https://www.ncbi.nlm.nih.gov/pubmed/30307362
Machine and deep learning for sport-specific movement recognition: a systematic review of model development and performance.
Author information
- 1
- a Institute for Health and Sport (IHES) , Victoria University , Melbourne , Australia.
- 2
- b Western Bulldogs Football Club , Melbourne , Australia.
Abstract
Objective assessment of an athlete's performance is of importance in elite sports to facilitate detailed analysis. The implementation of automated detection and recognition of sport-specific movements overcomes the limitations associated with manual performance analysis methods. The object of this study was to systematically review the literature on machine and deep learning for sport-specific movement recognition using inertial measurement unit (IMU) and, or computer vision data inputs. A search of multiple databases was undertaken. Included studies must have investigated a sport-specific movement and analysed via machine or deep learning methods for model development. A total of 52 studies met the inclusion and exclusion criteria. Data pre-processing, processing, model development and evaluation methods varied across the studies. Model development for movement recognition were predominantly undertaken using supervised classification approaches. A kernel form of the Support Vector Machine algorithm was used in 53% of IMU and 50% of vision-based studies. Twelve studies used a deep learning method as a form of Convolutional Neural Network algorithm and one study also adopted a Long Short Term Memory architecture in their model. The adaptation of experimental set-up, data pre-processing, and model development methods are best considered in relation to the characteristics of the targeted sports movement(s).
KEYWORDS:
Sport movement classification; computer vision; inertial sensors; machine learning; performance analysis
- PMID:
- 30307362
- DOI:
- 10.1080/02640414.2018.1521769
스포츠 움직임에 특정적인 운동을 분석하는 여러 방법들에 대한 리뷰 논문.
52개의 논문을 리뷰함.
SVM 방법도 있고, Deep learning 방법도 있고, LSTM 방법도 있고.
2018 Machine and deep learning for sport-specific movement recognition.pdf
