Updating ”Medical Radar Signal Dataset for Non-Contact Respiration and Heart Rate Measurement” with Expanded Data on Laboratory Rats under Isoflurane Anesthesia

Published: 19 June 2024| Version 1 | DOI: 10.17632/swk27btvgd.1
Guanghao Sun


The data were collected using a noncontact vital sign monitoring system. The system includes: (1) a Raspberry Pi 4 Model B with a 64-bit quad-core Cortex-A72 processor and 8 GB RAM; (2) a 24.05-24.25 GHz I/Q channel microwave radar with an 8-element TX/RX antenna (SHARP, model DC6M4JN3000); (3) a CMOS multi-function analog laser sensor (Keyence, models IL-1000 & IL-S065) with a 2 μm repeatability accuracy; and (4) an Arduino data acquisition board converting I/Q and laser signals to digital at 1092 Hz, 10-bit resolution. Tests were performed on four spontaneously breathing rats under isoflurane anesthesia (2.5% to 1.0% over 32 minutes), measuring respiratory rate variations to evaluate anesthesia depth. This dataset includes data files and MATLAB code. The data folder contains four data files: RatA.csv, RatB.csv, RatC.csv, and RatD.csv, which correspond to the raw data from radar and laser measurements. The columns in these files are structured as follows: Column 1: Time; Column 2: Radar I channel; Column 3: Radar Q channel; Column 4: Laser. The MATLAB code (estRespRate_rat.m) scripts can be used for signal visualization and FFT (fast Fourier transform) based respiration rate estimation.



Denki Tsushin Daigaku


Biomedical Engineering


Ministry of Education, Culture, Sports, Science, and Technology of Japan

a Grant-in-Aid for Scientific Research (C) (23 K11301)