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 .
This action is in response to the filing on 11/11/2025. Since the previous filing, no claims have been added, amended or cancelled. Thus, claims 1-37 are pending in the application.
This action is in response to the Pre-Appeal Brief filed 11/11/2025. Applicant has correctly pointed out a limitation within three of the independent claims that has not been addressed. The previous Action has been vacated and the current action will supersede wherein the rejections are reentered, modified to incorporate the missing limitations, below.
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) 1, 4 and 6-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamner (US 2020/0093400) in view of Caban (US 2020/0147382), Prabhu (US 2021/0248215) and Huen (WO 2019/144869).
In regards to claim 1, Hamner discloses a gait assisting apparatus (wearable unit 200) comprising: a coupling module (band 202) configured to couple to a user; and, a wearable vibration device comprising: a housing (housing 204) coupled to the coupling module; a sensor module (sensors 70, Fig 1) configured to generate a sensor measurement from measured data associated with the user; an actuator (paragraph 92) configured to provide gait assistance to the user, wherein the actuator comprises a vibration module (vibration motor, paragraph 93) configured to generate vibration gait assistance; a controller (processor 210) operably coupled to the sensor module, comprising an activation module and a local learning model (Naïve Bayes classifier, paragraph 100), wherein the local learning model comprises a plurality of weighting configured to classify a gait situation based on a classification input (paragraph 100), wherein a gait situation classification comprises no gait assistance and at least one intensity level of gait assistance (evaluates for deviations in gait to determine if/how much feedback to apply which would include no gait assistance when not required, paragraph 94 and 97), and the activation module is configured to generate an activation level to control the actuator based on the gait situation classification (paragraph 94 and 97); and, a communication module operably coupled to the controller, the communication module is configured to connect to a remote machine learning model (paragraph 100 and 103), wherein the remote machine learning model is connected in data communication with a network of remote gait assisting apparatus (paragraph 106), such that, in an online mode, the local learning model is configured to receive update weighting input from the remote machine learning model as a function of training inputs, wherein the training inputs comprise updated training output parameters generated by the local learning models from the network of remote gait assisting apparatus based on sensor measurements from corresponding gait assisting apparatus (paragraph 106); and, in the online mode and in an offline mode, upon receiving the sensor measurement from the sensor module, the activation module independently applies the local learning model to the classification input comprising the received sensor measurement to determine the activation level of the actuator such that the gait assisting apparatus provides a gait assistant function to prevent gait impairment injuries in real time (paragraph 92, 100, 103 and 105-106).
In the alternative, if Hamner is deemed insufficient to disclose an offline and online mode wherein the activation module independently applies the local learning model in both the online mode and an offline mode, Caban teaches that it is known for a movement assistance device to have an offline and online mode wherein the activation module independently applies the local learning model in both the online mode and an offline mode (paragraph 335-348 and paragraph 356-368, Fig 11 and 12).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the activation module independently applies the local learning model in both the online mode and an offline mode as taught by Caban as this would ensure that the device can operate to the assistance of the user in all conditions.
Hamner does not disclose wherein the machine learning model is a federated machine learning model or and a vision assistance module (190b) configured to generate an illumination guidance from the wearable vibration device coupled to the user and along a gait path of the user.
However, Prabhu teaches it is known to use a federated machine learning model (paragraph 17).
Therefore, it would have been obvious to one of ordinary skill in the art before the
effective filing date of the claimed invention to modify Hamner to have a federated machine learning model as taught by Prabhu as this would provide improved security of data (claim 10).
Further, Huen teaches a wearable gait assistance apparatus having a vision assistance module (visual indicating device 10) configured to generate an illumination guidance from the wearable device couple to the user and along a gait path of the user (device 10 projects light sign 60, page 6 paragraph 1).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner to have a vision assistance module configured to generate an illumination guidance from the wearable device couple to the user and alone a gait path of the user as taught by Huen as this would provide a visual cue to the user to guide them.
In regards to claim 4, Hamner in view of Caban, Prabhu and Huen teaches the device of claim 1 and Hamner further discloses wherein the coupling module is configured to a lower extremity of the user (paragraph 97).
