DETAILED ACTION
Response to Arguments
Applicant’s arguments filed 9/8/2026 with respect to 112 (f) have been fully considered and are persuasive. However, Applicant’s argument regarding 103 rejection are not persuasive.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
In this case applicant argued “First, Nduka2 paragraph [0016] identifies a facial expression, not an individual. The passage matches detected magnitude and direction of movement to "a respective stored magnitude and direction of movement for each of those optical flow sensors for that facial expression." (Emphasis added.) The stored templates in Nduka2 are expression-specific, not person-specific: matching them tells the system what expression was made, not who made it. Nduka2 itself confirms this purpose, stating at paragraph [0078] that its system enables "the determination of facial expression”. The examiner disagrees because applicants improperly treat para. [16] in isolation. The rejection relies on the combined teaching of Nduka in view of Nduka2, where Nduka provides the person specific authentication that applicant alleges is missing. Nduka teaches enrolling and storing facial skin characteristics (time-varying signals) for individual users, comparing skin information with stored information, and authenticating the captured information as belonging to a particular user. Nduka further teaches extracting the direction and speed of facial skin movement and states that skin velocity may distinguish subjects. Nduka also teaches that the manner in which a wrinkles or other facial features develops over time differs among people and provides user identifying information for authentication against a stored database. for further clarification, see the following Paragraphs.
[Abstract “Some embodiments are directed to a biometric authentication system including headwear having a plurality of biosensors each configured to sample muscle activity so as to obtain a respective time-varying signal, a data store for storing a data set representing characteristic muscle activity for one or more users, and a processor configured to process the time-varying signals from the biosensors in dependence on the stored data set so as to determine a correspondence between a time-varying signal and characteristic muscle activity of one of the one or more users, and in dependence on the determined correspondence, authenticate the time-varying signals as being associated with that user.
Para. 2 systems for detecting facial muscle activity and facial skin characteristics
Para. 12 “Suitably the data set includes a stored time-varying signal, and the processor is configured to process the time-varying signals in dependence on the stored data set by comparing the time-varying signals to the stored time-varying signal. Suitably the data set includes one or more stored signal features, and the processor is configured to process the time-varying signals in dependence on the stored data set by comparing one or more signal features of the time-varying signals to the one or more stored signal features”
Para. 23 “Suitably one or more of the plurality of biosensors are optical sensors configured to capture a series of images of an area of skin of a user so as to obtain a time-varying signal characteristic of the area of skin imaged in the captured series of images; the data store is configured for storing a further data set representing skin characteristics for the one or more users; and the processor is configured to process the image signal in dependence on the stored further data set so as to determine a correspondence between the image signal and the skin characteristics for the one or more users, and in dependence on the determined correspondence, to authenticate the image signal as being associated with one of the one or more users.”
Para. 183 “Optical sensors may be optical flow sensors configured to output as a time-varying signal a vector describing the direction and/or magnitude of skin movement over some predefined time period which is representative of muscle activity. For example, an optical flow sensor may be arranged at wearable apparatus to measure the movement of an area of skin overlying a muscle where the movement of that area of skin is representative of the activity of that muscle.”
Para. 188 “The area of the skin can be imaged during an enrolment phase, similar to the discussion above in the context of time-varying electrical muscle activity signals. Thus, the system is suitably configured to store a data set representing skin characteristics for one or more user. The data set can be stored at one or both of the headwear 100, 200 and the remote device 400, as discussed herein. Suitably, where an optical sensor is provided, the processor is configured to process the image signal in dependence on the stored data set so as to determine a correspondence between the image signal and the skin characteristics for the one or more users, and in dependence on the determined correspondence, to authenticate the image signal as being associated with one of the one or more users].
However, Nduka2 is introduced to provide additional details concerning the comparison of detected skin movement vectors with stored movement vectors [see para. 152], not because Nduka didn’t teach user authentication based on user’s skin movement. Since direction of facial skin movement varies from person to person, Nduka2 teaches a predefined series of facial expression may be used to authenticate a user.
Also, for further clarification see the following paragraphs in Nduka2
[Para. 2, Some embodiments relate to a system including wearable apparatus for detecting facial muscle activity and wearable apparatus for detecting facial skin movement.
