Alicia M. Gal, Travis Douglas, A. Chan, Dean C. Hay
{"title":"利用IMU雪橇运动数据在自然环境中进行自主线性、曲线和相位检测的潜力","authors":"Alicia M. Gal, Travis Douglas, A. Chan, Dean C. Hay","doi":"10.1109/MeMeA49120.2020.9137225","DOIUrl":null,"url":null,"abstract":"Inertial measurement units (IMUs) were investigated as a means to provide data for sports analytics for para ice-hockey. Algorithms were developed to automatically detect linear skating cycles (i.e., stroke count) and turns. On-ice data are from 2 task expert participants and 5 task naïve participants. Algorithms correctly identified 100% of the trials analyzed, using manually analyzed video recordings as a ground-truth. In addition, visual analysis suggests that IMU data is able to differentiate between task expert and task naïve participants, potentially allowing for performance indicators to be derived. Results from this preliminary study suggest strong potential for IMUs to be a useful tool for sports analytics in para ice-hockey.","PeriodicalId":152478,"journal":{"name":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Potential for autonomous linear, curvilinear, and phase detection in natural context para skating using IMU sledge motion data\",\"authors\":\"Alicia M. Gal, Travis Douglas, A. Chan, Dean C. Hay\",\"doi\":\"10.1109/MeMeA49120.2020.9137225\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Inertial measurement units (IMUs) were investigated as a means to provide data for sports analytics for para ice-hockey. Algorithms were developed to automatically detect linear skating cycles (i.e., stroke count) and turns. On-ice data are from 2 task expert participants and 5 task naïve participants. Algorithms correctly identified 100% of the trials analyzed, using manually analyzed video recordings as a ground-truth. In addition, visual analysis suggests that IMU data is able to differentiate between task expert and task naïve participants, potentially allowing for performance indicators to be derived. Results from this preliminary study suggest strong potential for IMUs to be a useful tool for sports analytics in para ice-hockey.\",\"PeriodicalId\":152478,\"journal\":{\"name\":\"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MeMeA49120.2020.9137225\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MeMeA49120.2020.9137225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Potential for autonomous linear, curvilinear, and phase detection in natural context para skating using IMU sledge motion data
Inertial measurement units (IMUs) were investigated as a means to provide data for sports analytics for para ice-hockey. Algorithms were developed to automatically detect linear skating cycles (i.e., stroke count) and turns. On-ice data are from 2 task expert participants and 5 task naïve participants. Algorithms correctly identified 100% of the trials analyzed, using manually analyzed video recordings as a ground-truth. In addition, visual analysis suggests that IMU data is able to differentiate between task expert and task naïve participants, potentially allowing for performance indicators to be derived. Results from this preliminary study suggest strong potential for IMUs to be a useful tool for sports analytics in para ice-hockey.
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