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Khazaeli M, Javadpour L. Golf Club Selection with AI-Based Game Planning. ENTROPY (BASEL, SWITZERLAND) 2024; 26:800. [PMID: 39330132 PMCID: PMC11431687 DOI: 10.3390/e26090800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 09/11/2024] [Accepted: 09/13/2024] [Indexed: 09/28/2024]
Abstract
In the dynamic realm of golf, where every swing can make the difference between victory and defeat, the strategic selection of golf clubs has become a crucial factor in determining the outcome of a game. Advancements in artificial intelligence have opened new avenues for enhancing the decision-making process, empowering golfers to achieve optimal performance on the course. In this paper, we introduce an AI-based game planning system that assists players in selecting the best club for a given scenario. The system considers factors such as distance, terrain, wind strength and direction, and quality of lie. A rule-based model provides the four best club options based on the player's maximum shot data for each club. The player picks a club, shot, and target and a probabilistic classification model identifies whether the shot represents a birdie opportunity, par zone, bogey zone, or worse. The results of our model show that taking into account factors such as terrain and atmospheric features increases the likelihood of a better shot outcome.
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Affiliation(s)
- Mehdi Khazaeli
- School of Engineering and Computer Science, University of the Pacific, Stockton, CA 95211, USA
| | - Leili Javadpour
- Eberhardt School of Business, University of the Pacific, Stockton, CA 95211, USA
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Hollaus B, Heyer Y, Steiner J, Strutzenberger G. Location Matters-Can a Smart Golf Club Detect Where the Club Face Hits the Ball? SENSORS (BASEL, SWITZERLAND) 2023; 23:9783. [PMID: 38139629 PMCID: PMC10748325 DOI: 10.3390/s23249783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 11/20/2023] [Accepted: 12/05/2023] [Indexed: 12/24/2023]
Abstract
In golf, the location of the impact, where the clubhead hits the ball, is of imperative nature for a successful ballflight. Direct feedback to the athlete where he/she hits the ball could improve a practice session. Currently, this information can be measured via, e.g., dual laser technology; however, this is a stationary and external method. A mobile measurement method would give athletes the freedom to gain the information of the impact location without the limitation to be stationary. Therefore, the aim of this study was to investigate whether it is possible to detect the impact location via a motion sensor mounted on the shaft of the golf club. To answer the question, an experiment was carried out. Within the experiment data were gathered from one athlete performing 282 golf swings with an 7 iron. The impact location was recorded and labeled during each swing with a Trackman providing the classes for a neural network. Simultaneously, the motion of the golf club was gathered with an IMU from the Noraxon Ultium Motion Series. In the next step, a neural network was designed and trained to estimate the impact location class based on the motion data. Based on the motion data, a classification accuracy of 93.8% could be achieved with a ResNet architecture.
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Affiliation(s)
- Bernhard Hollaus
- Department of Medical, Health & Sports Engineering, MCI, Maximilianstraße 2, 6020 Innsbruck, Austria;
| | - Yannic Heyer
- Department of Medical, Health & Sports Engineering, MCI, Maximilianstraße 2, 6020 Innsbruck, Austria;
| | - Johannes Steiner
- Johannes Steiner Golf, Robert-Fuchs-Str. 40, 8053 Graz, Austria;
| | - Gerda Strutzenberger
- Institute for Sports Medicine Alpine Medicine & Health Tourism (ISAG), UMIT TIROL—Private University for Health Sciences and Health Technology, Eduard-Wallnoefer-Zentrum 1, 6060 Hall in Tirol, Austria;
- MOTUM—Human Performance Center, Steinbockallee 31, 6063 Rum, Austria
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Kim SE, Burket Koltsov JC, Richards AW, Zhou J, Schadl K, Ladd AL, Rose J. Validation of Inertial Measurement Units for Analyzing Golf Swing Rotational Biomechanics. SENSORS (BASEL, SWITZERLAND) 2023; 23:8433. [PMID: 37896527 PMCID: PMC10611231 DOI: 10.3390/s23208433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 10/10/2023] [Accepted: 10/11/2023] [Indexed: 10/29/2023]
Abstract
Training devices to enhance golf swing technique are increasingly in demand. Golf swing biomechanics are typically assessed in a laboratory setting and not readily accessible. Inertial measurement units (IMUs) offer improved access as they are wearable, cost-effective, and user-friendly. This study investigates the accuracy of IMU-based golf swing kinematics of upper torso and pelvic rotation compared to lab-based 3D motion capture. Thirty-six male and female professional and amateur golfers participated in the study, nine in each sub-group. Golf swing rotational kinematics, including upper torso and pelvic rotation, pelvic rotational velocity, S-factor (shoulder obliquity), O-factor (pelvic obliquity), and X-factor were compared. Strong positive correlations between IMU and 3D motion capture were found for all parameters; Intraclass Correlations ranged from 0.91 (95% confidence interval [CI]: 0.89, 0.93) for O-factor to 1.00 (95% CI: 1.00, 1.00) for upper torso rotation; Pearson coefficients ranged from 0.92 (95% CI: 0.92, 0.93) for O-factor to 1.00 (95% CI: 1.00, 1.00) for upper torso rotation (p < 0.001 for all). Bland-Altman analysis demonstrated good agreement between the two methods; absolute mean differences ranged from 0.61 to 1.67 degrees. Results suggest that IMUs provide a practical and viable alternative for golf swing analysis, offering golfers accessible and wearable biomechanical feedback to enhance performance. Furthermore, integrating IMUs into golf coaching can advance swing analysis and personalized training protocols. In conclusion, IMUs show significant promise as cost-effective and practical devices for golf swing analysis, benefiting golfers across all skill levels and providing benchmarks for training.
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Affiliation(s)
- Sung Eun Kim
- Department of Orthopaedic Surgery, Stanford University, Stanford, CA 94305, USA; (S.E.K.); (J.C.B.K.); (J.Z.); (K.S.); (A.L.L.)
- Motion & Gait Analysis Lab, Lucile Packard Children’s Hospital, Palo Alto, CA 94304, USA
| | - Jayme Carolynn Burket Koltsov
- Department of Orthopaedic Surgery, Stanford University, Stanford, CA 94305, USA; (S.E.K.); (J.C.B.K.); (J.Z.); (K.S.); (A.L.L.)
| | - Alexander Wilder Richards
- Department of Orthopaedic Surgery, Stanford University, Stanford, CA 94305, USA; (S.E.K.); (J.C.B.K.); (J.Z.); (K.S.); (A.L.L.)
| | - Joanne Zhou
- Department of Orthopaedic Surgery, Stanford University, Stanford, CA 94305, USA; (S.E.K.); (J.C.B.K.); (J.Z.); (K.S.); (A.L.L.)
| | - Kornel Schadl
- Department of Orthopaedic Surgery, Stanford University, Stanford, CA 94305, USA; (S.E.K.); (J.C.B.K.); (J.Z.); (K.S.); (A.L.L.)
- Motion & Gait Analysis Lab, Lucile Packard Children’s Hospital, Palo Alto, CA 94304, USA
| | - Amy L. Ladd
- Department of Orthopaedic Surgery, Stanford University, Stanford, CA 94305, USA; (S.E.K.); (J.C.B.K.); (J.Z.); (K.S.); (A.L.L.)
| | - Jessica Rose
- Department of Orthopaedic Surgery, Stanford University, Stanford, CA 94305, USA; (S.E.K.); (J.C.B.K.); (J.Z.); (K.S.); (A.L.L.)
- Motion & Gait Analysis Lab, Lucile Packard Children’s Hospital, Palo Alto, CA 94304, USA
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