{"title":"\"A New Approach to Assess the Physical Demands of Young Tennis Players: Inertial Movement Analysis. Preliminary Data\"","authors":"Carlos Galé Ansodi","doi":"10.19080/arr.2019.05.555660","DOIUrl":null,"url":null,"abstract":"In recent years, there has been an increased interest around the use of wearable microsensor technology in order to improve the knowledge about activities patterns such as accelerations, decelerations, jumps and changes of direction. This complex information is a result of accelerometers, magnetometers and gyroscopes and is processed with an advanced algorithm to provide Inertial Movement Analysis (IMA). This technology may also calculate the magnitude and the direction of an agility action, classifying events within intensity and direction. Therefore, the aim of this study was to describe the physical profile of elite young tennis players focusing in the “IMA” patterns. Twenty female young high-level tennis players took part in the study (14.3 age ± 0.8 years). All tennis players were tracked at least in two matches-play (n=62) on hard court. Twelve Portable GPS devices (Minimax X S4, Catapult Innovations) operating at a sampling frequency of 10 Hz were used to collect velocity data. The GPS unit contains a tri-axial piezoelectric linear accelerometer (Kionix: KXP94) sampling at a frequency of 100 Hz. The most common axis of movement was the vertical (V_axis:39.3 ±1.9%). On the other hand, lateral displacement were the most common movements of tennis players (right:6.4±1.2 effort· min 1; left:6.3±1. effort· min 1). Furthermore, low accelerations were the most common acceleration pattern in tennis (low accelerations: 7.4±2.3 effort·min-1), whereas, the high intensity accelerations (>1.0 m·s-2) were the less frequent (high accelerations: 5.1±1.6 effort·min-1). Therefore, further literature should focus on “IMA” patterns to improve tennis players’ performance. .","PeriodicalId":93074,"journal":{"name":"Annals of reviews and research","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of reviews and research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.19080/arr.2019.05.555660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In recent years, there has been an increased interest around the use of wearable microsensor technology in order to improve the knowledge about activities patterns such as accelerations, decelerations, jumps and changes of direction. This complex information is a result of accelerometers, magnetometers and gyroscopes and is processed with an advanced algorithm to provide Inertial Movement Analysis (IMA). This technology may also calculate the magnitude and the direction of an agility action, classifying events within intensity and direction. Therefore, the aim of this study was to describe the physical profile of elite young tennis players focusing in the “IMA” patterns. Twenty female young high-level tennis players took part in the study (14.3 age ± 0.8 years). All tennis players were tracked at least in two matches-play (n=62) on hard court. Twelve Portable GPS devices (Minimax X S4, Catapult Innovations) operating at a sampling frequency of 10 Hz were used to collect velocity data. The GPS unit contains a tri-axial piezoelectric linear accelerometer (Kionix: KXP94) sampling at a frequency of 100 Hz. The most common axis of movement was the vertical (V_axis:39.3 ±1.9%). On the other hand, lateral displacement were the most common movements of tennis players (right:6.4±1.2 effort· min 1; left:6.3±1. effort· min 1). Furthermore, low accelerations were the most common acceleration pattern in tennis (low accelerations: 7.4±2.3 effort·min-1), whereas, the high intensity accelerations (>1.0 m·s-2) were the less frequent (high accelerations: 5.1±1.6 effort·min-1). Therefore, further literature should focus on “IMA” patterns to improve tennis players’ performance. .
近年来,人们对可穿戴微传感器技术的使用越来越感兴趣,以提高对加速、减速、跳跃和方向改变等活动模式的了解。这些复杂的信息是加速度计、磁力计和陀螺仪的结果,并通过高级算法进行处理,以提供惯性运动分析(IMA)。这项技术还可以计算敏捷动作的幅度和方向,根据强度和方向对事件进行分类。因此,本研究的目的是描述以“IMA”模式为主的优秀年轻网球运动员的身体状况。20名年轻高水平女子网球运动员参加了这项研究(14.3岁±0.8岁)。所有网球运动员至少在硬地球场上进行了两场比赛(n=62)。12台便携式GPS设备(Minimax X S4,Catapult Innovations)以10Hz的采样频率运行,用于收集速度数据。GPS单元包含一个以100Hz频率采样的三轴压电线性加速度计(Kionix:KXP94)。最常见的运动轴是垂直(V_axis:39.3±1.9%)。另一方面,网球运动员最常见的动作是侧向位移(右:6.4±1.2用力·min1;左:6.3±1)。努力·分钟1)。此外,低加速度是网球运动中最常见的加速度模式(低加速度:7.4±2.3用力·min-1),而高强度加速度(>1.0 m·s-2)则不太常见(高加速度:5.1±1.6用力·min-2)。因此,进一步的文献应该关注“IMA”模式,以提高网球运动员的表现。