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).
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1109/EMBC40787.2023.10340063 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A novel adaptive lightweight multimodal efficient feature inference network ALME-FIN for EEG emotion recognition.
Cogn Neurodyn
December 2025
School of Mechatronical Engineering, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100081 China.
Enhancing the accuracy of emotion recognition models through multimodal learning is a common approach. However, challenges such as insufficient modal feature learning in multimodal inference and scarcity of sample data continue to pose obstacles that need to be overcome. Therefore, we propose a novel adaptive lightweight multimodal efficient feature inference network (ALME-FIN).
View Article and Find Full Text PDFNeural decoding reveals dynamic patterns of visual chunk memory processes.
Brain Res Bull
January 2025
Centre for Cognitive and Brain Sciences, University of Macau, Macau SAR, China; Faculty of Health Sciences, University of Macau, Macau SAR, China. Electronic address:
Chunk memory constitutes the basic unit that manages long-term memory and converts it into immediate decision-making processes, it remains unclear how to interpret and organize incoming information to form effective chunk memory. This paper investigates electroencephalography (EEG) patterns from the perspective of time-domain feature extraction using chunk memory in visual statistical learning and combines time-resolved multivariate pattern analysis (MVPA). The GFP and MVPA results revealed that chunk memory processes occurred during specific time windows in the learning phase.
View Article and Find Full Text PDFEnhancing prosthetic hand control: A synergistic multi-channel electroencephalogram.
Wearable Technol
November 2024
Embedded Systems and Robotics Lab, Tezpur University, Tezpur, Assam, India.
Electromyogram (EMG) has been a fundamental approach for prosthetic hand control. However it is limited by the functionality of residual muscles and muscle fatigue. Currently, exploring temporal shifts in brain networks and accurately classifying noninvasive electroencephalogram (EEG) for prosthetic hand control remains challenging.
View Article and Find Full Text PDFAECuration: Automated event curation for spike sorting.
J Neural Eng
January 2025
Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania, 15213, UNITED STATES.
Spike sorting is a commonly used analysis method for identifying single-units and multi-units from extracellular recordings. The extracellular recordings contain a mixture of signal components, such as neural and non-neural events, possibly due to motion and breathing artifacts or electrical interference. Identifying single and multi-unit spikes using a simple threshold-crossing method may lead to uncertainty in differentiating the actual neural spikes from non-neural spikes.
View Article and Find Full Text PDFA Novel Real-Time Threshold Algorithm for Closed-Loop Epilepsy Detection and Stimulation System.
Sensors (Basel)
December 2024
The Department of Information Systems and Computer Science, Ateneo de Manila University, Quezon City 1108, Philippines.
Epilepsy, as a common brain disease, causes great pain and stress to patients around the world. At present, the main treatment methods are drug, surgical, and electrical stimulation therapies. Electrical stimulation has recently emerged as an alternative treatment for reducing symptomatic seizures.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!