is 20 V PP' After adoption of phased array control and integration with the CMOS circuit, the transducer circuit noise decreases in addition to emission sensitivity increase and parasitic capacitance reduction. Therefore, the driving voltage and power consumption can be reduced to further meet the requirements of portable applications.”)
Referring to Claim 2, SUN teaches the apparatus of claim 1, further comprising: an ultrasonic transceiver that generates the ultrasonic information (See Fig. 5.).
Referring to Claim 3, SUN teaches the apparatus of claim 2, wherein the ultrasonic information comprises ultrasonic time of flight range information (See page 12, right column: “Based on time-of-flight (TOF) pulse echoes and a dynamic unsupervised learning method, we achieved eye state recognition as a demonstration of portable human blink monitoring.”).
Referring to Claim 4, SUN teaches the apparatus of claim 1, wherein the ultrasonic transceiver is positioned within the wearable device such that the field of view of the ultrasonic transceiver will cover at least one body part of the user that experiences movement relative to the ultrasonic transceiver when the wearable device is being worn by the user (See Figs. 5-6.).
Referring to Claim 5, SUN teaches the apparatus of claim 1, wherein the determination of liveness is based at least in part on at least one of the proximity or a change in the proximity, a physiological event detection, a predetermined time delay, or a predetermined classification cycle delay (See Fig. 5 and the Abstract; “Low-power pulse-echo ultrasound featuring biosafety is transmitted and received by microelectromechanical system (MEMS) ultrasonic transducers seamlessly integrated on glasses.”).
Referring to Claim 6, SUN teaches the apparatus of claim 5, wherein the physiological event detection comprises at least one of a pulse rate detection, a circulatory flow detection, a respiratory event detection, an eye movement detection, an eye blink detection, a facial movement detection, or a facial expression change detection ((See Figs. 6, Fig. 8a., and 8c.).
Referring to Claim 7, SUN teaches the apparatus of claim 1, wherein the determination component is further configured to generate the determination of the at least one of the proximity or the liveness of the user of the wearable device as a donned or doffed state of the wearable device (Detection/classification of one of the four states in Fig. 8c implies that the system first determines that the glasses are worn.).
Referring to Claim 8, SUN teaches the apparatus of claim 7, wherein the ultrasonic transceiver is configured to emit ultrasonic pulses and receive echoes as the ultrasonic information (See Fig. 5 and the Abstract; “Low-power pulse-echo ultrasound featuring biosafety is transmitted and received by microelectromechanical system (MEMS) ultrasonic transducers seamlessly integrated on glasses.”), and wherein the liveness classification algorithm is configured to analyze expected echoes of the ultrasonic pulses on the user to determine whether the wearable device is being worn by the user (See Figs. 6, 8a., and 8c.).
Referring to Claim 9, SUN teaches the apparatus of claim 8, wherein the liveness classification algorithm is based at least in part on a machine learning model trained on captured and classified ultrasonic information received during a plurality of states of use of a test wearable device (See page 12, left column: “The first 100 sets of data at the beginning of the experiment are divided into two clusters, which are regarded as labeled data. The midpoint of the two cluster centers is used as the criterion to classify the subsequent data. After that, the classified data are added to the cluster, the cluster center is recalculated, and the criteria are updated. Compared with supervised learning, this method does not need to label large amounts of data.”).
Referring to Claim 10, SUN teaches the apparatus of claim 9, wherein the machine learning model is based on a liveness detection classifier decision tree trained on the captured and the classified ultrasonic information received during the plurality of states of use of the test wearable device (See page 12, left column: “The first 100 sets of data at the beginning of the experiment are divided into two clusters, which are regarded as labeled data. The midpoint of the two cluster centers is used as the criterion to classify the subsequent data. After that, the classified data are added to the cluster, the cluster center is recalculated, and the criteria are updated. Compared with supervised learning, this method does not need to label large amounts of data.”).
