US20180169471A1 - Selection support apparatus, selection support system, and selection support method - Google Patents

Selection support apparatus, selection support system, and selection support method Download PDF

Info

Publication number
US20180169471A1
US20180169471A1 US15/800,728 US201715800728A US2018169471A1 US 20180169471 A1 US20180169471 A1 US 20180169471A1 US 201715800728 A US201715800728 A US 201715800728A US 2018169471 A1 US2018169471 A1 US 2018169471A1
Authority
US
United States
Prior art keywords
club
golf
golfer
types
characteristic suitable
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US15/800,728
Other languages
English (en)
Inventor
Daisuke Kondo
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Bridgestone Sports Co Ltd
Original Assignee
Bridgestone Sports Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Bridgestone Sports Co Ltd filed Critical Bridgestone Sports Co Ltd
Assigned to BRIDGESTONE SPORTS CO., LTD. reassignment BRIDGESTONE SPORTS CO., LTD. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: KONDO, DAISUKE
Publication of US20180169471A1 publication Critical patent/US20180169471A1/en
Abandoned legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B1/00—Horizontal bars
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B69/00—Training appliances or apparatus for special sports
    • A63B69/36—Training appliances or apparatus for special sports for golf
    • A63B69/3605—Golf club selection aids informing player of his average or expected shot distance for each club
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B69/00—Training appliances or apparatus for special sports
    • A63B69/36—Training appliances or apparatus for special sports for golf
    • A63B69/3623—Training appliances or apparatus for special sports for golf for driving
    • A63B69/3632—Clubs or attachments on clubs, e.g. for measuring, aligning
    • A63B2069/3605—
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00—Measuring of physical parameters relating to sporting activity
    • A63B2220/30—Speed
    • A63B2220/34—Angular speed
    • A63B2220/35—Spin
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00—Measuring of physical parameters relating to sporting activity
    • A63B2220/40—Acceleration
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
    • A63B24/0003—Analysing the course of a movement or motion sequences during an exercise or trainings sequence, e.g. swing for golf or tennis

