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Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand

机译：根据原始加速度数据计算出的平均幅度偏差：一种用于分类青少年运动强度的新方法而与加速度计品牌无关

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BackgroundUsing raw acceleration data to assess the intensity of physical activity enables direct comparisons between studies using different accelerometer brands. Mean amplitude deviation (MAD in mg) calculated from resultant tri-axial raw acceleration signal was recently shown to perform best in classifying the intensity of physical activity in adults irrespective of the accelerometer brand. This study compared MAD values and cut-points between two different accelerometers in adolescents.

机译：背景技术使用原始加速度数据评估身体活动强度可在使用不同加速度计品牌的研究之间进行直接比较。最近，从合成的三轴原始加速度信号计算出的平均幅度偏差（MAD以mg为单位）显示出在对成人体力活动强度进行分类时效果最佳，而与加速度计品牌无关。这项研究比较了两种不同加速度计在青少年中的MAD值和临界点。

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期刊名称 BMC Sports Science Medicine and Rehabilitation
作者
Minna Aittasalo; Henri Vähä-Ypyä; Tommi Vasankari; Pauliina Husu; Anne-Mari Jussila; Harri Sievänen;
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作者单位

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年(卷),期 2015(7),-1
年度 2015
页码 18
总页数 7
原文格式 PDF
正文语种
中图分类康复;
关键词
Adolescents Physical activity Accelerometer Raw acceleration data Classification;

机译：青少年;体育活动;加速度计;原始加速度数据;分类;

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专利

1. Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand [J] . Minna Aittasalo, Henri V?h?-Ypy?, Tommi Vasankari, BMC sports science, medicine & rehabilitation . 2015,第1期

机译：根据原始加速度数据计算出的平均幅度偏差：一种用于分类青少年身体活动强度的新方法，而与加速度计品牌无关
2. Advanced analytical methods to assess physical activity behaviour using accelerometer raw time series data: a protocol for a scoping review [J] . Tripti Rastogi, Anne Backes, Susanne Schmitz, Systematic Reviews . 2020,第1期

机译：使用加速度计原始时间序列数据评估物理活动行为的高级分析方法：用于审查评论的协议
3. Evaluating and Enhancing the Generalization Performance of Machine Learning Models for Physical Activity Intensity Prediction From Raw Acceleration Data [J] . Farrahi Vahid, Niemela Maisa, Tjurin Petra, Biomedical and Health Informatics, IEEE Journal of . 2020,第1期

机译：从原始加速数据评估和提高机器学习模型的泛化性能
4. Human Activity Recognition from Triaxial Accelerometer Data Feature Extraction and Selection Methods for Clustering of Physical Activities [C] . Ines Machado, Ricardo Gomes, Hugo Gamboa, International Conference on Bio-inspired Systems and Signal Processing . 2014

机译：来自三轴加速度计数据特征提取和选择体育活动的人类活动识别
5. Development of novel analytical techniques to classify physical activity mode using accelerometers. [D] . Pober, David M. 2007

机译：利用加速度计对体育活动模式进行分类的新型分析技术的发展。
6. Intensity Thresholds on Raw Acceleration Data: Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) Approaches [O] . Kishan Bakrania, Thomas Yates, Alex V. Rowlands, -1

机译：原始加速度数据的强度阈值：欧几里得减一（ENMO）和平均幅度偏差（MAD）方法
7. Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand [O] . Minna Aittasalo, Henri Vähä-Ypyä, Tommi Vasankari, 2015

机译：根据原始加速度数据计算出的平均幅度偏差：一种用于分类青少年运动强度的新方法，而与加速度计品牌无关
8. The Correlation of Peak Ground Acceleration Amplitude with Seismic Intensity and Other Physical Parameters, [R] . o'brien, l. j. murphy, j. r. 1977

机译：峰值地面加速度幅度与地震烈度和其他物理参数的相关性，

Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand

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