Abstract, Some embodiments are directed to a biometric authentication system including headwear having a plurality of biosensors each configured to sample muscle activity so as to obtain a respective time-varying signal, a data store for storing a data set representing characteristic muscle activity for one or more users, and a processor configured to process (compare) the time-varying signals from the biosensors in dependence on the stored data set so as to determine a correspondence (match) between a time-varying signal and characteristic muscle activity of one of the one or more users, and in dependence on the determined correspondence, authenticate the time-varying signals as being associated with that user.
Para. 8, each optical flow sensor being configured to capture time-varying data describing movement of the respective area of skin substantially in the plane of the imaged area of skin.
Para. 11, The time-varying data may include one or more of: vector information describing the magnitude and direction of movement of the area of skin; and a time series of images of the area of skin.
Para. 16, The processor may be configured to identify a facial expression when the magnitude and direction of movement detected at each of one or more of the optical flow sensors matches within predefined bounds a respective stored magnitude and direction of movement for each of those optical flow sensors for that facial expression.]
Applicant also argued that “Second, the movements detected by Nduka2 are not "facial skin micromovements" as that term is used in claim 561. Nduka2's optical flow sensors track skin displacement produced by gross expressions
such as surprise and frowning. See Nduka2, Figs. 11(a) and 11(b). The term "facial skin micromovements" must be given its meaning in light of the specification, which describes them as "skin motions on the face that may be detectable using a sensor, but which might not be readily detectable to the naked eye," occurring "in the range of micrometers to millimeters." Specification at paragraph [0153]. Even taking Nduka2's expression-driven displacement at face value, the Examiner has not shown that the cited references teach or suggest the "particular facial skin micromovements" and "reference facial skin micromovements" recited by claim 561”.
Examiner disagrees because applicant’s proposed distinction is inconsistent with the claim language and applicant’s own specification. Para. 153 of pending applicant, states that facial skin micromovement may form part of a larger scale skin movement visible to the naked eye [Para. 153 “In some cases, the facial skin micromovements are part of a larger-scale skin movement visible to the naked eye (e.g., a smile may involve many facial skin micromovements).”]. The specification provides a smile as an example of a visible movement that may include numerous facial skin micromovements. Since the claim doesn’t explicitly define what “micromovement” is, any “small” movement facial skin movement, i.e. smiling, could be considered a micromovement.
Nduka2 also doesn’t characterize all expression related movements as gross movements. Para. 186, and Para. 187 states distinguishing among brief micro-expressions, small or normal expression, and gross expressions. These paragraphs explain that optical flow sensors may capture brief micro expressions and provide a signal for small or normal expressions.
Furthermore, fig. 11 (a) and (b) use arbitrary displacement units. The figures therefore do not establish that the detected movements have amplitudes outside the micrometer to millimeter ranges; Also, nowhere in the claim states micrometer or millimeters ranges.
Applicant also argued “Third, the Examiner's rationale for combining Agrafioti is conclusory. A single boilerplate paragraph - stating that the modification "improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access" - is repeated verbatim for every Agrafioti-based limitation. For claim 583, for example, the Examiner recites the missing element as "initiating a secured pairing based on authentication," which bears no relation to a claim that merely recites a list of computing device types. Moreover, Agrafioti is directed to an ECG-based, wrist-worn biometric device that preauthorizes a user through an authorized authentication device. The Examiner has not articulated any reason why a person of ordinary skill in the art would graft that architecture onto head-mounted optical skin sensing, other than by reciting the alleged benefit as the reason for the combination. Such circular reasoning does not satisfy the requirement for an articulated rationale with a rational underpinning. See KSR Int'l Co. v.Teleflex Inc., 550 U.S. 398, 418 (2007)” examiner disagrees.
Applicant’s characterization of Agrafioti as limited to an ECG based wrist device is inaccurate. Agrafioti describes biometric information broadly and identifies facial characteristics, EMG information, optical information and other biometric modalities. Agrafioti also identifies glasses, hates, and headbands as possible wearable device configuration [see para. 45 and 89].
Nduka in view Nduka2 provides facial biometric authentication determination, while Agrafioti provides access to restricted device.
Nduka in view of Nduka2 teaches Bluetooth enabled headwear, gernation of an authentication signal following successful biometric comparison, while Agrafieti teaches comparing biometric information with stored user profile, successful match places the wearable device in a preauthorized state for obtaining access to otherwise locked paired devices.
