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 .
Response to Arguments
Applicant’s arguments, filed on 11/22/2025, have been fully considered by the examiner.
In response to “claims 13-16 are objected to as being dependent up on a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims and furthermore overcoming the 101 abstract idea rejection above. Initially, Applicant thanks the Examiner for the finding of allowability of claim 13. In this Amendment, Applicant has re-written this claim in independent form. In re-writing this claim, Applicant has removed some limitations and added other limitations that are more germane to the subject matter recited in claim 13.”
Examiner clarifies that the statement states “would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims and furthermore overcoming the 101 abstract idea”, which meant to incorporate claims 13 and 12 into 11, because claim 13 depended on claim 12 and claim 12 depended on claim 11. However, the applicant has amended all the claims from 1-19 in different ways that necessitude a new rejection. Therefore, applicant's arguments filed with respect to the prior art rejections have been fully considered but they are moot. Applicant has amended the claims to recite new combinations of limitations. Applicant' s arguments are directed at the amendment. Please see below for new grounds of rejection, necessitated by Amendment.
In response to applicant’s arguments and amendments, with respect to claim rejection under 35 U.S.C. §101 of claims, applicant’s arguments have been fully considered and are not persuasive. Examiner notes the rejection under 35 USC § 101 has been updated to address amended claim elements as necessitated by the amendments to the claims under the 2019 Revised Patent Subject Matter Eligibility Guidance. MPEP 2106 provides the rules for determining eligibility of claims in accordance with the 2019 Revised Patent Subject Matter Eligibility Guidance.
Applicant argues: “Claims 1-19 were rejected under 35 U.S.C. 101. Applicant respectfully submits that these claims recite statutory subject matter as they do not recite abstract but rather recite a practical application, which in this case involves providing feedback to a golfer. Furthermore, as recited, the claims now positively recite operations performed by one or more mobile devices of the golfer, in order to produce feedback that is provided to the golfer. As such, Applicant respectfully submits pending claims 1-19 recite statutory subject matter, and request reconsideration and withdrawal of the rejection under 35 U.S.C. 101.”
In response, the examiner respectfully disagrees. The claim is still an abstract idea Wherein a person skilled in the art would be able to analyze or calculate metrics sound impact and give feedback. The use of a smart phone or a smart watch are generic computer components in these steps are recited at a high-level of generality (i.e., as a generic computer component performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. See full rejection below.
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 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The analysis of the claims will follow the 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50-57 (January 7, 2019) (“2019 PEG”).
Claim 1
Step 1: The claim recites a “method”.
Step 2A Prong 1: The claim recites, inter alia:
identifying a plurality of impact sound parameters associated with the impact between the clubhead and the target ball object, the plurality of impact sound parameters representing one or more time durations of sounds associated with the impact, one or more amplitudes of sounds associated with the impact and one or more frequencies of sounds associated with the impact; analyzing the plurality of impact sound parameters, including one or more durations of sounds, one or more amplitudes of sounds, and one or more frequencies of sounds, to produce feedback to provide to the golfer: this limitation could be construed to be directed either to the abstract idea of mental processes or to the abstract idea of mathematical operations. Wherein a person skilled in the art would be able to analyze or calculate metrics sound impact and give feedback.
Step 2A, prong two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No—the judicial exception is not integrated into a practical application.
a mobile device of the golfer: Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
providing the produced feedback to the particular golfer through an interface of the mobile device: Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g).
The generic computer components in these steps are recited at a high-level of generality (i.e., as a generic computer component performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No—there are no additional limitations beyond the mental processes identified above. The limitation treated above, are directed to the well-understood, routine, and conventional activity of storing and retrieving information in memory. See MPEP § 2106.05(d)(II); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015). It also includes limitations that Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). The additional element is insignificant application, which is similar to examples of activities that the courts have found to be insignificant extra-solution activity, in accordance with MPEP 2106.05(g), Insignificant Extra-Solution Activity. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Thus, considering the additional elements individually and in combination and the claims as a whole, the additional elements do not provide significantly more than the abstract idea. This claim is not patent eligible.
Regarding Claim 2,
Claim 2 is dependent on claim 1, “wherein analyzing the plurality of impact sound parameters comprises providing the plurality of impact sound parameters to a trained neural network to produce at least a subset of feedback”.
Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
Regarding Claim 3,
Claim 3 is dependent on claim 1, “wherein the feedback comprises a set of metrics including (i) swing speed, (ii) swing path, (iii) ball speed, (iv) launch angle, (v) ball spin direction, (vi) ball spin rate, and (vii) virtual impact tape that provides a representation of a location on the clubhead that made contact with the target ball object”. this limitation could be construed to be directed either to the abstract idea of mental processes or to the abstract idea of mathematical operations. Wherein a person skilled in the art would be able to analyze or calculate metrics such as (i) swing speed, (ii) swing path, (iii) ball speed, (iv) launch angle, (v) ball spin direction, and (vi) ball spin rate.
Regarding Claim 4,
Claim 4 is dependent on claim 1, “wherein providing the produced feedback comprises providing a set of one or more corrective action for the golfer to take to improve the golf swing”. this limitation could be construed to be directed either to the abstract idea of mental processes or to the abstract idea of mathematical operations.
Regarding Claim 5,
Claim 5 is dependent on claim 1, “prior to identifying the plurality of impact sound parameters, capturing through a microphone of the mobile device, audio data regarding the golf swing”.
the mere gathering of data or transmitting data, which is insignificant extra-solution activity. See MPEP § 2106.05(g) and involves the mere gathering of data, which is well-understood, routine, and conventional activity of storing and retrieving information in memory. See MPEP § 2106.05(d)(II).
