DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status
In the response dated December 24th, 2025, Applicant amended claims 1-15 and 17. Applicant deleted claim 16. Claims 1-15 and 17 are pending.
Examiner’s Note
Applicant is reminded that any claim amendments require markings to show changes in compliance with 37 CFR 1.121 and MPEP 714(c).
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. KR10-2022-0152001, filed on November 14th, 2022.
Should applicant desire to obtain the benefit of foreign priority under 35 U.S.C. 119(a)-(d) prior to declaration of an interference, a certified English translation of the foreign application must be submitted in reply to this action. 37 CFR 41.154(b) and 41.202(e).
Failure to provide a certified translation may result in no benefit being accorded for the non-English application.
Applicant provided copies of the search report in response to the previous Office Action and a certified English of the foreign application was not submitted in reply to the previous action.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on January 13th, 2026 is being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
“a workout target setter” in claims 10-11.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 1
Claims 1- 17 recite subject matter within a statutory category as a process, machine, and/or article of manufacture. However, it will be shown in the following steps, that claims 1-17 are nonetheless unpatentable under 35 U.S.C. 101.
Step 2A Prong One
Claim 9 states:
A workout guide method implemented by a workout guide apparatus including at least one processor and at least one memory storing instructions that, when executed by the at least one processor, cause the workout guide apparatus to perform the method comprising:
estimating PMWestimation of fitness equipment to be used by a user, based on an estimated muscular strength value calculated based on user data; and
providing PMWindividual for the fitness equipment by complementing the PMWestimation with an individual objectification index of the user,
wherein the individual objectification index comprises regularity of repetitions (reps) in units of sets, and optionally comprises one or more of at least some of a weight of the fitness equipment, a number of repetitions (reps), a number of sets, a workout trajectory, and a moving velocity, and regularity of reps in units of sets, which are determined when the user uses the fitness equipment for a pre-set period of time,
sensing, by a sensor, distance information of the fitness equipment while the user uses the fitness equipment,
determining a workout trajectory based on the distance information sensed by the sensor, wherein the workout trajectory corresponds to movement displacement of the fitness equipment plotted against time,
during execution of a set, determining regularity of repetitions in units of sets based on workout trajectories of a plurality of repetitions configuring the set, wherein the regularity of reps in units of sets is determined based on whether the workout trajectories match each other, based on a distance between the workout trajectories, or based on a length of a time series,
during execution of the set, determining whether all repetitions configuring the set have been completed,
during execution of the set, determining a degree of completion of the repetitions based on a division of the regularity into an early regularity, a middle regularity, and a latter regularity within the set, and converting the determined degree of completion into a numerical value which indicates the individual objectification index,
wherein the individual objectification index further reflects at least one of.
a standard deviation of an ascent starting point, a standard deviation of a descent starting point, a standard deviation of a height, a standard deviation of an ascending section velocity, and a standard deviation of a descending section velocity, calculated from the workout trajectories of the repetitions, and
determining the PMWindividual based on the individual objectification index during execution of the set.
The broadest reasonable interpretation of these steps includes mental processes and/or mathematical concepts because each bolded component can practically be performed by the human mind or with pen and paper. Nothing in the claims precludes the bold-font portions from practically being performed in the mind. For example, “estimating PMWestimation of fitness equipment to be used by a user, based on an estimated muscular strength value calculated based on user data” in the context of this claim encompasses a user calculating how much more weight a user can sustain before becoming critically fatigued. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” or “Mathematical concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
A workout guide method implemented by a workout guide apparatus … storing instructions that … cause the workout guide apparatus to perform the method comprising:
estimating PMWestimation of fitness equipment to be used by a user, based on an estimated muscular strength value calculated based on user data; and
providing PMWindividual for the fitness equipment by complementing the PMWestimation with an individual objectification index of the user,
wherein the individual objectification index comprises regularity of repetitions (reps) in units of sets, and optionally comprises one or more of at least some of a weight of the fitness equipment, a number of repetitions (reps), a number of sets, a workout trajectory, and a moving velocity, and regularity of reps in units of sets, which are determined when the user uses the fitness equipment for a pre-set period of time,
during execution of a set, determining regularity of repetitions in units of sets based on workout trajectories of a plurality of repetitions configuring the set, wherein the regularity of reps in units of sets is determined based on whether the workout trajectories match each other, based on a distance between the workout trajectories, or based on a length of a time series,
during execution of the set, determining whether all repetitions configuring the set have been completed,
during execution of the set, determining a degree of completion of the repetitions based on a division of the regularity into an early regularity, a middle regularity, and a latter regularity within the set, and converting the determined degree of completion into a numerical value which indicates the individual objectification index,
wherein the individual objectification index further reflects at least one of.
a standard deviation of an ascent starting point, a standard deviation of a descent starting point, a standard deviation of a height, a standard deviation of an ascending section velocity, and a standard deviation of a descending section velocity, calculated from the workout trajectories of the repetitions, and
determining the PMWindividual based on the individual objectification index during execution of the set.
as drafted, could lay out the precise calculations of repetitions and sets for a personal trainer noting the progress of an athlete as they progress through an extended workout routine. Therefore, under the broadest reasonable interpretation, these steps include multiple abstract ideas that will be identified as a single abstract idea moving forward.
Independent claims 1 and 17 cover similar steps of estimating the degree of use of fitness equipment and provide and objectification index of a user. These claims fall under the same category of an abstract idea and follows the same rationale as claim 9.
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claim 15, reciting particular aspects of how “when the workout trajectory is used as the individual objectification index, completion of the workout trajectory is determined by using an ascent starting point, a descent starting point, an ascending section average velocity, a descending section average velocity, and a height, which are determined from the workout trajectory, a degree of the completion of the workout trajectory is converted into a numerical value, and the numerical value is used as the individual objectification index.” may be performed in the mind but for recitation of generic computer components).
Dependent claims 6 and 14 add additional elements to their parent claims which will be further inspected in the following steps for a practical application to their abstract idea.