In regards to claim 6, Hamner in view of Caban, Prabhu and Huen teaches the device of claim 1 and Hamner further discloses wherein the sensor module comprises a force sensor on an inside perimeter of the housing, wherein the force sensor is configured to detect a relative position of the wearable vibration device to the user during limb movements (force sensors used to determine gait kinematics such as foot progression, knee angle, step width, etc. wherein the device is on the limb and the determined position of the limb is relative to the body of the user based on foot progression, knee angle, step width, etc., paragraph 91-92).
In regards to claim 7, Hamner in view of Caban, Prabhu and Huen teaches the device of claim 1 and Hamner further discloses wherein the actuator further comprises an audio module configured to generate sound guidance to the user (paragraph 93).
In regards to claim 8, Hamner in view of Caban, Prabhu and Huen teaches the device of claim 1 and Hamner further discloses wherein the activation level comprises a plurality of intensity levels of gait assistance (paragraph 94 line 25-31 and paragraph 105).
In regards to claim 9, Hamner in view of Caban, Prabhu and Huen teaches the device of claim 1 and Hamner further discloses wherein the classification input further comprises a current time (paragraph 106) and user input (paragraph 108).
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamner (US 2020/0093400) in view of Caban (US 2020/0147382), Prabhu (US 2021/0248215) and Huen (WO 2019/144869) and in further view of Rogers (US 2021/0113099).
In regards to claim 2, Hamner in view of Caban, Prabhu and Huen teaches the device of claim 1.
While Hamner teaches a coupling module may comprise silicone (paragraph 122) and that the device may be placed on the wrist (paragraph 132), it does not teach wherein the coupling module comprises a medical grade silicone wristband.
However, Rogers teaches wherein the coupling module comprises a medical grade silicone wristband (paragraph 218).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the coupling module comprises a medical grade silicone wristband as taught by Rogers as this is a known material for attaching devices to a patient body.
Claim(s) 3 and 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamner (US 2020/0093400) in view of Caban (US 2020/0147382), Prabhu (US 2021/0248215) and Huen (WO 2019/144869) and in further view of Dar (US 2012/0330395).
In regards to claim 3, Hamner in view of Caban, Prabhu and Huen teaches the device of claim 1.
Hamner does not disclose wherein the coupling module comprises a disposable strap that attaches to the housing of the wearable vibration device.
However, Dar teaches wherein the coupling module comprises a disposable strap that attaches to the housing of the wearable vibration device (stimulation unit 46, Fig 3, layer 118 is disposable, paragraph 243).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the coupling module comprises a disposable strap that attaches to the housing of the wearable vibration device as taught by Dar as this would allow the housing to be changed to new straps with the straps being easily discardable when needed.
In regards to claim 5, Hamner in view of Caban, Prabhu and Huen teaches the device of claim 1.
Hamner does not disclose wherein the housing is releasably coupled to the coupling module.
However, Dar teaches wherein the housing is releasably coupled to the coupling module (Fig 7).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the housing is releasably coupled to the coupling module as taught by Dar as this would allow the device to be moved to another strap should the first one be damaged.
Claim(s) 10-14, 17, 24-26 and 34 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamner (US 2020/0093400) in view of Huen (WO 2019/144869).
In regards to claim 10, Hamner discloses a stability assisting apparatus (wearable unit 200) comprising: a coupling module (band 202) configured to couple to a user; and, a wearable vibration device comprising: a housing (housing 204) coupled to the coupling module; a sensor module (sensors 70, Fig 1) configured to generate a sensor measurement from measured data associated with the user; an actuator (paragraph 92) configured to provide stability assistance to the user, wherein the actuator comprises a vibration module (vibration motor, paragraph 93) configured to generate vibration stability assistance, a controller (processor 210) operably coupled to the sensor module, comprising an activation module and a local classification model (Naïve Bayes classifier, paragraph 100), wherein the local classification model comprises a plurality of weightings configured to classify a gait situation based on a classification input (paragraph 94), wherein the gait situation comprises no gait assistance and at least one intensity level of gait assistance (evaluates for deviations in gait to determine if/how much feedback to apply which would include no gait assistance when not required, paragraph 94 and 96-97), and the activation module is configured to generate an activation level to control the actuator based on the gait situation classification (paragraph 94), wherein: in operation, the activation module applies the local classification model to the classification input comprising received sensor measurements to determine the activation level of the actuator such that the stability assisting apparatus provides a stability assistant function to prevent stability-related injuries in real time (abstract, paragraph 94 and 100).