Regarding Claim 6,
Claim 6 is dependent on claim 2, “wherein the neural network is trained through a training process that uses sounds associated with other golf swings and feedback data associated with the other golf swings as known inputs and known outputs of the training process.”: Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
Regarding Claim 7,
Claim 7 is dependent on claim 6, “wherein: the neural network comprises a plurality of processing nodes each having adjustable parameters; and each adjustable parameter comprises a weight associated with a connection between a pair of inputs.”: Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
Regarding Claim 8,
Claim 8 is dependent on claim 1, “wherein the mobile device is a mobile phone or a smart watch”: Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
Regarding Claim 9,
Claim 9 is dependent on claim 1, “identifying at least one non-impact sound parameter associated with the golf swing and using the non-impact sound parameter in the analysis that produces the feedback”: this limitation could be construed to be directed either to the abstract idea of mental processes or to the abstract idea of mathematical operations.
Regarding Claim 10,
Claim 10 is dependent on claim 1, “wherein the mobile device is a mobile phone and analyzing the plurality of impact sound parameters comprises analyzing the impact sound parameters with a set of sensor data captured by a smart watch of the golfer in order to produce the feedback.”: this limitation could be construed to be directed either to the abstract idea of mental processes or to the abstract idea of mathematical operations.
Claim 11
Step 1: The claim recites a “method”.
Step 2A Prong 1: The claim recites, inter alia:
processing the set of sound data to generate a feedback data that identifies at least one corrective action for improving subsequent golf swings, the feedback data comprising a visual presentation of a virtual impact tape showing a location of impact on the clubhead; and providing the feedback data, including the virtual impact tape, to the golfer; this limitation could be construed to be directed either to the abstract idea of mental processes or to the abstract idea of mathematical operations.
Step 2A, Prong Two: the claim includes additional elements that do not integrate the judicial exception into a practical application because:
at a mobile device of the golfer: Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
capturing a set of sound data associated with a set of golf swings of the golfer, the sound data comprising (i) a set of impact sounds corresponding to impacts between a target ball object and a clubhead of a golf club used by the golfer for the set of golf swings, and (ii) a set of non-impact sounds associated with movement of the club during the set of golf swings: Adding insignificant extra-solution activity to the judicial exception, data gathering, as discussed in MPEP § 2106.05(g).
The generic computer components in these steps are recited at a high-level of generality (i.e., as a generic computer component performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No—there are no additional limitations beyond the mental processes identified above. The limitation treated above, are directed to the well-understood, routine, and conventional activity of storing and retrieving information in memory. See MPEP § 2106.05(d)(II); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015). It also includes limitations that Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). The additional element is insignificant application, which is similar to examples of activities that the courts have found to be insignificant extra-solution activity, in accordance with MPEP 2106.05(g), Insignificant Extra-Solution Activity. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Thus, considering the additional elements individually and in combination and the claims as a whole, the additional elements do not provide significantly more than the abstract idea. This claim is not patent eligible.
Regarding Claim 12,
Claim 12 is dependent on claim 11, “wherein processing the set of input data to generate the first set of output data comprises processing the set of input data by a trained neural network to generate the first set of output data”.
Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
Claim 13
Step 1: The claim recites a “method”.
Step 2A Prong 1: The claim recites, inter alia:
based on the identified range of statistical variance, assigning the golfer to one category from a plurality of categories; based on the golfer's assigned category, generating feedback that identifies at least one corrective action for improving subsequent golf swings; and providing the feedback to the golfer.: this limitation could be construed to be directed either to the abstract idea of mental processes or to the abstract idea of mathematical operations. Wherein a person skilled in the art would be able to analyze or calculate metrics sound impact and give feedback.
Step 2A, prong two: Does the claim recite additional elements that integrate the judicial exception into a practical application? No—the judicial exception is not integrated into a practical application.
a mobile device of the golfer: Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
capturing a set of sound data associated with a set of golf swings of the golfer; processing the set of sound data to identify a range of statistical variance between the golf swings in the set of golf swings: Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g).
The generic computer components in these steps are recited at a high-level of generality (i.e., as a generic computer component performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No—there are no additional limitations beyond the mental processes identified above. The limitation treated above, are directed to the well-understood, routine, and conventional activity of storing and retrieving information in memory. See MPEP § 2106.05(d)(II); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015). It also includes limitations that Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). The additional element is insignificant application, which is similar to examples of activities that the courts have found to be insignificant extra-solution activity, in accordance with MPEP 2106.05(g), Insignificant Extra-Solution Activity. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Thus, considering the additional elements individually and in combination and the claims as a whole, the additional elements do not provide significantly more than the abstract idea. This claim is not patent eligible.
Regarding Claim 14,
Claim 14 is dependent on claim 13, “wherein the first mobile device is a smart watch, and processing the set of sound data comprises processing the set of sound data with sensor data captured about the set of golf swings by the smart watch”.
Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
Regarding Claim 15,
Claim 15 is dependent on claim 13, “wherein a higher statistical variance between each golf swing in the set of golf swings is associated with a lower skill level than a lower statistical variance between each golf swing in the set of golf swings.”.
Further limiting the mathematical/mental process of claim 14.