So, a person of ordinary skill would have applied Agrafioti’s preauthorization access procedure to Nduka’s Bluetooth enabled biometric headwear to improve Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
This constitutes an articulated technical rationale with underpinning, rather than merely stating the claimed result as the reasons for the combination.
Applicant’s argument also incorrectly assumes that claim 1 requires successful biometric authentication to initiate Bluetooth bonding. The body of claim 1 instead requires transmitting authentication information to another device “to enable authenticated access to the computing device”. Agrafioti supplies that authenticated access procedure for devices having a paired wireless relationship. If applicant intends to require authentication to initiate Bluetooth pairing operation, that particular sequence is not expressly recited in the body of the claim 1 (not in the preamble). Even though the examiner introduced the second teaching reference, the recitation that “initiating a secured pairing” has not been given patentable weight because it has been held that a preamble is denied the effect of a limitation where the claim is drawn to a structure and the portion of the claim following the preamble is a self-contained description of the structure not depending for completeness upon the introductory clause. Kropa v. Robie, 88 USPQ 478 (CCPA 1951).
Therefore, the rejection is maintained.
Here is additional related reference applicant may want to consider: Bakish et al. (US 2018/0232511).
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.
Claims 561-563, 566-568, 574-579, and 582-585 are rejected under 35 U.S.C. 103 as being unpatentable over NDUKA et al. (Pub. No. US 2020/0065569) in view of NDUKA et al. (Pub. No. US 2020/0034608 hereinafter Nduka2) further in view of Agrafioti et al. (Pub. No. US 2016/0267732).
Regarding claims 561, 584, and 585, Nduka teaches authenticating the user based on user’s skin, and coupling user device with remote device. [Para. 105 and 107]; a head mountable system for initiating a pairing (coupling) with a computing device (remote device) based on facial skin micromovements [Para. 105, Para. 2, “system for detecting facial biosignals for biometric authentication. In particular, some embodiments relate to systems for detecting facial muscle activity and facial skin characteristics”; Para. 176 “The authentication signal can provide the user access to functionality at the headwear and/or at a remote computing device”];
a wearable housing configured to be worn on a head (headwear) of an individual [Para. 10, 84, abstract, fig. 1, 2 and related description];
at least one light source incorporated with the wearable housing and configured to project light towards a facial region of the head [Para. 188 “the headwear 100, 200 may include at least one optical sensor as well as or instead of other types of sensor”; Para. 192 “The optical sensor includes a light source 1020, a light sensor 1022, and a processor 1024 for processing the output of the light sensor so as to determine a time-varying signal representative of dynamic information such as the relative movement between the sensor 1000 and the skin 1004. The light source 1020 is arranged to illuminate the patch of skin 1004 whose dynamic behaviour is to be detected”]; at least one detector (light sensor) incorporated with the wearable housing (headwear) and configured to receive light reflections from the facial region and to output associated reflection signals (time-varying signal) [Para. 188 “the headwear 100, 200 may include at least one optical sensor as well as or instead of other types of sensor”; Para. 192 “The optical sensor includes a light source 1020, a light sensor 1022, and a processor 1024 for processing the output of the light sensor so as to determine a time-varying signal representative of dynamic information such as the relative movement between the sensor 1000 and the skin 1004” and “a suitable lens 1002 may be provided in the reflected light path so as to, for a given distance 1005 from the sensor to the skin, focus the reflected light onto the light sensor 1022”];
a wireless transmitter (wireless connection module) configured to communicate with a computing device (remote computing device) to which access is restricted [Para. 107 “The wireless connection module 406 can, for example, include a Bluetooth module such as a module configured to communicate using the Bluetooth LE protocol” and “Preferably or advantageously, the headwear 100, 200
includes a Bluetooth module and the remote device 400 includes a Bluetooth module, permitting the headwear and the remote device to communicate with one another wirelessly using the Bluetooth protocol”; and Para. 177 “The non-authentication signal (or a lack of an authentication signal) can restrict user access to functionality at the headwear and/or at a remote computing device”]; and
at least one processor configured to: analyze the received light reflections for use in authenticating the individual based on reference facial skin [Para. 23, 27, 188, and 192. For clarification purposes, examiner added more citations stated below. Abstract “Some embodiments are directed to a biometric authentication system including headwear having a plurality of biosensors each configured to sample muscle activity so as to obtain a respective time-varying signal, a data store for storing a data set representing characteristic muscle activity for one or more users, and a processor configured to process the time-varying signals from the biosensors in dependence on the stored data set so as to determine a correspondence between a time-varying signal and characteristic muscle activity of one of the one or more users, and in dependence on the determined correspondence, authenticate the time-varying signals as being associated with that user.