Hamner does not disclose a vision assistance module (190b) configured to generate an illumination guidance from the wearable vibration device along a path of the user.
However, Huen teaches a wearable gait assistance apparatus having a vision assistance module (visual indicating device 10) configured to generate an illumination guidance from the wearable device couple to the user and alone a gait path of the user (device 10 projects light sign 60, page 6 paragraph 1).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner to have a vision assistance module configured to generate an illumination guidance from the wearable device couple to the user and alone a gait path of the user as taught by Huen as this would provide a visual cue to the user to guide them.
In regards to claim 11, Hamner in view of Huen teaches the device of claim 10 and Hamner further discloses wherein the stability assistance to the user comprises gait assistance, the stability assistant function comprises gait assistant function, and stability-related injuries comprises gait injuries (paragraph 100 and abstract).
In regards to claim 12, Hamner in view of Huen teaches the device of claim 10 and Hamner further discloses wherein the local classification model comprises a machine learning model preloaded into the controller, wherein the machine learning model is pre-trained with a common data set (paragraph 100, Naïve Bayes classifier).
In regards to claim 13, Hamner in view of Huen teaches the device of claim 10 and Hamner further discloses further comprising a communication module operably coupled to the controller, wherein the communication module is configured to, upon receiving new weightings of the local classification model, update the local classification model (paragraph 106).
In regards to claim 14, Hamner in view of Huen teaches the device of claim 10 and Hamner further discloses wherein the coupling module comprises a band configured to a limb of the user (paragraph 97).
In regards to claim 17, Hamner in view of Huen teaches the device of claim 10 and Hamner further discloses wherein the sensor module comprises a force sensor on an inside perimeter of the housing, wherein the force sensor is configured to detect a relative position of the wearable vibration device to the user during limb movements (force sensors sued to determine gait kinematics such as foot progression, knee angle, step width, etc. wherein the device is on the limb and the determined position of the limb is relative to the body of the user based on foot progression, knee angle, step width, etc., paragraph 91-92).
In regards to claim 24, Hamner in view of Huen teaches the device of claim 10 and the combination further teaches wherein the illumination guidance comprises illuminating the path in a first direction (Huen: page 6 paragraph 1).
In regards to claim 25, Hamner in view of Huen teaches the device of claim 10 and Hamner further discloses wherein the vibration module is configured to provide a haptic feedback through an ankle bone of the user (vibrotactile stimulation affecters 302 may be on the ankle, paragraph 97).
In regards to claim 26, Hamner in view of Huen teaches the device of claim 10 and Hamner further discloses wherein the vibration module is configured such that the stability assistant function comprises proprioception feedback such that the stability assistance provides a body location feedback to the user (triggering of device utilized to alter gait as needed to correct improper positioning of body/limbs, paragraph 97).
In regards to claim 34, Hamner in view of Huen teaches the device of claim 10.
Hamner does not disclose wherein the vision assistance module is configured to generate the illumination guidance based on ambient light level detected by an ambient light sensor and the gait situation classification.
However, Huen teaches wherein the vision assistance module is configured to generate the illumination guidance based on ambient light level detected by an ambient light sensor and the gait situation classification (page 8 paragraph 6 line 1-5).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the vision assistance module is configured to generate the illumination guidance based on ambient light level detected by an ambient light sensor and the gait situation classification as taught by Huen as this would ensure that the illumination guidance was visible no matter the environment.
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamner (US 2020/0093400) in view of Huen (WO 2019/144869) ad in further view of Martin (US 2023/0148973).
