Inertial sensor and cluster analysis for discriminating agility run technique and quantifying changes across load

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• 作者：Ryan S. McGinnis^a ; ^{ryan.mcginnis@uvm.edu} ; Stephen M. Cain^b ; ^{smcain@umich.edu} ; Steven P. Davidson^c ; ^{stevepd@umich.edu} ; Rachel V. Vitali^b ; ^{vitalir@umich.edu} ; Scott G. McLean^c ; ^{mcleansc@umich.edu} ; Noel C. Perkins^b ; ^{ncp@umich.edu}
• 关键词：Inertial measurement units ; Optimization ; Drift correction ; Human performance ; Agility ; Load carriage
• 刊名：Biomedical Signal Processing and Control
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：32
• 期：Complete
• 页码：150-156
• 全文大小：2080 K
• 卷排序：32

文摘

Wearable sensor and optimization algorithm enable subject trajectory estimation. K-means cluster analysis reveals two distinct groups based on turning technique. Groups exhibit different adaptations to 20.5 kg load carriage. Load carriage eliminates group differences in turning technique. Future use of method includes informing training plans and equipment modifications.