Detailed Action
This is the Final Rejection based on application 18/327,841 filed on 06/01/2023, and which claims as amended on 01/26/2026 have been considered in the ensuing 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 .
Priority
Acknowledgment is made to the instant application’s claim for priority to provisional application 63/338,194 and as such the date of priority of 05/04/2022 is granted to the instant application.
Response to Amendment
The amendments have not been sufficient to overcome the drawing objections presented in the previous Non-Final Action.
Drawings
Photographs, color photographs and color drawings are not accepted in utility applications unless a petition filed under 37 CFR 1.84(a)(2) is granted. Any such petition must be accompanied by the appropriate fee set forth in 37 CFR 1.17(h), one set of color drawings or color photographs, as appropriate, if submitted via the USPTO patent electronic filing system or three sets of color drawings or color photographs, as appropriate, if not submitted via the via USPTO patent electronic filing system, and, unless already present, an amendment to include the following language as the first paragraph of the brief description of the drawings section of the specification:
The patent or application file contains at least photograph/scan of a screen. Specifically figures 11-26, and 34-35 are either scans of screen images, or scans of drawings, and must be replaced with line drawings in order to avoid loss of clarity of the figures. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
Photographs, color photographs will be accepted if the conditions for accepting color drawings and black and white photographs have been satisfied. See 37 CFR 1.84(b)(2).
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) 1-4,8-14,16, and 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ward et al. US 20200047055 A1, and further in view of Bissonnette et al. US 20220314074 A1.
Regarding claim 1:
Ward teaches an artificial intelligence-based exercise apparatus (Interactive exercise machine system 100) comprising: an exercise support member configured to support a user (“In one embodiment, wireless connection can be made to sensor equipped external exercise equipment, including a pressure sensor mat 124 or accelerometer/gyroscope/force sensor equipped weights, balls, bars, tubes, balance systems, stationary or moveable or other exercise devices 126.” See paragraph [0041]. Figures 1A-3 show a free standing exercise cabinet with a user standing/exercising with use of the system with cameras, while figures 34-36 depict various embodiments of a bench with resistance cables and motors meant to support the user. As such, Ward stating that the user can use various implements such as balls, and other stationary/movable exercise devices and shows the user being supported by the frame of the exercise apparatus and a pressure sensitive mat 124 shows that a bench or other external supporting structure can be used with the system. ); a plurality of exercise resistance components (“A movable arm at least partially surrounding a cord connected to a reel and a force-controlled motor can also be provided.” See paragraph [0010].The examiner notes that Paragraph [00158] of the instant application’s specification states, “the resistance of exercise resistance components, such as cables (e.g., of a cable machine), free weights, automatic adjustable weights, and the like.” Therefore the cord connected to a reel and a force-controlled motor are a plurality of exercise resistance components. ) configured to provide resistance in one or more of a vertical direction, a horizontal direction, and an angled direction (“In one embodiment at least one movable arm is connected to the mechanical support system, with the movable arm having a rotational arm mechanism for pivoting upward and downward arm rotation. The movable arm can also have an arm length adjustable by use of an articulating arm system.” See paragraph [0013] and figure 1); a three-dimensional camera (camera 112, “The three-dimensional cameras can provide absolute or relative distance measurements with respect to user position.” See paragraph [0045]); a computer component portion (“As will be understood, interactive exercise machine system 100 can include connections to either a wired or wireless connect subsystem for interaction with devices such as servers, desktop computers, laptops, tablets, smart phones, or sensor equipped exercise equipment.” See paragraph [0048]) of the artificial intelligence-based exercise apparatus configured to include: one or more processors (“Realtime analysis by local processing system 1110 can involve use of locally available CPU/VPU/GPU/Neural Net accelerator/FPGA/or other programmable logic.” See paragraph [0073]. The examiner