Step 2A Prong Two
This judicial exception of “Mental Processes” or “Mathematical Concepts” is not integrated into a practical application because the independent claims do not recite any additional limitations that practically applies the abstract idea. Independent claim 9' s method recites additional elements such as a processor, memory, and sensor. In addition to the generic components and additional elements listed above, independent claim 17' s apparatus also includes a non-transitory computer readable medium and computing device. The processor, memory, sensor, non-transitory computer readable medium and computing device will be treated as a generic computer component. In particular, these additional elements do not integrate the abstract idea into a practical application because the additional elements:
amount to mere instructions to apply an exception (such as recitation of “including at least one processor and at least one memory” and “when executed by the at least one processor,” amounts to invoking computers as a tool to perform the abstract idea, see MPEP 2106.05(f))
add insignificant extra-solution activity to the abstract idea (such as recitation of “sensing, by a sensor, distance information of the fitness equipment while the user uses the fitness equipment,” amounts to mere data gathering, recitation of “determining a workout trajectory based on the distance information sensed by the sensor, wherein the workout trajectory corresponds to movement displacement of the fitness equipment plotted against time,” amounts to insignificant application, see MPEP 2106.05(g))
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims. For instance, dependent claims 6 and 14 add additional elements of a “display” to their parent claims. Additionally, the dependent claims:
add insignificant extra-solution activity to the abstract idea (such as claims 6 and 14 recitation of “wherein the providing of the PMWindividual comprises displaying, through a display, the PMWindividual or a change amount of maximum weight that is liftable when the fitness equipment is used.” adds insignificant extra-solution activity to the abstract idea which amounts to necessary data outputting, see MPEP 2106.05(g)
Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
The remaining dependent claims 2-5, 7, 8, 10-13, and 15 do not recite additional elements or activity but further narrow or define the abstract idea embodied in the claims and hence also do not integrate the aforementioned abstract idea into a practical application.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the independent claims contain no additional elements to apply an exception, add insignificant extra-solution activity to the abstract idea, or generally link the abstract idea to a particular technological environment or field of use.
Dependent claims recite additional subject matter which, with respect to integration of the abstract idea into a practical application, amount to add insignificant extra-solution activity to the abstract idea. These additional limitations amount to an additional elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As previously noted, the claim recites an additional element of a display. Dugan (US 20020160883) demonstrates in para [0028] “During exercise, the video game player may display conventional exercise information such as pulse rate, distance traveled, etc.” that displaying exercise information on a graphical user interface was conventional long before the priority data of the claimed invention. As such, this additional element, individually and in combination with the prior additional element, does not amount to significantly more.
Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-6, 8-15, and 17 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Belson et al. (US20210402259).
Regarding claim 1, Belson (‘259) teaches.
A workout guide apparatus comprising at least one processor and at least one memory storing instructions, the at least one processor is configured to: ([0095] “The controller may further emulate the actions of a trainer using an expert system and thus exhibit artificial intelligence” and [0009] The invention can be implemented in numerous ways, including as a process; an apparatus; a system; a composition of matter; a computer program product embodied on a computer readable storage medium; and/or a processor, such as a processor configured to execute instructions stored on and/or provided by a memory coupled to the processor.”)
estimate PMWestimation of fitness equipment to be used by a user, based on an estimated muscular strength value calculated based on user data; ([0114] “Progressive strength calibration engine 222 is configured to determine the right weight for a user over the course of a set of repetitions of a movement (e.g., a weight that is challenging for the user, but will not push the user to failure by the end of a set).” Where the calibration engine [comprising the PMW estimator] estimates the right weight for a user [comprising PMW estimation for a user] based on a set of repetitions of a user [i.e., an estimated muscular strength value calculated based on user data])
provide PMWindividual for the fitness equipment by complementing the PMWestimation with an individual objectification index of the user, ([0094] “In some embodiments, the exercise machine includes a media controller and/or processor, which monitors/measures user performance (for example, using the one or more sensors described above), and determines loads to be applied to the user's efforts in the resistance unit”)
wherein PMW indicates muscular strength exerted by an individual against a resistance of a weight with an utmost effort,([0013] “the user is brought to maximum effort”) and
wherein the individual objectification index comprises regularity of repetitions (reps) in units of sets, ([0104] “the progressive strength calibration is performed in part by processing and analyzing sensor data (e.g., from accessories and the MCB), as well as user data stored in user data store” where the strength calibration [i.e., objectification index] comprises sensor and user data) and [0193] “set includes a number of repetitions. For example, the set may include 10 repetitions. Other numbers of repetitions may be used in a calibration set. The calibration set ends after the predefined number of repetitions is completed.” Where different repetitions, chosen by the user, are the regulatorily of reps in units of sets pre-set by the user)
and optionally comprises one or more of:
of a weight of the fitness equipment, ([0041] “a user tension sensor; a torque/tension/strain sensor and/or gauge to measure how much tension/force is being applied to the actuator (1010) by the user.” Where tension being applied to an actuator comprises weight of fitness equipment) a number of repetitions (reps), a number of sets, and a workout trajectory, a moving velocity, which are determined when the user uses the fitness equipment for a pre- set period of time. ([0043] “In some embodiments, an IMU is placed on the cable (e.g., via a clip) to determine inertial measurements with respect to the cable” where the inertial measurements comprise a moving velocity of a hand) ([0193] “set includes a number of repetitions. For example, the set may include 10 repetitions. Other numbers of repetitions may be used in a calibration set. The calibration set ends after the predefined number of repetitions is completed.” Where different repetitions, chosen by the user, are the regulatorily of reps in units of sets pre-set by the user)
wherein the workout guide apparatus further comprises a sensor, ([0039] “One example of an encoder is a position encoder; a sensor to measure position of the actuator (1010)”)
wherein the workout trajectory is determined based on the distance information sensed by the sensor and corresponds to movement displacement of the fitness equipment plotted against time, ([0042] “Another example of sensors includes inertial measurement units (IMUs) and [0187] “As described above, the progressive calibration is based on the measurement of the user's speed, which as one example is determined from sensor measurements on the change in cable position” where change in cable position by an inertial measurement units over time comprise determining a workout trajectory for a user based on acceleration of cables over time.