Definitions

  • the present invention relates to a technique of supporting the golf club selection of a golfer.
  • a method of selecting a golf club that is suitable for a golfer there is a method of classifying a golf swing by extracting a specific feature of the golf swing. For example, a classification by the angle of a swing track can be performed.
  • the golf swing of a human is complex. Hence, even if some golfers have a specific feature in common, it does not mean that a golf club of the same characteristic will be suitable for all of these golfers.
  • a selection support apparatus comprising: an obtaining unit configured to obtain a measurement result of a golf swing movement of a golfer; and a selection unit configured to select, from a plurality of types of club characteristics of a golf club, a club characteristic suitable for the golfer based on the measurement result, wherein the selection unit selects a club characteristic suitable for the golfer based on machine learning results of teacher data indicating a club characteristic suitable for a golf swing movement of each tester of a plurality of testers.
  • a selection support system comprising: a measurement device configured to measure a golf swing movement of a golfer; and an information processing apparatus configured to select, from a plurality of types of club characteristics of a golf club, a club characteristic suitable for the golfer based on a measurement result of the measurement device, wherein the information processing apparatus selects a club characteristic suitable for the golfer based on machine learning results of teacher data indicating a club characteristic suitable for a golf swing movement of each tester of a plurality of testers.
  • a selection support method comprising: measuring a golf swing movement of a golfer; and selecting, from a plurality of types of club characteristics of a golf club, a club characteristic suitable for the golfer based on the measurement result of the measurement, wherein a club characteristic suitable for the golfer is selected in the selecting based on machine learning results of teacher data indicating a club characteristic suitable for a golf swing movement of each tester of a plurality of testers.
  • FIG. 1 is a schematic view of a selection support system according to one embodiment of the present invention.
  • FIG. 2 is a flowchart showing a procedure to make an artificial intelligence perform learning
  • FIG. 3A is an explanatory view of a swing movement range used for teacher data and the like
  • FIG. 3B is a schematic view showing classification examples of club characteristics
  • FIG. 4 is a view showing examples of swing movement measurement data and swing information
  • FIG. 5 is a view showing examples of ball-striking test results and suitable club information
  • FIG. 6 is a view showing an example of data used for machine learning
  • FIG. 7 is a view showing a flowchart that shows an example of selection support processing and examples of information.
  • FIG. 8 is a view showing another example of a selection support system.
  • FIG. 1 is a schematic view of a selection support system 1 according to an embodiment of the present invention.
  • the system 1 includes a measurement device 2 , an information processing apparatus 3 , a display device 4 , and an input device 5 .
  • the measurement device 2 is a device that measures the golf swing movement of a golfer 100 .
  • the measurement device 2 is a device that measures the behavior of a golf club 101 , is a device attached to the shaft (or the grip) of the golf club 101 , and includes an acceleration sensor and an angular velocity sensor.
  • TSND 121 of ATR-Promotions, Inc. or M-tracer of Seiko Epson Corporation can be used as the measurement device 2 .
  • the time-series data of three-dimensional acceleration and the time-series data of three-dimensional angular velocity of the golf club 101 during a swing from are obtained from the detection results of the measurement device 2 .
  • the information processing apparatus 3 is a computer that functions as a selection support apparatus that recommends a golf club suitable for the golfer 100 .
  • a driver is assumed to be the recommendation target golf club.
  • the information processing apparatus 3 includes a processing unit 31 , a storage unit 32 , and an I/F unit (interface unit) 33 that are electrically connected to each other.
  • the processing unit 31 is a processor such as a CPU.
  • the storage unit 32 includes one or a plurality of storage devices.
  • a storage device is, for example, a RAM, a ROM, a hard disk, or the like.
  • Programs to be executed by the processing unit 31 and various kinds of data are stored in the storage unit 32 .
  • a program to be executed by the processing unit 31 can be formed by a plurality of instructions which can be read by the processing unit 31 .
  • an artificial intelligence program that estimates the golf club characteristics suitable for the golfer 100 is included as a program to be executed by the processing unit 31 , and a database 32 a that makes the artificial intelligence perform machine learning is included in the storage unit 32 .
  • the I/F unit 33 performs input and output of data between an external device and the processing unit 31 .
