{"title":"使用惯性测量单元对大学女子足球运动员的动作进行分类","authors":"Yuki Masui, Nobuyoshi Hirotsu, Yu Shimasaki, Masafumi Yoshimura","doi":"10.1177/17543371241278032","DOIUrl":null,"url":null,"abstract":"This study aimed to classify the movements of female soccer players during matches using raw data measured by inertial measurement units (IMUs). Twelve collegiate female soccer players were equipped with IMUs (100 Hz), and raw triaxial acceleration data from eight official matches were analyzed. The measurement data were separated every 3 s, and a Fast Fourier Transform (FFT) was performed. After FFT, the Euclidean distances between the data when the players were in the stationary state and other states were calculated to classify the movements of the players using the k-means method. The data of the clustering numbers classified as the stationary state were eliminated after analyzing the movements of players by video filming the matches. After classification, the average Euclidean distances between the stationary state and other movements were calculated. Consequently, the results showed that the upward and downward directions of the raw data affected the classification. Using the methods of this study, it was also shown that the distribution of Euclidean distances differed from player to player. Our findings indicate that the method used in this study can be used to classify and characterize the movements of female collegiate soccer players.","PeriodicalId":20674,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology","volume":"49 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Classification of movements of collegiate female soccer players using inertial measurement units\",\"authors\":\"Yuki Masui, Nobuyoshi Hirotsu, Yu Shimasaki, Masafumi Yoshimura\",\"doi\":\"10.1177/17543371241278032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aimed to classify the movements of female soccer players during matches using raw data measured by inertial measurement units (IMUs). Twelve collegiate female soccer players were equipped with IMUs (100 Hz), and raw triaxial acceleration data from eight official matches were analyzed. The measurement data were separated every 3 s, and a Fast Fourier Transform (FFT) was performed. After FFT, the Euclidean distances between the data when the players were in the stationary state and other states were calculated to classify the movements of the players using the k-means method. The data of the clustering numbers classified as the stationary state were eliminated after analyzing the movements of players by video filming the matches. After classification, the average Euclidean distances between the stationary state and other movements were calculated. Consequently, the results showed that the upward and downward directions of the raw data affected the classification. Using the methods of this study, it was also shown that the distribution of Euclidean distances differed from player to player. Our findings indicate that the method used in this study can be used to classify and characterize the movements of female collegiate soccer players.\",\"PeriodicalId\":20674,\"journal\":{\"name\":\"Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology\",\"volume\":\"49 1\",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2024-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1177/17543371241278032\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/17543371241278032","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
Classification of movements of collegiate female soccer players using inertial measurement units
This study aimed to classify the movements of female soccer players during matches using raw data measured by inertial measurement units (IMUs). Twelve collegiate female soccer players were equipped with IMUs (100 Hz), and raw triaxial acceleration data from eight official matches were analyzed. The measurement data were separated every 3 s, and a Fast Fourier Transform (FFT) was performed. After FFT, the Euclidean distances between the data when the players were in the stationary state and other states were calculated to classify the movements of the players using the k-means method. The data of the clustering numbers classified as the stationary state were eliminated after analyzing the movements of players by video filming the matches. After classification, the average Euclidean distances between the stationary state and other movements were calculated. Consequently, the results showed that the upward and downward directions of the raw data affected the classification. Using the methods of this study, it was also shown that the distribution of Euclidean distances differed from player to player. Our findings indicate that the method used in this study can be used to classify and characterize the movements of female collegiate soccer players.
期刊介绍:
The Journal of Sports Engineering and Technology covers the development of novel sports apparel, footwear, and equipment; and the materials, instrumentation, and processes that make advances in sports possible.