wherein the regularity of reps in units of sets is determined based on workout trajectories of a plurality of repetitions configuring one set, wherein the regularity of reps in units of sets is determined based on whether the workout trajectories match each other, based on a distance between the workout trajectories, or based on a length of a time series, ([0114] “Progressive strength calibration engine 222 is configured to determine the right weight for a user over the course of a set of repetitions of a movement” and [0104] “progressive strength calibration is performed in part by processing and analyzing sensor data (e.g., from accessories and the MCB), as well as user data stored in user data store 226 (e.g., user profile, measurements, goals, suggested weights, etc.), workout data (e.g., current move, load profile for the current move, etc.), camera and microphone information, etc.” and where determining the right weight for a user over a course of repetitions using the sensor measurement data from measurements comprises determining a workout trajectory based on the length of a time series.)
wherein the at least one processor is further configured to: ([0094] In some embodiments, the exercise machine includes a media controller and/or processor”)
determine whether all repetitions configuring the set have been completed; ([0193] “the set may include 10 repetitions. Other numbers of repetitions may be used in a calibration set. The calibration set ends after the predefined number of repetitions is completed.” Where completing calibration based on a number of repetitions completed comprises determining whether all repetitions have been completed)
determine a degree of completion of the repetitions based on a division of the regularity into an early regularity, a middle regularity, and a latter regularity within the set; and ([0239] “As described above, the weight is increased during the concentric phase when the user moves quickly (e.g., above the reference speed), and the weight is decreased when the user moves slowly (e.g., below the reference speed). As the set goes on and the more reps are done (e.g., as the number of reps completed increases), the weight changes are more gradual as the user approaches the appropriate weight for them” where the completion of the repetitions at varying speeds comprises a degree of completion at varying regularity; see also [0194] “In this example, an estimate of the user's strength was determined by progressively increasing the weight over a number of repetitions, and observing the user's speed relative to the reference speed. “ where the speeds comprise a varying regularity)
convert the determined degree of completion into a numerical value which indicates the individual objectification index, ([0133] As one example, the exercise machine determines, with 95% confidence that the user's strength is between two weights. Those two weights are set as the low and high weight parameters for the progressive strength calibration mode.” Where the strength of completing a set between the two weights [comprising a degree of completion] indicates the weight parameters [comprising individual objectification index])
wherein the individual objectification index further reflects at least one of a standard deviation of an ascent starting point, a standard deviation of a descent starting point, a standard deviation of a height, a standard deviation of an ascending section velocity, and a standard deviation of a descending section velocity, calculated from the workout trajectories of the repetitions, and ([0105] “User data store 226 includes information aggregated from multiple users of multiple exercise machines, and includes, for example, population statistics for all or subsets of users. The user data store also includes data specific to individual users. As will be described in further detail below, the data in user data store 226 is used to determine personalized calibration parameters.” and [0253] “5th percentile of sets' weight is selected as the default low weight, and the 90th percentile as the default high weight” and [0189-0190] “In some embodiments, the progressive strength calibration and motor control is performed in real time. For example, during the concentric phase, cable speed measurements are taken periodically (e.g., at 50 Hz, or every 20 milliseconds), and at every time step, the weight is progressively adjusted. If, during the concentric phase, the user is above the reference speed, then additional weight is added” where the percentile weight chosen as a statistical measurement for the concentric phase of cable speed repetitions comprises an objectification index of a standard deviation of an ascending section velocity calculated from the workout trajectories of the repetitions; see also [0236] where the difference between measured and target speed depict a standard deviation of velocity)
wherein the at least one processor is configured to determine the PMWindividual based on the individual objectification index. ([0104] “Progressive calibration engine 222 is configured to execute progressive strength calibration. In some embodiments, this includes controlling the motor (e.g., using firmware to control MCB 210) to implement progressive strength calibration. The progressive strength calibration is performed using calibration parameters. Further details regarding progressive strength calibration are described below. As will be described in further detail below, the progressive strength calibration is performed in part by processing and analyzing sensor data (e.g., from accessories and the MCB), as well as user data stored in user data store 226 (e.g., user profile, measurements, goals, suggested weights, etc.), workout data (e.g., current move, load profile for the current move, etc.), camera and microphone information, etc… the user data store also includes data specific to individual users. As will be described in further detail below, the data in user data store 226 is used to determine personalized calibration parameters.” Where personalized profiles [comprising PMWindividual] for various strength calibration parameters [comprising individual objectification] in the workout equipment is determined based on the repetitions within the set)
Regarding claim 2, Belson (‘259) teaches all of the limitations of claim 1. Belson (‘259) also teaches:
the at least one processor configured to automatically set an initial target weight of the fitness equipment to be used by the user, based on the PMWestimation. ([0133] “As one example, the exercise machine determines, with 95% confidence that the user's strength is between two weights. Those two weights are set as the low and high weight parameters for the progressive strength calibration mode.” Where determining that the user’s strengths is between two weights comprise setting an initial target weight; see optionally [Table 1] “target weight” is automatically adjusted by the controller circuit)
Regarding claim 3, Belson (‘259) teaches all of the limitations of claim 1. Belson (‘259) also teaches
the at least one processor configured to automatically update a target weight of the fitness equipment to be used by the user, based on the PMWindividual. ([0011] “The progressive calibration mode described herein progressively increases or decreases the applied weight until settling on a weight that is appropriate and challenging for the user for a given move.” Where increasing or decreasing the target weight is automatically updating the weight of the fitness equipment)
Regarding claim 4, Belson (‘259) teaches all of the limitations of claim 1. Belson (‘259) also teaches:
wherein the at least one processor is further configured to update the PMWidividual to a value greater than the PMWestimation when the individual objectification index is equal to or greater than a first reference value, ([0013]” the progressive strength calibration continuously increases the weight until the user's speed reduces”) and update the PMWindividual to a value less than PMWestimation when the individual objectification index is equal to or less than a second reference value.([0139] “The exercise machine further determines, based on a record of when the user last used the exercise machine, that it has been several months since they used the machine. Based on the amount of time away from the machine, the exercise machine further adjusts the low/high weights (e.g., by reducing the low weight by a percentage that is determined based on the amount of time away).” Where reducing the low weight by a percentage based on the amount of time away is updating the individual’s PMW to a value less than the estimated PMW when the individual index is less than a second reference value)
