A Triaxial Accelerometry and Physical Activity Intensity Dataset for Chinese Primary and Secondary School Students

This dataset provides triaxial accelerometry data and synchronized physical activity intensity measurements for Chinese primary and secondary school students. The study involved a stratified sample across 12 grades (Grades 1-12). Key features include the following: Multiple Sensor Placements: the mid-sternum, distal posterior aspect of the radius (left and right), anterior superior iliac spine (left and right), mid-lateral aspect of the femur (left and right), and distal lateral aspect of the fibula (left and right). Diverse Activity Protocols: Participants performed 13 types of activities: radio calisthenics, vigorous running, brisk walking, basketball dribbling, jogging, slow walking, rope skipping, basketball shooting, single-leg hopping (left/right), badminton, soccer passing, and soccer dribbling. Physical activity intensity: Provided in terms of metabolic equivalents (METs), including raw data and average values within 10-second time windows. Known Data Quality Issues: An anomaly was observed in the right anterior superior iliac spine sensor during data acquisition. Users intending cross-site sensor fusion or lower-limb/trunk kinematic analyses are strongly advised to exclude the right anterior superior iliac spine channel or apply appropriate imputation/sensitivity analyses. The remainder of the dataset retains high quality for most research applications. This dataset is designed to support researchers in developing robust human activity recognition algorithms and physical activity intensity estimation models tailored for the pediatric population.本数据集提供了针对中国中小学生的高分辨率三轴加速度计数据及同步的能量消耗（energy expenditure, EE）测量结果。本研究采用分层抽样方案，覆盖1至12年级共12个年级。 核心特性如下： 多传感器部署：数据采集自9个身体部位，包括胸部、左/右手腕、左/右髋部、左/右大腿以及左/右足部。 多样化活动范式：受试者完成13类活动，分别为广播体操、高强度跑步、快走、篮球运球、慢跑、慢走、跳绳、篮球投篮、单腿跳（左/右侧）、羽毛球运动、足球传球及足球运球。 金标准参照：能量消耗以代谢当量（Metabolic Equivalents, METs）形式提供，包含原始数据与10秒窗口滑动平均值。 本数据集旨在助力研究者开发针对儿童群体的鲁棒人类活动识别（human activity recognition, HAR）算法与精准能量消耗估计模型。