  • the I/F unit 33 can include an I/O interface and a communication interface.
  • the measurement device 2 is communicably connected to the information processing apparatus 3 by wired or wireless communication, and the measurement results are obtained by the information processing apparatus 3 .
  • the display device 4 and the input device 5 are connected to the information processing apparatus 3 .
  • the display device 4 is, for example, an electronic image display device such as a liquid crystal display device and displays the processing result of the information processing apparatus 3 .
  • the input device 5 is a mouse and a keyboard and accepts data inputs and operation instructions to the information processing apparatus 3 .
  • the swing movement of the golfer 100 is measured by the measurement device 2 , and the information processing apparatus 3 which functions as an artificial intelligence specifies the club characteristics of a golf club suitable for the golfer 100 .
  • the artificial intelligence is provided with, as teacher data, information of club characteristics suitable for the features of each golf swing movement and is made to learn the provided data. If no teacher data is provided, massive amounts of input data would be necessary. However, the amount of data necessary for algorithm formation can be reduced by providing teacher data and making the artificial intelligence learn the teacher data.
  • FIG. 2 is a flowchart showing the procedure related to the learning process of the artificial intelligence.
  • step S 1 the measurement of the swing movement of each of the plurality of testers and the ball-striking tests of a plurality of types of golf clubs by each tester are performed. From the point of machine learning accuracy improvement, it is preferable for the number of testers to be, for example, 100 or more. The measurement of each swing movement will be described first.
  • the measurement of each swing movement is performed by using the same device as the measurement device 2 that forms the system 1 of FIG. 1 or a device which has a similar function.
  • Swing movement measurement results to be extracted as feature amounts may be obtained from the entire swing from the address to the finish or may be obtained from a partial range of the swing.
  • the target is set to be a range from the top until impact in which the characteristics of the golfer can easily appear.
  • FIG. 3A is an explanatory view of this range.
  • FIG. 3A shows a state in which a tester T has swung a golf club GC and has reached impact.
  • the measurement device 2 has been attached to the golf club GC and measures the swing movement of the golf club GC.
  • the golf club GC may be a club usually used by the tester T as long as it is a type of a club (a driver in this embodiment) which is a selection support target.
  • a track BS indicates the track of a golf club head during a back swing
  • a track DS indicates the track of the golf club head from a top TOP until an impact IP.
  • the measurement device 2 measures the behavior of the golf club GC from the address until the follow through after the impact but uses the measurement results from the top TOP until the impact IP as the swing feature data.
  • FIG. 4 exemplifies measurement results D 0 and swing information Din generated from the measurement results D 0 .
  • the swing information Din forms the swing feature data of the golf swing movement.
  • the example of FIG. 4 shows the measurement results of a tester “A”.
  • Each measurement result D 0 is time-series data representing the behavior of the golf club GC in a predetermined time unit (0.001 sec in this case).
  • each measurement result D 0 includes the accelerations in the respective three axis-directions of X, Y, and Z and the angular velocities about these respective three axes. That is, each measurement result includes the three-dimensional acceleration and angular velocity data of the golf club GC.
  • the X axis is set to be positive in the vertical-axis direction of the shaft
  • the Y axis is set to be positive in the shot direction (parallel to a vertical plane of the face)
  • the Z axis is set to be positive in a direction from the head toward the proximal end in the shaft axis direction.
  • the top data and the impact data are specified from these data. For example, since the angular velocity about the X axis or the Y axis tends to change from a negative value to a positive value at the top, this can be specified as the top data.
  • the minimum value of Y-axis acceleration can be specified as the impact data.
  • the data of 0.968 sec has been specified as the top and the data of 1.364 sec has been specified as the impact.
  • data D 1 from 0.968 sec to 1.364 sec is used as the swing feature data.
  • the tempo of the swing differs depending on the person. Hence, the time (number of data) from the top until impact differs. From the point of machine learning accuracy improvement, it is preferable to have a large number of data.
  • 1000 frames are set as the predetermined number of data, and a known data processing technique can be used to thin out or interpolate any exceeding or insufficient frames.