Regarding claim 5, Belson (‘259) teaches all of the limitations of claim 4. Belson (‘259) also teaches:
wherein the at least one processor is further configured to newly update the updated PMWindividual based on the individual objectification index in units of the pre-set periods of time. ([0130] The various parameters used to determine the progressive strength calibration are dynamically adjustable” where a dynamic adjustability comprises updating the newly updated PMW based on the individual index; see also [0132] “In some embodiments, the parameters are determined based on whether there is historical information about the user (e.g., stored in user data store 226). For example, if there is historical information about the user (e.g., the user has performed the move for which progressive strength calibration is being performed), then that information is used to determine personalized low/high weights and personalized reference speed” where historical information about the user comprises pre-set periods of time)
Regarding claim 6, Belson (‘259) teaches all of the limitations of claim 1. Belson (‘259) also teaches:
wherein the at least one processor comprises a display configured to display a target weight of the fitness equipment, the target weight being automatically updated based on the PMWindividual. ([0199] “As another example, various measurements taken during the performance of the calibration set are stored. For example, the N-rep max weight (or final weight or resistance applied or assessed during the calibration set) is stored.” [0202] “The results of the calibration may also be displayed or otherwise presented to the user. For example, the one-rep max (e.g., converted from the N-rep max) may be displayed to the user.” Where continuous measurements comprise the displayed information for the user)
Regarding claim 8, Belson (‘259) teaches all of the limitations of claim 1. Belson (‘259) also teaches:
wherein the at least one processor is further configured to, when the reps are used as the individual objectification index, determine completion of the reps based on regularity between workout trajectories of all reps configuring one set and a performance time of performing the all reps configuring the one set, convert a degree of the completion of the reps into a numerical value, and use the numerical value as the individual objectification index. ([0195] “In some embodiments, the N-rep max is determined as the final weight applied to the last repetition during the calibration set. In some embodiments, the N-rep maximum estimated as a result of the calibration set is converted to a one-rep max, where the one-rep max is a fraction of the N-rep max estimate.”; see also[0196] “In some embodiments, the conversion is performed according to a mapping. One example of a mapping is one that maps a number of repetitions to a percentage of the one-rep maximum. The mapping may be a linear function, an exponential function, etc. Different mappings may be used for different types of moves and people.” Where correlating the repetition data to the progression of a user by the percentage of repetitions correlated to the overall strength comprises using a regularity between workout trajectories of all repetitions to convert a degree a completion of the reps into a numerical value for use in the objectification index)
Regarding claim 9, Belson (‘259) teaches:
An artificial intelligence (Al) workout guide method implemented by a workout guide apparatus including at least one processor and at least one memory storing instructions that, when executed by the at least one processor, cause the workout guide apparatus to perform the method comprising: [0009] The invention can be implemented in numerous ways, including … as a process” and [0009] The invention can be implemented in numerous ways, including as a process; an apparatus; a system; a composition of matter; a computer program product embodied on a computer readable storage medium; and/or a processor, such as a processor configured to execute instructions stored on and/or provided by a memory coupled to the processor.”)
Estimating PMWestimation of fitness equipment to be used by a user, based on an estimated muscular strength value calculated based on user data; and ([0114] “Progressive strength calibration engine 222 is configured to determine the right weight for a user over the course of a set of repetitions of a movement (e.g., a weight that is challenging for the user, but will not push the user to failure by the end of a set).” Where the calibration engine [comprising the PMW estimator] estimates the right weight for a user [comprising PMW estimation for a user] based on a set of repetitions of a user [i.e., an estimated muscular strength value calculated based on user data])
providing PMWindividual for the fitness equipment by complementing the PMWestimation with an individual objectification index of the user, ([0094] “In some embodiments, the exercise machine includes a media controller and/or processor, which monitors/measures user performance (for example, using the one or more sensors described above), and determines loads to be applied to the user's efforts in the resistance unit”)
wherein the individual objectification index comprises a regularity of repetitions (reps) in units of sets, ([0104] “the progressive strength calibration is performed in part by processing and analyzing sensor data (e.g., from accessories and the MCB), as well as user data stored in user data store” where the strength calibration [i.e., objectification index] comprises sensor and user data and [0193] “set includes a number of repetitions. For example, the set may include 10 repetitions. Other numbers of repetitions may be used in a calibration set. The calibration set ends after the predefined number of repetitions is completed.” Where different repetitions, chosen by the user, are the regulatorily of reps in units of sets pre-set by the user) and optionally comprises one or more of a weight of the fitness equipment, ([0041] “a user tension sensor; a torque/tension/strain sensor and/or gauge to measure how much tension/force is being applied to the actuator (1010) by the user.” Where tension being applied to an actuator comprises weight of fitness equipment) a number of repetitions (reps), a number of sets, a workout trajectory, and a moving velocity, ([0043] “In some embodiments, an IMU is placed on the cable (e.g., via a clip) to determine inertial measurements with respect to the cable” where the inertial measurements comprise a moving velocity of a hand) which are determined when the user uses the fitness equipment for a pre-set period of time. ([0193] “set includes a number of repetitions. For example, the set may include 10 repetitions. Other numbers of repetitions may be used in a calibration set. The calibration set ends after the predefined number of repetitions is completed.” Where different repetitions, chosen by the user, are the regulatorily of reps in units of sets pre-set by the user)
sensing, by a sensor, distance information of the fitness equipment while the user uses the fitness equipment, ([0039] “One example of an encoder is a position encoder; a sensor to measure position of the actuator (1010)”; see also [0187])
determining a workout trajectory based on the distance information sensed by the sensor, wherein the workout trajectory corresponds to movement displacement of the fitness equipment plotted against time, ([0042] “Another example of sensors includes inertial measurement units (IMUs) and [0187] “As described above, the progressive calibration is based on the measurement of the user's speed, which as one example is determined from sensor measurements on the change in cable position” where change in cable position by an inertial measurement units over time comprise determining a workout trajectory for a user based on acceleration of cables over time.
