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 .
Status of Claims
This office action is in response to the filing of the application on 12/21/2023. Since the initial filing, claims 1-4, 7-14, 16, 28, and 33-39 have been amended or added, and claims 5-6, 15, 21-22, and 30 have been canceled. Thus claims 1-4, 7-14, 16-20, 23-29 and 31-39 are pending in the application.
Specification
The specification is objected to as failing to provide proper antecedent basis for the claimed subject matter. See 37 CFR 1.75(d)(1) and MPEP § 608.01(o). Correction of the following is required:
Claims 1, 8, 12-14, 17, 24, and 28-29 recite the limitation “compliant actuator” this limitation is not detailed in the “Detailed Description” of the specification and therefore lacks proper antecedent basis for the claimed component of the device.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-39 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The claim limitation of “configured to sense one or more parameters” is not detailed within the specifications. The specification does not list what these parameters are that the sensors to be made reference to nor how they are calculated to impact the movement of the device. Further clarification is required.
Any remaining claims are rejected as being dependent upon a rejected base claim.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-39 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The claim limitation “at least one baseline threshold parameter” lacks clarity as it is unclear on whether there is a specific threshold per user or for the machine device as a hold. There is also in question on how this ambiguous threshold is being calculated. Paragraphs [0086-0088] detail the steps of the algorithm but lack the necessary details of what a threshold is in terms of the actuators and its movements. Further clarification is required.
Any remaining claims are rejected as being dependent upon a rejected base claim.
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 1-4, 7-11, 17-20, and 23-26 are rejected under 35 U.S.C. 103 as being unpatentable over Chauhan et al. (US 20230166391 A1) and further in view of Bhugra (US 20210106490 A1).
Regarding claim 1, Chauhan discloses a wearable system for facilitating rehabilitation exercises, functional activity, and/or assessing activity quality, the wearable system comprising (Intelligent Hand Exoskeleton with Grasping Assistance, FIG 1):
a flexible wearable robotic system configured to be worn on an appendage of a user (exoskeleton glove with attached finger mechanisms), the flexible wearable robotic system including one or more compliant actuators configured to apply a force to one or more joints of the appendage (actuators 10 movable via revolute joint’s R attached to the user’s fingers by linkage lengths 11/12/13, push/pulling forces of actuators detailed in FIG 4B; [0069] “The virtual spring in this system directly connects the user/wearer and the actuator while the real force is transmitted from the actuator to the user/wearer by the physical springs in the SEA”);
one or more sensors configured to sense one or more parameters related to movement of the appendage ([0064] “user intent can be determined using other sensor types, such as electromyography (EMG) sensors, force sensors, finger joint position sensors, and/or combinations of sensor types”); and
at least one processor operatively coupled with the one or more sensors and the one or more compliant actuators ([0070] “The value of x.sub.2 is integrated twice to determine a reference position that is input into a low-level PID controller responsible for moving the actuator itself, running on the microcontroller unit (MCU)”), wherein the at least one processor is configured to:
operate the one or more compliant actuators to perform one or more rehabilitation activities ([0070] “The motor PID controller instructs the motor of the actuator, such as an SEA, to provide a certain amount of force (Fmotor) to the exoskeleton system/device, to assist the user with the desired grasp”), and
determine intentional user engagement with the one or more activities with an intention detection algorithm configured to compare the one or more parameters with at least one baseline threshold parameter. (Within paragraph [0088], Chauhan details that the user can personalize the exoskeleton glove to meet the users’ preferences and current movement ability. The individual can many let their limits and range of function and edit these through their rehabilitation as to allow the user to go through their exercises at their own pace. [0073] “ the device can be programmed with a predetermined set of values for range of motion based on user parameters such as age, sex, prior injury, disease presence, and/or dominant vs. non-dominant hand. The predetermined set values can be re-adjusted at any time according to a particular user/wearer's needs and as those need may change over time.” With this mechanism, the user may create their own threshold and parameters or use those that have already been calculated set up their device to the specifications they need for their exercise and the user can compare their exercise data to the preprogramed ones installed with the system.
Chauhan is silent on output feedback related to the one or more parameters to the user using a display operatively coupled to the at least one processor.
Bhugra teaches of a stroke rehabilitation device to help retain an individual’s motor skills through the use of repetitive exercise, Fig 1. An aspect utilized by this device is a media display where the user can visually see and record their hand movements on a computer program and can be given details on their exercise in an easy-to-understand manor in real time, FIG 1A.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to modify the device of Chauhan to include a multimedia display output as to give the user a more precise and individualized rehabilitation device. By allowing the user to see how their hand and be given guidance on the exercises while at home allows the user to keep up with their rehabilitation on their own time but still track their results efficiently and accurately. [0083] “the reports provided to the central system 116 may be reviewed by a health care provider or other rehabilitation specialist to see what if any progress is being made with the rehabilitation effort, and provide instructions for future therapy sessions, feedback, and perhaps encouragement to the patient where appropriate. In some implementations, information included in reports from multiple patients may be anonymized and aggregated to identify factors and trends which may generally lead to improved rehabilitation results for patients. ” This allows an individual to be given not only visual guidance on the exercises that the user should be doing but also track their progress, receive advice on what muscles/fingers to focus on, and provide visual encouragement.
