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Respiration Sensing with Cell-free Massive MIMO

Citation Author(s):
Haoqiu Xiong (KU Leuven)
Robbert Beerten (KU Leuven)
Sofie Pollin (KU Leuven & IMEC)
Submitted by:
Haoqiu Xiong
Last updated:
DOI:
10.21227/0dey-xx67
Research Article Link:
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Abstract

We introduce BS-Breath, the first open dataset for respiration sensing using a cell-free massive MIMO system. Collected from a 64-antenna MIMO testbed, this dataset provides uplink Channel State Information (CSI) at 3.51 GHz, captured from 10 subjects performing controlled breathing. Ground truth respiration data is synchronized using a Motion Capture (MoCap) system, enabling precise validation. The dataset includes raw CSI measurements, processed breathing signals, and MoCap recordings, supporting research in Integrated Sensing and Communication (ISAC), wireless health monitoring, and smart environments. By making this dataset publicly available, we aim to accelerate advancements in wireless-based vital sign monitoring and multi-antenna signal processing techniques.

 

Instructions:

download the dataset and run with code (https://gitlab.kuleuven.be/u0149002/bs-breath)