  • the number of data of the data D 1 is 396 but it has been interpolated and set as the swing information Din of 1000 frames.
  • each data array of the swing information Din is not data per each predetermined time unit, it may be called time-series data since it represents the temporal change of the accelerations and angular velocities of the golf club GC.
  • the swing information Din has been formed as data arrays of the accelerations and the angular velocities of a golf club, the present invention is not limited to this as long as the standard of information is uniform, and any type of physical data and data format (as another example, waveform data) may be used.
  • the swing information Din may be any kind of information as long as the series of behaviors of a golf club or a tester during a swing can be specified.
  • FIG. 5 shows ball-striking test data D 10 and suitable club information Dout.
  • the suitable club information Dout will be used to form the teacher data.
  • the example of FIG. 5 shows the ball-striking test results of the tester “A”.
  • the ball-striking test data D 10 is largely classified into information about the golf club used in each ball-striking test and information of each ball-striking result.
  • the example of FIG. 5 shows that ball-striking tests have been performed for 14 clubs (drivers) from club #01 to club #14. Of the plurality of types of club feature amounts, at least one club feature amount is different in each of the 14 clubs. Each club feature amount is a design value that characterizes the golf club. In the example of FIG.
  • a shaft flex (R, SR, S, and X) which indicates the hardness of a shaft, the weight of a shaft, the center-of-gravity distance of a head (the distance between the center-of-gravity of a head and a shaft axis) are shown as the club feature amounts.
  • club feature amounts are the weight of a head, the center-of-gravity angle of a head, the center-of-gravity depth of a head, the loft angle of a head, the lie angle of a head, the face angle of a head, the torque of a shaft, the rigidity of a shaft, the moment of inertia of a head, the moment of inertia of an entire club, the center-of-gravity position of an entire club, the length of a shaft, the weight of a grip, and the like.
  • the club characteristics are the classification of golf clubs based on the club feature amounts. In this embodiment, there are four types of club characteristics ranging from 1 to 4. However, there may be five or more types of club characteristics. Although the club characteristics may be set to be three or less types, setting only two types of club characteristics will not contribute much in narrowing down to a recommended golf club.
  • the club characteristics are classified based on the plurality of types of club feature amounts.
  • the application of a club characteristic that has been classified by a single type of club feature amount is possible, it may reduce the suitability of the recommended golf club for the golfer.
  • the classification becomes complex.
  • dimensionality reduction of the plurality of types of club feature amounts can be achieved by performing principal component analysis.
  • FIG. 3B is a schematic view showing an example of this operation.
  • FIG. 3B includes three classification axes U, V, and W, and a space defined by these three axes has been quartered to classify the club characteristics 1 to 4. At least one of the values of the three axes can be regarded as a dimensionality-reduced value obtained by performing principal component analysis of a plurality of types of club feature amounts.
  • the value of the U axis can be set as
  • the value of the V axis can be set as
  • V coefficient 4 ⁇ center-of-gravity angle of head+coefficient 5 ⁇ shaft torque
  • the value of the W axis can be set as the moment of inertia of the entire club.
  • the values of the respective U axis and V axis are the dimensionality-reduced values and the value of the W axis is a value that has not undergone dimensionality reduction.
  • the ball-striking results are the evaluation criteria for a golf club that suits the swing movement of the tester.
  • the head speed, the carry of the golf ball, the face angle at impact, and sensory evaluation are shown as the four criteria.
  • the face angle at impact is the direction of the face of the head at impact and is measured by setting a state in which the face is perpendicular to a ball-line direction as 0° on a plane parallel to a horizontal plane.
  • the head speed, the carry, and the face angle at impact are measurable by various types of measurement devices.
  • it can use a ball-flight measurement device arranged in the back of the ball line with respect to the golf ball that is to be struck.
  • TRACKMAN available from TRACKMAN GOLF can be used.
  • Sensory evaluation is a criterion obtained by quantifying a tester's experience items such as the hitting sound, the hitting feel, and the swing ease, and uses a five-point rating scale ranging from 1 to 5 in the example of FIG. 5 .
  • 1 is the worst value
  • 5 is the best value.
  • the sensory evaluation may be formed from one type of experience item or may be formed from a plurality of experience items.