In regards to claim 15, Hamner in view of Huen teaches the device of claim 10.
Hamner does not teach wherein the coupling module comprises a helmet.
However, Martin teaches wherein the coupling module comprises a helmet (paragraph 29).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the coupling module comprises a helmet as taught by Martin as this is a known means to attach a body worn device to a user.
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamner (US 2020/0093400) in view of Huen (WO 2019/144869) and in further view of Dar (US 2012/0330395).
In regards to claim 16, Hamner in view of Huen teaches the device of claim 10.
Hamner does not disclose wherein the housing is releasably coupled to the coupling module.
However, Dar teaches wherein the housing is releasably coupled to the coupling module (Fig 7).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the housing is releasably coupled to the coupling module as taught by Dar as this would allow the device to be moved to another strap should the first one be damaged.
Claim(s) 18, 22 and 37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamner (US 2020/0093400) in view of Caban (US 2020/0147382), Prabhu (US 2021/0248215).
In regards to claim 18, Hamner discloses a gait assisting apparatus (wearable unit 200) comprising: a coupling module (band 202) configured to couple to a user; and, a wearable vibration device comprising: a housing (housing 204) coupled to the coupling module; a sensor module (sensors 70, Fig 1) configured to generate a sensor measurement from measured data associated with the user; an actuator (paragraph 92) comprising a vibration module (vibration motor, paragraph 93) configured to generate vibration gait assistance to provide gait assistance; a controller (processor 210) operably coupled to the sensor module, comprising an activation module and a local learning model (Naïve Bayes classifier, paragraph 100), wherein the local learning model comprises a plurality of weightings configured to classify a gait situation based on a classification input, wherein the gait situation comprises no gait assistance and at least one intensity level of gait assistance, and the activation module is configured to generate an activation level to control the actuator based on the gait situation classification (evaluates for deviations in gait to determine if/how much feedback to apply which would include no gait assistance when not required, paragraph 94 and 97), wherein, a communication module, operably coupled to the controller, configured to connect to a remote machine learning model (paragraph 100 and 103), wherein the remote machine learning model is connected in data communication with a network of remote gait assisting apparatus (paragraph 106), such that, in an online mode, the local learning model is configured to receive updated weighting input from the remote federated machine learning model as a function of training inputs, wherein the training inputs comprise updated training output parameters generated by the local learning models from the network of remote gait assisting apparatus based on sensor measurements from corresponding gait assisting apparatus; and, upon receiving the sensor measurement from the sensor module, the activation module independently applies the local learning model to the classification input comprising the received sensor measurement to determine the activation level of the actuator such that the gait assisting apparatus provides a gait assistant function to prevent gait impairment injuries in real time (paragraph 103 and 106).
In the alternative, if Hamner is deemed insufficient to disclose an offline and online mode wherein the activation module independently applies the local learning model in both the online mode and an offline mode, Caban teaches that it is known for a movement assistance device to have an offline and online mode wherein the activation module independently applies the local learning model in both the online mode and an offline mode (paragraph 335-348 and paragraph 356-368, Fig 11 and 12).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the activation module independently applies the local learning model in both the online mode and an offline mode as taught by Caban a this would ensure that the device can operate to the assistance of the user in all conditions.
Hamner does not disclose wherein the machine learning model is a federated machine learning model.
However, Prabhu teaches it is known to use a federated machine learning model (paragraph 17).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner to have a federated machine learning model as taught by Prabhu as this would provide improved security of data (claim 10).
In regards to claim 22, Hamner in view of Prabhu teaches the device of claim 18 and Hamner further discloses wherein the sensor module comprises a force sensor on an inside perimeter of the housing, wherein the force sensor is configured to detect a relative position of the wearable vibration device to the user during limb movements (force sensors sued to determine gait kinematics such as foot progression, knee angle, step width, etc. wherein the device is on the limb and the determined position of the limb is relative to the body of the user based on foot progression, knee angle, step width, etc., paragraph 91-92).