Regarding claim 2, Chauhan and Bhugra teach the modified device of claim 1, wherein the at least one processor is configured to provide feedback in real-time. (Chauhan details in [0064] that the sensors chosen to adorn the phalanges need to be able to process data quickly as to ensure the hand moves at the right moment based on the user’s input. Chauhan [0069] “Intelligent assistance prevents uncomfortable motion beyond the natural range of motion of the fingers while reacting very quickly to the user's physical input.” As quickly for a processor is seconds in comparison to a humans processing ability, it should be noted that the feedback from the sensors would be therefore communicated to the processor in “real-time”. Additionally, within the modified device of Chauhan, the sensors are in communication with the processors of Bhugra’s design to display the concurrent motions of the hand on a multimedia device, the computer would therefore be showing the user’s movements in “real-time” as to assist the user in their exercises.)
Regarding claim 3, Chauhan discloses the modified device of claim 1, wherein the at least one processor is operatively coupled to non-transitory computer-readable memory comprising one or more instructions to perform the one or more rehabilitation activities. (Chauhan details in [0071] and [0080] that the PID controller may be attached to a non-transitory computer-readable medium as to program specific grip motions as well as execute movements of GRASP therapy; the use of GRASP taxonomy for rehabilitation.)
Regarding claim 4, Chauhan and Bhugra teach the modified device of claim 3, wherein the non- transitory computer-readable memory is configured to store the feedback, and wherein the at least one processor is configured to provide the feedback to the user on-demand. (Chauhan [0069] “In embodiments, the controller can be connected to the exoskeleton either wirelessly or through a wired connection in a manner such that the controller is capable of providing instructions to generate the particular force desired of the actuator and causing the actuator to perform the desired function/motion.” As stated by Chauhan, as the controller can be connected to a readable media system and provide specific functions based on the data provided by the glove, the exoskeleton glove therefore must be delivering the data to the media system in real time and providing feedback upon the hand motions being conducted by the user. Additionally, within the modified device of Chauhan, the sensors are in communication with the processors of Bhugra’s design to display the concurrent motions of the hand on a multimedia device, the computer would therefore be showing the user’s movements “on-demand” as to assist the user in their exercises. In order for the data to be transferred and reviewed by the user, the data would therefore be stored by the system as to allow the user time to review and asses the data gathered during the exercise.)
Regarding claim 7, Chauhan and Bhugra teach the modified device of claim 1.
Chauhan is silent on the display configured to communicate one or more prompts to the user to perform the one or more rehabilitation activities.
As detailed in claim 1’s rejection, Bhugra teaches the use of an orthosis device that utilizes a rehabilitation system which receives information from the user and then outputs the corresponding motions done by the user onto a multimedia display. Within Bhugra’s [0062], the media output may also provide exercises for the user to use through visual or auditorial prompts with instructions on the ways to execute the exercise.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to modify the display output detailed by Bhugra to provide prompts and exercise details to the user as to allow for more effective rehabilitation exercise to occur. As there many different injuries and disease that can cause a decrease in hand motion, having a personalized display to give the use a more effective rehabilitation exercise by ensuring the user is doing the correct movements and track the users progress. Bhugra [0062] “local computing system 110 with one or more associated application programs and a user display device 112 to provide instruction, guidance, prompts, and information for set-up, performing rehabilitation sessions, and monitoring progress”)
Regarding claim 8, Chauhan and Bhugra teach the modified device of claim 1, wherein the one or more compliant actuators are configured to actively move the appendage when operated by the at least one processor. (Chauhan, [0070] ”The motor PID controller instructs the motor of the actuator, such as an SEA, to provide a certain amount of force (Fmotor) to the exoskeleton system/device, to assist the user with the desired grasp.”)
Regarding claim 9, Chauhan and Bhugra teach the modified device of claim 1, wherein the at least one processor is further configured to output the feedback related to the one or more parameters to a remote user. (While Chauhan does not disclose that the data is transferred remotely, using the modified display processors of Bhurga, the user’s exercise data can be stored and reviewed through the system. Bhugra [0062] “a network accessible central rehabilitation management computing system 116, which may be used in the set-up and on-going operation and monitoring of the local aspects of the rehabilitation system 100 and may be located remote from where the patient performs rehabilitation activities, for example, at a healthcare facility (e.g., hospital, clinic, etc.) or facilities of some other type such as a rehabilitation services provider.”)
Regarding claim 10, Chauhan and Bhugra teach the modified device of claim 3, wherein the non- transitory computer-readable memory is configured to store the feedback, and wherein the at least one processor is configured to provide the feedback to a remote user in an on-demand manner. (While Chauhan does not disclose that the data is transferred remotely, using the modified display processors of Bhurga, the user’s exercise data can be stored and reviewed through the system. Bhugra [0062] “a network accessible central rehabilitation management computing system 116, which may be used in the set-up and on-going operation and monitoring of the local aspects of the rehabilitation system 100 and may be located remote from where the patient performs rehabilitation activities, for example, at a healthcare facility (e.g., hospital, clinic, etc.) or facilities of some other type such as a rehabilitation services provider.” In order for the data to be transferred and reviewed by a remote user, the data would therefore be stored by the system as to allow the medical profession time to review and asses the data given by the user.)
