UP - Fall Detection

[17-APR-2020: WE ARE STILL UPLOADING THE DATASET, PLEASE WAIT UNTIL IT IS COMPLETED] -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.

[2020年4月17日：数据集仍在上传中，请等待上传完成]
本数据集专为多模态跌倒检测（multimodal fall detection）构建，收录了17名受试者完成的11类不同动作数据。本次实验共涵盖5类跌倒动作与6类日常活动。数据采集采用了5款可穿戴传感器（wearable sensors）、1款脑电头盔传感器、6台部署于室内的红外传感器以及2台RGB摄像头（RGB cameras）。针对每项动作均录制3次重复尝试。本数据集包含原始信号与3套基于滑动窗口的特征集。此外，本数据集关联一篇已发表的学术论文，该论文给出了可作为基准基线的跌倒检测核心实验结果。