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 4/27/2026. Since the previous filing, claims 1, 10, 18, 23-24 and 34 have been amended, claims 38 and 39 have been added and no claims have been cancelled. Thus, claims 1-39 are pending in the application.
In regards to the previous 103 Rejections, Applicant has amended to overcome these rejections and they are therefore withdrawn with new rejections entered below.
Claim Rejections - 35 USC § 102
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 10-14, 25-26 and 38-39 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Brodie (US 2023/0134637).
In regards to claim 10, Brodie discloses a stability assisting apparatus comprising: a coupling module (stimulation device 1) configured to couple to a user; and, a wearable vibration device (stimulators 2 may be vibration motors, paragraph 86) comprising: a housing coupled to the coupling module (Fig 2, 4, 12 and 13); a sensor module (sensors 18, paragraph 94) configured to generate a sensor measurement from measured data associated with the user; an actuator configured to provide stability assistance to the user, wherein the actuator comprises a vibration module (stimulators 2 may be vibration motors, paragraph 86) configured to generate vibration stability assistance, a controller (control unit 6) operably coupled to the sensor module (paragraph 94), comprising an activation module and a local classification model (paragraph 101 and 104-105), wherein the local classification model comprises a plurality of weightings configured to classify a gait situation based on a classification input (paragraph 109), and the activation module is configured to generate an activation level to control the actuator based on the gait situation classification (paragraph 89), such that the actuator does not output gait assistance during a no gait assistance state while gait is not detected, and the actuator outputs at least one intensity level gait assistance while gait is detected and before the controller detects a gait abnormality (voluntary stopping can be detected, paragraph 151, control unit automatically determines activation/deactivation of stimulators, paragraph 153, maintenance phase allows for lower level assistance that automatically adjusts in response to sensors, paragraph 190-191), 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).
In regards to claim 11, Brodie discloses the device of claim 10 and Brodie 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 190-191).
In regards to claim 12, Brodie discloses the device of claim 10 and Brodie 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 104-105 and 109).
In regards to claim 13, Brodie discloses the device of claim 10 and Brodie 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 104-105 and 109).
In regards to claim 14, Brodie discloses the device of claim 10 and Brodie further discloses wherein the coupling module comprises a band configured to a limb of the user (paragraph 91 and 94).
In regards to claim 25, Brodie discloses the device of claim 10 and Brodie further discloses wherein the vibration module is configured to provide a haptic feedback through an ankle bone of the user (paragraph 91).
In regards to claim 26, Brodie discloses the device of claim 10 and Brodie 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 (paragraph 106 and 111).
In regards to claim 38, Brodie discloses the device of claim 10 and Brodie further discloses wherein the controller is configured to dynamically vary the activation level of the actuator in response to the controller detecting the gait abnormality (paragraph 190-191).
In regards to claim 39, Brodie discloses the device of claim 38 and Brodie further discloses wherein dynamically varying the activation level comprises increasing the at least one intensity level of gait assistance in response to the controller detecting the gait abnormality (paragraph 107).
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 Brodie (US 2023/0134637) in view of Hamner (US 2020/0093400), Caban (US 2020/0147382), Prabhu (US 2021/0248215) and Huen (WO 2019/144869).
In regards to claim 1, Brodie discloses a gait assisting apparatus comprising: a coupling module (stimulation device 1) configured to couple to a user; and, a wearable vibration device (stimulators 2 may be vibration motors, paragraph 86) comprising: a housing coupled to the coupling module (Fig 2, 4, 12 and 13); a sensor module (sensors 18, paragraph 94) configured to generate a sensor measurement from measured data associated with the user; an actuator configured to provide gait assistance to the user, wherein the actuator comprises a vibration module (stimulators 2 may be vibration motors, paragraph 86) configured to generate vibration gait assistance; a controller (control unit 6) operably coupled to the sensor module (paragraph 94), comprising an activation module and a local learning model (paragraph 101 and 104-105), wherein the local learning model comprises a plurality of weighting configured to classify a gait situation based on a classification input (paragraph 109), and the activation module is configured to generate an activation level to control the actuator based on the gait situation classification (paragraph 89); such that the actuator does not output gait assistance during a no gait assistance state while gait is not detected, and the actuator outputs at least one intensity level gait assistance while gait is detected and before the controller detects a gait abnormality (voluntary stopping can be detected, paragraph 151, control unit automatically determines activation/deactivation of stimulators, paragraph 153, maintenance phase allows for lower level assistance that automatically adjusts in response to sensors, paragraph 190-191), wherein 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 (maintenance phase allows for lower level assistance that automatically adjusts in response to sensors, paragraph 190-191, paragraph 104-105 and 109).