notes that a CPU is a processor); memory storing instructions (“In addition, sources of local data (e.g. a hard drive, solid state drive, flash memory, or any other suitable memory, including dynamic memory, such as SRAM or DRAM) that can allow for local data storage of user-specified preferences or protocols.” See paragraph [0048]) that, when executed by the one or more processors, cause the artificial intelligence-based exercise apparatus to perform: tracking, using the three-dimensional camera and a machine learning model, the user's motion over a period of time the user is performing an exercise (“Three-dimensional user position data is captured (step 904) and a kinematic model (step 906) created. Using one or both of heuristic rules (step 908) or trained machine learning systems (step 910), live feedback (step 912) is provided to the user.” See paragraph [0066]); detecting, based on the plurality of exercise resistance components, a rate of motion of the user over the period of time ( “This permits, for example, providing three dimensional (3D) augmented reality with dynamics virtual pointers, text, or other indicators to allow a user to better interact with the exercise machine or connected friends or exercise class members, while still providing real-time information such as instantaneous or average force applied for each exercise, heart rate, or breathing/respiratory rate.” See paragraph [0047]. The examiner notes that the system tracks the user motion and forces through the handles 110 and force sensors 114 as shown in figure 1, and performance in real-time includes the rate of the user’s motion, specifically the speed of an exercise is shown to be tracked by the system as stated in paragraph [0077] where it states, “This is particularly useful, for example, when trying to match heart rate, breathing rate, effective weight moved, or speed in exercises completed before an injury or a period of non-use of the interactive exercise machine.”); dynamically adjusting, a resistance value of at least one of the one or more exercise components in any of the vertical direction, the horizontal direction, and the angled direction (“Advantageously, force control can be modified using scripted control inputs or dynamic force adjustments based on three-dimensional user position and/or kinematic user motion models.” See paragraph [0056]; wherein the dynamically adjusting the resistance value includes: increasing, the resistance value of at least one of the plurality of exercise resistance components in any of the vertical direction, the horizontal direction, and the angled direction (The examiner notes that as stated throughout the rejection above, the system of Ward makes dynamic real-time adjustments to the resistance/forces the user acts against during exercise, in response to the rate of the user’s motion or the preset inputs the user enters, and as stated in paragraph [0010] the motor, pulleys, cord/cable, and handles exert the force changes in all the three dimensional-directions according to the position of the arms shown in figure 1).
[AltContent: textbox (FIG. 1 is an illustration of one embodiment of an interactive exercise machine system 100 with personalized training capabilities being used by a user 101. See paragraph [0040])]
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Ward fails to teach determining, based on the tracked user's motion over the period of time and the detected rate of motion of the user over the period of time, a number of repetitions in reserve at a particular point of time during the period of time the user is performing the exercise, and that the dynamic adjustment of the resistance value is based on the determined number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise, and that increasing resistance value is in response to determining the number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise, and wherein an amount the resistance value is increased is based on the determined number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise and past exercises performed by the user and past exercises performed by other users.
The examiner notes that the specification of the instant application does not specify what the “reserve” is regarding the repetitions, but that based off of the claim language the examiner is interpreting the limitation to mean that the apparatus can keep track of how many repetitions of the particular exercise the user has completed, and has a number that they need to complete for each exercise, which Ward can do as stated in paragraph [0074], where it discusses repeated motion analysis, and with paragraph [0077] discusses long term exercises optimization with force of repetitions for exercises, which show that some tracking of repetitions occur, and shown in figure 6A.