Referring to Claim 11, SUN teaches the apparatus of claim 10, wherein the liveness detection classifier component is configured to generate the classification of the ultrasonic information as indicative of the at least one of the proximity or the liveness based at least in part on the liveness classification algorithm, wherein the liveness classification algorithm is configured to compute magnitude of samples of ultrasonic information, wherein the liveness classification algorithm is configured to normalize the magnitude of samples of ultrasonic information as a function of ultrasonic transceiver operating frequency to generate normalized magnitude ultrasonic information, wherein the liveness classification algorithm is configured to compute a set of feature vectors in the normalized magnitude ultrasonic information, and wherein the liveness classification algorithm is configured to determine a set of feature classification labels and corresponding confidence factors using the liveness detection classifier decision tree (See the normalized voltage in Fig. 6.; page 12, left column: “The first 100 sets of data at the beginning of the experiment are divided into two clusters, which are regarded as labeled data. The midpoint of the two cluster centers is used as the criterion to classify the subsequent data. After that, the classified data are added to the cluster, the cluster center is recalculated, and the criteria are updated. Compared with supervised learning, this method does not need to label large amounts of data.” K-means clustering assigns vectors to centroids.).
Referring to Claim 12, SUN teaches the apparatus of claim 11, wherein the determination component is configured to generate the determination of the at least one of the proximity or the liveness based at least in part on the set of feature classification labels and corresponding confidence factors (See page 12, left column: “K-means clustering is performed on the first 100 groups of TOF data obtained from the experiment”).
Referring to Claim 13, SUN teaches the apparatus of claim 12, wherein the determination component is further configured to generate the determination of the at least one of the proximity or the liveness of the user of the wearable device as the donned or the doffed state of the wearable device, based at least in part on at least one of an eye blink detection classification component determination of an eye blink or repeated cycles of a determined doff state (Detection/classification of one of the four states in Fig. 8c implies that the system first determines that the glasses are worn.).
Claim 19 is essentially the same as Claim 1 and refers to a system for the method of Claim 1. Therefore Claim 19 is rejected for the same reasons as applied to Claim 1 above.
Claim 20 is essentially the same as Claim 3 and is rejected for the same reasons as applied to Claim 3 above.
Claim 21 is essentially the same as Claim 4 and is rejected for the same reasons as applied to Claim 4 above.
Claim 22 is essentially the same as Claim 5 and is rejected for the same reasons as applied to Claim 5 above.
Claim 23 is essentially the same as Claim 6 and is rejected for the same reasons as applied to Claim 6 above.
Claim 24 is essentially the same as Claim 7 and is rejected for the same reasons as applied to Claim 7 above.
Claim 25 is essentially the same as Claim 8 and is rejected for the same reasons as applied to Claim 8 above.
Claim 26 is essentially the same as Claim 9 and is rejected for the same reasons as applied to Claim 9 above.
Claim 27 is essentially the same as Claim 10 and is rejected for the same reasons as applied to Claim 10 above.
Claim 28 is essentially the same as Claim 11 and is rejected for the same reasons as applied to Claim 11 above.
Claim 29 is essentially the same as Claim 12 and is rejected for the same reasons as applied to Claim 12 above.
Claim 30 is essentially the same as Claim 13 and is rejected for the same reasons as applied to Claim 13 above.
Claim Rejections - 35 USC § 103
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.
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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 14 and 31 are rejected under 35 U.S.C. 103 as being unpatentable over SUN as applied to Claim(s) 1 and 19 above, and further in view of AKHBARI (US 2019/0354238 A1).
Referring to Claim 14, SUN teaches the apparatus of claim 9, but doesn’t explicitly teach wherein the machine learning model is based on a liveness detection classifier recursive neural network (RNN) trained on the captured and the classified ultrasonic information received during the plurality of states of use of the test wearable device.
AKHBARI teaches the machine learning model is based on a liveness detection classifier recursive neural network (RNN) trained on the captured and the classified ultrasonic information received during the plurality of states of use of the test wearable device (See [0082]; Figs. 55-57).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the apparatus disclosed in SUN with the recursive neural network (RNN) taught in AKHBARI with a reasonable expectation of success because it would have targeted fish at a specific depth by creating downward pressure that forces the lure underwater, as taught by AKHBARI ([0082]; Figs. 55-57).
Claim 31 is essentially the same as Claim 14 and is rejected for the same reasons as applied to Claim 14 above.