during execution of a set, determining regularity of repetitions in units of sets based on workout trajectories of a plurality of repetitions configuring the set, wherein the regularity of reps in units of sets is determined based on whether the workout trajectories match each other, based on a distance between the workout trajectories, or based on a length of a time series, ([0114] “Progressive strength calibration engine 222 is configured to determine the right weight for a user over the course of a set of repetitions of a movement” and [0104] “progressive strength calibration is performed in part by processing and analyzing sensor data (e.g., from accessories and the MCB), as well as user data stored in user data store 226 (e.g., user profile, measurements, goals, suggested weights, etc.), workout data (e.g., current move, load profile for the current move, etc.), camera and microphone information, etc.” and where determining the right weight for a user over a course of repetitions using the sensor measurement data from measurements comprises determining a workout trajectory based on the length of a time series.)
during execution of the set, determining whether all repetitions configuring the set have been completed, ([0193] “the set may include 10 repetitions. Other numbers of repetitions may be used in a calibration set. The calibration set ends after the predefined number of repetitions is completed.” Where completing calibration based on a number of repetitions completed comprises determining whether all repetitions have been completed)
during execution of the set, determining a degree of completion of the repetitions based on a division of the regularity into an early regularity, a middle regularity, and a latter regularity within the set, and converting the determined degree of completion into a numerical value which indicates the individual objectification index, ([0239] “As described above, the weight is increased during the concentric phase when the user moves quickly (e.g., above the reference speed), and the weight is decreased when the user moves slowly (e.g., below the reference speed). As the set goes on and the more reps are done (e.g., as the number of reps completed increases), the weight changes are more gradual as the user approaches the appropriate weight for them” where the completion of the repetitions at varying speeds comprises a degree of completion at varying regularity; see also [0194] “In this example, an estimate of the user's strength was determined by progressively increasing the weight over a number of repetitions, and observing the user's speed relative to the reference speed.” And [0133] As one example, the exercise machine determines, with 95% confidence that the user's strength is between two weights. Those two weights are set as the low and high weight parameters for the progressive strength calibration mode.” Where the strength of completing a set between the two weights [comprising a degree of completion] indicates the weight parameters [comprising individual objectification index]) where the speeds comprise a varying regularity)
wherein the individual objectification index further reflects at least one of a standard deviation of an ascent starting point, a standard deviation of a descent starting point, a standard deviation of a height, a standard deviation of an ascending section velocity, and a standard deviation of a descending section velocity, calculated from the workout trajectories of the repetitions, and ([0105] “User data store 226 includes information aggregated from multiple users of multiple exercise machines, and includes, for example, population statistics for all or subsets of users. The user data store also includes data specific to individual users. As will be described in further detail below, the data in user data store 226 is used to determine personalized calibration parameters.” and [0253] “5th percentile of sets' weight is selected as the default low weight, and the 90th percentile as the default high weight” and [0189-0190] “In some embodiments, the progressive strength calibration and motor control is performed in real time. For example, during the concentric phase, cable speed measurements are taken periodically (e.g., at 50 Hz, or every 20 milliseconds), and at every time step, the weight is progressively adjusted. If, during the concentric phase, the user is above the reference speed, then additional weight is added” where the percentile weight chosen as a statistical measurement for the concentric phase of cable speed repetitions comprises an objectification index of a standard deviation of an ascending section velocity calculated from the workout trajectories of the repetitions; see also [0236] where the difference between measured and target speed depict a standard deviation of velocity)
determining the PMWindividual based on the individual objectification index during execution of the set. ([0104] “Progressive calibration engine 222 is configured to execute progressive strength calibration. In some embodiments, this includes controlling the motor (e.g., using firmware to control MCB 210) to implement progressive strength calibration. The progressive strength calibration is performed using calibration parameters. Further details regarding progressive strength calibration are described below. As will be described in further detail below, the progressive strength calibration is performed in part by processing and analyzing sensor data (e.g., from accessories and the MCB), as well as user data stored in user data store 226 (e.g., user profile, measurements, goals, suggested weights, etc.), workout data (e.g., current move, load profile for the current move, etc.), camera and microphone information, etc… the user data store also includes data specific to individual users. As will be described in further detail below, the data in user data store 226 is used to determine personalized calibration parameters.” Where personalized profiles [comprising PMWindividual] for various strength calibration parameters [comprising individual objectification] in the workout equipment is determined based on the repetitions within the set)
Regarding claim 10, Belson (‘259) teaches all of the limitations of claim 9. Belson (‘259) also teaches:
further comprising automatically setting, by a workout target setter, an initial target weight of the fitness equipment, based on the PMWestimation. ([0133] “As one example, the exercise machine determines, with 95% confidence that the user's strength is between two weights. Those two weights are set as the low and high weight parameters for the progressive strength calibration mode.” Where determining that the user’s strengths is between two weights comprise setting an initial target weight; see optionally [Table 1] “target weight” is automatically adjusted by the controller circuit)
Regarding claim 11, Belson (‘259) teaches all of the limitations of claim 9. Belson (‘259) also teaches:
further comprising automatically updating, by an AI workout target setter, a target weight of the fitness equipment, based on the PMWindividual. ([0011] “The progressive calibration mode described herein progressively increases or decreases the applied weight until settling on a weight that is appropriate and challenging for the user for a given move.” Where increasing or decreasing the target weight is automatically updating the weight of the fitness equipment)
Regarding claim 12, Belson (‘259) teaches all of the limitations of claim 9. Belson (‘259) also teaches:
wherein the providing of the PMWindividual comprises updating the PMWindividual to a value greater than the PMWestimation when the individual objectification index is equal to or greater than a first reference value, ([0013]” the progressive strength calibration continuously increases the weight until the user's speed reduces”) and the PMWindividual to a value less than PMWestimation when the individual objectification index is equal to or less than a second reference value. ([0139] “The exercise machine further determines, based on a record of when the user last used the exercise machine, that it has been several months since they used the machine. Based on the amount of time away from the machine, the exercise machine further adjusts the low/high weights (e.g., by reducing the low weight by a percentage that is determined based on the amount of time away).” Where reducing the low weight by a percentage based on the amount of time away is updating the individual’s PMW to a value less than the estimated PMW when the individual index is less than a second reference value)
Regarding claim 13, Belson (‘259) teaches all of the limitations of claim 12. Belson (‘259) also teaches:
wherein the providing of the PMWindividual comprises newly updating the updated PMWindividual in units of the pre-set periods of time, based on the individual objectification index. ([0130] The various parameters used to determine the progressive strength calibration are dynamically adjustable” where a dynamic adjustability comprises updating the newly updated PMW based on the individual index; see also [0132] “In some embodiments, the parameters are determined based on whether there is historical information about the user (e.g., stored in user data store 226). For example, if there is historical information about the user (e.g., the user has performed the move for which progressive strength calibration is being performed), then that information is used to determine personalized low/high weights and personalized reference speed” where historical information about the user comprises pre-set periods of time)
Regarding claim 14, Belson (‘259) teaches all of the limitations of claim 9. Belson (‘259) also teaches:
wherein the providing of the PMWindividual comprises displaying, through a display, the PMWindividual or a change amount of maximum weight that is liftable when the fitness equipment is used. ([0199] “As another example, various measurements taken during the performance of the calibration set are stored. For example, the N-rep max weight (or final weight or resistance applied or assessed during the calibration set) is stored.” [0202] “The results of the calibration may also be displayed or otherwise presented to the user. For example, the one-rep max (e.g., converted from the N-rep max) may be displayed to the user.” Where continuous measurements comprise the displayed information for the user)
Regarding claim 17, Belson (‘259) teaches:
A non-transitory computer-readable recording medium storing commands for enabling a computing device to: [0009] The invention can be implemented in numerous ways, including … a computer program product embodied on a computer readable storage medium”)
estimate PMWestimation of fitness equipment to be used by a user, based on an estimated muscular strength value calculated based on user data; and ([0114] “Progressive strength calibration engine 222 is configured to determine the right weight for a user over the course of a set of repetitions of a movement (e.g., a weight that is challenging for the user, but will not push the user to failure by the end of a set).” Where the calibration engine [comprising the PMW estimator] estimates the right weight for a user [comprising PMW estimation for a user] based on a set of repetitions of a user [i.e., an estimated muscular strength value calculated based on user data])
provide PMWindividual for the fitness equipment by complementing the PMWestimation with an individual objectification index of the user, ([0094] “In some embodiments, the exercise machine includes a media controller and/or processor, which monitors/measures user performance (for example, using the one or more sensors described above), and determines loads to be applied to the user's efforts in the resistance unit”)
wherein the individual objectification index regularity of repetitions (reps) in units of sets, and optionally comprises one or more of ([0104] “the progressive strength calibration is performed in part by processing and analyzing sensor data (e.g., from accessories and the MCB), as well as user data stored in user data store” where the strength calibration [i.e., objectification index] comprises sensor and user data) and [0193] “set includes a number of repetitions. For example, the set may include 10 repetitions. Other numbers of repetitions may be used in a calibration set. The calibration set ends after the predefined number of repetitions is completed.” Where different repetitions, chosen by the user, are the regulatorily of reps in units of sets pre-set by the user)
at least some of a weight of the fitness equipment, ([0041] “a user tension sensor; a torque/tension/strain sensor and/or gauge to measure how much tension/force is being applied to the actuator (1010) by the user.” Where tension being applied to an actuator comprises weight of fitness equipment) a number of repetitions (reps), a number of sets, a workout trajectory, a moving velocity, ([0043] “In some embodiments, an IMU is placed on the cable (e.g., via a clip) to determine inertial measurements with respect to the cable” where the inertial measurements comprise a moving velocity of a hand) and regularity of reps in units of sets, which are determined when the user uses the fitness equipment for a pre-set period of time. ([0193] “set includes a number of repetitions. For example, the set may include 10 repetitions. Other numbers of repetitions may be used in a calibration set. The calibration set ends after the predefined number of repetitions is completed.” Where different repetitions, chosen by the user, are the regulatorily of reps in units of sets pre-set by the user)
sense, by a sensor, distance information of the fitness equipment while the user uses the fitness equipment; ([0039] “One example of an encoder is a position encoder; a sensor to measure position of the actuator (1010)”)
determine a workout trajectory based on the distance information sensed by the sensor, wherein the workout trajectory corresponds to movement displacement of the fitness equipment plotted against time; ([0042] “Another example of sensors includes inertial measurement units (IMUs) and [0187] “As described above, the progressive calibration is based on the measurement of the user's speed, which as one example is determined from sensor measurements on the change in cable position” where change in cable position by an inertial measurement units over time comprise determining a workout trajectory for a user based on acceleration of cables over time.)
during execution of a set, determine regularity of repetitions in units of sets based on workout trajectories of a plurality of repetitions configuring the set, wherein the regularity of reps in units of sets is determined based on whether the workout trajectories match each other, based on a distance between the workout trajectories, or based on a length of a time series; ([0114] “Progressive strength calibration engine 222 is configured to determine the right weight for a user over the course of a set of repetitions of a movement” and [0104] “progressive strength calibration is performed in part by processing and analyzing sensor data (e.g., from accessories and the MCB), as well as user data stored in user data store 226 (e.g., user profile, measurements, goals, suggested weights, etc.), workout data (e.g., current move, load profile for the current move, etc.), camera and microphone information, etc.” and where determining the right weight for a user over a course of repetitions using the sensor measurement data from measurements comprises determining a workout trajectory based on the length of a time series.)
