Smart Neonatal Monitoring for Tele-Health

With advances in digital stethoscopes, the 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, the low-quality of recordings complicates remote monitoring and diagnosis, particularly for neonatal care. Currently available stethoscopes cannot provide the neonatologists with diagnostic quality heart and breathing sounds, when used for preterm babies. This is due to the weakness of baby's chest sounds, irregular breathing and fast heart rate, interference and noise in the NICU, particularly due to the respiratory support devices and baby's internal body sounds. Our team at Monash BSPL have been working on developing new methods to improve neonatal monitoring by digital stethoscopes, in order to:

• Objectively and automatically assess the signal quality in real-time;

• Separate heart and lung sounds and remove noise and interference

• Accurately estimate vital signs, including heart rate, breathing rate and other related measures

• Predict the occurrence of respiratory distress in babies, as early as 1 minute after birth

• objectively assess lung aeration and lung development over time for preterm babies

• And more to come!

our software is device-agnostic, can be used with any digital stethoscope. A new digital stethoscope is currently under development by our team, to provide a more affordable and low-noise option.

Our team at Monash University:

• Principal Investigator and lab Head: Dr Faezeh Marzbanrad , Electrical and Computer Systems Engineering Department, Monash University.

• Clinical Collaborator: A/Prof Atul Malhotra , Monash Newborn, Monash Children's Hospital and Department of Paediatrics, Monash University

• Postdoctoral Research Fellow: Dr Chiranjibi Sitaula , Electrical and Computer Systems Engineering Department, Monash University.

• PhD student: Ethan Grooby , Electrical and Computer Systems Engineering Department, Monash University.

• Medical team and students: Dr Lindsay Zhou, Arrabella King and Ashwin Ramanathan

Collaborators:

• Prof Guy Dumont, The University of British Columbia (UBC)

• Dr Reza Sameni, Emory University

• A/Prof Ken Tan, Monash Children's Hospital and Department of Paediatrics, Monash University

Our research in funded by:

• Monash Institute of Medical Engineering (MIME)

• Monash Data Future Institute (MDFI)

Publications:

1. Grooby, E., Sitaula, C., Fattahi, D., Sameni, R., Tan, K., Zhou, L., King, A., Ramanathan, A., Malhotra, A., Dumont, G.A. and Marzbanrad, F., 2022. Real-Time Multi-Level Neonatal Heart and Lung Sound Quality Assessment for Telehealth Applications. IEEE Access. Full text

2. Grooby, E., Sitaula, C., Tan, K., Zhou, L., King, A., Ramanathan, A., Malhotra, A., Dumont, G.A. and Marzbanrad, F., 2022. Prediction of Neonatal Respiratory Distress in Term Babies at Birth from Digital Stethoscope Recorded Chest Sounds. [Under Review] arXiv preprint arXiv:2201.10105. Full Text

3. Grooby, E., Sitaula, C., Fattahi, D., Sameni, R., Tan, K., Zhou, L., King, A., Ramanathan, A., Malhotra, A., Dumont, G.A. and Marzbanrad, F., 2022. Noisy Neonatal Chest Sound Separation for High-Quality Heart and Lung Sounds. [Under Review] arXiv preprint arXiv:2201.03211. Full text

4. Grooby, E., He, J., Fattahi, D., Zhou, L., King, A., Ramanathan, A., Malhotra, A., Dumont, G.A. and Marzbanrad, F., 2021, November. A New Non-Negative Matrix Co-Factorisation Approach for Noisy Neonatal Chest Sound Separation. In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 5668-5673). IEEE. Full text

5. Grooby, E., He, J., Kiewsky, J., Fattahi, D., Zhou, L., King, A., Ramanathan, A., Malhotra, A., Dumont, G.A. and Marzbanrad, F., 2020. Neonatal heart and lung sound quality assessment for robust heart and breathing rate estimation for telehealth applications. IEEE Journal of Biomedical and Health Informatics. Full text

6. King, A., Blank, D., Bhatia, R., Marzbanrad, F. and Malhotra, A., 2020. Tools to assess lung aeration in neonates with respiratory distress syndrome. Acta Paediatrica, 109(4), pp.667-678. Full text

7. Zhou, L., Marzbanrad, F., Ramanathan, A., Fattahi, D., Pharande, P. and Malhotra, A., 2020. Acoustic analysis of neonatal breath sounds using digital stethoscope technology. Pediatric pulmonology, 55(3), pp.624-630. Full text

8. Ramanathan, A., Marzbanrad, F., Tan, K., Zohra, F.T., Acchiardi, M., Roseby, R., Kevat, A. and Malhotra, A., 2020. Assessment of breath sounds at birth using digital stethoscope technology. European journal of pediatrics, 179(5), pp.781-789. Full text

9. Zhou, L., Marzbanrad, F., Fattahi, D., King, A. and Malhotra, A., 2020. THE DIGITAL STETHOSCOPE AND COMPUTERISED SOUND ANALYSIS–A NOVEL METHOD FOR EXAMINING NEONATAL BREATH SOUNDS. Medicine, 372(10), pp.933-43.

10. Ramanathan, A., Zhou, L., Marzbanrad, F., Roseby, R., Tan, K., Kevat, A. and Malhotra, A., 2019. Digital stethoscopes in paediatric medicine. Acta Paediatrica, 108(5), pp.814-822. Full text