While Brodie does discuss a communication module operably coupled to the controller, the communication module configured to connect to a remote machine (control unit 6 may be in communication with other user interface with data transmission between them, paragraph 110, data transferred to remote device or database, paragraph 109), it does not disclose a communication module operably coupled to the controller, the communication module is configured to connect to a remote machine learning model, wherein the remote machine learning model is connected in data communication with a network of remote gait assisting apparatus, 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.
However, Hamner teaches a gait assistance device having 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).
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 Brodie to have a communication module operably coupled to the controller, the communication module is configured to connect to a remote machine learning model, wherein the remote machine learning model is connected in data communication with a network of remote gait assisting apparatus, 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, wherein the activation module independently applies the local learning model in both the online mode and an offline mode as taught by Hamner and Caban as this would ensure that the device can operate to the assistance of the user in all conditions.
Brodie does not disclose wherein the machine learning model is a federated machine learning model or and a vision assistance module 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 Brodie 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 Brodie 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, Brodie in view of Hamner, Caban, Prabhu and Huen teaches the device of claim 1 and Brodie further discloses wherein the coupling module is configured to a lower extremity of the user (Fig 3).
In regards to claim 6, Brodie in view of Hamner, Caban, Prabhu and Huen teaches the device of claim 1.
Brodie does not disclose 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 movement.
However, Hamner teaches 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).
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 Brodie 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 movement as taught by Hamner as these are commonly used sensors for monitoring a gait.
In regards to claim 7, Brodie in view of Hamner, Caban, Prabhu and Huen teaches the device of claim 1 and Brodie further discloses wherein the actuator further comprises an audio module configured to generate sound guidance to the user (paragraph 137).
In regards to claim 8, Brodie in view of Hamner, Caban, Prabhu and Huen teaches the device of claim 1 and brodie further discloses wherein the activation level comprises a plurality of intensity levels of gait assistance (paragraph 190-191).
In regards to claim 9, Brodie in view of Hamner, Caban, Prabhu and Huen teaches the device of claim 1 and Brodie further discloses wherein the classification input further comprises a current time (paragraph 109) and user input (paragraph 104).
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brodie (US 2023/0134637) in view of Hamner (US 2020/0093400), 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, Brodie in view of Hamner, Caban, Prabhu and Huen teaches the device of claim 1.
While Brodie teaches a coupling module may be placed on the wrist (paragraph 86), 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 Brodie 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 Brodie (US 2023/0134637) in view of Hamner (US 2020/0093400), 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, Brodie in view of Hamner, Caban, Prabhu and Huen teaches the device of claim 1.
Brodie 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 Brodie 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, Brodie in view of Hamner, Caban, Prabhu and Huen teaches the device of claim 1.
Brodie 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 Brodie 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) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brodie (US 2023/0134637) in view of Hamner (US 2020/0093400).
In regards to claim 17, Brodie discloses the device of claim 10.
Brodie does not disclose 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.
However, Hamner teaches 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).
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 Brodie 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 movement as taught by Hamner as these are commonly used sensors for monitoring a gait.
Claim(s) 24 and 34 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brodie (US 2023/0134637) in view of Huen (WO 2019/144869).
In regards to claim 24, Brodie discloses the device of claim 10.