Regarding claim 11, Chauhan and Bhugra teach the modified device of claim 1, wherein the one or more rehabilitation activities comprises at least one force assessment configured to assess motor function of the appendage. (While Chauhan does not disclose that the data is used to asses the current user’s hand movements, using the modified display processors of Bhurga, the user’s exercise data can be evaluated and reviewed through the system. Bhurga [0119] “The system 100 may also display, for example at the end of a rehabilitation session, a summary report of all of the exercises that were performed during the rehabilitation session, and in addition a general assessment of the patient's progress toward certain goals with the rehabilitation effort.” The summary in this instance would be the assessment of the exercise completed, detailing where the users progress through the rehabilitation session and giving an accurate assessment of how the user is doing.)
Regarding claim 17, Chauhan discloses a method of rehabilitation comprising:
positioning a flexible wearable robotic system on an appendage of a user (Intelligent Hand Exoskeleton with Grasping Assistance, FIG 1);
operating one or more compliant actuators of the flexible wearable robotic system with at least one processor operatively coupled to the one or more compliant actuators to apply a force to one or more joints of the appendage to perform one or more rehabilitation activities (actuators 10 movable via revolute joint’s R attached to the user’s fingers by linkage lengths 11/12/13, push/pulling forces of actuators detailed in FIG 4B; [0069] “The virtual spring in this system directly connects the user/wearer and the actuator while the real force is transmitted from the actuator to the user/wearer by the physical springs in the SEA”);
sensing one or more parameters related to movement of the appendage with one or more sensors of the flexible wearable robotic system ([0064] “user intent can be determined using other sensor types, such as electromyography (EMG) sensors, force sensors, finger joint position sensors, and/or combinations of sensor types”); and
determining intentional user engagement with the one or more activities with an intention detection algorithm configured to compare the one or more parameters with at least one baseline threshold parameter. (Chauhan [0088], details that the user can personalize the exoskeleton glove to meet the users’ preferences and current movement ability. The individual can many set their limits and range of function and edit these through their rehabilitation as to allow the user to go through their exercises at their own pace. [0073] “ the device can be programmed with a predetermined set of values for range of motion based on user parameters such as age, sex, prior injury, disease presence, and/or dominant vs. non-dominant hand. The predetermined set values can be re-adjusted at any time according to a particular user/wearer's needs and as those need may change over time.” With this mechanism, the user may create their own threshold and parameters or use those that have already been calculated set up their device to the specifications they need for their exercise and the user can compare their exercise data to the preprogramed ones installed with the system.)
Chauhan is silent on output feedback related to the one or more parameters to the user using a display operatively coupled to the at least one processor.
Bhugra teaches of a stroke rehabilitation device to help retain an individual’s motor skills through the use of repetitive exercise, Fig 1. An aspect utilized by this device is a media display where the user can visually see and record their hand movements on a computer program and can be given details on their exercise in an easy-to-understand manor in real time, FIG 1A.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to modify the device of Chauhan to include a multimedia display output as to give the user a more precise and individualized rehabilitation device. By allowing the user to see how their hand and be given guidance on the exercises while at home allows the user to keep up with their rehabilitation on their own time but still track their results efficiently and accurately. Bhugra [0083] “the reports provided to the central system 116 may be reviewed by a health care provider or other rehabilitation specialist to see what if any progress is being made with the rehabilitation effort, and provide instructions for future therapy sessions, feedback, and perhaps encouragement to the patient where appropriate. In some implementations, information included in reports from multiple patients may be anonymized and aggregated to identify factors and trends which may generally lead to improved rehabilitation results for patients. ” This allows an individual to be given not only visual guidance on the exercises that the user should be doing but also track their progress, receive advice on what muscles/fingers to focus on, and provide visual encouragement.
Regarding claim 18, Chauhan and Bhugra teach the modified method of claim 17, wherein outputting feedback related to the one or more parameters comprises outputting real-time feedback to the user. (Chauhan details in [0064] that the sensors chosen to adorn the phalanges need to be able to process data quickly as to ensure the hand moves at the right moment based on the user’s input. Chauhan [0069] “Intelligent assistance prevents uncomfortable motion beyond the natural range of motion of the fingers while reacting very quickly to the user's physical input.” As quickly for a processor is seconds in comparison to a humans processing ability, it should be noted that the feedback from the sensors would be therefore communicated to the processor in “real-time”. Additionally, within the modified device of Chauhan, the sensors are in communication with the processors of Bhugra’s design to display the concurrent motions of the hand on a multimedia device, the computer would therefore be showing the user’s movements in “real-time” as to assist the user in their exercises. Bhugra [0062] “a network accessible central rehabilitation management computing system 116, which may be used in the set-up and on-going operation and monitoring of the local aspects of the rehabilitation system 100 and may be located remote from where the patient performs rehabilitation activities, for example, at a healthcare facility (e.g., hospital, clinic, etc.) or facilities of some other type such as a rehabilitation services provider.” )
Regarding claim 19, Chauhan and Bhugra teach the modified method of claim 17, further comprising storing one or more instructions to perform the one or more rehabilitation activities in non-transitory computer-readable memory operatively coupled to the at least one processor. (Chauhan [0071] “The motion amplification controller and PID controller can comprise computer programs comprising computer executable instructions, which when the program is executed by a computer, cause the computer to carry out any one or more of the processes, methods, and/or algorithms according to the above.”)