during execution of the set, determine whether all repetitions configuring the set have been completed; ([0193] “the set may include 10 repetitions. Other numbers of repetitions may be used in a calibration set. The calibration set ends after the predefined number of repetitions is completed.” Where completing calibration based on a number of repetitions completed comprises determining whether all repetitions have been completed)
during execution of the set, determine a degree of completion of the repetitions based on a division of the regularity into an early regularity, a middle regularity, and a latter regularity within the set, and convert the determined degree of completion into a numerical value which indicates the individual objectification index; ([0239] “As described above, the weight is increased during the concentric phase when the user moves quickly (e.g., above the reference speed), and the weight is decreased when the user moves slowly (e.g., below the reference speed). As the set goes on and the more reps are done (e.g., as the number of reps completed increases), the weight changes are more gradual as the user approaches the appropriate weight for them” where the completion of the repetitions at varying speeds comprises a degree of completion at varying regularity; see also [0194] “In this example, an estimate of the user's strength was determined by progressively increasing the weight over a number of repetitions, and observing the user's speed relative to the reference speed.” And [0133] As one example, the exercise machine determines, with 95% confidence that the user's strength is between two weights. Those two weights are set as the low and high weight parameters for the progressive strength calibration mode.” Where the strength of completing a set between the two weights [comprising a degree of completion] indicates the weight parameters [comprising individual objectification index]) where the speeds comprise a varying regularity)
wherein the individual objectification index further reflects at least one of: a standard deviation of an ascent starting point, a standard deviation of a descent starting point, a standard deviation of a height, a standard deviation of an ascending section velocity, and a standard deviation of a descending section velocity, calculated from the workout trajectories of the repetitions; and ([0105] “User data store 226 includes information aggregated from multiple users of multiple exercise machines, and includes, for example, population statistics for all or subsets of users. The user data store also includes data specific to individual users. As will be described in further detail below, the data in user data store 226 is used to determine personalized calibration parameters.” and [0253] “5th percentile of sets' weight is selected as the default low weight, and the 90th percentile as the default high weight” and [0189-0190] “In some embodiments, the progressive strength calibration and motor control is performed in real time. For example, during the concentric phase, cable speed measurements are taken periodically (e.g., at 50 Hz, or every 20 milliseconds), and at every time step, the weight is progressively adjusted. If, during the concentric phase, the user is above the reference speed, then additional weight is added” where the percentile weight chosen as a statistical measurement for the concentric phase of cable speed repetitions comprises an objectification index of a standard deviation of an ascending section velocity calculated from the workout trajectories of the repetitions; see also [0236] where the difference between measured and target speed depict a standard deviation of velocity)
determine the PMWindividual based on the individual objectification index during execution of the set. ([0104] “Progressive calibration engine 222 is configured to execute progressive strength calibration. In some embodiments, this includes controlling the motor (e.g., using firmware to control MCB 210) to implement progressive strength calibration. The progressive strength calibration is performed using calibration parameters. Further details regarding progressive strength calibration are described below. As will be described in further detail below, the progressive strength calibration is performed in part by processing and analyzing sensor data (e.g., from accessories and the MCB), as well as user data stored in user data store 226 (e.g., user profile, measurements, goals, suggested weights, etc.), workout data (e.g., current move, load profile for the current move, etc.), camera and microphone information, etc… the user data store also includes data specific to individual users. As will be described in further detail below, the data in user data store 226 is used to determine personalized calibration parameters.” Where personalized profiles [comprising PMWindividual] for various strength calibration parameters [comprising individual objectification] in the workout equipment is determined based on the repetitions within the set)
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 7 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Belson et al. (US20210402259) in view of Belson et al. (US20220296963).
Regarding claim 7, Belson (‘259) teaches all of the limitations of claim 1. Belson’s first reference does not explicitly teach, as taught by Belson (‘963):
wherein the at least one processor is further configured to, ([0038] “encoders: In various embodiments, encoders are used to measure cable lengths (e.g., left and right cable lengths in this example), cable speeds, weight (tension), etc.” where the encoders comprise sensors which collect user information for determining the workout trajectory) when the workout trajectory is used as the individual objectification index, determine completion of the workout trajectory by using an ascent starting point, a descent starting point, ([0137] “In some embodiments, sensors are used to determine a zero position for the cables. In some embodiments, re-zeroing is performed. For example, when the cart height changes (e.g., vertical translation of the arm along sliders), sensors that are at the locked positions are used to determine whether there is a new locked position, and if there is a new locked position, then re-zeroing (i.e., recalculating of zero point) is performed. This is because as the cart height runs along a column, the amount of cable that is pulled out changes when the cart height is adjusted up or down” where the zero position of the cables [i.e., an ascending starting point, a descending starting point] helps determine the completion of a rep [comprising determine completion of a workout trajectory) an ascending section average velocity, a descending section average velocity, ([0210] “As shown in the example above, speed (e.g., based on cable measurements) is determined. The first derivative of motion, velocity, may be considered. Other derivatives of position, such as the second derivative motion, acceleration, may be considered. For example, the third derivative (jerk) and the fourth derivative (snap) may also be considered.” Where acceleration is a numerical vector depicting an average velocity using a magnitude and a direction [i.e., ascending section average velocity, a descending section average velocity]) and a height, which are determined from the workout trajectory, ([0143] “the rules for the deadlift include a set of rules for monitoring, during the eccentric phase of a repetition, the cable position relative to a threshold. If the cable position is determined to be above the threshold at the end of the eccentric phase, then it is determined that the user has not gone low enough for this portion of the exercise,” where the rules engine uses various sensor information to determine the completion of a repetition [i.e., the workout trajectory] by using the cable position [comprising the height]) convert a degree of the completion of the workout trajectory into a numerical value, and use the numerical value as the individual objectification index. (“[0134] In some embodiments, angle of the cable is determined. As one example, the length of the cable, in conjunction with the position of an arm, may be used to determine that the cable is within a range of angles. The estimate of the angle of the cable may also be used as an input to a rule when determining whether incorrect form has been detected.” Where determining whether a user is within a range of angles [i.e., convert a degree of the completion of a workout into a numerical form] comprises data that quantifies strength performance of an individual [i.e., individual index])
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Belson (‘259) with the teachings of Belson (‘963), with a reasonable expectation of success, by explicitly incorporating various sensor feedbacks to model the user’s physical performance trajectory over a period of time. This would have improved the safety of the workout apparatus by preventing the system from creating unsafe levels of resistance to the user, therefore reducing a user’s risk for injury. Belson (‘963) is adaptable to Belson (‘259) as both inventions are intended to be used in the same workout apparatus created by the same company. Belson (‘259) would have recalled the inventor’s own teaching in (‘963) that occurred a few months prior while working for the same company on the same technology.