Brodie does not disclose further comprising a vision assistance module configured to generate an illumination guidance from the wearable vibration device along a path of the user, wherein the illumination guidance comprises illuminating the path in a first direction.
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), wherein the illumination guidance comprises illuminating the path in a first direction (Huen: 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 Brodie to further comprise a vision assistance module configured to generate an illumination guidance from the wearable vibration device along a path of the user, wherein the illumination guidance comprises illuminating the path in a first direction as taught by Huen as this would provide a visual cue to the user to guide them.
In regards to claim 34, Brodie in view of Huen the device of claim 24.
Brodie 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 Brodie 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 Brodie (US 2023/0134637) in view of Martin (US 2023/0148973).
In regards to claim 15, Brodie discloses the device of claim 10.
While Brodie discloses wherein head worn devices (head band or hat, paragraph 94 line 10), it 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 Brodie 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 Brodie (US 2023/0134637) in view of Dar (US 2012/0330395).
In regards to claim 16, Brodie discloses the device of claim 10.
Brodie 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 Brodie 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 and 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brodie (US 2023/0134637) in view of Hamner (US 2020/0093400) and Prabhu (US 2021/0248215).
In regards to claim 18, Brodie discloses a gait assisting apparatus comprising: a coupling module (stimulation device 1) configured to couple to a user; and, a wearable vibration device comprising: a housing (stimulators 2 may be vibration motors, paragraph 86) coupled to the coupling module; a sensor module (sensors 18, paragraph 94) configured to generate a sensor measurement from measured data associated with the user; an actuator comprising a vibration module (stimulators 2 may be vibration motors, paragraph 86) configured to generate vibration gait assistance to provide gait assistance; a controller (control unit 6) operably coupled to the sensor module, comprising an activation module and a local learning model (paragraph 101 and 104-105), wherein the local learning model comprises a plurality of weightings configured to classify a gait situation based on a classification input (paragraph 109), and the activation module is configured to generate an activation level to control the actuator based on the gait situation classification (paragraph 89), such that the actuator does not output gait assistance during a no gait assistance state while gait is not detected, and the actuator outputs at least one intensity level gait assistance while gait is detected and before the controller detects a gait abnormality (voluntary stopping can be detected, paragraph 151, control unit automatically determines activation/deactivation of stimulators, paragraph 153, maintenance phase allows for lower level assistance that automatically adjusts in response to sensors, paragraph 190-191), 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 (maintenance phase allows for lower level assistance that automatically adjusts in response to sensors in real time, paragraph 190-191, paragraph 104-105 and 109).
While Brodie does disclose a communication module operably coupled to the controller, the communication module configured to connect to a remote machine (control unit 6 may be in communication with other user interface with data transmission between them, paragraph 110, data transferred to remote device or database, paragraph 109), it does not disclose a communication module operably coupled to the controller, the communication module is configured to connect to a remote machine learning model, wherein the remote machine learning model is connected in data communication with a network of remote gait assisting apparatus, 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.
However, Hamner teaches a gait assistance device having 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 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).
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 Brodie a communication module operably coupled to the controller, the communication module is configured to connect to a remote machine learning model, wherein the remote machine learning model is connected in data communication with a network of remote gait assisting apparatus, 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 as taught by Hamner as this would ensure that the device can operate to the assistance of the user in all conditions.
Brodie 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 Brodie 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, Brodie in view of Hamner and Prabhu teaches the device of claim 18.
Brodie does not disclose 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 movement.
However, Hamner teaches 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).
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 Brodie 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 movement as taught by Hamner as these are commonly used sensors for monitoring a gait.
Claim(s) 37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brodie (US 2023/0134637) in view of Hamner (US 2020/0093400) and Prabhu (US 2021/0248215) and in further view of Caban (US 2020/0147382).
In regards to claim 37, Brodie in view of Hamner and 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)
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 Brodie wherein the activation module independently applies the local learning model in both the online mode and an offline mode as taught by Hamner and Caban as this would ensure that the device can operate to the assistance of the user in all conditions.