Regarding claim 20, Chauhan and Bhugra teach the modified method of claim 19, further comprising:
storing the feedback in the non-transitory computer-readable memory, and
outputting the feedback to the user in an on-demand manner. (Chauhan details in [0064] that the sensors chosen to adorn the phalanges need to be able to process data quickly as to ensure the hand moves at the right moment based on the user’s input. Chauhan [0069] “Intelligent assistance prevents uncomfortable motion beyond the natural range of motion of the fingers while reacting very quickly to the user's physical input.” As quickly for a processor is seconds in comparison to a humans processing ability, it should be noted that the feedback from the sensors would be therefore communicated to the processor in “real-time” or in an “on-demand” manor. Additionally, within the modified device of Chauhan, the sensors are in communication with the processors of Bhugra’s design to display the concurrent motions of the hand on a multimedia device, the computer would therefore be showing the user’s movements in “real-time” as to assist the user in their exercises. In order for the data to be transferred and reviewed by a remote user, the data would therefore be stored by the system as to allow the medical profession time to review and asses the data given by the user.)
Regarding claim 23, Chauhan and Bhugra teach the modified method of 17, further comprising outputting one or more prompts to the user using the display to perform the one or more rehabilitation activities. As detailed in claim 17’s rejection, Bhugra teaches the use of an orthosis device that utilizes a rehabilitation system which receives information from the user and then outputs the corresponding motions done by the user onto a multimedia display. Within Bhugra’s [0062], the media output may also provide exercises for the user to use through visual or auditorial prompts with instructions on the ways to execute the exercise.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to modify the display output detailed by Bhugra to provide prompts and exercise details to the user as to allow for more effective rehabilitation exercise to occur. As there many different injuries and disease that can cause a decrease in hand motion, having a personalized display to give the use a more effective rehabilitation exercise by ensuring the user is doing the correct movements and track the users progress. Bhugra [0062] “local computing system 110 with one or more associated application programs and a user display device 112 to provide instruction, guidance, prompts, and information for set-up, performing rehabilitation sessions, and monitoring progress”)
Regarding claim 24, Chauhan and Bhugra teach the modified method of 17, further wherein operation of the one or more compliant actuators further comprises moving the appendage. (Chuahan [0060] “The finger mechanism comprises one or more actuators 10 that are capable of being connected to a finger by one or more phalanx pads 14.”)
Regarding claim 25, Chauhan and Bhugra teach the modified method of claim 17, further comprising outputting the feedback related to the one or more parameters to a remote user. (While Chauhan does not disclose that the data is transferred remotely, using the modified display processors of Bhurga, the user’s exercise data can be stored and reviewed through the system. Bhugra [0062] “a network accessible central rehabilitation management computing system 116, which may be used in the set-up and on-going operation and monitoring of the local aspects of the rehabilitation system 100 and may be located remote from where the patient performs rehabilitation activities, for example, at a healthcare facility (e.g., hospital, clinic, etc.) or facilities of some other type such as a rehabilitation services provider.”)
Regarding claim 26, Chauhan and Bhugra teach the modified method of claim 17, further comprising:
storing the feedback in the non-transitory computer-readable memory, and
outputting the feedback to a remote user in an on-demand manner. (While Chauhan does not disclose that the data is transferred remotely, using the modified display processors of Bhurga, the user’s exercise data can be stored and reviewed through the system. Bhugra [0062] “a network accessible central rehabilitation management computing system 116, which may be used in the set-up and on-going operation and monitoring of the local aspects of the rehabilitation system 100 and may be located remote from where the patient performs rehabilitation activities, for example, at a healthcare facility (e.g., hospital, clinic, etc.) or facilities of some other type such as a rehabilitation services provider.” In order for the data to be transferred and reviewed by a remote user, the data would therefore be stored by the system as to allow the medical profession time to review and asses the data given by the user.)
Claims 12, 16, 27-28, 31-32, 35, and 37-39 are rejected under 35 U.S.C. 103 as being unpatentable over Chauhan and Bhugra as applied to the claims above and further in view of Krimon et al. (US 20190038222 A1).
Regarding claim 12, Chauhan and Bhugra teach the modified wearable system of claim 1.
Chauhan and Bhugra are both silent on one or more rehabilitation activities comprises at least one active assessment configured to assess movement of the one or more joints without actuation of the one or more compliant actuators.
Krimon teaches of a wearable assistance system to mitigate neuro-muscular ailments such as unintentional motions or loss of hand strength. One aspect of this system is the constant motoring system that continually assess the user’s strength and rang of motion as well as asses the exercises being done by the user and help the user better utilize the exercises and track their progress.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified system of Chauhan and Bhugra to be continually asses the individuals hand motions through the exercise as to monitor the efficiency of the rehab system both with and without the help of the actuators. Krimon [0064] “During assistance mode, for instance during the user standard operating mode, and especially during the exercise mode, the assistance system may continuously assess the user's current muscle strength, flexibility, and motor control. UMR 551 may update the UPP 543 database. UMR 551 may also monitor a range of physical attributes (e.g., strength, tremor intensity, biometrics, and particular activities).” As the assistance device is constantly asses the range of motion and evaluating the exercises for the user, there must in turn be an initial assessment of the user’s current range of motion and strength without the help of the actuators assistance; this allows for the system to then know how much an individual has improves and what specific exercises would be most effective to regain movement and strength. Having a thorough assessment not only at the beginning of the rehabilitation but continuously throughout the rehab sessions and exercises allows the user and the clinician to better understanding of how the user’s hand movement is improving and what steps should be taken in the future.