  • the plurality of experience items may be set as a dimensionality-reduced value by performing principal component analysis. For example, it may be set as
  • the evaluation criteria are not limited to the four types shown in FIG. 5 and may be, for example, the side spin amount of a golf ball, the back spin amount of a golf ball, and the like. Also, although a plurality of types of evaluation criteria have been used in this embodiment, only one type of evaluation criterion may be used.
  • the suitable club information Dout is created from the ball-striking test data D 10 .
  • the suitable club information Dout is information that indicates the club characteristics of a golf club which has the highest evaluation.
  • club #03 has the highest head speed. Since the club characteristic of club #03 is “2”, the suitable club characteristic related to the head speed of the tester A is “2”.
  • Club #09 has the longest carry. Since the club characteristic of club #09 is “1”, the suitable club characteristic related to the carry of the tester A is “1”. As the club whose face angle at impact is closest to square (0°) is club #12, the suitable club characteristic related to the face angle at impact of the tester A is “4”.
  • Club #02 has the best sensory evaluation, and the suitable club characteristic related to the sensory evaluation of the tester A is “5”. As a principle, one type of characteristic is used as a suitable club characteristic with respect to each evaluation criterion. However, a plurality of types of club characteristics may be associated if there are clubs that have the same score.
  • the suitable club information Dout shows the relation between the evaluation criteria and the club characteristics. This means that the golf club used for the ball-striking test can be different for each tester. That is, although the tester A used 14 clubs (drivers) ranging from #01 to #14 to perform the ball-striking tests in the example of FIG. 5 , it is not necessary for another tester to use the same 14 clubs. It is sufficient as long as a plurality of types of golf clubs that have different club characteristics are used to perform the ball-striking tests.
  • step S 2 data to be used for machine learning is created.
  • data Dt is the combination of the swing information Din and the suitable club information Dout serving as teacher data. That is, FIG. 6 exemplifies the combination of the teacher data and the swing characteristic data of the swing movement related to the tester A, and this combination is created for each tester.
  • the swing information Din and the suitable club information Dout are in a relation in which the former is the input and the latter is the output. These data are input to the information processing apparatus 3 and stored in the database 32 a of the storage unit 32 .
  • step S 3 machine learning is executed in the information processing apparatus 3 .
  • the processing unit 31 reads out the data Dt stored in the database 32 a and generates an artificial intelligence algorithm to derive the suitable club information Dout from the swing information Din by executing machine learning.
  • the generated algorithm is stored in the storage unit 32 . After the algorithm has been generated, the algorithm may be updated by periodically adding new swing feature data and teacher data and executing machine learning again.
  • FIG. 7 is a flowchart showing an example of the selection support processing and is processing executed by the processing unit 31 of the information processing apparatus 3 .
  • step S 11 the swing movement of the golfer is measured by the measurement device 2 .
  • the golfer 100 actually strikes a golf ball by using the golf club 101 , and the measurement device 2 measures the behavior of the golf club 101 .
  • the golf club 101 may be a club usually used by the golfer.
  • step S 12 measurement results are obtained from the measurement device 2 .
  • the information processing apparatus 3 obtains the same data as the measurement results D 0 of FIG. 4 from the measurement device 2 .
  • step S 13 swing information D 11 is created from the measurement results obtained in step S 12 .
  • the swing information D 11 is created in the same manner as the swing information Din of FIG. 4 .
  • step S 14 the artificial intelligence selects, from the swing information D 11 created in step S 13 , a club characteristic suitable for the golfer for each evaluation criterion and creates club characteristic information D 12 .
  • characteristic 3 has been selected for the head speed and the carry
  • characteristic 2 has been selected for the face angle at impact
  • characteristic 4 has been selected for the sensory evaluation.
  • step S 15 product information D 13 of golf clubs is obtained.
  • the product information D 13 is stored in the storage unit 32 .
  • the product information D 13 includes information about the types, the club characteristics, and the specifications of golf clubs.
  • the club characteristics and the specifications of 9 types of golf clubs from A to I have been recorded.
  • Each specification corresponds to club feature amounts.
  • golf clubs E and G are suitable for the golfer.
  • golf clubs C and D are suitable for the golfer.
  • golf clubs B and H are suitable for the golfer.