Para. 2 systems for detecting facial muscle activity and facial skin characteristics
Para. 12 “Suitably the data set includes a stored time-varying signal, and the processor is configured to process the time-varying signals in dependence on the stored data set by comparing the time-varying signals to the stored time-varying signal. Suitably the data set includes one or more stored signal features, and the processor is configured to process the time-varying signals in dependence on the stored data set by comparing one or more signal features of the time-varying signals to the one or more stored signal features”
Para. 23 “Suitably one or more of the plurality of biosensors are optical sensors configured to capture a series of images of an area of skin of a user so as to obtain a time-varying signal characteristic of the area of skin imaged in the captured series of images; the data store is configured for storing a further data set representing skin characteristics for the one or more users; and the processor is configured to process the image signal in dependence on the stored further data set so as to determine a correspondence between the image signal and the skin characteristics for the one or more users, and in dependence on the determined correspondence, to authenticate the image signal as being associated with one of the one or more users.”
Para. 183 “Optical sensors may be optical flow sensors configured to output as a time-varying signal a vector describing the direction and/or magnitude of skin movement over some predefined time period which is representative of muscle activity. For example, an optical flow sensor may be arranged at wearable apparatus to measure the movement of an area of skin overlying a muscle where the movement of that area of skin is representative of the activity of that muscle.”
Para. 188 “The area of the skin can be imaged during an enrolment phase, similar to the discussion above in the context of time-varying electrical muscle activity signals. Thus, the system is suitably configured to store a data set representing skin characteristics for one or more user. The data set can be stored at one or both of the headwear 100, 200 and the remote device 400, as discussed herein. Suitably, where an optical sensor is provided, the processor is configured to process the image signal in dependence on the stored data set so as to determine a correspondence between the image signal and the skin characteristics for the one or more users, and in dependence on the determined correspondence, to authenticate the image signal as being associated with one of the one or more users.”].
However, Nduka doesn’t explicitly teach that the authentication is based on reference facial skin micromovements.
Nduka2 teaches the authentication is based on reference (stored magnitude and direction of movement) particular facial skin micromovements (movement of the respective area of skin) [Para. 8 “wearable apparatus including a plurality of optical flow sensors each located so as to, in use when the apparatus is worn, image an area of skin associated with one or more facial muscles, each optical flow sensor being configured to capture time-varying data describing movement of the respective area of skin substantially in the plane of the imaged area of skin”; Para. 16 “The processor may be configured to identify a facial expression when the magnitude and direction of movement detected at each of one or more of the optical flow sensors matches within predefined bounds a respective stored magnitude and direction of movement for each of those optical flow sensors for that facial expression”].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka’s optical sensor authentication processing by incorporating Nduka2’s teaching of particular facial skin micromovement compared with preference facial skin micromovements (stored magnitude and direction of movement) so that Nduka stored biometric comparison uses localized optical skin movement vectors. This modification improves Nduka by suing localized facial muscle skin movement vectors. This medication improves Nduka by using localized facial muscle skin movement features as discriminating biometric features, thereby improving user authentication accuracy.
Nduka in view of Nduka2 doesn’t explicitly teach initiating a secured pairing with a computing device based on authentication.
However, Agrafioti teaches initiating a secured pairing (Bluetooth) with a computing device based on authentication [Para. 132 “the particular steps employed for pairing the biometric device with the AAD may vary depending on the underlying technology employed by the biometric device and the AAD for sensing and communicating. For example, well-known methods for Bluetooth pairing may be employed”; Para. 133 “In at least one of the various embodiments, the AAD may be, for example, a smartphone, tablet, desktop computer, laptop computer, a terminal or network connected personal device”; and Para. 139 “additional authentication factors may be employed during enrollment for high security applications”].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access pared computing devices. This medication improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Nduka teaches transmit authentication information (signal) associated with the particular facial skin to the computing device [para. 57 “The term “authentication signal” as used herein refers to the signal sent by the biometric device to an access point which may be a physical access, an augmented reality access or access to a computer-based environment. The authentication signal may be a binary encoded sequence transmitted by wireless transmitter, such as a wireless protocol, or wired component, such as a cable or electrical wire”; Para. 176 “The authentication signal can provide the user access to functionality at the headwear and/or at a remote computing device”].