Bissonnette, however, teaches a system and methods for generating an improved exercise plan for a user to perform using an exercise machine through the use of artificial intelligence engines, and further teaches determining, based on the tracked user's motion over the period of time and the detected rate of motion of the user over the period of time, a number of repetitions in reserve at a particular point of time during the period of time the user is performing the exercise (“The levels of attainment may be quantified by, measured by, or associated with measurements (e.g., range of motion extension and/or flexion angles, exerted force measurements, amount of weight lifted, pressed, or curled, etc.), achievements (e.g., number of sets completed, number of repetitions completed, number of exercise sessions completed, weight lost, calories consumed, steps walked, etc.), and the like.” See paragraph [0260], with the examiner noting that as stated above under the broadest reasonable interpretation of what “repetitions in reserve’ is meant to be the system measures the current activity to track the users motion and decide a repetition has been completed as the sensors on the exercise machine or the user track the users range of motion as discussed throughout Bissonnette, and compares that against the number of repetitions required in the exercise plan in order to make its adjustments.), and that the dynamic adjustment of the resistance value is based on the determined number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise (“Based on attributes of the user, performance measurements of the user, user-reported difficulty levels of exercises, and/or user-reported pain levels, the exercises and attributes of operating parameters may change dynamically as a user performs the exercise plan” See paragraph [0266], where the examiner notes that the operating parameters include a resistance of the exercise machine), and that increasing resistance value is in response to determining the number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise (See above discussions regarding how the system tracks repetitions and current performance to change the operating parameters dynamically during exercise), and wherein an amount the resistance value is increased is based on the determined number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise (“The muscular strength target threshold may be determined based on a historical performance of the user using the exercise machine (e.g., amount of pounds lifted for a particular exercise, amount of force applied associated with each body part, etc.) and/or other exercise machines, a fitness level (e.g., how active the user is) of the user, a diet of the user, a protocol for determining a muscular strength target, etc.” See paragraph [0082]. The examiner notes that the target thresholds are used by the machine learning program to determine when adjustments to resistance or exercise need to be made in order for the user to meet their goals) and past exercises performed by the user and past exercises performed by other users (“The machine learning model 60 may be trained to select the exercises and/or an order of the exercises for a user based on whether the user enjoyed the exercise and/or exercise order or whether other users indicated they enjoyed the exercise and/or exercise order.” See paragraph [0267]. The examiner further notes that the machine learning program has been stated to use the data of other users to find similarities in goals, exercise plans, and treatment needs in order to curate the exercises and exercise plans of the current user which includes resistance adjustments from past sessions of the other users.).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the artificial intelligence software of Ward to use data regarding the current number of repetitions, and how many repetitions for a particular exercise remain, as well as data from past exercises performed by the user, and other users, to increase the resistance the user is exercising against as taught by Bissonnette, as Ward already includes social engagement functions to foster competition or comparison to friends, and this would allow each user to tailor their exercise sessions more specifically to reach a variety of different goals.
Regarding claim 2:
Ward as modified discloses the artificial intelligence-based exercise apparatus of claim 1, wherein the plurality of exercise resistance components includes a plurality of motors and a plurality of cables (“A force-controlled motor is attached to the mechanical support system and a reel is driven by the force-controlled motor.” See paragraph [0010] and figure 4A which shows the cable and motor inside one of the arms of the machine in figure 1, which includes the same structures for both arms making multiple motors and cables), wherein a first motor of the plurality of motors provides dynamic resistance for a first cable of the plurality of cables (“The interactive exercise system also has a handle graspable by a user and includes a cord extending between the reel and the handle, force applied through the force-controlled motor is based at least in part on detected user force input” See paragraph [0010]), and wherein a second motor of the plurality of motors provides dynamic resistance for a second cable of the plurality of cables (See above citations of paragraph [0010] which apply to both arms, motors, and cables of the exercise machine as stated previously).
Regarding claim 3:
Ward as modified discloses the artificial intelligence-based exercise apparatus of claim 1, wherein the plurality of exercise resistance components includes any of free weights and automatic adjustable weights (See rejection of claim 1 and figure 1, with respect to reference numeral 126).
Regarding claim 4:
Ward as modified discloses the artificial intelligence-based exercise apparatus of claim 2, wherein the detecting the rate of motion of the user over the period of time includes: determining, based on the first motor of the plurality of motors and the second motor of the plurality of motors, the rate of motion of the user over the period of time (“In operation, the sensor/pulley assembly 408A provides instantaneous force data to allow for immediate control of applied force by motor 402A.” See paragraph [0056]. The examiner notes that paragraph [0056] further states, “In some embodiments, optional cord braking systems, tensioners, or sensors can be used. Force, cord distance, acceleration, torque or twist sensors can also be used in various embodiments. Advantageously, force control can be modified using scripted control inputs or dynamic force adjustments based on three-dimensional user position and/or kinematic user motion models”, where acceleration sensors measure the motion of the user through the force controlled motors, reels, and pulleys and would be a measure of the rate of the user’s motion over time.)