Regarding claim 15, Belson (‘259) teaches all of the limitations of claim 9. Belson’s first reference does not explicitly teach, as taught by Belson (‘963):
wherein, when the workout trajectory is used as the individual objectification index, completion of the workout trajectory is determined by using an ascent starting point, a descent starting point, ([0137] “In some embodiments, sensors are used to determine a zero position for the cables. In some embodiments, re-zeroing is performed. For example, when the cart height changes (e.g., vertical translation of the arm along sliders), sensors that are at the locked positions are used to determine whether there is a new locked position, and if there is a new locked position, then re-zeroing (i.e., recalculating of zero point) is performed. This is because as the cart height runs along a column, the amount of cable that is pulled out changes when the cart height is adjusted up or down” where the zero position of the cables [i.e., an ascending starting point, a descending starting point] helps determine the completion of a rep [comprising determine completion of a workout trajectory) an ascending section average velocity, a descending section average velocity, ([0210] “As shown in the example above, speed (e.g., based on cable measurements) is determined. The first derivative of motion, velocity, may be considered. Other derivatives of position, such as the second derivative motion, acceleration, may be considered. For example, the third derivative (jerk) and the fourth derivative (snap) may also be considered.” Where acceleration is a numerical vector depicting an average velocity using a magnitude and a direction [i.e., ascending section average velocity, a descending section average velocity] ) and a height, which are determined from the workout trajectory, ([0143] “the rules for the deadlift include a set of rules for monitoring, during the eccentric phase of a repetition, the cable position relative to a threshold. If the cable position is determined to be above the threshold at the end of the eccentric phase, then it is determined that the user has not gone low enough for this portion of the exercise,” where the rules engine uses various sensor information to determine the completion of a repetition [i.e., the workout trajectory]) a degree of the completion of the workout trajectory is converted into a numerical value, and the numerical value is used as the individual objectification index. ([0134] “In some embodiments, angle of the cable is determined. As one example, the length of the cable, in conjunction with the position of an arm, may be used to determine that the cable is within a range of angles. The estimate of the angle of the cable may also be used as an input to a rule when determining whether incorrect form has been detected.” Where determining whether a user is within a range of angles [i.e., convert a degree of the completion of a workout into a numerical form] comprises data that quantifies strength performance of an individual [i.e., individual index])
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Belson (‘259) with the teachings of Belson (‘963), with a reasonable expectation of success, by explicitly incorporating various sensor feedbacks to model the user’s physical performance trajectory over a period of time. This would have improved the safety of the workout apparatus by preventing the system from creating unsafe levels of resistance to the user, therefore reducing a user’s risk for injury. Belson (‘963) is adaptable to Belson (‘259) as both inventions are intended to be used in the same workout apparatus created by the same company. Belson (‘259) would have recalled the inventor’s own teaching in (‘963) that occurred a few months prior while working for the same company on the same technology.
Response to Arguments
Examiner acknowledges Applicant’s amendments and will address them in the order they were presented.
Regarding page 12, Applicant’s arguments regarding 112(f) interpretation have been fully considered but are moot in view of the amended claim language.
Regarding pages 13-14, Applicant’s arguments regarding 112 rejection have been fully considered but are moot in view of the amended claim language.
Regarding pages 14-17, Applicant’s arguments regarding Subject Matter Eligibility have been fully considered but are moot in view of the amended claim language. Examiner’s SME analysis regarding he amended claim language may be found above
Regarding pages 18-23, Applicant’s arguments regarding 102 and 103 rejections have been fully considered but are moot in view of the amended claim language.
Regarding page 19], Applicant’s arguments have been fully considered but are not persuasive. Applicant discloses that Belton does not teach comparing repetitions within a set or time series length. Examiner maintains that Belton does teach this, as seen in the prior art rejection above and paragraphs [0029 and 0190] of Belton which describe the continuous adjustment of weight parameters within every single repetition.
Regarding page 20, Applicant’s arguments have been fully considered but are not persuasive. Applicant discloses that Belton does not teach dividing repetition performance into temporal phases. Examiner maintains that Belton teaches the evolution of repetition regularity within the set, as seen in the prior art rejection above and paragraphs [0117-0119] of Belton which discuss how the user’s reference speed alters the progressive strength feedback system.
Regarding page 21, Applicant’s arguments have been fully considered but are not persuasive. Applicant argues that the prior art does not teach the newly amended claim language of standard deviation. Examiner turned to paragraph [0099] to determine the interpretation of standard deviation for each parameter. Examiner interpreted this deviation to be any velocity deviation which is not expected. While the prior art references the use of historical statistics for workout users, the apparatus also comprises determining any deviation from a target speed. Examiner maintains that the prior art’s disclosure of the difference between measured and target speed depicts a standard deviation of velocity.
Regarding page 22, Applicant’s arguments have been fully considered but are not persuasive. Applicant argues that the prior art does not teach the sensor’s level of detail as described in the amended claim language. Examiner maintains that the analysis of the amended claim language, above, reflects the sensor’s structure and function.
Additional Considerations
The prior art made of record and not relied upon that is considered pertinent to applicant’s disclosure can be found on PTO-892 of the prior office action dated September 25th, 2025.
Von Prellwitz et al. (US20180001181) discloses a method for automating, personalizing and optimizing a resistance force in an exercise. Prellwitz discloses a system for setting program exercise weights, repetitions, and more, processing sensor information such as accelerometer data within a neural network to display results in a computing system.
Smith et al. (pat. 11246221) discloses a user-agnostic workout training profile that integrates alongside network devices to track the performance of a user.Smith displays various physiological parameters in a computer.
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.
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/R.A.S/Examiner, Art Unit 3792
/KAMBIZ ABDI/Supervisory Patent Examiner, Art Unit 3685