Claim(s) 19 and 35-36 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brodie (US 2023/0134637) in view of Hamner (US 2020/0093400) and Prabhu (US 2021/0248215) and in further view of Huen (WO 2019/144869).
In regards to claim 19, Brodie in view of Hamner and Prabhu teaches the device of claim 18.
Brodie does not disclose 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).
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 Brodie to further comprise a vision assistance module configured to generate an illumination guidance from the wearable vibration device along a path of the user, wherein the illumination guidance comprises illuminating the path in a first direction as taught by Huen as this would provide a visual cue to the user to guide them.
In regards to claim 35, Brodie in view of Hamner, 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, Brodie in view of Hamner, Prabhu and Huen teaches the device of claim 19.
While the modified Brodie 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 109). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify Brodie 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 Brodie 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 Brodie (US 2023/0134637) in view of Hamner (US 2020/0093400), Prabhu (US 2021/0248215) and in further view of Dar (US 2012/0330395).
In regards to claim 20, Brodie in view of Hamner and Prabhu teaches the device of claim 18.
Brodie 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 Brodie 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, Brodie in view of Hamner and Prabhu teaches the device of claim 18.
Brodie 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 Brodie 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 Brodie (US 2023/0134637) in view of Martin (US 2023/0148973).
In regards to claim 23, Brodie discloses a stability assisting apparatus comprising: a wearable vibration device (stimulators 2 may be vibration motors, paragraph 86) comprising: a housing (Fig 2, 4, 12 and 13); a sensor module (sensors 18, paragraph 94) configured to generate a sensor measurement from measured data associated with the user; an actuator configured to provide stability assistance to the user (stimulators 2); a controller (control unit 6) operably coupled to the sensor module (paragraph 94), comprising an activation module and a local classification model (paragraph 101 and 104-105) wherein the local classification model comprises a plurality of weightings configured to classify a gait situation based on a classification input (paragraph 109), 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 (paragraph 89), wherein, the actuator does not output gait assistance during a no gait assistance state while gait is not detected, and the actuator outputs at least one intensity level of gait assistance while gait is detected and before the controller detects a gait abnormality (voluntary stopping can be detected, paragraph 151, maintenance phase allows for lower level assistance that automatically adjusts in response to sensors, paragraph 190-191), and 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 (maintenance phase allows for lower level assistance that automatically adjusts in response to sensors, paragraph 190-191, paragraph 104-105 and 109).
While Brodie discloses wherein head worn devices (head band or hat, paragraph 94 line 10), it does not teach 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 Brodie 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, Brodie in view of Martin teaches the device of claim 23 and Brodie further discloses wherein the actuator comprises a vibration module configured to generate vibration stability assistance (stimulators 2 may be vibration motors, paragraph 86).
In regards to claim 28, Brodie in view of Martin teaches the device of claim 23 and Brodie further discloses wherein the gait assistance comprises at least one of: haptic, auditory or electrical stimulus (paragraph 86 and 91).
In regards to claim 29, Brodie in view of Martin teaches the device of claim 23.
Brodie 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 Brodie 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, Brodie 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 (Brodie: vibration motor, paragraph 86) by the helmet (Martin: device attached to a helmet, paragraph 29).
In regards to claim 31, Brodie in view of Martin teaches the device of claim 23 and Brodie further discloses a second wearable vibration device configured to be disposed on another location of a body of the user from the helmet (plurality of stimulators 2, paragraph 85).
In regards to claim 32, Brodie in view of Martin teaches the device of claim 23.
Brodie 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 Brodie wherein the device is configured to be a pre-injury detection system as taught by Martin as this would help the user prevent an injury.
In regards to claim 33, Brodie in view of Martin teaches the device of claim 23 and Brodie 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 motions and direction and rotation of body parts, paragraph 94).
Response to Arguments
In regards to the arguments concerning the amended claims, these arguments concern the amendments made to the claims and are addressed in the new rejections entered above.
In regards to the arguments concerning the new claims, these arguments are addressed in the new rejections entered above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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
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