Regarding claim 6:
Ward as modified teaches the apparatus of claim 1, but fails to teach wherein the dynamically adjusting the resistance value includes: decreasing, in response to detecting the rate of motion of the user over the period of time and based on the detected rate of motion of the user over the period of time, the resistance value of at least one of the plurality of exercise resistance components in any of the vertical direction, the horizontal direction, and the angled direction. The examiner notes that as stated above in the rejection of claim 1, the system of Ward makes dynamic real-time adjustments to the resistance/forces the user acts against during exercise, in response to the rate of the user’s motion or the preset inputs the user enters, and as stated in paragraph [0010] the motor, pulleys, cord/cable, and handles exert the force changes in multiple directions according to the position of the arms shown in figure 1. Ward doesn’t specifically teach the wording that the system increases or decreases the resistance in response, only that the system will adjust accordingly.
Bissonnette, however, teaches a system and methods for generating an improved exercise plan for a user to perform using an exercise machine through the use of artificial intelligence engines, and further teaches that the resistance provided by the machine is increased or decreased based on the user performance by the artificial intelligence control system (“For example, the cloud-based computing system 16 may increase or decrease the intensity of the exercise by modifying a parameter (e.g., resistance, speed, etc.) of the exercise machine 100.” See paragraph [0203]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Ward to increase or decrease the resistance in response to the user’s performance as taught by Bissonnette since the system of Ward already makes automatic real-time dynamic adjustments to the forces/resistances the user exercises with as the rate of exercise is monitored by the system.
Regarding claim 8:
Ward as modified teaches the apparatus of claim 6, wherein an amount the resistance value is decreased is based on the detected rate of motion of the user over the period of time (See rejection of claim 6) (“In some embodiments the exercises can be provided via a personal exercise history module able to store exercise history, including at least one of three-dimensional user pose, video of user, and skeletal extraction data.” See paragraph [0019]), user input (“In other embodiments, a force applied through the force-controlled component is based at least in part on detected user input.” See paragraph [0017]), and past exercises performed by other users.
The examiner notes that the phrase “one or more of” preceding the list of options which the invention uses to determine the amount the resistance values decreases by requires only that one of the options are needed for the invention, and that Ward as modified Bissonnette teaches at least one of the options as stated above.
Regarding claim 9:
Ward as modified discloses the artificial intelligence-based exercise apparatus of claim 1, further comprising a display (display 102), and wherein the instructions, when executed by the one or more processors, cause the artificial intelligence-based exercise apparatus to perform: presenting on the display an instructor performing one or more exercises being performed by the user (“Visual feedback may also include additional windowed video clips, inserted video clips into trainer video showing a trainer providing specific feedback, and audio overlays or instructions.” See paragraph [0063]).
Regarding claim 10:
Ward as modified discloses the artificial intelligence-based exercise apparatus of claim 1, further comprising a mobile device of the user (“With the exception of the mirrored user face presentation, the illustrated data of FIGS. 10A-B can also be available for viewing on desktop computers, laptops, tablets or smartphones” See paragraph [0067]), wherein the mobile device of the user is configured to execute a mobile application capable of controlling the artificial intelligence-based exercise apparatus (“User interface modules can include screen displays, audio (via headphone or speaker), music service providers such as Spotify, video render services, and voice, touchscreen, or smartphone app mediated command input.” See paragraph [0056])..
