UP - Fall Detection

The dataset comprises a set of 11 different actions performed by 17 subjects that is created for multimodal fall detection. Five types of falls and six daily activities were considered in the experiment. Data collection comes from five wearable sensors, one brainwave helmet sensor, six infrared sensors around the room and two RGB-cameras. Three attempts per action were recorded. The dataset contains raw signals as well as three windowing-based feature sets. Furthermore, this dataset is associated to a published article. The latter presents main results for fall detection that can be used as baseline.

本数据集专为多模态跌倒检测（multimodal fall detection）构建，收录17名受试者完成的11类不同动作数据。本次实验涵盖5类跌倒场景与6类日常活动。数据采集依托5台可穿戴传感器、1台脑电波头盔传感器（brainwave helmet sensor）、房间内布设的6台红外传感器以及2台RGB相机（RGB-camera）完成。每类动作均录制3次重复尝试。本数据集既包含原始信号，也包含3类基于窗口划分的特征集。此外，本数据集关联一篇已发表学术论文，该论文给出了可作为基准基线的跌倒检测核心实验结果。