Regarding Claim 16,
Claim 16 is dependent on claim 13, “wherein the first mobile device is a mobile phone, and processing the set of sound data comprises processing the set of sound data with sensor data captured about the set of golf swings by the smart watch.”: Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
Regarding Claim 17,
Claim 17 is dependent on claim 11, “wherein the mobile device is a mobile phone and processing the set of sound data comprises processing the set of sound data with sensor data captured about the set of golf swings by a smart watch of the golfer.”: Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
Regarding Claim 18,
Claim 18 is dependent on claim 13, “wherein the assigned category comprises an indication of a skill level of the golfer and the skill level is used to determine a lexicon to use for the feedback.”: this limitation could be construed to be directed either to the abstract idea of mental processes.
Regarding Claim 19,
Claim 19 is dependent on claim 11, “wherein the mobile device is a smart watch and processing the set of sound data comprises processing the set of sound data with sensor data captured about the set of golf swings by the smart watch”: Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
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, 4-5, 8-11, 13-17 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Leech et al. (US 20180345110 A1) in view of Hadden et al. (US 20140278207 A1).
Regarding claim 1.
Leech discloses a method of analyzing a golf swing of a particular golfer that results in an impact between a clubhead of a golf club used for the golf swing and a target ball object, (see ¶ 19, “FIG. 1 is a diagram of a system 100 configured to determine a characteristic of a golf swing based on a sound signal before an impact of golf club 102 with a golf ball 104”, also see ¶ 22), the method comprising: at a mobile device of the golfer (see ¶ 28, “FIG. 3 is a diagram of a positional relationship between the system 100, implemented as a mobile device 300, and the golf ball 104, in an example embodiment. As illustrated, the mobile device 300 is positioned in a predetermined orientation at a predetermined distance D from the golf ball 104 relative to a swing path 302 generally followed by the head 116 during a swinging motion of the club 102.”):
identifying a plurality of impact sound parameters associated with the impact between the clubhead and the target ball object (see ¶ 22, “When a head 116 of the golf club 102 impacts the golf ball 104, a sound 118 is generated. The sound 118 propagates from the head 116 and may ultimately be sensed by the microphone 106. Upon the microphone 106 sensing the sound 118, the microphone outputs a sound signal 120 to the processor 110 via the connection 108.”, also see ¶ 23, “FIG. 2A illustrates a waveform 200 of the sound signal 120 as generated by the microphone 106 and transmitted to the processor 110, in an example embodiment, and FIGS. 2B and 2C are illustrations of the head 116 in relation to the ball 104 at various associated times covered in the waveform 200.”, also see ¶ 26),
the plurality of impact sound parameters representing one or more time durations of sounds associated with the impact, one or more amplitudes of sounds associated with the impact and one or more frequencies of sounds associated with the impact (see ¶¶ 24-25 and 37, the waveform 200 comprises a pre-impact window 202, exemplary Identified parameters being sound pressure level and peak frequency amplitude, also see ¶ 87, “optionally further includes that the sound signal includes an intensity of the sound over time and wherein the processor is further configured to identify a time of impact based on a local minimum of the intensity that corresponds to a rate of change of the intensity transcending a threshold and determine the characteristic of the swing from the portion of the sound signal corresponding to a predetermined time period ending at the time of impact (i.e. duration of sounds associated with the impact).”, ¶ 60, “the processor 110 calculates the peak frequency amplitude of the waveform 200, as filtered at 716, during the pre-impact window 202. The processor 110 may utilize any methodology for calculating the peak frequency amplitude known in the art. In an example, the processor 110 performs a Fourier transform of the waveform 200, as filtered at 716, during the pre-impact window 202 and identifies a peak frequency of the resultant transform. The processor 110 then ends the flowchart 700.”);
analyzing the plurality of impact sound parameters, including one or more durations of sounds, one or more amplitudes of sounds, and one or more frequencies of sounds, to produce feedback to provide to the golfer (see ¶ 34 and 43, analyzing the pre-impact window 202, and the impact window 203, determining a time of impact from the impact window, and determining a characteristic of the golf swing from the pre-impact window 202, also see ¶ 43, a characteristic, such as speed, of the golf swing; paragraph, also see ¶ 18, equipment recommendations or personal training suggestions based on a change in the characteristic over time, also see ¶¶ 24-25 and 37, the waveform 200 comprises a pre-impact window 202, exemplary Identified parameters being sound pressure level and peak frequency amplitude, also see ¶ 87, “optionally further includes that the sound signal includes an intensity of the sound over time and wherein the processor is further configured to identify a time of impact based on a local minimum of the intensity that corresponds to a rate of change of the intensity transcending a threshold and determine the characteristic of the swing from the portion of the sound signal corresponding to a predetermined time period ending at the time of impact (i.e. duration of sounds associated with the impact).”, ¶ 60, “the processor 110 calculates the peak frequency amplitude of the waveform 200, as filtered at 716, during the pre-impact window 202. The processor 110 may utilize any methodology for calculating the peak frequency amplitude known in the art. In an example, the processor 110 performs a Fourier transform of the waveform 200, as filtered at 716, during the pre-impact window 202 and identifies a peak frequency of the resultant transform. The processor 110 then ends the flowchart 700.”);
and providing the produced feedback to the particular golfer through an interface of the mobile device (see ¶ 43, output of the characteristic and suggestions to a user interface 114, also see ¶ 18, “by identifying a particular time of the impact based on an analysis of the sound signal and then assessing the sound signal including at least a portion of the sound signal before the time of impact, a characteristic, such as a speed of the golf club, may be determined with suitable accuracy and reliability in many conditions to obtain useful information. Information related to the characteristic may then be presented to a user, such as by displaying the information on a user interface. Such information may further or alternatively include equipment recommendations and personal training based on changes in the characteristic over time.”, also see ¶ 28, “FIG. 3 is a diagram of a positional relationship between the system 100, implemented as a mobile device 300, and the golf ball 104, in an example embodiment. As illustrated, the mobile device 300 is positioned in a predetermined orientation at a predetermined distance D from the golf ball 104 relative to a swing path 302 generally followed by the head 116 during a swinging motion of the club 102.”).