Nduka in view of Nduka2 doesn’t explicitly teach transmit authentication information associated with the particular facial skin micromovements to another device to enable authenticated access to the computing device.
Agrafioti teaches transmit authentication information associated with the particular facial skin (micromovements) to another device to enable authenticated access to the computing device [Para. 160 “If the answer is affirmative for both authorization and range to access point, the wearable biometric device may be arranged to transmit a control signal to the access point that affirmatively confirms that the biometric device is preauthorized” and “authorization for access to an access point may be enabled by the wearable device at multiple access points subsequent to a single authorization by the AAD”; and, Para. 164 “if a wearable biometric device has been preauthorized, other paired devices such as smartphones, computer terminals, tablets, laptops, environmental control systems which do not have the capability to authorize the wearable biometric device, but which would be otherwise locked, may be accessed via a control signal transmitted by the preauthorized wearable biometric device”].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access paired computing devices. This modification improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Regarding claim 562, Nduke teaches wherein another device is the computing device (remote device) [fig. 4b, 8 and related description].
Regarding claim 563, Nduke in view of Nduke2 further in view Agrafioti teach all claim limitations as stated above. Furthermore, Agrafioti teaches wherein another device is a server (cloud server) associated with the computing device [Para. 102 and 103].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access paired computing devices. This medication improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Regarding claim 566, Nduka in view of Nduka2 further in view of Agrafioti teach all claim limitations as stated above.
Furthermore, Agrafioti teaches wherein enabling the authenticated access to the computing device includes unlocking the computing device (Smartphone) [Para. 106].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access paired computing devices. This medication improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Regarding claim 567, Nduka in view of Nduka2 further in view of Agrafioti teach all claim limitations as stated above.
Furthermore, Agrafioti teaches wherein unlocking the computing device involves using a biosignature (biometric profile) in conjunction with an associated password or passphrase [Para. 136].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access paired computing devices. This medication improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Regarding claim 568, Nduka in view of Nduka2 further in view of Agrafioti teach all claim limitations as stated above.
Furthermore, Agrafioti teaches wherein enabling the authenticated access to the computing device includes communicating personal information over a wireless communication channel [Para. 137, and 94].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access paired computing devices. This medication improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Regarding claim 574, Nduka doesn’t explicitly teach the claim limitations.
However, NKUKA2 teaches wherein the at least one processor is configured to compare (matches) the particular facial skin micromovements (movement) with the reference facial skin micromovements (stored magnitude and direction of movement) to authenticate the individual [Para. 16].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka’s optical sensor authentication processing by incorporating Nduka2’s teaching of particular facial skin micromovement compared with preference facial skin micromovements (stored magnitude and direction of movement) so that Nduka stored biometric comparison uses localized optical skin movement vectors. This modification improves Nduka by suing localized facial muscle skin movement vectors. This medication improves Nduka by using localized facial muscle skin movement features as discriminating biometric features, thereby improving user authentication accuracy.
Regarding claim 575, Nduka doesn’t explicitly teach the claim limitations.
However, NKUKA2 (Pub. No. US 2020/0034608) teaches wherein the at least one processor is configured to use a trained machine learning model to analyze the particular facial skin micromovements relative to the reference facial skin micromovements to authenticate the individual [Para. 155].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka’s optical sensor authentication processing by incorporating Nduka2’s teaching of particular facial skin micromovement compared with preference facial skin micromovements (stored magnitude and direction of movement) so that Nduka stored biometric comparison uses localized optical skin movement vectors. This modification improves Nduka by suing localized facial muscle skin movement vectors. This medication improves Nduka by using localized facial muscle skin movement features as discriminating biometric features, thereby improving user authentication accuracy.
Regarding claim 576, Nduka in view of Nduka2 doesn’t explicitly teach initiating a secured pairing with a computing device based on authentication.
However, Agrafioti teaches wherein the at least one processor is further configured to determine that the computing device is located in proximity to the head mountable system [Para. 96].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access pared computing devices. This medication improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Regarding claim 577, Nduka in view of Nduka2 doesn’t explicitly teach initiating a secured pairing with a computing device based on authentication.