Regarding claim 11:
Ward teaches a method of exercising using an artificial intelligence-based exercise apparatus (Interactive exercise machine system 100) , the method comprising: an exercise support member configured to support a user (“In one embodiment, wireless connection can be made to sensor equipped external exercise equipment, including a pressure sensor mat 124 or accelerometer/gyroscope/force sensor equipped weights, balls, bars, tubes, balance systems, stationary or moveable or other exercise devices 126.” See paragraph [0041]. The examiner notes that this limitation of the cited prior art appears to be mixing the embodiments of the claimed invention shown in the drawings of the instant application. Figures 1A-3 show a free standing exercise cabinet with a user standing/exercising with use of the system with cameras, while figures 34-36 depict various embodiments of a bench with resistance cables and motors meant to support the user. As such, Ward stating that the user can use various implements such as balls, and other stationary/movable exercise devices and shows the user being supported by the frame of the exercise apparatus and a pressure sensitive mat 124 shows that a bench or other external supporting structure can be used with the system. ); a plurality of exercise resistance components (“A movable arm at least partially surrounding a cord connected to a reel and a force-controlled motor can also be provided.” See paragraph [0010]. The examiner notes that Paragraph [00158] of the instant application’s specification states, “the resistance of exercise resistance components, such as cables (e.g., of a cable machine), free weights, automatic adjustable weights, and the like.” Therefore the cord connected to a reel and a force-controlled motor are a plurality of exercise resistance components.) configured to provide resistance in one or more of a vertical direction, a horizontal direction, and an angled direction (“In one embodiment at least one movable arm is connected to the mechanical support system, with the movable arm having a rotational arm mechanism for pivoting upward and downward arm rotation. The movable arm can also have an arm length adjustable by use of an articulating arm system.” See paragraph [0013] and figure 1); a three-dimensional camera (camera 112, “The three-dimensional cameras can provide absolute or relative distance measurements with respect to user position.” See paragraph [0045]); a computer component portion (“As will be understood, interactive exercise machine system 100 can include connections to either a wired or wireless connect subsystem for interaction with devices such as servers, desktop computers, laptops, tablets, smart phones, or sensor equipped exercise equipment.” See paragraph [0048]) of the artificial intelligence-based exercise apparatus configured to include: one or more processors (“Realtime analysis by local processing system 1110 can involve use of locally available CPU/VPU/GPU/Neural Net accelerator/FPGA/or other programmable logic.” See paragraph [0073]. The examiner notes that a CPU is a processor); memory storing instructions (“In addition, sources of local data (e.g. a hard drive, solid state drive, flash memory, or any other suitable memory, including dynamic memory, such as SRAM or DRAM) that can allow for local data storage of user-specified preferences or protocols.” See paragraph [0048]) that, when executed by the one or more processors, cause the artificial intelligence-based exercise apparatus to perform: tracking, using the three-dimensional camera and a machine learning model, the user's motion over a period of time the user is performing an exercise (“Three-dimensional user position data is captured (step 904) and a kinematic model (step 906) created. Using one or both of heuristic rules (step 908) or trained machine learning systems (step 910), live feedback (step 912) is provided to the user.” See paragraph [0066]); detecting, based on the plurality of exercise resistance components, a rate of motion of the user over the period of time ( “This permits, for example, providing three dimensional (3D) augmented reality with dynamics virtual pointers, text, or other indicators to allow a user to better interact with the exercise machine or connected friends or exercise class members, while still providing real-time information such as instantaneous or average force applied for each exercise, heart rate, or breathing/respiratory rate.” See paragraph [0047]. The examiner notes that the system tracks the user motion and forces through the handles 110 and force sensors 114 as shown in figure 1, and performance in real-time includes the rate of the user’s motion, specifically the speed of an exercise is shown to be tracked by the system as stated in paragraph [0077] where it states, “This is particularly useful, for example, when trying to match heart rate, breathing rate, effective weight moved, or speed in exercises completed before an injury or a period of non-use of the interactive exercise machine.”); dynamically adjusting, a resistance value of at least one of the one or more exercise components in any of the vertical direction, the horizontal direction, and the angled direction (“Advantageously, force control can be modified using scripted control inputs or dynamic force adjustments based on three-dimensional user position and/or kinematic user motion models.” See paragraph [0056]; wherein the dynamically adjusting the resistance value includes: increasing, the resistance value of at least one of the plurality of exercise resistance components in any of the vertical direction, the horizontal direction, and the angled direction (The examiner notes that as stated throughout the rejection above, the system of Ward makes dynamic real-time adjustments to the resistance/forces the user acts against during exercise, in response to the rate of the user’s motion or the preset inputs the user enters, and as stated in paragraph [0010] the motor, pulleys, cord/cable, and handles exert the force changes in all the three dimensional-directions according to the position of the arms shown in figure 1).
Ward fails to teach determining, based on the tracked user's motion over the period of time and the detected rate of motion of the user over the period of time, a number of repetitions in reserve at a particular point of time during the period of time the user is performing the exercise, and that the dynamic adjustment of the resistance value is based on the determined number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise, and that increasing resistance value is in response to determining the number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise, and wherein an amount the resistance value is increased is based on the determined number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise and past exercises performed by the user and past exercises performed by other users.