Leech teaches characteristics of the swing, but do not specifically teach providing the produced feedback to the particular golfer.
Hadden teaches providing the produced feedback to the particular golfer (see ¶ 45, “the user may be prompted to create the golf ball impact by an instruction from the computing device. As such, a user might only begin swinging at the golf ball upon receiving a corresponding instruction from the computing device.”, also see ¶ 47, “In step 310, the computing device may generate an output based on the analysis of the impact data. The output may include visuals, audio data, textual information and/or haptic feedback.”, also see ¶ 56, “upon determining the user's club head speed, the computing system may recommend a corresponding type of golf ball. Other factors beyond club head speed may also be taken into account in generating the recommendation including club type, lie angle, gender of the player and the like.”).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have included based on the golfer's assigned category, generating feedback that identifies at least one corrective action for improving subsequent golf swings as in Hadden. The motivation would have been to “The impact between the golf ball and the surface may be measured based on sound and/or motion sensors (e.g., gyroscopes, accelerometers, etc.). Based on motion and/or sound data, various equipment-related information including golf ball compression, club head speed and impact location may be derived. Such information and/or other types of data may be conveyed to a user to help improve performance, aid in selecting golf equipment and/or to insure quality of golfing products.” (see Hadden abstract ).
Regarding claim 4.
Leech and Hadden teach the method of claim 1,
Leech further teaches wherein providing the produced feedback comprises providing a set of one or more corrective action for the golfer to take to improve the golf swing (see ¶ 18, 73-74, providing the characteristic and suggestions to a user interface 114 on a display 900 of a user's mobile device 300).
Regarding claim 5.
Leech and Hadden teach the method of claim 1,
Leech further teaches further comprising prior to identifying the plurality of impact sound parameters, capturing through a microphone of the mobile device, audio data regarding the golf swing (see ¶ 20 and 32, receiving the sound signal 120 of the golf swing on a processor 110 of a mobile device 300 running the interface 114).
Regarding claim 8.
Leech and Hadden teach the method of claim 1,
Leech further teaches wherein the mobile device is a mobile phone or a smart watch (see ¶ 29, the mobile device 300 may be a smartphone such as an iPhone).
Regarding claim 9.
Leech and Hadden teach the method of claim 1,
Leech further teaches identifying at least one non-impact sound parameter associated with the golf swing and using the non-impact sound parameter in the analysis that produces the feedback (see ¶ 18, 40-43, the equipment recommendations are determined from the change in the characteristic over time, which is based on the pre-impact window 202 sound parameters).
Regarding claim 11.
Leech teaches a method of analyzing golf swings of a golfer, the method comprising:
at a mobile device of the golfer: (see ¶ 22-23 and 71-72, receiving through a microphone 106 of a mobile device 300, such as a smartphone, sound signals 120 associated with the swing or set of swings and impacts with the ball 104, see ¶ 19 and 22, determining a characteristic of a golf swing before and after an impact of a golf club 102 with a golf ball 104 based on sound signals, the golf swing performed by a user),
capturing a set of sound data associated with a set of golf swings of the golfer, the sound data comprising (i) a set of impact sounds corresponding to impacts between a target ball object and a clubhead of a golf club used by the golfer for the set of golf swings, and (ii) a set of non-impact sounds associated with movement of the club during the set of golf swings; (see ¶¶ 24-25 and 37, the waveform 200 comprises a pre-impact window 202, exemplary Identified parameters being sound pressure level and peak frequency amplitude, also see ¶ 87, “optionally further includes that the sound signal includes an intensity of the sound over time and wherein the processor is further configured to identify a time of impact based on a local minimum of the intensity that corresponds to a rate of change of the intensity transcending a threshold and determine the characteristic of the swing from the portion of the sound signal corresponding to a predetermined time period ending at the time of impact (i.e. duration of sounds associated with the impact).”, ¶ 60, “the processor 110 calculates the peak frequency amplitude of the waveform 200, as filtered at 716, during the pre-impact window 202. The processor 110 may utilize any methodology for calculating the peak frequency amplitude known in the art. In an example, the processor 110 performs a Fourier transform of the waveform 200, as filtered at 716, during the pre-impact window 202 and identifies a peak frequency of the resultant transform. The processor 110 then ends the flowchart 700.”, also see ¶ 22-23 and 71-72, receiving through a microphone 106 of a mobile device 300, such as a smartphone, sound signals 120 associated with the swing or set of swings and impacts with the ball 104);
processing the set of sound data to generate a feedback data that identifies at least one corrective action for improving subsequent golf swings, the feedback data comprising a visual presentation of a virtual impact tape showing a location of impact on the clubhead (see ¶ 34 and 43, analyzing the pre-impact window 202, and the impact window 203, determining a time of impact from the impact window, and determining a characteristic of the golf swing from the pre-impact window 202, also see ¶ 43, a characteristic, such as speed, of the golf swing; paragraph, also see ¶ 18, equipment recommendations or personal training suggestions based on a change in the characteristic over time, also see ¶ 71-72, from the sound signals determining a characteristic of the swings such as swing speed, or average swing speed of the set of swings);
and providing the see ¶ 43, output of the characteristic and suggestions to a user interface 114, also see ¶ 18, “by identifying a particular time of the impact based on an analysis of the sound signal and then assessing the sound signal including at least a portion of the sound signal before the time of impact, a characteristic, such as a speed of the golf club, may be determined with suitable accuracy and reliability in many conditions to obtain useful information. Information related to the characteristic may then be presented to a user, such as by displaying the information on a user interface. Such information may further or alternatively include equipment recommendations and personal training based on changes in the characteristic over time.”, also see ¶ 28, “FIG. 3 is a diagram of a positional relationship between the system 100, implemented as a mobile device 300, and the golf ball 104, in an example embodiment. As illustrated, the mobile device 300 is positioned in a predetermined orientation at a predetermined distance D from the golf ball 104 relative to a swing path 302 generally followed by the head 116 during a swinging motion of the club 102.”, also see ¶ 18, based on the change in the characteristic over time, making equipment recommendations or personal training suggestions, also see ¶ 18 and 73-74, providing the characteristic and suggestions to a user interface 114 on a display 900 of a user's mobile device 300).
