WoW - Wearable Respiration Monitoring Dataset

This dataset was acquired by the Institute of Systems and Robotics, University of Coimbra, as a part of the CMU-Portugal WoW project, Wireless biOmonitoring stickers and smart bed architecture: toWards Untethered Patients (https://inovglintt.com/financiamento/wow/). The main objective of the project is to develop wearable devices for remote and continuous patient monitoring. As a part of this project, we focused on respiration data, to evaluate methods for estimation of human respiration rate through simple and low-cost wearable patches. We are as well interested to understand how body motion, and position (sitting/standing/moving) affects the accuracy of the estimation. Hence, we have recorded data from different sensor inputs. This includes printed, thin-film, and stretchable skin-mounted strain gauges installed on different body locations, bioimpedance measurements via skin-interfacing electrodes, and a chest/belly-mounted accelerometer. This dataset contains respiration data from 4 subjects. In all measurement sessions, we also acquired ground truth data via a nose-mounted thermistor. The dataset can be used along with sensor fusion and machine learning techniques, in order to develop algorithms that can precisely estimate the respiration rate, during different body positions and activities.

本数据集由科英布拉大学系统与机器人研究所（Institute of Systems and Robotics, University of Coimbra）采集，作为CMU-Portugal WoW项目的一部分，该项目全称为“无线生物监测贴纸与智能床架构：面向无束缚患者（Wireless biOmonitoring stickers and smart bed architecture: toWards Untethered Patients）”，项目详情页面为https://inovglintt.com/financiamento/wow/。本项目的核心目标是研发用于患者远程持续监测的可穿戴设备。作为本项目的子任务，我们聚焦于呼吸数据研究，以评估基于简易低成本可穿戴贴片估算人体呼吸频率的方法。同时，我们亦希望探究人体运动与体位（坐姿/站姿/移动状态）对估算精度的影响。因此，我们采集了多类传感器的输入数据，包括安装于不同身体部位的印刷式、薄膜型与可拉伸式皮肤应变片、通过皮肤接触式电极采集的生物阻抗数据，以及安装于胸部或腹部的加速度计。本数据集包含4名受试者的呼吸数据。在所有测量环节中，我们还通过安装于鼻部的热敏电阻采集了真实参考数据（ground truth）。本数据集可结合传感器融合与机器学习技术，用于研发可在不同体位与活动状态下精准估算呼吸频率的算法。