The examiner notes that the specification of the instant application does not specify what the “reserve” is regarding the repetitions, but that based off of the claim language the examiner is interpreting the limitation to mean that the apparatus can keep track of how many repetitions of the particular exercise the user has completed, and has a number that they need to complete for each exercise, which Ward can do as stated in paragraph [0074], where it discusses repeated motion analysis, and with paragraph [0077] discusses long term exercises optimization with force of repetitions for exercises, which show that some tracking of repetitions occur, and shown in figure 6A.
Bissonnette, however, teaches a system and methods for generating an improved exercise plan for a user to perform using an exercise machine through the use of artificial intelligence engines, and further teaches determining, based on the tracked user's motion over the period of time and the detected rate of motion of the user over the period of time, a number of repetitions in reserve at a particular point of time during the period of time the user is performing the exercise (“The levels of attainment may be quantified by, measured by, or associated with measurements (e.g., range of motion extension and/or flexion angles, exerted force measurements, amount of weight lifted, pressed, or curled, etc.), achievements (e.g., number of sets completed, number of repetitions completed, number of exercise sessions completed, weight lost, calories consumed, steps walked, etc.), and the like.” See paragraph [0260], with the examiner noting that as stated above under the broadest reasonable interpretation of what “repetitions in reserve’ is meant to be the system measures the current activity to track the users motion and decide a repetition has been completed as the sensors on the exercise machine or the user track the users range of motion as discussed throughout Bissonnette, and compares that against the number of repetitions required in the exercise plan in order to make its adjustments.), and that the dynamic adjustment of the resistance value is based on the determined number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise (“Based on attributes of the user, performance measurements of the user, user-reported difficulty levels of exercises, and/or user-reported pain levels, the exercises and attributes of operating parameters may change dynamically as a user performs the exercise plan” See paragraph [0266], where the examiner notes that the operating parameters include a resistance of the exercise machine), and that increasing resistance value is in response to determining the number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise (See above discussions regarding how the system tracks repetitions and current performance to change the operating parameters dynamically during exercise), and wherein an amount the resistance value is increased is based on the determined number of repetitions in reserve at the particular point of time during the period of time the user is performing the exercise (“The muscular strength target threshold may be determined based on a historical performance of the user using the exercise machine (e.g., amount of pounds lifted for a particular exercise, amount of force applied associated with each body part, etc.) and/or other exercise machines, a fitness level (e.g., how active the user is) of the user, a diet of the user, a protocol for determining a muscular strength target, etc.” See paragraph [0082]. The examiner notes that the target thresholds are used by the machine learning program to determine when adjustments to resistance or exercise need to be made in order for the user to meet their goals) and past exercises performed by the user and past exercises performed by other users (“The machine learning model 60 may be trained to select the exercises and/or an order of the exercises for a user based on whether the user enjoyed the exercise and/or exercise order or whether other users indicated they enjoyed the exercise and/or exercise order.” See paragraph [0267]. The examiner further notes that the machine learning program has been stated to use the data of other users to find similarities in goals, exercise plans, and treatment needs in order to curate the exercises and exercise plans of the current user which includes resistance adjustments from past sessions of the other users.).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the artificial intelligence software of Ward to use data regarding the current number of repetitions, and how many repetitions for a particular exercise remain, as well as data from past exercises performed by the user, and other users, to increase the resistance the user is exercising against as taught by Bissonnette, as Ward already includes social engagement functions to foster competition or comparison to friends, and this would allow each user to tailor their exercise sessions more specifically to reach a variety of different goals.
Regarding claim 12:
Ward discloses the method of claim 11, wherein the plurality of exercise resistance components includes a plurality of motors and a plurality of cables (“A force-controlled motor is attached to the mechanical support system and a reel is driven by the force-controlled motor.” See paragraph [0010] and figure 4A which shows the cable and motor inside one of the arms of the machine in figure 1, which includes the same structures for both arms making multiple motors and cables), wherein a first motor of the plurality of motors provides dynamic resistance for a first cable of the plurality of cables (“The interactive exercise system also has a handle graspable by a user and includes a cord extending between the reel and the handle, force applied through the force-controlled motor is based at least in part on detected user force input” See paragraph [0010]), and wherein a second motor of the plurality of motors provides dynamic resistance for a second cable of the plurality of cables (See above citations of paragraph [0010] which apply to both arms, motors, and cables of the exercise machine as stated previously).