Regarding claim 16, Chauhan and Bhugra teach the modified wearable system of claim 1.
Chauhan and Bhugra are silent on wherein the at least one processor is further configured to determine continuous user engagement with the one or more rehabilitation activities with a continuous engagement detection algorithm configured to compare the one or more parameters with at least one parameter measured by the one or more sensors when the flexible wearable robotic system actively actuates the one or more joints.
Krimon teaches of a wearable assistance system to mitigate neuro-muscular ailments such as unintentional motions or loss of hand strength. One aspect of this system is the constant motoring system that continually assess the user’s strength and range of motion as well as asses the exercises being done by the user and help the user better utilize the exercises and track their progress
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified system of Chauhan and Bhugra to be continually asses the individuals hand motions through the exercise as to monitor the efficiency of the rehab system both with and without the help of the actuators. Krimon [0056] “Therefore, if the user has a loss of strength in only some muscles, or varying levels of strength loss, actuators may be activated at different levels of intensity. If the user has tremors in specific muscles, then the actuators corresponding to the muscles prone to tremor may be activated to suppress the tremors” Having a thorough assessment not only at the beginning of the rehabilitation but continuously throughout the rehab sessions and exercises allows the user and the clinician to better understanding of how the user’s hand movement is improving and what steps should be taken in the future. This also allows the user to use the device in their day-to-day activities in order to regain parts of their life that have been affected by the lack of movability in their hand; such as drinking coffee or picking up a pen. As the device assess the motions done by the individual during daily activities it can continuously gather data for the machine learning operations and fine-tune its operative features to enhance user experience, [0057].
Regarding claim 27, Chauhan and Bhugra teach the modified method of claim 17.
Chauhan and Bhugra are silent on further comprising assessing motor function of the appendage during at least one force assessment.
Krimon teaches of a wearable assistance system to mitigate neuro-muscular ailments such as unintentional motions or loss of hand strength. One aspect of this system is the constant motoring system that continually assess the user’s strength and range of motion as well as asses the exercises being done by the user and help the user better utilize the exercises and track their progress.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified system of Chauhan and Bhugra to be continually asses the individuals hand motions through the exercise as to monitor the efficiency of the rehab system both with and without the help of the actuators. Krimon [0064] “During assistance mode, for instance during the user standard operating mode, and especially during the exercise mode, the assistance system may continuously assess the user's current muscle strength, flexibility, and motor control. UMR 551 may update the UPP 543 database. UMR 551 may also monitor a range of physical attributes (e.g., strength, tremor intensity, biometrics, and particular activities).” As the assistance device is constantly asses the range of motion and evaluating the exercises for the user, there must in turn be an initial assessment of the user’s current range of motion and strength without the help of the actuators assistance; this allows for the system to then know how much an individual has improves and what specific exercises would be most effective to regain movement and strength. Having a thorough assessment not only at the beginning of the rehabilitation but continuously throughout the rehab sessions and exercises allows the user and the clinician to better understanding of how the user’s hand movement is improving and what steps should be taken in the future.
Regarding claim 28, Chauhan and Bhugra teach the modified method of claim 17.
Chauhan and Bhugra are silent on further comprising assessing movement grip strength of the appendage during at least one active assessment configured to assess movement of the one or more joints without actuation of the one or more compliant actuators.
Krimon teaches of a wearable assistance system to mitigate neuro-muscular ailments such as unintentional motions or loss of hand strength. One aspect of this system is the constant motoring system that continually assess the user’s strength and range of motion as well as asses the exercises being done by the user and help the user better utilize the exercises and track their progress.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified system of Chauhan and Bhugra to be continually asses the individuals hand motions through the exercise as to monitor the efficiency of the rehab system both with and without the help of the actuators. Krimon [0064] “During assistance mode, for instance during the user standard operating mode, and especially during the exercise mode, the assistance system may continuously assess the user's current muscle strength, flexibility, and motor control. UMR 551 may update the UPP 543 database. UMR 551 may also monitor a range of physical attributes (e.g., strength, tremor intensity, biometrics, and particular activities).” As the assistance device is constantly asses the range of motion and evaluating the exercises for the user, there must in turn be an initial assessment of the user’s current range of motion and strength without the help of the actuators assistance; this allows for the system to then know how much an individual has improves and what specific exercises would be most effective to regain movement and strength. Having a thorough assessment not only at the beginning of the rehabilitation but continuously throughout the rehab sessions and exercises allows the user and the clinician to better understanding of how the user’s hand movement is improving and what steps should be taken in the future.
Regarding claim 31, Chauhan and Bhugra teach the modified method of claim 17.
Chauhan and Bhugra are silent on further comprising determining continuous user engagement with the one or more rehabilitation activities with a continuous engagement detection algorithm configured to compare the one or more parameters with at least one parameter measured by the one or more sensors when the flexible wearable robotic system actively actuates the one or more joints.