However, Agrafioti teaches wherein upon authenticating the individual and determining that the computing device is located in proximity to the head mountable system the at least one processor is configured to automatically establish a communication channel (control signals may be exchanged) between the computing device and the head mountable system [Para. 106 and 195].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access pared computing devices. This medication improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Regarding claim 578, Nduka in view of Nduka2 doesn’t explicitly teach initiating a secured pairing with a computing device based on authentication.
However, Agrafioti teaches a pairing interface (Bluetooth) for establishing a wireless communication channel (wireless connectivity module) with the computing device to which access is restricted, wherein the wireless communication channel enables data transfer (transmitting and receiving function) between the head mountable system and the computing device [Para. 132 and 94].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access pared computing devices. This medication improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Regarding claim 579 Nduka in view of Nduka2 doesn’t explicitly teach initiating a secured pairing with a computing device based on authentication.
However, Agrafioti teaches wherein the pairing interface is configured to search and detect (sense) compatible and nearby computing devices (access points) with which a connection is establishable [Para. 195].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access pared computing devices. This medication improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Regarding claim 582, Nduka in view of Nduka2 doesn’t explicitly teach initiating a secured pairing with a computing device based on authentication.
However, Agrafioti teaches wherein when the individual is not authenticated, the at least one processor is configured to generate a notification indicating that access to the computing device is denied (access to the encountered access point may be denied) [Para. 198 and 187].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access pared computing devices. This medication improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Regarding claim 583, Regarding claim 582, Nduka in view of Nduka2 doesn’t explicitly teach initiating a secured pairing with a computing device based on authentication.
However, Agrafioti teaches wherein the computing device includes at least one of a laptop, a PC, a tablet, a smartphone, a wearable device, an electronic door lock, an entry gate, a vehicle, a communications device, an earphone, a smart home device, or an loT (Internet of Things) device [Para. 164].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2’s authentication signal transmission by incorporating Agrafioti’s access control implementation so that Nduka’s authenticated facial signal result is used to unlock or access pared computing devices. This medication improves Nduka by making the generated authentication signal usable for restricted paired device access, thereby extending biometric authentication from user verification to controlled device access.
Claims 564 and 570-572 are rejected under 35 U.S.C. 103 as being unpatentable over NDUKA et al. (Pub. No. US 2020/0065569) in view of NDUKA et al. (Pub. No. US 2020/0034608 hereinafter Nduka2) further in view of Agrafioti et al. (Pub. No. US 2016/0267732) and further in view of Mutlu et al. (Pub. No. US 2020/0370879)..
Regarding claim 564, Nduka in view of Nduka2 further in view of Agrafioti doesn’t explicitly teach the claim limitations.
However, Mutlu teaches wherein the at least one processor is further configured to identify the individual based on a voice print (voice patterns) [Para. 68].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2 further in view of Agrafioti by incorporating Mutlu’s stored voice patterns to identify the wearer using voice derived biometric information. This modification improves Nduka by adding a second user specific biometric modality, thereby increasing authentication reliability.
Regarding claim 570, Nduka in view of Nduka2 further in view of Agrafioti doesn’t explicitly teach the claim limitations.
However, Mutlu teaches wherein the at least one processor is further configured to determine the reference facial skin micromovements (skin deformation information) by correlating audio signals (output signal) with specific facial skin micromovements associated with vocalized words (voiced command) [Para. 13, and 71].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2 further in view of Agrafioti by incorporating Mutlu’s stored voice patterns to identify the wearer using voice derived biometric information. This modification improves Nduka by adding a second user specific biometric modality, thereby increasing authentication reliability.
Regarding claim 571, Nduka in view of Nduka2 further in view of Agrafioti doesn’t explicitly teach the claim limitations.
However, Mutlu wherein the reference facial skin micromovements (skin deformation) correspond to muscle recruitment during pronunciation of a predefined expression (passcode) in an absence of a subsequent vocalization (inaudibly form words) [Para. 73].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2 further in view of Agrafioti by incorporating Mutlu’s stored voice patterns to identify the wearer using voice derived biometric information. This modification improves Nduka by adding a second user specific biometric modality, thereby increasing authentication reliability.
Regarding claim 572, Nduka in view of Nduka2 further in view of Agrafioti doesn’t explicitly teach the claim limitations.