Leech teaches characteristics of the swing, but do not specifically teach providing the produced feedback to the particular golfer.
Hadden teaches providing the produced feedback to the particular golfer (see ¶ 45, “the user may be prompted to create the golf ball impact by an instruction from the computing device. As such, a user might only begin swinging at the golf ball upon receiving a corresponding instruction from the computing device.”, also see ¶ 47, “In step 310, the computing device may generate an output based on the analysis of the impact data. The output may include visuals, audio data, textual information and/or haptic feedback.”, also see ¶ 56, “upon determining the user's club head speed, the computing system may recommend a corresponding type of golf ball. Other factors beyond club head speed may also be taken into account in generating the recommendation including club type, lie angle, gender of the player and the like.”).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have included based on the golfer's assigned category, generating feedback that identifies at least one corrective action for improving subsequent golf swings as in Hadden. The motivation would have been to “The impact between the golf ball and the surface may be measured based on sound and/or motion sensors (e.g., gyroscopes, accelerometers, etc.). Based on motion and/or sound data, various equipment-related information including golf ball compression, club head speed and impact location may be derived. Such information and/or other types of data may be conveyed to a user to help improve performance, aid in selecting golf equipment and/or to insure quality of golfing products.” (see Hadden abstract ).
Regarding claim 13.
Leech teaches a method of analyzing golf swings of a golfer, the method comprising:
at a first mobile device of the golfer (see ¶ 28, “FIG. 3 is a diagram of a positional relationship between the system 100, implemented as a mobile device 300, and the golf ball 104, in an example embodiment. As illustrated, the mobile device 300 is positioned in a predetermined orientation at a predetermined distance D from the golf ball 104 relative to a swing path 302 generally followed by the head 116 during a swinging motion of the club 102.”): capturing a set of sound data associated with a set of golf swings of the golfer (see ¶ 22, “When a head 116 of the golf club 102 impacts the golf ball 104, a sound 118 is generated. The sound 118 propagates from the head 116 and may ultimately be sensed by the microphone 106. Upon the microphone 106 sensing the sound 118, the microphone outputs a sound signal 120 to the processor 110 via the connection 108.”, also see ¶ 23, “FIG. 2A illustrates a waveform 200 of the sound signal 120 as generated by the microphone 106 and transmitted to the processor 110, in an example embodiment, and FIGS. 2B and 2C are illustrations of the head 116 in relation to the ball 104 at various associated times covered in the waveform 200.”, also see ¶ 26);
processing the set of sound data to identify a range of statistical variance between the golf swings in the set of golf swings; see ¶ 22, “When a head 116 of the golf club 102 impacts the golf ball 104, a sound 118 is generated. The sound 118 propagates from the head 116 and may ultimately be sensed by the microphone 106. Upon the microphone 106 sensing the sound 118, the microphone outputs a sound signal 120 to the processor 110 via the connection 108.”, also see ¶ 23, “FIG. 2A illustrates a waveform 200 of the sound signal 120 as generated by the microphone 106 and transmitted to the processor 110, in an example embodiment, and FIGS. 2B and 2C are illustrations of the head 116 in relation to the ball 104 at various associated times covered in the waveform 200.”, also see ¶ 26);
and providing the feedback to the golfer (see ¶ 43, output of the characteristic and suggestions to a user interface 114, also see ¶ 18, “by identifying a particular time of the impact based on an analysis of the sound signal and then assessing the sound signal including at least a portion of the sound signal before the time of impact, a characteristic, such as a speed of the golf club, may be determined with suitable accuracy and reliability in many conditions to obtain useful information. Information related to the characteristic may then be presented to a user, such as by displaying the information on a user interface. Such information may further or alternatively include equipment recommendations and personal training based on changes in the characteristic over time.”, also see ¶ 28, “FIG. 3 is a diagram of a positional relationship between the system 100, implemented as a mobile device 300, and the golf ball 104, in an example embodiment. As illustrated, the mobile device 300 is positioned in a predetermined orientation at a predetermined distance D from the golf ball 104 relative to a swing path 302 generally followed by the head 116 during a swinging motion of the club 102.”).
