An evaluation of temporal and club angle parameters during golf swings using low cost video analyses packages

Hunter, Henry H.; Ugbolue, Ukadike C.; Sorbie, Graeme G.; Lam, Wing-Kai; Grace, Fergal; Iacono, Antonio Dello; Liang, Minjun; Dutheil, Frédéric; Gu, Yaodong; Baker, Julien S.

doi:10.1038/s41598-022-17175-2

Cited by 3 publications

(3 citation statements)

References 43 publications

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“…Figure 2 shows an example of a manually annotated frame. Assuming time is not a constraint, KV is an easy-to-use and cost-effective video annotation software for 2D kinematic analysis ( 20 ). It offers many features for manual and frame-by-frame video editing and its reliability and validity have been assessed both in a clinical setting ( 21 – 23 ) and in sports performance ( 24 – 27 ).…”

Section: Methodsmentioning

confidence: 99%

Gait analysis comparison between manual marking, 2D pose estimation algorithms, and 3D marker-based system

Menychtas,

Petrou,

Kansizoglou

et al. 2023

Front. Rehabil. Sci.

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IntroductionRecent advances in Artificial Intelligence (AI) and Computer Vision (CV) have led to automated pose estimation algorithms using simple 2D videos. This has created the potential to perform kinematic measurements without the need for specialized, and often expensive, equipment. Even though there's a growing body of literature on the development and validation of such algorithms for practical use, they haven't been adopted by health professionals. As a result, manual video annotation tools remain pretty common. Part of the reason is that the pose estimation modules can be erratic, producing errors that are difficult to rectify. Because of that, health professionals prefer the use of tried and true methods despite the time and cost savings pose estimation can offer.MethodsIn this work, the gait cycle of a sample of the elderly population on a split-belt treadmill is examined. The Openpose (OP) and Mediapipe (MP) AI pose estimation algorithms are compared to joint kinematics from a marker-based 3D motion capture system (Vicon), as well as from a video annotation tool designed for biomechanics (Kinovea). Bland-Altman (B-A) graphs and Statistical Parametric Mapping (SPM) are used to identify regions of statistically significant difference.ResultsResults showed that pose estimation can achieve motion tracking comparable to marker-based systems but struggle to identify joints that exhibit small, but crucial motion.DiscussionJoints such as the ankle, can suffer from misidentification of their anatomical landmarks. Manual tools don't have that problem, but the user will introduce a static offset across the measurements. It is proposed that an AI-powered video annotation tool that allows the user to correct errors would bring the benefits of pose estimation to professionals at a low cost.

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Section: Methodsmentioning

confidence: 99%

Gait analysis comparison between manual marking, 2D pose estimation algorithms, and 3D marker-based system

Menychtas,

Petrou,

Kansizoglou

et al. 2023

Front. Rehabil. Sci.

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show abstract

“…Another article titled "An evaluation of temporal and club angle parameters during golf swings using low cost video analyses packages" also tried to find a low-cost way of analyzing golf swings [6]. It compares swing time and the angles of golf clubs by using low-cost, 2D Augmented-Video-based-Portable-Systems (AVPS).…”

Section: Related Workmentioning

confidence: 99%

An Intelligent Mobile Program to Provide Zero Cost but Effective Golf Coaching by Analyzing Golfer’s Swings Using AI and Machine Learning

Yang,

Ngoi

2023

Software Engineering and Applications

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Golf is enjoyed by many individuals, however the high coaching costs hinder golfers, particularly those from lower-income backgrounds, from reaching their potential. This issue not only affects the golfers themselves but also impacts the growth and diversity of its community. To address this, I've developed the "GolfBud" app in which users can use their smartphones to record their swing and the app will use algorithms to generate comparisons with professional swings in the form of still images: providing personalized feedback for improvement. It has three main components, including a Flutter mobile interface, a server hosting the golf engine analyzer, and Firebase for image storage. The videos submitted by users are analyzed frame by frame, and get the body angles using OpenCV and Mediapipe [11][12]. These frames are grouped using K-means and then one frame is chosen from each group. Lastly, each of those frames are compared with similar frames from a professional swing. Three main challenges were figuring the methods to analyze golf swings, finding features to group the frames together and devising a way to allow easy access to the golf analyzer [14]. This innovative solution offers an affordable way to enhance a golfer's skills without having to pay the high coaching fee. It is affordable, accessible, and effective.

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“…Three-dimensional motion capture is considered the gold standard for human movement analysis. However, it is expensive and requires a significant amount of time [ 22 , 23 ]. Rather, the video-based observation method, hereby meaning observation recorded via cameras with further image-registered behavior coding, requires little cooperation from the target individuals and is easier to set up.…”

Section: Introductionmentioning

confidence: 99%

Video-Based Behaviorally Coded Movement Assessment for Adolescents with Intellectual Disabilities: Application in Leg Dribbling Performance

Cheng

et al. 2022

Sensors

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Measuring motor performance in individuals with intellectual disabilities (ID) is quite challenging. The objective of this study was to compare the motor performances of individuals with ID and those with typical development (TD) during soccer dribbling through video-based behavior-coded movement assessment along with a wearable sensor. A cross-sectional research design was adopted. Adolescents with TD (N = 25) and ID (N = 29) participated in the straight-line and zigzag soccer dribbling tests. The dribbling performance was videotaped, and the footage was then analyzed with customized behavior-coding software. The coded parameters were the time for movement completion, the number of kicks, blocks, steps, the number of times the ball went out of bounds, the number of missed cones, and the trunk tilt angle. Participants with ID exhibited significantly poorer performance and demonstrated greater variances in many time and frequency domain parameters. It also revealed that participants with ID kicked with both feet while dribbling, whereas those with TD mainly used the dominant foot. The present findings demonstrated how the ID population differed from their peers in lower-extremity strategic control. The customized video-based behavior-coded approach provides an efficient and effective way to gather behavioral data and calculate performance parameter statistics in populations with intellectual disabilities.

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An evaluation of temporal and club angle parameters during golf swings using low cost video analyses packages

Cited by 3 publications

References 43 publications

Gait analysis comparison between manual marking, 2D pose estimation algorithms, and 3D marker-based system

Gait analysis comparison between manual marking, 2D pose estimation algorithms, and 3D marker-based system

An Intelligent Mobile Program to Provide Zero Cost but Effective Golf Coaching by Analyzing Golfer’s Swings Using AI and Machine Learning

Video-Based Behaviorally Coded Movement Assessment for Adolescents with Intellectual Disabilities: Application in Leg Dribbling Performance

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