In regards to claim 37, Hamner in view of Prabhu teaches the device of claim 18 and the combination further discloses wherein the activation module independently applies the local learning model in both the online mode and an offline mode (Hamner: discussion of calculations in order to determine therapy to be applied and makes no mention of any remote communications involved in any way, paragraph 100, discussion communication with a remote system to store various data to and call data from that remote system, paragraphs 92, 103 and 105-106; Caban: paragraph 335-348 and paragraph 356-368, Fig 11 and 12)
Claim(s) 19 and 35-36 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamner (US 2020/0093400) in view of Caban (US 2020/0147382), Prabhu (US 2021/0248215) and in further view of Huen (WO 2019/144869).
In regards to claim 19, Hamner in view of Caban and Prabhu teaches the device of claim 18.
Hamner does not discloses wherein the actuator further comprises a vision assistance module configured to generate an illumination guidance.
However, Huen teaches a wearable gait assistance apparatus having a vision assistance module (visual indicating device 10) configured to generate an illumination guidance (device 10 projects light sign 60, page 6 paragraph 1).
In regards to claim 35, Hamner in view of Caban, Prabhu and Huen teaches the device of claim 19 and the combination further teaches wherein the vision assistance module is configured to generate the illumination guidance by illuminating a path in front of the user (Huen: device 10 projects light sign 60, page 6 paragraph 1).
In regards to claim 36, Hamner in view of Caban, Prabhu and Huen teaches the device of claim 19.
While Hamner does not explicitly disclose wherein the vision assistance module is configured to generate the illumination guidance based on a time of day and the gait situation classification, it does teach activation of various functions based on the time of day and gait situations (paragraph 157). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the vision assistance module is configured to generate the illumination guidance based on a time of day and the gait situation classification as taught by Hamner as this would allow the device to trigger assistance as such times as the user needs.
Claim(s) 20 and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamner (US 2020/0093400) in view of Caban (US 2020/0147382), Prabhu (US 2021/0248215) and in further view of Dar (US 2012/0330395).
In regards to claim 20, Hamner in view of Caban and Prabhu teaches the device of claim 18.
Hamner does not disclose wherein the coupling module comprises a disposable strap that attaches to the housing of the wearable vibration device.
However, Dar teaches wherein the coupling module comprises a disposable strap that attaches to the housing of the wearable vibration device (stimulation unit 46, Fig 3, layer 118 is disposable, paragraph 243).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the coupling module comprises a disposable strap that attaches to the housing of the wearable vibration device as taught by Dar as this would allow the housing to be changed to new straps with the straps being easily discardable when needed.
In regards to claim 21, Hamner in view of Caban and Prabhu teaches the device of claim 18.
Hamner does not disclose wherein the housing is releasably coupled to the coupling module.
However, Dar teaches wherein the housing is releasably coupled to the coupling module (Fig 7).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the housing is releasably coupled to the coupling module as taught by Dar as this would allow the device to be moved to another strap should the first one be damaged.
Claim(s) 23 and 27-33 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hamner (US 2020/0093400) in view of Martin (US 2023/0148973).
In regards to claim 23, Hamner discloses a stability assisting apparatus (wearable unit 200) comprising: and, a wearable vibration device comprising: a housing (housing 204; a sensor module (sensors 70, Fig 1) configured to generate a sensor measurement from measured data associated with the user; an actuator (paragraph 92) configured to provide stability assistance to the user; a controller (processor 20) operably coupled to the sensor module, comprising an activation module and a local classification model (Naïve Beyes classifier, paragraph 100) wherein the local classification model comprises a plurality of weightings configured to classify a gait situation based on a classification input (paragraph 94), wherein a gait situation classification comprises no gait assistance and at least one intensity level of gait assistance, and the activation module is configured to generate an activation level to control the actuator based on the gait situation classification such that in-time assistance is selectively provided to the user when predicted to have trouble with gait (evaluates for deviations in gait to determine if/how much feedback to apply which would include no gait assistance when not required, paragraph 94 and 97), wherein, in operation, the activation module applies the local classification model to the classification input comprising received sensor measurements to determine the activation level of the actuator such that the stability assisting apparatus provides a stability assistant function configured to prevent stability-related injuries in real time (abstract, paragraph 100).