Leech do not teach based on the identified range of statistical variance, assigning the golfer to one category from a plurality of categories; based on the golfer's assigned category, generating feedback that identifies at least one corrective action for improving subsequent golf swings and providing the feedback to the golfer.
Hadden teaches based on the identified range of statistical variance, assigning the golfer to one category from a plurality of categories; based on the golfer's assigned category, generating feedback that identifies at least one corrective action for improving subsequent golf swings and providing the feedback to the golfer (see ¶ 67, “FIG. 7 illustrates an example grid 703 dividing an area of the golf club face 701. The grid 703 divides the area of face 701 into nine regions and represents the level of granularity with which the impact location may be specified. Accordingly, each hit may be categorized into one of these nine regions”, see ¶ 45, “the user may be prompted to create the golf ball impact by an instruction from the computing device. As such, a user might only begin swinging at the golf ball upon receiving a corresponding instruction from the computing device.”, also see ¶ 47, “In step 310, the computing device may generate an output based on the analysis of the impact data. The output may include visuals, audio data, textual information and/or haptic feedback.”, also see ¶ 56, “upon determining the user's club head speed, the computing system may recommend a corresponding type of golf ball. Other factors beyond club head speed may also be taken into account in generating the recommendation including club type, lie angle, gender of the player and the like.”).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have included based on the golfer's assigned category, generating feedback that identifies at least one corrective action for improving subsequent golf swings as in Hadden. The motivation would have been to “The impact between the golf ball and the surface may be measured based on sound and/or motion sensors (e.g., gyroscopes, accelerometers, etc.). Based on motion and/or sound data, various equipment-related information including golf ball compression, club head speed and impact location may be derived. Such information and/or other types of data may be conveyed to a user to help improve performance, aid in selecting golf equipment and/or to insure quality of golfing products.” (see Hadden abstract ).
Regarding claim 15.
Leech and Hadden teach the method of claim 13,
Leech teaches wherein a higher statistical variance between each golf swing in the set of golf swings is associated with a lower skill level than a lower statistical variance between each golf swing in the set of golf swings (see ¶ 67, “FIG. 7 illustrates an example grid 703 dividing an area of the golf club face 701. The grid 703 divides the area of face 701 into nine regions and represents the level of granularity with which the impact location may be specified. Accordingly, each hit may be categorized into one of these nine regions).
Claim(s) 2, 6-7 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Leech et al. (US 20180345110 A1) in view of Hadden et al. (US 20140278207 A1) in view of Borowski et al. (US 20160360378 A1).
Regarding claim 2.
Leech teach the method of claim 1,
Leech do not teach the limitation of claim 2.
Borowski teaches wherein analyzing the plurality of impact sound parameters comprises providing the plurality of impact sound parameters to a trained neural network to produce at least a subset of feedback (see ¶¶ 46, 50, 52, 79-80, a wearable device 100 has audio sensors 606 for translating sound from a swing motion of a golf club and contact with a ball into machine readable audio data 616, said audio data is passed to a shot detection machine 620 having classifiers, i.e. neural networks, 622 trained with audio data from previously executed golf swings, and determines a magnitude metric of the golf shot, a feedback parameter).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have included analyzing the first set of impact sound parameters and the second set of non-impact sound parameters to extract the set
of feedback parameters comprises analyzing the set of input data by a trained neural network to extract the set of feedback parameters as in Borowski. The motivation would have been to simplify data collection to audio alone (see Borowski paragraph [00521), requiring
fewer sensors and peripheral devices to achieve a similar result.
Regarding claim 6.
Leech do not teach the limitation of claim 6.
Borowski teaches wherein the neural network is trained through a training process that uses sounds associated with other golf swings and feedback data associated with the other golf swings as known inputs and known outputs of the training process (see ¶ 50 and 52, the shot detection machine may be previously trained with training audio data of previously executed golf shots, allowing it to identify a swing magnitude of subsequent shots see ¶ 501, a shot detection machine 620 having a plurality of classifiers 622).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have included wherein the swing analyzer application comprises a neural network, wherein before receiving the set of sound input, the method
comprises training the neural network to infer the set of feedback parameters based on impact and non-impact sounds associated with a golf swing. The motivation would have been to simplify data collection to audio alone (see Borowski paragraph [0052]), requiring fewer sensors and peripheral devices to achieve a similar result.
Regarding claim 7.
Leech and Borowski teach the method of claim 6,
Borowski teaches wherein: the neural network comprises a plurality of processing nodes each having adjustable parameters; and each adjustable parameter comprises a weight associated with a connection between a pair of inputs (see ¶ 50 and 52, as a neural network the shot detection machine 620 will have a plurality of neurons, with adjustable weights between them, also see ¶ 79, a neural network trained on audio data to output a magnitude of a shot will include both volume and duration and a connection there between which will be adjusted during training).
The motivation utilized in the combination of claim 6, super, applies equally as well to claim 7.
Regarding claim 12.
Leech teach the method of claim 11,
Leech do not teach the limitation of claim 12.
Borowski teaches wherein processing the set of input data to generate the set of output data comprises processing the set of input data by a trained neural network operating on the mobile device to generate the set of output data (see ¶ 79, processing the sensor data, which may be audio data 616 by the shot detection machine 620 to generate a swing magnitude metric which will be further processed).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have included processing the set of input data to generate the first set of output data comprises processing the set of input data by a trained neural network to generate the first set of output data. The motivation would have been to simplify data collection to audio alone (see Borowski paragraph [0052), requiring fewer sensors and peripheral devices to achieve a similar result.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Leech et al. (US 20180345110 A1) in view of Hadden et al. (US 20140278207 A1) in view of DeLeon et al. (US 20200147470 A1).