Krimon teaches of a wearable assistance system to mitigate neuro-muscular ailments such as unintentional motions or loss of hand strength. One aspect of this system is the constant motoring system that continually assess the user’s strength and range of motion as well as asses the exercises being done by the user and help the user better utilize the exercises and track their progress
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified system of Chauhan and Bhugra to be continually asses the individuals hand motions through the exercise as to monitor the efficiency of the rehab system both with and without the help of the actuators. Krimon [0056] “Therefore, if the user has a loss of strength in only some muscles, or varying levels of strength loss, actuators may be activated at different levels of intensity. If the user has tremors in specific muscles, then the actuators corresponding to the muscles prone to tremor may be activated to suppress the tremors” Having a thorough assessment not only at the beginning of the rehabilitation but continuously throughout the rehab sessions and exercises allows the user and the clinician to better understanding of how the user’s hand movement is improving and what steps should be taken in the future. This also allows the user to use the device in their day-to-day activities in order to regain parts of their life that have been affected by the lack of movability in their hand; such as drinking coffee or picking up a pen. As the device assess the motions done by the individual during daily activities it can continuously gather data for the machine learning operations and fine-tune its operative features to enhance user experience, [0057].
Regarding claim 32, Chauhan and Bhugra teach the modified method of claim 17.
Chauhan and Bhugra are silent on assessing at least one of spasticity, tone, and muscle rigidity with the flexible wearable robotic system.
Krimon teaches of a wearable assistance system to mitigate neuro-muscular ailments such as unintentional motions or loss of hand strength. One aspect of this system is the constant motoring system that continually assess the user’s strength and range of motion as well as asses the exercises being done by the user and help the user better utilize the exercises and track their progress.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified system of Chauhan and Bhugra to be asses the individuals’ physical characteristics as well as their movement ability. As the individual’s strength and muscle tone and deeply affect an individual’s range of motion, the assessment system of Krimon must take an individual’s characteristics into account before calculating the best treatment and rehabilitation exercises. Krimon [0064] “the assistance system may continuously assesses the user's current muscle strength, flexibility, and motor control. UMR 551 may update the UPP 543 database. UMR 551 may also monitor a range of physical attributes (e.g., strength, tremor intensity, biometrics, and particular activities)”. This allows the device to have a greater efficiency for an individual’s rehabilitation by customizing their exercise routines as to fit what the user is capable of.
Regarding claim 35, Chauhan and Bhugra teach the modified system of claim 1.
Chauhan and Bhugra are silent on wherein the intention detection algorithm is further configured to determine when the user attempts to initiate a movement by analyzing data from the one or more sensors to determine when the user is attempting to extend or contract the appendage.
Krimon teaches of a wearable assistance system to mitigate neuro-muscular ailments such as unintentional motions or loss of hand strength. One aspect of this system is the constant motoring system that continually assess the user’s strength and range of motion as well as asses the exercises being done by the user and help the user better utilize the exercises and track their progress.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified system of Chauhan and Bhugra to be asses when the user would like to contract the glove to pick up something vs extend the glove as to release the hold on the object. As detailed in Krimon [0062-0066], the device comprises of a machine learning assistance feature which calculates the data from the numerous sensors throughout the hand in order to assist the user in their daily activities. This machine learning software is constantly review and comparing the data from previous uses but also current movements of the user as to predict the next motions the user might do. Since the program is assessing all details of the user’s movement during use, it would therefore be understood that the device is analyzing when and if the hand will need to expand or contract and utilizing such details to understand how much force is necessary when picking up or setting down an object. As stated in [0067], it is necessary to always be analyzing and learning as their would-be significant difference for the user should they wish to pick up a ceramic mug vs a paper cup, thus allowing the device to measure expanding and contracting data points of the user’s hand.
Regarding claim 37, Chauhan and Bhugra teach the modified system of claim 11.
Chauhan and Bhugra are silent on wherein during the at least one force assessment, the at least one processor is configured to:
operate the one or more compliant actuators to apply a resistance force; and
prompt the user to apply a maximum force in a direction opposing the resistance force.
Krimon teaches of a wearable assistance system to mitigate neuro-muscular ailments such as unintentional motions or loss of hand strength. One aspect of this system is the constant motoring system that continually assess the user’s strength and range of motion as well as asses the exercises being done by the user and help the user better utilize the exercises and track their progress.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified system of Chauhan and Bhugra to be asses the individuals’ physical characteristics as well as their movement ability. Krimon [0058] “In an embodiment, the assistance system includes an exercise mode. This mode provides an exercise regimen for the user (e.g., stretching and strengthening). In this mode, the system may first prompt the user before engaging in a resistance training course. The MME 545 may locally adjust how much resistance or stretching to use depending on the strength remaining in particular muscle(s)”. This allows the device to have a greater efficiency for an individual’s rehabilitation by customizing their exercise routines as to fit what the user is capable of at their maximum strength. The assessment will also be cable to compare the maximum strength before rehabilitation and after rehabilitation as to show the improvement to the user and their clinician.
Regarding claim 38, Chauhan and Bhugra teach the modified system of claim 12, wherein the at least one active assessment is a calibration assessment to evaluate an active range of motion of the appendage by prompting the user to extend or contract the appendage to a greatest comfortable capacity.