However, Mutlu teaches wherein the reference facial skin micromovements correspond to muscle recruitment during pronunciation of one or more vocalized syllables (speech) [Para. 86].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2 further in view of Agrafioti by incorporating Mutlu’s stored voice patterns to identify the wearer using voice derived biometric information. This modification improves Nduka by adding a second user specific biometric modality, thereby increasing authentication reliability.
Claims 565, 580 and 581 are rejected under 35 U.S.C. 103 as being unpatentable over NDUKA et al. (Pub. No. US 2020/0065569) in view of NDUKA et al. (Pub. No. US 2020/0034608 hereinafter Nduka2) further in view of Agrafioti et al. (Pub. No. US 2016/0267732) and further in view of Du et al. (Pub. No. 20150242605).
Regarding claim 565, Nduka in view of Nduka2 further in view of Agrafioti doesn’t explicitly teach the claim limitations.
However, Du teaches wherein the at least one processor is further configured to receive reference GPS signals for verifying the individual [Para. 67].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2 further in view of Agrafioti by incorporating Du’s reference FPS signals additional verification input, which reduces the likelihood of successful authentication form an unexpected location.
Regarding claim 580, Nduka in view of Nduka2 further in view of Agrafioti doesn’t explicitly teach the claim limitations.
However, Du teaches wherein the at least one processor is further configured to continuously compare new facial skin micromovements with the reference facial skin micromovements to determine an instantaneous level of certainty [Para. 36 and 51].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2 further in view of Agrafioti by incorporating Du’s reference FPS signals additional verification input, which reduces the likelihood of successful authentication form an unexpected location.
Regarding claim 581, Nduka in view of Nduka2 further in view of Agrafioti doesn’t explicitly teach the claim limitations.
However, Du teaches wherein, after authenticating access to the computing device and when the instantaneous certainty level (trust coefficient value) drops below a threshold, the at least one processor is configured to transmit a subsequent signal restricting access to the computing device [Para. 74 and 87].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2 further in view of Agrafioti by incorporating Du’s reference FPS signals additional verification input, which reduces the likelihood of successful authentication form an unexpected location.
Claim 569 is rejected under 35 U.S.C. 103 as being unpatentable over NDUKA et al. (Pub. No. US 2020/0065569) in view of NDUKA et al. (Pub. No. US 2020/0034608 hereinafter Nduka2) further in view of Agrafioti et al. (Pub. No. US 2016/0267732) and further in view of Kane et al. (Pub. No. US 20050010780).
Regarding claim 569, Nduka in view of Nduka2 further in view of Agrafioti doesn’t explicitly teach the claim limitations.
However, Kane teaches wherein enabling the authenticated access to the computing device includes granting the individual an ability to read, write, modify, or use of information stored in the computing device [Para. 8].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2 further in view of Agrafioti by incorporating Kane’s token-controlled access priviliges to permit the authenticated individual to read, write, or modify stored personal information. This modification improves Nduka by tying biometric authentication to granular information access permissions, thereby limiting access according to the authenticated user’s authorization level.
Claim 573 is rejected under 35 U.S.C. 103 as being unpatentable over NDUKA et al. (Pub. No. US 2020/0065569) in view of NDUKA et al. (Pub. No. US 2020/0034608 hereinafter Nduka2) further in view of Agrafioti et al. (Pub. No. US 2016/0267732) and further in view of Manabe et al. (Pub. No. US 20050102134).
Regarding claim 573, Nduka in view of Nduka2 further in view of Agrafioti doesn’t explicitly teach the claim limitations.
However, Manabe teaches wherein the particular facial skin micromovements correspond to prevocalization muscle recruitment (EMG) that occur between 0.1 seconds to 0.5 seconds prior to vocalization (voice signal) [Para. 136 and 137].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Nduka in view of Nduka2 further in view of Agrafioti by incorporating Manabe’s teaching that EMG-based muscle activity is generated before voice generation, so that the detected particular facial skin micromovements are treated as prevocalization muscle recruitment occurring in the pre-vocal timing window. This medication improves Nduka by enabling authentication from earlier speech-preparatory facial muscle activity, thereby allowing the system to detect and process the biometric pattern before acoustic vocalization begins.
Conclusion
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 extension fee 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 date of this final action.
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/SOLOMON G BEZUAYEHU/
Primary Examiner, Art Unit 2666