  • step S 16 the information of the recommended golf clubs is displayed on the display device 4 .
  • the golf club information suitable for the golfer may be displayed for each of the four evaluation criteria or the golf club information suitable for the golfer may be displayed for one evaluation criterion or each of a plurality of evaluation criteria desired by the golfer.
  • the swing measurement results of the golfer may be displayed.
  • the selection support processing thus ends from the above procedures. Subsequently, by performing test shots using each recommended golf club displayed in step S 16 , the golfer can actually experience whether the club is suitable for him/her.
  • this embodiment can analyze a wider range of series of swing movements and determine the suitable club characteristics. Hence, it is possible to make a more multifaceted determination and more accurately determine the club characteristics suitable for a golfer.
  • the system of FIG. 1 has exemplified a measurement device 2 and an information processing apparatus 3 that are arranged in a comparatively short distance from each other and capable of being placed in a shop or the like.
  • a measurement device 2 and an information processing apparatus 3 that are arranged in a comparatively short distance from each other and capable of being placed in a shop or the like.
  • FIG. 8 shows another arrangement example of a selection support system 1 .
  • an information processing apparatus 3 can serve as a server to communicate with a communication device (such as a portable terminal 112 or a personal computer 115 ) via a network 110 and distribute information related to each golf club.
  • the network 110 is, for example, the Internet.
  • a measurement-side arrangement example Ex 1 is a system including the portable terminal 112 and the measurement device 2 .
  • the portable terminal 112 is, for example, a smartphone and includes a short-range wireless communication function with the measurement device 2 and a wireless communication function via the network 110 and a base station (not shown).
  • the measurement results of the measurement device 2 are transmitted to the portable terminal 112 .
  • the portable terminal 112 transmits, to the information processing apparatus 3 , the received measurement results as is or as data of a predetermined format which is processable on the side of the information processing apparatus 3 .
  • the information processing apparatus 3 specifies each recommended golf club and transmits the information to the portable terminal 112 .
  • the portable terminal 112 displays the received information. That is, the process of step S 11 of FIG.
  • step S 7 is executed in the measurement device 2
  • the process of step S 12 is executed in the portable terminal 112 and the information processing apparatus 3
  • the processes of steps S 13 and S 14 are executed in the information processing apparatus 3
  • the process of step S 15 is executed in the portable terminal 112 and the information processing apparatus 3
  • the process of step S 16 is executed in the portable terminal 112 .
  • the execution method is not limited to this.
  • the recommended golf club may be specified by the portable terminal 112 by executing the process of step S 14 in the information processing apparatus 3 and transmitting the information generated in step S 14 to the portable terminal 112 .
  • a measurement-side arrangement example Ex 2 is a system including the personal computer 115 and a plurality of measurement devices 2 A.
  • Each measurement device 2 A is an image capturing apparatus such as a video camera.
  • the personal computer 115 includes a function to process the images captured by the image capturing devices 2 A and a wireless communication function via the network 110 .
  • the golfer performs the test shot in a test shot room or the like.
  • the three-dimensional behavior of a golf club 101 is captured by capturing the golfer from various directions by the plurality of image capturing apparatuses 2 A in the test shot room.
  • the captured images are loaded and analyzed in the personal computer 115 and subsequently transmitted to the information processing apparatus 3 as data of a predetermined format which is processable on the side of the information processing apparatus 3 .
  • the information processing apparatus 3 specifies each recommended golf club and transmits the information to the personal computer 115 .
  • the personal computer 115 displays the received information. That is, the process of step S 11 of FIG. 7 is executed in the measurement devices 2 A, the process of step S 12 is executed in the personal computer 115 and the information processing apparatus 3 , the processes of steps S 13 and S 14 are executed in the information processing apparatus 3 , the process of step S 15 is executed in the personal computer 115 and the information processing apparatus 3 , and the process of step S 16 is executed in the personal computer 115 .
  • the execution method is not limited to this.
  • the recommended golf club may be specified by the personal computer 115 by executing the process of step S 14 in the information processing apparatus 3 and transmitting the information generated in step S 14 to the personal computer 115 .