Hamner does not disclose that the apparatus comprises a helmet configured to couple to a user.
However, teaches wherein the apparatus comprises a helmet configured to couple to a user (paragraph 29).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the coupling module comprises a helmet as taught by Martin as this is a known means to attach a body worn device to a user.
In regards to claim 27, Hamner in view of Martin teaches the device of claim 23 and Hamner further discloses wherein the actuator comprises a vibration module configured to generate vibration stability assistance (vibrotactile stimulation, paragraph 97).
In regards to claim 28, Hamner in view of Martin teaches the device of claim 23 and Hamner further discloses wherein the gait assistance comprises at least one of: haptic, auditory or electrical stimulus (paragraph 94 line 12-17).
In regards to claim 29, Hamner in view of Martin teaches the device of claim 23.
Hamner does not disclose wherein the gait assistance comprises a warning.
However, Martin teaches wherein the gait assistance comprises a warning (abstract, paragraph 73-74).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the gait assistance comprises a warning as taught by Martin as this would allow the device to help the user avoid injury.
In regards to claim 30, Hamner in view of Martin teaches the device of claim 23 and the combination further teaches wherein the wearable vibration device is coupled to a body of the user (Hamner: vibration motor, paragraph 93) by the helmet (Martin: device attached to a helmet, paragraph 29).
In regards to claim 31, Hamner in view of Martin teaches the device of claim 23 and Hamner further discloses a second wearable vibration device configured to be disposed on another location of a body of the user from the helmet (multiple devices may be at a different location from that of the wearable unit, paragraph 126).
In regards to claim 32, Hamner in view of Martin teaches the device of claim 23.
Hamner does not disclose wherein the device is configured to be a pre-injury detection system.
However, Martin teaches wherein the device is configured to be a pre-injury detection system (title, abstract).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Hamner wherein the device is configured to be a pre-injury detection system as taught by Martin as this would help the user prevent and injury.
In regards to claim 33, Hamner in view of Martin teaches the device of claim 23 and Hamner further discloses wherein the sensor module comprises a sensor configured to detect a relative position of the wearable vibration device to the user during limb movements (sensors determine gait characteristic such as step width and foot position during movement and relative positions detected, paragraph 102).
Response to Arguments
In regards to the arguments concerning the use of Hamner as a base reference, these arguments are partially persuasive. Applicant correctly points out that in the previous rejections of claims 1, 10 and 18 do not include the limitations of wherein a gait classification can be no gait assistance. The new rejections entered above have been modified to include these limitations. Applicant further argues that Hamner describes a prediction of pain levels and not gait activation. Examiner disagrees. The cited passages describe prediction of pain levels as being one of several factors, including monitoring of the gait, associated with determining if/when gait assistance is provided as a corrected gait would help reduce pain. Further arguments with regards to proactive vs reactive assistance is moot as the claims do not include such descriptions and details of the specification are not usually relied upon for evaluation of the claims.
In regards to the arguments against secondary reference Prabhu, these arguments are not persuasive. Applicant argues that the centralized system of Hamner would be broken by combining with a decentralized system as seen in Prabhu. Examiner disagrees. Hamner describes the data storage in that it “could be” centrally arranged. While this is the exemplary description, it is an optional one. Prabhu teaches that it is known in the art for body worn and responsive devices to use a federated system and as Hamner does provide a local system, the Examiner does not believe it unreasonable to combine art recognized systems.
In regards to the arguments against secondary reference Huen, these arguments are not persuasive. Applicant argues that Huan does not provide an illumination guidance along a gait path of the user to provide vision assistance to the user. Examiner disagrees. The cited passages of Huen as seen in the above rejections describe light based vision assistance to help and guide the user walking.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Arielle Wolff whose telephone number is (571)272-8727. The examiner can normally be reached Mon-Fri 8:00-4:00.
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/ARIELLE WOLFF/ Examiner, Art Unit 3785
/KENDRA D CARTER/ Supervisory Patent Examiner, Art Unit 3785