Time-domain Features of Angular-velocity Signals for Camera-based Respiratory RoI detection: A Clinical Study in NICU

Yongshen Zeng1; Xiaoyan Song2; Jie Yang2; Wenjin Wang1

10.1109/EMBC40787.2023.10340063

2023

45th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

2375-7477

1558-4615

979-8-3503-2448-8

2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

1-6

24-27 July 2023

Sydney, Australia

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Camera-based measurement of respiratory rate (RR) is emerging for preterm infants monitoring in Neonatal Intensive Care Units (NICU). Accurate detection of respiratory region of interest (Resp-RoI), e.g. thorax and abdomen of infants, is essential for achieving a fully-automatic solution and for high-quality RR estimation. However, the application of fast Fourier transform (FFT) for detecting Resp-RoI in premature infants may not be appropriate due to their irregular breathing patterns. This study proposes a new method for detecting Resp-RoIs in premature infants that uses time-domain features of angular-velocity of respiration. By fusing respiratory motion on orthogonal directions, the proposed method is more robust to variations of infant posture in the incubator.. In addition, using inter-beat interval (IBI) features in the time domain helps to distinguish between Resp-RoI and background. The proposed method was validated on 20 preterm infants in NICU. It obtains a clear improvement on Resp-RoI detection (RoI correspondence = 0.74) and RR estimation (MAE = 3.62 bpm) against the benchmarked approaches (maxFFT: RoI correspondence = 0.45, MAE = 5.61 bpm).

Respiration camera NICU region of interest

第一

英语

EI ; CPCI-S

National Key R&D Program of China[2022YFC2407800]

Computer Science ; Engineering

Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical

WOS:001133788300119

20240215361459

Cameras ; Fast Fourier transforms ; Feature extraction ; Image segmentation ; Intensive care units ; Time domain analysis

Hospitals, Equipment and Supplies:462.2 ; Photographic Equipment:742.2 ; Mathematics:921 ; Mathematical Transformations:921.3

IEEE

1.Department of Biomedical Engineering, Southern University of Science and Technology, China
2.Neonatal Intensive Care Unit, Nanfang Hospital of Southern Medical University, China

Yongshen Zeng,Xiaoyan Song,Jie Yang,et al. Time-domain Features of Angular-velocity Signals for Camera-based Respiratory RoI detection: A Clinical Study in NICU[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:1-6.