@inproceedings{947,
  author = {Yindong Hua and Zongxing Xie and Fan Ye},
  title = {A Study of Practical Radar-based Nighttime Respiration Monitoring at Home},
  abstract = {Radar-based solutions support practical and longi- tudinal respiration monitoring owing to their non-invasive nature. Nighttime respiration monitoring at home provides rich and high- quality data, mostly free of motion disturbances because the user is quasi-stationary during sleep, and 6-8 hours per day rather than tens of minutes, promising for longitudinal studies. However, most existing work was conducted in laboratory environments for short periods, thus the environment, user motions, and postures can differ significantly from those in real homes. To understand how to obtain quality, overnight respiration data in real homes, we conduct a thorough experimental study with 6 participants of various sleep postures over 9 nights in 4 real-home testbeds, each configured with 3–4 sensors around the bed. We first compare the performance among four typical sensor placements around the bed to understand which is the optimal location for high quality data. Then we explore methods to track range bins with high quality signals as occasional user motions change the distance thus signal qualities, and different aspects of amplitude and phase data to further improve the signal quality using metrics of the periodicity-to-noise ratio (PNR) and end-to-end (e2e) accuracy. The experiments demonstrate that the sensor placement is a vital factor, and the bedside is an optimal choice considering both accuracy and ease of deployment (2.65 bpm error at 80 percentile), also consistent among four typical sleep postures. We also observe that, a proper range bin selection method can improve the PNR by 2 dB at 75-percentile, and e2e accuracy by 0.9 bpm at 80-percentile. Both amplitude and phase data have comparable e2e accuracy, while phase is more sensitive to motions thus suitable for nighttime movement detection. Based on these discoveries, we develop a few simple practical guidelines useful for the community to achieve high quality, longitudinal home- based overnight respiration monitoring.},
  year = {2023},
  journal = {IEEE Radar conference},
  month = {01},
  url = {https://par.nsf.gov/biblio/10439719},
  doi = {10.1109/RadarConf2351548.2023.10149560},
}