Extensive Age-Balanced and Subject-Varied mmWave Radar Dataset of Referenced Records for Vital Signs

This repository contains a mmWave radar dataset of referenced records for vital signs. 110 participants have been recorded under four different tests. The database is structured in folders - one for each participant and each test - and each one contains the files for radar data (signals, time reference and chirp configuration), reference ECG and accelerometer data, and timestamps for the non-breathing part of some experiments. A deeper description will be added upon acceptance of the research paper accompanying the publication of the dataset. Devices: Reference: Movesense Medical Device Non-breathing indicator: USB push-button Lying tests: NodeNs IWR6843ISK Sitting tests: Texas Instruments IWR6843ISK-ODS The repository contains: db_records.zip - The database itself, with one folder for each participant ExampleCode.ipynb - Jupyter Notebook with example code on how to work with the data helper_fns.py - Python script with the functions needed by the notebook ParticipantsInfo.xlsx - Excel file with anonymised participant information Records: For each participant-test folder reference accelerometer and ECG measurements are stored in the files movesense_acc.csv and movesense_ecg.csv. Each row of these files contains the raw data as sent by the Movesense device - x, y and z acceleration components and a timestamp in the case of accelerometer data, and millivolts and a timestamp for the ECG data. For the tests in which participants were instructed to hold their breath, the USB push-button data were stored in the file non_breathing_ts.csv containing the begin and end timestamps of the non-breathing time. The radar chirp configuration is stored in the file radar_chirpConfig.json. Radar measurements are stored in the compressed file radar_rFFTs.zlib, packed using the pickle object serialisation library and saved using the zlib compression library, both part of the standard libraries of Python 3.11.0. The file contains a Python list of the range Fast Fourier Transforms (FFTs) as received from the radar and the range bins computed using the chirp configuration. The shape of the provided FFT arrays is $(n_v, n_b)$, being $n_v$ the number of virtual antennas and $n_b$ the number of range bins. Radar timestamps are saved as a Python list in the file radar_timestamps.csv. The example Jupyter notebook includes a detailed guide to working with all these files. It must be noted that 12 of the 440 experiments present some FFTs where all values were recorded as 0. Only a small number of frames, located at the beginning of the recording for all experiments, have been affected by this. The following table shows the affected experiments and the number of frames that must be skipped: Experiment Damaged Frame Count P004/Lying/Rest/ 11 P020/Sitting/Post-exercise/ 2 P023/Sitting/Post-exercise/ 2 P041/Sitting/Post-exercise/ 2 P046/Lying/Rest/ 4 P050/Sitting/Post-exercise/ 6 P056/Lying/Rest/ 4 P077/Lying/Rest/ 1 P084/Lying/Rest/ 4 P100/Sitting/Rest/ 2 P104/Sitting/Post-exercise/ 2 P106/Sitting/Rest/ 1 This should not have any impact on the extraction of vital signs, as in the first and most damaged experiment (P004/Lying/Rest) the ratio of damaged frames is 1.83% over the whole recording.本仓库包含用于生命体征参考记录的毫米波雷达（mmWave radar）数据集。共有110名受试者参与，在四种不同测试场景下完成数据采集。本数据库以文件夹结构组织：为每名受试者及每项测试单独设立文件夹，每个文件夹内包含雷达数据文件（信号、时间基准及啁啾配置）、参考心电图（ECG）与加速度计数据文件，以及部分实验中屏息阶段的时间戳文件。本数据集配套研究论文录用后，将补充更详细的说明文档。 ### 设备说明 参考采集设备：Movesense医疗设备 屏息触发装置：USB按键装置 卧位测试场景采集设备：NodeNs IWR6843ISK 坐位测试场景采集设备：德州仪器（Texas Instruments）IWR6843ISK-ODS ### 仓库包含内容 本仓库包含以下文件： 1. `db_records.zip`：数据集本体，内含每名受试者对应的独立文件夹 2. `ExampleCode.ipynb`：用于演示数据处理方法的Jupyter Notebook 3. `helper_fns.py`：配合Notebook使用的Python工具函数脚本 4. `ParticipantsInfo.xlsx`：包含匿名化受试者信息的Excel表格 ### 数据记录说明 在每个「受试者-测试场景」文件夹中，加速度计与心电图参考数据分别存储于`movesense_acc.csv`与`movesense_ecg.csv`文件中。两类文件的每一行均为Movesense设备原生发送的原始数据：加速度计数据包含x、y、z三轴加速度分量与时间戳，心电图数据包含毫伏级幅值与时间戳。对于要求受试者屏息的测试，USB按键装置采集的屏息时段数据将存储于`non_breathing_ts.csv`文件中，该文件包含屏息开始与结束的时间戳。雷达啁啾配置存储于`radar_chirpConfig.json`文件中。 雷达测量数据存储于压缩文件`radar_rFFTs.zlib`，该文件通过Python 3.11.0标准库中的pickle对象序列化工具打包，并经zlib压缩算法压缩。文件内容为从雷达设备接收的距离域快速傅里叶变换（FFT）结果列表，以及基于啁啾配置计算得到的距离 bin 列表。所提供的FFT数组维度为$(n_v, n_b)$，其中$n_v$为虚拟天线数量，$n_b$为距离 bin 总数。雷达时间戳以Python列表形式存储于`radar_timestamps.csv`文件中。示例Jupyter Notebook已包含针对所有文件的详细处理指南。 ### 异常数据说明 需注意，440次实验中有12次存在部分FFT数组全零的情况。此类异常仅出现在所有实验的初始少量帧中。下表列出受影响的实验及需跳过的帧数： | 实验路径 | 受损帧数 | |:---------------------------------|:--------| | P004/Lying/Rest/ | 11 | | P020/Sitting/Post-exercise/ | 2 | | P023/Sitting/Post-exercise/ | 2 | | P041/Sitting/Post-exercise/ | 2 | | P046/Lying/Rest/ | 4 | | P050/Sitting/Post-exercise/ | 6 | | P056/Lying/Rest/ | 4 | | P077/Lying/Rest/ | 1 | | P084/Lying/Rest/ | 4 | | P100/Sitting/Rest/ | 2 | | P104/Sitting/Post-exercise/ | 2 | | P106/Sitting/Rest/ | 1 | 需说明的是，此类异常不会对生命体征提取造成显著影响：以受损最严重的P004/Lying/Rest实验为例，受损帧占总记录帧数的比例仅为1.83%。