Landscapes

  • Health & Medical Sciences (AREA)
  • Physical Education & Sports Medicine (AREA)
  • General Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biophysics (AREA)
  • Engineering & Computer Science (AREA)
  • Epidemiology (AREA)
  • Medical Informatics (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Golf Clubs (AREA)
US15/800,728 2016-12-21 2017-11-01 Selection support apparatus, selection support system, and selection support method Abandoned US20180169471A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2016248316A JP6783646B2 (ja) 2016-12-21 2016-12-21 選択支援装置、選択支援システムおよび選択支援方法
JP2016-248316 2016-12-21

Publications (1)

Publication Number Publication Date
US20180169471A1 true US20180169471A1 (en) 2018-06-21

Family

ID=62556588

Family Applications (1)

Application Number Title Priority Date Filing Date
US15/800,728 Abandoned US20180169471A1 (en) 2016-12-21 2017-11-01 Selection support apparatus, selection support system, and selection support method

Country Status (2)

Country Link
US (1) US20180169471A1 (enrdf_load_stackoverflow)
JP (1) JP6783646B2 (enrdf_load_stackoverflow)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20210101066A1 (en) * 2019-10-04 2021-04-08 Sumitomo Rubber Industries, Ltd. Golf club fitting apparatus
US11850490B1 (en) * 2021-01-12 2023-12-26 Topgolf Callaway Brands Corp. Method and system for artificial intelligence club fitting

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP7319540B2 (ja) * 2019-08-27 2023-08-02 株式会社プロギア ショット管理システム、ショット管理方法及びプログラム

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5396580A (en) * 1991-09-09 1995-03-07 University Of Florida Translation of a neural network into a rule-based expert system
US6083123A (en) * 1997-02-11 2000-07-04 Zevo Golf Co., Inc. Method for fitting golf clubs for golfers
US20030078739A1 (en) * 2001-10-05 2003-04-24 Surromed, Inc. Feature list extraction from data sets such as spectra
US7089217B2 (en) * 2000-04-10 2006-08-08 Pacific Edge Biotechnology Limited Adaptive learning system and method
US8506425B2 (en) * 2001-04-05 2013-08-13 Taylor Made Golf Company, Inc. Method for matching a golfer with a particular golf club style
US9398138B2 (en) * 2013-05-31 2016-07-19 Bridgestone Sports Co., Ltd Selection support apparatus and selection support method
US9418288B2 (en) * 2013-05-31 2016-08-16 Bridgestone Sports Co., Ltd. Golf club selection support apparatus and selection support method
US9463366B2 (en) * 2013-10-16 2016-10-11 Dunlop Sports Co. Ltd. Golf club set fitting device, fitting method, and computer-readable medium storing fitting program
US9827464B2 (en) * 2007-09-28 2017-11-28 Karsten Manufacturing Corporation Methods, apparatus, and systems to custom fit golf clubs

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4063754B2 (ja) * 2002-11-20 2008-03-19 美津濃株式会社 ゴルフクラブ選択支援装置、ゴルフクラブ選択用ツール、ゴルフクラブの選択方法およびゴルフクラブの設計方法
JP4388567B2 (ja) * 2007-06-26 2009-12-24 学校法人 関西大学 ゴルフクラブ解析方法
JP5331908B2 (ja) * 2012-02-15 2013-10-30 美津濃株式会社 ゴルファに最適なゴルフクラブの相当単振り子長および慣性モーメントを求める方法およびシステム、ゴルフクラブの選定方法、ならびに各々のゴルファに適した錘の位置および重量を求める方法
JP6488126B2 (ja) * 2014-08-01 2019-03-20 住友ゴム工業株式会社 ゴルフクラブのフィッティング装置、方法及びプログラム
EP3299069A4 (en) * 2015-05-20 2019-02-20 Mitsubishi Chemical Corporation GOLF EQUIPMENT PASSING SYSTEM, GOLD EQUIPMENT PASS PROCEDURE, GOLD EQUIPMENT PASS PROGRAM, GOLF CLASSIFICATION METHOD, GOLF TREATMENT FIT, GOLF TREATMENT PASS PROCEDURE AND GOLF TREATMENT PASS PROGRAM

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5396580A (en) * 1991-09-09 1995-03-07 University Of Florida Translation of a neural network into a rule-based expert system
US6083123A (en) * 1997-02-11 2000-07-04 Zevo Golf Co., Inc. Method for fitting golf clubs for golfers
US7089217B2 (en) * 2000-04-10 2006-08-08 Pacific Edge Biotechnology Limited Adaptive learning system and method
US8506425B2 (en) * 2001-04-05 2013-08-13 Taylor Made Golf Company, Inc. Method for matching a golfer with a particular golf club style
US20030078739A1 (en) * 2001-10-05 2003-04-24 Surromed, Inc. Feature list extraction from data sets such as spectra
US9827464B2 (en) * 2007-09-28 2017-11-28 Karsten Manufacturing Corporation Methods, apparatus, and systems to custom fit golf clubs
US9398138B2 (en) * 2013-05-31 2016-07-19 Bridgestone Sports Co., Ltd Selection support apparatus and selection support method
US9418288B2 (en) * 2013-05-31 2016-08-16 Bridgestone Sports Co., Ltd. Golf club selection support apparatus and selection support method
US9463366B2 (en) * 2013-10-16 2016-10-11 Dunlop Sports Co. Ltd. Golf club set fitting device, fitting method, and computer-readable medium storing fitting program

