ArticleSensors (Basel, Switzerland)2020
Golf Swing Segmentation from a Single IMU Using Machine Learning.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- IMU Error Propagation in Position Reconstruction and Its Mitigation Through Task-Informed Dual-IMU Constrained Optimization: Application to Golf Putting.Sensors (Basel, Switzerland) · 2026Article
- Prediction of Three-Dimensional Ground Reaction Forces in the Golf Swing Using Wearable Inertial Measurement Units and Biomimetic Deep Learning Models.Biomimetics (Basel, Switzerland) · 2026Article
- Dynamic Golf Swing Analysis Framework Based on Efficient Similarity Assessment.Sensors (Basel, Switzerland) · 2025Article
- Golf Club Selection with AI-Based Game Planning.Entropy (Basel, Switzerland) · 2024Article
- Enhancing accuracy and convenience of golf swing tracking with a wrist-worn single inertial sensor.Scientific reports · 2024Article
- Location Matters-Can a Smart Golf Club Detect Where the Club Face Hits the Ball?Sensors (Basel, Switzerland) · 2023Article
- A Neural Network Approach for Inertial Measurement Unit-Based Estimation of Three-Dimensional Spinal Curvature.Sensors (Basel, Switzerland) · 2023Article
- Design, Assessment and Deployment of an Efficient Golf Game Dynamics Management System Based on Flexible Wireless Technologies.Sensors (Basel, Switzerland) · 2022Article
- Pilot Study of Embedded IMU Sensors and Machine Learning Algorithms for Automated Ice Hockey Stick Fitting.Sensors (Basel, Switzerland) · 2022Article
- Competitive Golf: How Longer Courses Are Changing Athletes and Their Approach to the Game.Nutrients · 2022Review
- The swing performance Index: Developing a single-score index of golf swing rotational biomechanics quantified with 3D kinematics.Frontiers in sports and active living · 2022Article
- Using Inertial Sensors to Determine Head Motion-A Review.Journal of imaging · 2021Review
- Use of IMU in Differential Analysis of the Reverse Punch Temporal Structure in Relation to the Achieved Maximal Hand Velocity.Sensors (Basel, Switzerland) · 2021Article
- A Data-Driven Approach to Predict Fatigue in Exercise Based on Motion Data from Wearable Sensors or Force Plate.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Golf swing segmentation with inertial measurement units (IMUs) is an essential process for swing analysis using wearables. However, no attempt has been made to apply machine learning models to estimate and divide golf swing phases. In this study, we proposed and verified two methods using machine learning models to segment the full golf swing into five major phases, including before and after the swing, from every single IMU attached to a body part. Proposed bidirectional long short-term memory-based and convolutional neural network-based methods rely on characteristics that automatically learn time-series features, including sequential body motion during a golf swing. Nine professional and eleven skilled male golfers participated in the experiment to collect swing data for training and verifying the methods. We verified the proposed methods using leave-one-out cross-validation. The results revealed average segmentation errors of 5-92 ms from each IMU attached to the head, wrist, and waist, accurate compared to the heuristic method in this study. In addition, both proposed methods could segment all the swing phases using only the acceleration data, bringing advantage in terms of power consumption. This implies that swing-segmentation methods using machine learning could be applied to various motion-analysis environments by dividing motion phases with less restriction on IMU placement.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.