Regarding claim 13:
Ward discloses the method of claim 11, wherein the plurality of exercise resistance components includes any of free weights and automatic adjustable weights (See rejection of claim 11 and figure 1, with respect to reference numeral 126).
Regarding claim 14:
Ward discloses the method of claim 12, wherein the detecting the rate of motion of the user over the period of time includes: determining, based on the first motor of the plurality of motors and the second motor of the plurality of motors, the rate of motion of the user over the period of time (“In operation, the sensor/pulley assembly 408A provides instantaneous force data to allow for immediate control of applied force by motor 402A.” See paragraph [0056]. The examiner notes that paragraph [0056] further states, “In some embodiments, optional cord braking systems, tensioners, or sensors can be used. Force, cord distance, acceleration, torque or twist sensors can also be used in various embodiments. Advantageously, force control can be modified using scripted control inputs or dynamic force adjustments based on three-dimensional user position and/or kinematic user motion models”, where acceleration sensors measure the motion of the user through the force controlled motors, reels, and pulleys and would be a measure of the rate of the user’s motion over time.)
Regarding claim 16:
Ward teaches the method of claim 11, but fails to teach wherein the dynamically adjusting the resistance value includes: decreasing, in response to detecting the rate of motion of the user over the period of time and based on the detected rate of motion of the user over the period of time, the resistance value of at least one of the plurality of exercise resistance components in any of the vertical direction, the horizontal direction, and the angled direction.
The examiner notes that as stated above in the rejection of claim 11, the system of Ward makes dynamic real-time adjustments to the resistance/forces the user acts against during exercise, in response to the rate of the user’s motion or the preset inputs the user enters, and as stated in paragraph [0010] the motor, pulleys, cord/cable, and handles exert the force changes in multiple directions according to the position of the arms shown in figure 1. Ward doesn’t specifically teach the wording that the system increases or decreases the resistance in response, only that the system will adjust accordingly.
Bissonnette, however, teaches a system and methods for generating an improved exercise plan for a user to perform using an exercise machine through the use of artificial intelligence engines, and further teaches that the resistance provided by the machine is increased or decreased based on the user performance by the artificial intelligence control system (“For example, the cloud-based computing system 16 may increase or decrease the intensity of the exercise by modifying a parameter (e.g., resistance, speed, etc.) of the exercise machine 100.” See paragraph [0203]).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Ward to increase or decrease the resistance in response to the user’s performance as taught by Bissonnette since the system of Ward already makes automatic real-time dynamic adjustments to the forces/resistances the user exercises with as the rate of exercise is monitored by the system.
Regarding claim 18:
Ward as modified teaches the method of claim 16, wherein an amount the resistance value is decreased is based on the detected rate of motion of the user over the period of time (See rejection of claim 16) and one or more of past exercises performed by the user(“In some embodiments the exercises can be provided via a personal exercise history module able to store exercise history, including at least one of three-dimensional user pose, video of user, and skeletal extraction data.” See paragraph [0019]), user input (“In other embodiments, a force applied through the force-controlled component is based at least in part on detected user input.” See paragraph [0017]), and past exercises performed by other users.
The examiner notes that the phrase “one or more of” preceding the list of options which the invention uses to determine the amount the resistance values decreases by requires only that one of the options are needed for the invention, and that Ward as modified Bissonnette teaches at least one of the options as stated above.
Regarding claim 19:
Ward discloses the method of claim 11, wherein the artificial intelligence-based exercise apparatus further comprises a display (display 102), and wherein the instructions, when executed by the one or more processors, cause the artificial intelligence-based exercise apparatus to perform: presenting, on the display, an instructor performing one or more exercises being performed by the user (“Visual feedback may also include additional windowed video clips, inserted video clips into trainer video showing a trainer providing specific feedback, and audio overlays or instructions.” See paragraph [0063]).