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20210101066A1 (en) * 2019-10-04 2021-04-08 Sumitomo Rubber Industries, Ltd. Golf club fitting apparatus
US11819749B2 (en) * 2019-10-04 2023-11-21 Sumitomo Rubber Industries, Ltd. Golf club fitting apparatus
US11850490B1 (en) * 2021-01-12 2023-12-26 Topgolf Callaway Brands Corp. Method and system for artificial intelligence club fitting

Also Published As

Publication number Publication date
JP2018099452A (ja) 2018-06-28
JP6783646B2 (ja) 2020-11-11

Similar Documents

Publication Publication Date Title
US10600056B2 (en) Motion analysis device, motion analysis system, motion analysis method, program, and recording medium
JP6613684B2 (ja) スイング診断方法、スイング診断プログラム、記録媒体、スイング診断装置及びスイング診断システム
KR101826837B1 (ko) 볼의 비행정보 연산장치, 볼의 비행정보 연산방법 및 이를 기록한 컴퓨팅장치에 의해 판독 가능한 기록매체
US10786717B2 (en) Impact point estimation apparatus
US20170120122A1 (en) Electronic apparatus, system, method, program, and recording medium
US10307656B2 (en) Swing diagnosis apparatus, swing diagnosis system, swing diagnosis method, and recording medium
WO2015083429A1 (ja) 解析装置、解析方法および記録媒体
US20180169471A1 (en) Selection support apparatus, selection support system, and selection support method
US10576350B2 (en) Simulation apparatus, simulation method, and simulation system
US20180221711A1 (en) Motion analysis method and display method
JP2017023636A (ja) スイング診断装置、スイング診断システム、スイング診断方法、スイング診断プログラム及び記録媒体
JP2015073821A (ja) 運動解析方法、運動解析装置、および運動解析プログラム
JP2017189190A (ja) ゴルフクラブのウェイトパターン決定装置及び推奨装置
JP6697851B2 (ja) ゴルフボールの弾道予測方法、ゴルフボールの弾道予測装置及びゴルフクラブの選定方法
JP6697850B2 (ja) ゴルフボールの弾道予測方法、ゴルフボールの弾道予測装置及びゴルフクラブの選定方法
JP2021100453A (ja) 情報処理装置、情報処理方法、プログラム
JP2017051580A (ja) ゴルフスイングの分析装置
JP6984682B2 (ja) 打点推定装置
US20200398120A1 (en) Information processing apparatus, information processing method, storage medium, and information processing system
US20170120123A1 (en) Electronic apparatus, system, method, program, and recording medium
JP6828952B2 (ja) 選択支援装置および選択支援方法
US20180229079A1 (en) Data processing method, program, storage medium and motion analysis device
JP7371427B2 (ja) ゴルフスイング分析装置
JP5764044B2 (ja) ゴルフスイングの計測解析システム、計測解析装置、ゴルフクラブ及び計測解析方法
JP6984326B2 (ja) 打具のフィッティング装置

Legal Events

Date Code Title Description
AS Assignment

Owner name: BRIDGESTONE SPORTS CO., LTD., JAPAN

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:KONDO, DAISUKE;REEL/FRAME:044009/0786

Effective date: 20171005

STPP Information on status: patent application and granting procedure in general

Free format text: FINAL REJECTION MAILED

STCB Information on status: application discontinuation

Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION