Earable & IoT Dataset from: ERICA - Enabling real-time mistake detection & corrective feedback for free-weights exercises

Wearables or infrastructure sensors have been widely proposed for automated tracking and analysis of individual-level exercise activities. This dataset is collected as part of building a pervasive, low-cost digital personal trainer system, that supports fine-grained tracking of an individual’s free-weights exercises via a combination of (a) sensors on personal wireless ear-worn devices (‘earables’) and (b) inexpensive IoT sensors attached to exercise equipment (e.g., dumbbells). The dataset is comprised of sensor signals acquired from two 6-axis IMUs and contains a total of 324 samples for 3 different free-weight exercises performed by 27 individuals.

可穿戴设备或基础设施传感器已被广泛应用于个体层级的运动活动自动跟踪与分析。本数据集的收集旨在构建一个普及性高、成本低的数字个人教练系统，该系统通过结合（a）个人无线耳机式设备（即‘耳戴式传感器’）上的传感器和（b）附着在运动器材（例如哑铃）上的低成本物联网传感器，实现对个体自由重量练习的精细跟踪。该数据集由两个6轴惯性测量单元（IMU）采集的传感器信号组成，包含27名个体完成3种不同自由重量练习的共计324个样本。