Krimon teaches of a wearable assistance system to mitigate neuro-muscular ailments such as unintentional motions or loss of hand strength. One aspect of this system is the constant motoring system that continually assess the user’s strength and range of motion as well as asses the exercises being done by the user and help the user better utilize the exercises and track their progress.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified system of Chauhan to be continually asses the individuals hand motions through the exercise as to monitor the efficiency of the rehab system both with and without the help of the actuators. Krimon [0064] “During assistance mode, for instance during the user standard operating mode, and especially during the exercise mode, the assistance system may continuously assess the user's current muscle strength, flexibility, and motor control. UMR 551 may update the UPP 543 database. UMR 551 may also monitor a range of physical attributes (e.g., strength, tremor intensity, biometrics, and particular activities).” As the assistance device is constantly asses the range of motion and evaluating the exercises for the user, there must in turn be an initial assessment of the user’s current range of motion and strength without the help of the actuators assistance; this allows for the system to then know how much an individual has improves and what specific exercises would be most effective to regain movement and strength. Having a thorough assessment not only at the beginning of the rehabilitation but continuously throughout the rehab sessions and exercises allows the user and the clinician to better understanding of how the user’s hand movement is improving and what steps should be taken in the future.
Regarding claim 39, Chauhan and Bhugra teach the modified system of claim 12.
Chauhan and Bhugra are silent wherein data from the at least one active assessment is stored for comparison with data from other active assessments at an end of a rehabilitation session to monitor effects and progress of the rehabilitation session.
Krimon teaches of a wearable assistance system to mitigate neuro-muscular ailments such as unintentional motions or loss of hand strength. One aspect of this system is the constant motoring system that continually assess the user’s strength and range of motion as well as asses the exercises being done by the user and help the user better utilize the exercises and track their progress.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified system of Chauhan to be continually asses the individuals hand motions through the exercise as to monitor the efficiency of the rehab system both with and without the help of the actuators. Krimon [0064] “During assistance mode, for instance during the user standard operating mode, and especially during the exercise mode, the assistance system may continuously assess the user's current muscle strength, flexibility, and motor control. UMR 551 may update the UPP 543 database. UMR 551 may also monitor a range of physical attributes (e.g., strength, tremor intensity, biometrics, and particular activities).” As the assistance device is constantly asses the range of motion and evaluating the exercises for the user, there must in turn be an initial assessment of the user’s current range of motion and strength without the help of the actuators assistance; this allows for the system to then know how much an individual has improves and what specific exercises would be most effective to regain movement and strength. Having a thorough assessment not only at the beginning of the rehabilitation but at the end of the rehab sessions and exercises allows the user and the clinician to better understanding of how the user’s hand movement is improving and what steps should be taken in the future.
Claims 13-14 and 29 are rejected under 35 U.S.C. 103 as being unpatentable over Chauhan and Bhugra as applied to the claims above and further in view of Wijesundara et al. (US 20180303698 A1).
Regarding claim 13, Chauhan and Bhugra teach the modified wearable system of claim 1.
Chauhan and Bhugra are silent on wherein the one or more parameters comprises a deformation and/or change in shape of at least one of the one or more compliant actuators.
Wijesundara teaches of a rehabilitation glove that utilizes actuators along the fingers of a glove type device. These fluid-driven actuators contain ridged and semi-ridged sections along the phalanges of the glove to allow the fingers of the user to expand and contract as well as allow the device to help the user in expanding and contracting said fingers, [0084]. These soft sections are small bellows that change shape slightly or “deform” as to follow the natural movement of the users’ fingers, Fig 23A-B and fig 24A-D.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified device of Chauhan and Bhugra as to utilize interchanging ridged and semi-ridged actuators for more precise and flexible angular movement. Combining a soft and hard actuation system for rehabilitation combines the advantages of both system (hard actuation- better for complex motions; soft actuation- less cumbersome, heavy, and obtrusive). This allows the user to be able to do both complex hand motions as well as utilize a devise that easy and simple to wear or take on and off. The device would also need to incorporate the parameters and threshold data by the individual as to move the actuators and bellows in the correct manor as it pertains the individual user for an individualized experience. As most individuals have issues putting on heavy and obtrusive devices as well as tend to avoid the use of objects they don’t understand; a light and easy rehabilitation system is necessary for these individuals. Most individuals that have undergone a stroke or have similar motor function diseases are older and find most technology difficult to handle or understand, an easy system of rehabilitation would allow them the use of the glove with personalized exercises with little hard ships and easy the discomfort and progression of their disease.
Regarding claim 14, Chauhan and Bhugra teach the modified wearable system of claim 13, wherein the deformation comprises a bending angle of the at least one of the one or more compliant actuators. (As iterated in claim 13’s rejection, Wijesundara’s fluid driven actuators are able to bend and contract in unison with the user’s finger movement. As the hand contracts the actuators and thus bending at an angle the user is wanting as to either make a fist or to hold an object, [0120-0121].)
Regarding claim 29, Chauhan and Bhugra teach the modified method of claim 17.
Chauhan and Bhugra are silent on wherein operating the one or more compliant actuators further comprises deforming the one or more compliant actuators.
Wijesundara teaches of a rehabilitation glove that utilizes actuators along the fingers of a glove type device. These fluid-driven actuators contain ridged and semi-ridged sections along the phalanges of the glove to allow the fingers of the user to expand and contract as well as allow the device to help the user in expanding and contracting said fingers, [0084]. These soft sections are small bellows that change shape slightly or “deform” as to follow the natural movement of the users’ fingers, Fig 23A-B and fig 24A-D.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified device of Chauhan and Bhugra as to utilize interchanging ridged and semi-ridged actuators for more precise and flexible angular movement. Combining a soft and hard actuation system for rehabilitation combines the advantages of both system (hard actuation- better for complex motions; soft actuation- less cumbersome, heavy, and obtrusive). This allows the user to be able to do both complex hand motions as well as utilize a devise that easy and simple to wear or take on and off. As most individuals have issues putting on heavy and obtrusive devices as well as tend to avoid the use of objects they don’t understand; a light and easy rehabilitation system is necessary for these individuals. Most individuals that have undergone a stroke or have similar motor function diseases are older and find most technology difficult to handle or understand, an easy system of rehabilitation would allow them the use of the glove with little hard ships and easy the discomfort and progression of their disease.
Claims 33 and 34 are rejected under 35 U.S.C. 103 as being unpatentable over Chauhan and Bhugra as applied to the claims above and further in view of Ban et al. (US 20160213978 A1).
Regarding claim 33, Chauhan and Bhugra teach the modified system of claim 1.
Chauhan and Bhurgra are silent on utilizing an inertial measurement sensor.
Ban teaches of a rehabilitation exercise device for the hands that contains an inertial sensor within each of the finger connectors as to measure position and evaluate the rang of motion in regards to the user with respect to the terrestrial magnetism, [0057-0059].
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified of Chauhan and Bhugra to include the inertial measurement sensors as to better collect data on the user for rehabilitation. Chauhan states [0064] “user intent can be determined using other sensor types, such as electromyography (EMG) sensors, force sensors, finger joint position sensors, and/or combinations of sensor types” which leaves open for the use of other sensors as to aid in the metrics of the device. This allows the combination of an inertial sensor to be well understood as an option when creating the device. An inertial sensor would be an obvious edition to the already assembled sensor types as to aid more thoroughly in feedback data to the user, such as hand orientation and velocity when conducting rehabilitation exercises. Additionally, the multi axis measurements of the inertial sensors can provide more detailed feedback to be displayed upon the screen so the user can get a better accurate picture of the hand motions.
Regarding claim 34, Chauhan and Bhugra teach the modified system of claim 33, wherein the one or more sensors includes at least one inertial measurement sensor placed on a finger of the flexible wearable robotic system and at least one inertial measurement sensor placed on a hand of the flexible wearable robotic system, and wherein the at least one inertial measurement sensor on the finger and the at least one inertial measurement sensor on the hand are configured to measure relative movement between each other. (As iterated in claim 33’s rejection, Ban teaches the inertial sensors of the modified device to be placed upon each finger and an additional sensor be placed upon the back of the hand portion of the device. As inertial sensors are multi directional sensors all connected and placed within each other’s vicinity, it would be obvious to one of ordinary skill in the art to understand that the IMU’s are measuring their relative placement not only to each other but to the rest of the hand as well. During data collection the IMU’s are calculating their relative positioning within a 3D plane and being translated on to a media player as to show a vertical hand with respect to the real hand the glove is placed upon.)
Claim 36 is rejected under 35 U.S.C. 103 as being unpatentable over Chauhan and Bhugra as applied to the claims above and further in view of Maddahi et al. (US 20220338761 A1)
Regarding claim 36, Chauhan and Bhugra teach the modified system of claim 2.
Chauhan and Bhugra are silent on the feedback provided in real-time including an animation on the display representing a movement of the user or a progression of an exercise of the user.
Maddahi teaches of a virtual reality-based rehabilitation system where the user wears a multi-use smart glove with connected sensors that then display the hand on a computer screen in a virtual reality simulation. With this aspect, the individual has a low-cost virtual rehab environment that can provide different user interactions: competition, cooperation, counter-operative, and mixed; at their own pace and in their own home. [0031] “The system receives real-time motion through a finger movement using a bending sensor and a three-axis movement of a hand through an IMU sensor, and expresses a virtual hand image in the content, and a vibration motor when the object in the image corresponds to the virtual hand image The system relates to a virtual reality-based hand rehabilitation system that enables tactile feedback to perform rehabilitation training by giving tactile feedback through.”
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filling date to design the modified device of Chauhan and Bhugra to incorporate the virtual reality aspects of Maddahi as to give a user a virtual reality environment to conduct their rehab in their own home. Not only does this give the user great accessibility to professionals in the field, but it allows the medical profession to evaluate the user’s exercises though a 3D frame of motion instead of strictly though a computer screen or having to wait for the user to make and attend an appointment. Maddahi [0032] “A low-cost, virtual environment, rehabilitation system and a glove input device for patients suffering from stroke or other neurological impairments for independent, in-home use, to improve upper extremity motor function, including hand and finger control. The system includes a low-cost input device for tracking arm, hand, and finger movement; an open-source gaming engine, and a processing device. The system is controllable to provide four types of multiple patient/user interactions: competition, cooperation, counter-operative, and mixed.”
Conclusion
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/DANIELLE B RESTAINO/Examiner, Art Unit 3785
/TIMOTHY A STANIS/Supervisory Patent Examiner, Art Unit 3785
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