Regarding claim 20:
Ward discloses the method of claim 11, wherein the artificial intelligence-based exercise apparatus further comprises a mobile device of the user (“With the exception of the mirrored user face presentation, the illustrated data of FIGS. 10A-B can also be available for viewing on desktop computers, laptops, tablets or smartphones” See paragraph [0067]), wherein the mobile device of the user is configured to execute a mobile application capable of controlling the artificial intelligence-based exercise apparatus (“User interface modules can include screen displays, audio (via headphone or speaker), music service providers such as Spotify, video render services, and voice, touchscreen, or smartphone app mediated command input.” See paragraph [0056]).
Response to Arguments
Applicant's arguments filed 01/26/2026 have been fully considered but they are not persuasive.
In regards to the applicant’s arguments with respect to the rejection(s) presented under 35 USC 103 in view of the combination of Ward and Bissonnette, the examiner respectfully disagrees and due to the lack of amendments to the claims, the rejection(s) have been maintained above. Specifically the examiner respectfully disagrees with the applicant’s arguments in regards to the interpretation of the phrase “repetitions in reserve” found throughout the claims, being incorrect and therefore the rejection does not teach the claimed limitations. The applicant has done no more than state that the examiner’s interpretation of the claim language is not the same as their intended definition, however, the applicant has not provided an alternative definition in the arguments, nor is any special definition provided in the specification of the instant application. The examiner notes that chapter 714.02 of the MPEP states, “In order to be entitled to reconsideration or further examination, the applicant or patent owner must reply to the Office action. The reply by the applicant or patent owner must be reduced to a writing which distinctly and specifically points out the supposed errors in the examiner’s action and must reply to every ground of objection and rejection in the prior Office action. The reply must present arguments pointing out the specific distinctions believed to render the claims, including any newly presented claims, patentable over any applied references. If the reply is with respect to an application, a request may be made that objections or requirements as to form not necessary to further consideration of the claims be held in abeyance until allowable subject matter is indicated. The applicant’s or patent owner’s reply must appear throughout to be a bona fide attempt to advance the application or the reexamination proceeding to final action. A general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references does not comply with the requirements of this section.”
Therefore, without providing sufficient definition for the phrase there is no proper distinction made. Furthermore, the examiner notes that the plain language definition for “repetitions in reserve” as described by the National Academy of Sports Medicine (NASM) is “Reps in Reserve (RIR) is rising in popularity as a method to measure the intensity of a lift by describing how many more repetitions you could perform before technical failure (an inability to perform the lift with good form).” Which the examiner noted above in the prior art rejections as an interpretation related to the control system of an exercise device, relates to an amount of repetitions a user has completed and an amount they need to complete or should complete which is used by the controller to determine when adjustments to the resistance are required. Since there is no specific definition as to what the applicant considers “repetitions in reserve” found in the specification of the instant application, the examiner has maintained the broadest reasonable interpretation noted in the prior art rejections above.
Acknowledgement is made to the applicant’s statements relating a perceived effort score to the repetitions in reserve, and notes that the example provided in paragraph [00258] of the specification where it states “For example, a detected rate of motion of the user over a period of time, form feedback, past exercises performed by the user, user input, and/or past exercises performed by other users can be used as input for the machine learning model, and the output can be used to determine a perceived effort score for a user performing an exercise. Thus, in one example, a user can be performing a bench press and the dynamic adjustment engine 3608 can determine that a user has three repetitions in reserve at a particular point of time during the exercise. This can be used to adjust resistance during the exercise and/or adjust or set the resistance of subsequent exercises and/or workout routines.”, shows a particular use of the dynamic adjustment engine generating a specific amount of repetitions in reserve for that particular user based off the inputs from the other components of the system provided a more specific meaning to the phrase, as now a specific score which is used by the system is generated which includes the broader repetitions in reserve that determines the adjustments made. The examiner suggests amending the claim language to include this more specific “perceived effort score”, as opposed to the more general “repetitions in reserve” phrasing found in the instant claims, in order to avoid the undefined language found with the phrase “repetitions in reserve” solely, as the plain definition as noted above is different than that of the argued definition, and if taken could cause clarity issues in future amendments.
Conclusion
THIS ACTION IS MADE FINAL. 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 JONATHAN ANGELO DICUIA whose telephone number is (703)756-4713. The examiner can normally be reached M-F 7:30-4:30.
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/J.A.D./Examiner, Art Unit 3784
/LOAN B JIMENEZ/Supervisory Patent Examiner, Art Unit 3784
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