Regarding claim 3.
Leech teach the method of claim 1,
Leech do not teach the limitation of claim 3.
Leech further teach (i) swing speed (see ¶ 38, a characteristic can include swing speed), however, Leech do not teach wherein the set of metrics comprises (i) swing speed, (ii) swing path, (iii) ball speed, (iv) launch angle, (v) ball spin direction, and (vi) ball spin rate.
Borowski teaches wherein the feedback comprises a set of metrics including (i) swing speed, (ii) swing path, (iii) ball speed, (iv) launch angle, (v) ball spin direction, (vi) ball spin rate, and (vii) virtual impact tape that provides a representation of a location on the clubhead that made contact with the target ball object (club path is measured; page 2, table), (iii) ball speed (ball speed at contact; page 2, table), (iv) launch angle (calculated launch angle; page 2, table) (v) ball spin direction (measured spin axis leaving tee; page 2, table), and (vi) ball spin rate (measured spin rate leaving tee; page 2, table).
If would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to include, (ii) swing path, (iii) ball speed, (iv) launch angle, (v) ball spin direction, and (vi) ball spin rate in the set of. metrics. The motivation would have
been to include more data by which a user can assess their performance and progress.
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Leech et al. (US 20180345110 A1) in view of Hadden et al. (US 20140278207 A1) in view of Choi et al. (KR 20160045975 A).
Regarding claim 18.
Leech and Choi teach the method of claim 13,
Choi teaches wherein the assigned category comprises an indication of a skill level of the golfer and the skill level is used to determine a lexicon to use for the feedback (see page 8, 3rd paragraph, depending on whether the swing was good or bad, i.e. the user skill was good or bad, outputting from a speech database 70 "boss, nice shot" or "I'm sorry" or the like).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have included wherein the indicated skill level of the user is used to determine a lexicon to use for the feedback second set of output data. The motivation would have been to provide a means to adapt the content of the feedback according to the user's skill.
Claim(s) 2, 6-7 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Leech et al. (US 20180345110 A1) in view of Hadden et al. (US 20140278207 A1) in view of Stites et al. (US 20100216564 A1).
Regarding claim 10.
Leech and Hadden teach the method of claim 1,
Leech and Hadden do not teach limitation of claim 10.
Stites teaches wherein the mobile device is a mobile phone and analyzing the plurality of impact sound parameters comprises analyzing the impact sound parameters with a set of sensor data captured by a smart watch of the golfer in order to produce the feedback (¶ 7, “The disclosed golf clubs may be self-contained and include sensors and transmitters located within the golf clubs. As a result, the golf clubs can be used during a round of golf and do not interfere with the golfer. In certain embodiments, the disclosed golf clubs wirelessly transmit golf swing characteristic data to a portable device, such as a personal digital assistant (PDA) or watch.”).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have sensor data captured by a smart watch as in Hadden. The motivation would have been to “variety of golf swing parameters are measured by the instrumented golf club and wirelessly transmitted to a portable computer device. The portable computer device generates a user interface that displays the golf swing parameters against preferred golf swing parameters. The instrumented golf club system allows a golfer to receive feedback in real time while playing golf.” (see Stites abstract ).
Regarding claim 14.
Leech and Hadden teach the method of claim 13,
Leech and Hadden do not teach limitation of claim 14.
Stites teaches wherein the first mobile device is a smart watch, and processing the set of sound data comprises processing the set of sound data with sensor data captured about the set of golf swings by the smart watch (¶ 7, “The disclosed golf clubs may be self-contained and include sensors and transmitters located within the golf clubs. As a result, the golf clubs can be used during a round of golf and do not interfere with the golfer. In certain embodiments, the disclosed golf clubs wirelessly transmit golf swing characteristic data to a portable device, such as a personal digital assistant (PDA) or watch.”).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have sensor data captured by a smart watch as in Hadden. The motivation would have been to “variety of golf swing parameters are measured by the instrumented golf club and wirelessly transmitted to a portable computer device. The portable computer device generates a user interface that displays the golf swing parameters against preferred golf swing parameters. The instrumented golf club system allows a golfer to receive feedback in real time while playing golf.” (see Stites abstract ).
Regarding claim 16.
Leech and Hadden teach the method of claim 13,
Leech and Hadden do not teach limitation of claim 16.
Stites teaches wherein the first mobile device is a mobile phone, and processing the set of sound data comprises processing the set of sound data with sensor data captured about the set of golf swings by the smart watch (¶ 7, “The disclosed golf clubs may be self-contained and include sensors and transmitters located within the golf clubs. As a result, the golf clubs can be used during a round of golf and do not interfere with the golfer. In certain embodiments, the disclosed golf clubs wirelessly transmit golf swing characteristic data to a portable device, such as a personal digital assistant (PDA) or watch.”).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have sensor data captured by a smart watch as in Hadden. The motivation would have been to “variety of golf swing parameters are measured by the instrumented golf club and wirelessly transmitted to a portable computer device. The portable computer device generates a user interface that displays the golf swing parameters against preferred golf swing parameters. The instrumented golf club system allows a golfer to receive feedback in real time while playing golf.” (see Stites abstract ).
