Neonatal Heart and Lung Sound Quality Assessment for Robust Heart and Breathing Rate Estimation for Telehealth Applications

• Published in: IEEE journal of biomedical and health informatics Vol. 25; no. 12; pp. 4255 - 4266
• Main Authors: Grooby, Ethan, He, Jinyuan, Kiewsky, Julie, Fattahi, Davood, Zhou, Lindsay, King, Arrabella, Ramanathan, Ashwin, Malhotra, Atul, Dumont, Guy A., Marzbanrad, Faezeh
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.12.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Acoustics; Algorithms; Auscultation; Breath sound; Chest; Classification; Diagnosis; dynamic classifier; Feature extraction; Heart; Heart rate; heart sound; Heart Sounds; Humans; Infant, Newborn; Internet of Things; Learning algorithms; Lungs; Machine learning; neonatal monitoring; Neonates; Neonatology; Newborn babies; Optimization; Phonocardiography; phonocardiography (PCG); Quality assessment; Quality control; Reliability analysis; Remote monitoring; Reproducibility of Results; Respiration; respiration rate; Respiratory Sounds - diagnosis; Sensitivity; Signal processing; Signal quality; Sound; Stethoscope; Stethoscopes; telehealth; Telemedicine

With advances in digital stethoscopes, internet of things, signal processing and machine learning, chest sounds can be easily collected and transmitted to the cloud for remote monitoring and diagnosis. However, low quality of recordings complicates remote monitoring and diagnosis, particularly for n...