Claim(s) 15-17 and 32-34 are rejected under 35 U.S.C. 103 as being unpatentable over SUN in view of AKHBARI as applied to Claim(s) 14 above, and further in view of GINERICA (US 2021/0383202 A1).
Referring to Claim 15, SUN teaches the apparatus of claim 14, but doesn’t explicitly teach wherein the liveness detection classifier RNN comprises a gated-recurrent unit (GRU) trained on the captured and the classified ultrasonic information received during the plurality of states of use of the test wearable device.
GINERICA teaches the liveness detection classifier RNN comprises a gated-recurrent unit (GRU) ([0023]; [0053]) trained on the captured and the classified ultrasonic information received during the plurality of states of use of the test wearable device ([0023]; [0053]; [0060]).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the apparatus disclosed in SUN with gated-recurrent unit (GRU) taught in GINERICA with a reasonable expectation of success because it would have provided a temporal neural-network architecture capable of processing sequential ultrasonic sensor observation while encoding and remembering previous states, thereby improving the handling of time-dependent sensor information, as taught by GINERICA ([0023]; [0053]-[0058]).
Referring to Claim 16, SUN teaches the apparatus of claim 15, but doesn’t explicitly teach wherein the GRU, for a plurality of measurement vectors associated with the ultrasonic information, is configured to generate a classification prediction of the donned or the doffed state of the wearable device.
GINERICA teaches the GRU, for a plurality of measurement vectors associated with the ultrasonic information, is configured to generate a classification prediction of the donned or the doffed state of the wearable device ([0053]; [0058]).
Referring to Claim 17, SUN teaches the apparatus of claim 16, wherein the classification prediction of the donned or the doffed state of the wearable device is based at least in part on the at least one of the proximity or the liveness of the user of the wearable device (Detection/classification of one of the four states in Fig. 8c implies that the system first determines that the glasses are worn.).
Claim 32 is essentially the same as Claim 15 and is rejected for the same reasons as applied to Claim 15 above.
Claim 33 is essentially the same as Claim 16 and is rejected for the same reasons as applied to Claim 16 above.
Claim 34 is essentially the same as Claim 17 and is rejected for the same reasons as applied to Claim 17 above.
Claim(s) 18 and 35 is/are rejected under 35 U.S.C. 103 as being unpatentable over SUN in view of AKHBARI in view of GINERICA as applied to Claim(s) 15 above, and further in view of SCALLY (US 2017/0261610 A1).
Referring to Claim 18, SUN teaches the apparatus of claim 16, but doesn’t explicitly teach wherein the classification prediction of the donned or the doffed state of the wearable device is based at least in part on the liveness of the user of the wearable device, which is based at least in part on detection of at least one of an eye movement, an eye blink, a facial movement, or a facial expression change in at least one echo of the echoes in the ultrasonic information as processed by the GRU.
SCALLY teaches the classification prediction of the donned or the doffed state of the wearable device is based at least in part on the liveness of the user of the wearable device, which is based at least in part on detection of at least one of an eye movement, an eye blink, a facial movement, or a facial expression change in at least one echo of the echoes in the ultrasonic information as processed by the GRU ([0029]; [0041]; [0049]).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the apparatus disclosed in SUN with detecting eye movement from ultrasonic echoes taught in SCALLY with a reasonable expectation of success because it would have provided additional user-state information by detecting movement and orientation of the user’s eye from reflected ultrasonic signals without relying on optional imaging, including while the eye is closes, as taught by SCALLY ([0029]).
Claim 35 is essentially the same as Claim 18 and is rejected for the same reasons as applied to Claim 18 above.
Examiner’s Note
Examiner has pointed out particular references contained in the prior art of record in the body of this action for the convenience of the Applicant. However, any citation to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275, 277 (CCPA 1968)). Applicant, in preparing the response, should consider fully the entire reference as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMIE M N'DURE whose telephone number is 571-272-6031. The examiner can normally be reached on 8AM-5:30PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Isam Alsomiri can be reached on 571-272-6970. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/AMIE M NDURE/Examiner, Art Unit 3645
/ABDALLAH ABULABAN/Primary Examiner, Art Unit 3645