Regarding claim 17.
Leech and Hadden teach the method of claim 11,
Leech and Hadden do not teach limitation of claim 17.
Stites teaches wherein the mobile device is a mobile phone and processing the set of sound data comprises processing the set of sound data with sensor data captured about the set of golf swings by a smart watch of the golfer (¶ 7, “The disclosed golf clubs may be self-contained and include sensors and transmitters located within the golf clubs. As a result, the golf clubs can be used during a round of golf and do not interfere with the golfer. In certain embodiments, the disclosed golf clubs wirelessly transmit golf swing characteristic data to a portable device, such as a personal digital assistant (PDA) or watch.”).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have sensor data captured by a smart watch as in Hadden. The motivation would have been to “variety of golf swing parameters are measured by the instrumented golf club and wirelessly transmitted to a portable computer device. The portable computer device generates a user interface that displays the golf swing parameters against preferred golf swing parameters. The instrumented golf club system allows a golfer to receive feedback in real time while playing golf.” (see Stites abstract ).
Regarding claim 19.
Leech and Hadden teach the method of claim 11,
Leech and Hadden do not teach limitation of claim 19.
Stites teaches wherein the mobile device is a smart watch and processing the set of sound data comprises processing the set of sound data with sensor data captured about the set of golf swings by the smart watch (¶ 7, “The disclosed golf clubs may be self-contained and include sensors and transmitters located within the golf clubs. As a result, the golf clubs can be used during a round of golf and do not interfere with the golfer. In certain embodiments, the disclosed golf clubs wirelessly transmit golf swing characteristic data to a portable device, such as a personal digital assistant (PDA) or watch.”).
It would have been obvious to one of ordinary skill at the time of the invention to have modified the method of Leech to have sensor data captured by a smart watch as in Hadden. The motivation would have been to “variety of golf swing parameters are measured by the instrumented golf club and wirelessly transmitted to a portable computer device. The portable computer device generates a user interface that displays the golf swing parameters against preferred golf swing parameters. The instrumented golf club system allows a golfer to receive feedback in real time while playing golf.” (see Stites abstract ).
Related closest arts:
Stites et al. (US 20100216564 A1) teaches A variety of golf swing parameters are measured by the instrumented golf club and wirelessly transmitted to a portable computer device. The portable computer device generates a user interface that displays the golf swing parameters against preferred golf swing parameters. The instrumented golf club system allows a golfer to receive feedback in real time while playing golf.
Lafortune et a. (US 9623284 B2) teaches providing coaching, training, or equipment specification information to individual golfers based on data generated during their individual golf swings. Additionally, data hubs are described that provide information and services to individuals based on data collected for a community of multiple golfers.
BOROWSKI et al. (US 20160354671 A1) teaches he device (100) has sensors for measuring swing motion. A first circuit is in communication with the motion sensors. The first circuit translates measurements of swing motion to machine-readable motion data and identifies a golf shot in which a golf club held by a golfer contacts a golf ball from the machine-readable motion data. A second circuit is previously trained with training motion data of previously-executed golf swings through machine learning, and increments a golf score of the golfer responsive to the golf shot being identified.
HIXENBAUGH et al. (US 20200155899 A1) teaches receives a current dynamic input that includes the golf club swing or the golf ball flight characteristics for a golf shot, from a golfer. A current static input which is a golfer or golf-equipment characteristics, is received through an input device. A trained machine-learning model is executed based on the current dynamic input and current static input to generate predicted golf club properties or predicted golf ball properties for the golfer.
PAO et al. (US 20210245005 A1) teaches providing a local platform for acquiring physical parameter data pertaining to motion and position of the user and motion and position of a golf club and a golf ball struck by the golf club during a golf swing by the user; transmitting via a network at least a portion of the physical parameter data of the motion and position of the golf club and the golf ball struck by the golf club during the golf swing and the physical parameter data associated with the motion and position of the user during the golf swing from the local platform to a machine learning analysis engine as input information; entering the input information into a machine learning model, the machine learning model having a set of rules and statistical techniques to learn patterns from the input data, and a model which is trained by using evolving training sets, wherein an initial training sets is formed from selected professional golf players physical and swing characteristics and are classified and used to train the machine learning model and resulting learned weighting factors are feedback and used to refine a model prediction, the machine learning model determining a user's skill deficiencies and providing correction suggestions; and providing a correction suggestion to the user.
Zhang et al. (“A Kinect-Based Golf Swing Classification System Using HMM and Neuro-Fuzzy”, 2012 conference) teaches a game controller, Kinect, is used to capture the 3D skeleton coordination of a golfer while swing is performed. Secondly, the time-sequential posture of golf swing features has been extracted. Thirdly, a HMM-NF model is used for scoring, which combines ability of HMM model for temporal data modeling with that of Fuzzy Neural Network for fuzz rule modeling and fuzzy defined in a fuzzy (I am not sure on this!!!). Results have shown that the proposed methods can be implemented to identify and score the golf swing effectively with up to 80% accuracy rate.
Krüger et al. (“Recognizing and classifying a golf swing using accelerometer in a Smartwatch”, Sweden, 2017) teaches Smartwatches are becoming more popular and the amount of golf related applications are growing. By using a pattern recognition algorithm on the accelerometer data one can identify and classify the user’s gestures and movements. Is it possible to correctly recognize and classify different types of golf swings by only using a smartwatch as a tool.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/IMAD KASSIM/Examiner, Art Unit 2129