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Welcome to the Biomedical Signal Processing Research Lab

Department of Electrical and Computer Systems Engineering

Our Research

Our research focuses on medical devices, particularly applications of advanced signal processing, machine learning and physiological modelling to develop affordable and reliable healthcare technologies, towards saving lives and reducing healthcare costs. Aiming to minimise the current and future burden of diseases, our research is applied in cardiovascular and respiratory health fields, maternal, foetal and neonatal health, diabetes, mental health, prevention of road accidents and MORE!

A list of available final year projects (FYP) can be found here (internal access only).


  • 8 Sep 2022  Our team team won the third prize in international George B. Moody PhysioNet Challenge 2022 in the outcome category! Over 300 entries were submitted by over 60 teams and this was a great achievement. Congratulations to our wonderful team, FYP student Zaria Imran and PhD student Ethan Grooby, post doc Chiranjibi Sitaula and our collaborators from Deakin!
  • 21 Jul 2022  Congratulations to our summer research student Samin Haque who received runner-up award for best presentation at The Undergraduate Research Opportunities Program (UROP) Conference at CSIRO. Well Done Samin!
  • 10 Jun 2022  Faezeh Marzbanrad received Dean's Award for Honours supervision from Faculty of Engineering.
  • 27 May 2022  Congratulations to our PhD student Emma Perkins on receiving 2022 Nancy Millis Bursary from Graduate Women Victoria. Emma was the only female student in Maths and Physics classes in her school in rural Victoria. She is now a biomedical engineer and an advocate for women in engineering. She has been volunteering in various clubs working with female students to reduce the hesitancies for girls to study engineering.
  • 28 Apr 2022 Faezeh marzbanrad is awarded Women Leading Tech award, in Education and Research category.
  • 17 Mar 2022  In an interview with Times Higher Education, Fae shared her perspective on a few topics related to her academic journey, research and gender diversity in engineering, in Iran and Australia.
  • 25 Feb 2022  Our summer research student Gretel Gibson-Bourke received the best 3-minute presentation award and the people's choice award in the faculty-wide summer research program competitions today.
  • 1 Feb 2022 Today Herald Sun published an article about our research on developing AI to improve neonatal cardio-respiratory monitoring with digital stethoscopes. our research aims to improve neonatal health, especially for preterm babies and those with cardiac and/or respiratory conditions. It is affordable and less specialised so that it could be used in low resource settings, rural and remote regions through Tele-Health. (More about our research in this field and publications can be found here.)
  • 14 Dec 2021 Faezeh Marzbanrad was awarded the 2021 Victoria Fellowship by Veski on behalf of the Victorian Government, for her work on mobile health technologies and foetal health monitoring systems aimed at reducing stillborn births and maternal high mortality rates in rural and remote communities.
  • 14 Nov 2021   Congratulations to our PhD student Ethan Grooby, for receiving the second prize in the IEEE Victorian Section Student Paper Competition, for his paper "A New Non-Negative Matrix Co-Factorisation Approach for Noisy Neonatal Chest Sound Separation".
  • 30  Apr 2021   BSPL welcomes  Dr Chiranjibi Sitaula who is joining our team as a research fellow.
  • 7 Apr 2021    BSPL welcomes Dr Yuxin Zhang, who just joined our team as a postdoctoral research fellow, working on "Fetal Kicks" research funded by NHMRC Ideas grant.
  • 26 Feb 2021    congratulations to PhD student Ethan Grooby on receiving 2021 MedTech Actuator Menzies Scholarship. It is well deserved for his outstanding achievements and passion for med-tech innovation for neonatal health.
  • 22 Feb 2021     BSPL welcomes Emma Perkins who just started her PhD on detecting driver drowsiness using a hybrid detection scheme.
  • 15 Dec 2020    Delighted to receive an NHMRC Ideas grant ($1M) for our research on "soft wearable patches for stillbirth prevention" led by Prof Wenlong Cheng, in collaboration with Prof Jonathan Morris, Dr William Yap, Dr Vin Smith and Prof Euan Wallace. We aim to develop AI-powered soft wearable patches for out-of-hospital fetal monitoring to help prevent stillbirths.
  • 27 Nov 2020    PhD student Ethan Grooby received the 2nd best poster prize in Tri-University workshop.

Our Team

We have a vibrant research team of undergraduate and post graduate students, interns and research assistants.

Lab Head:

Photo of Faezeh Marzbanrad

Dr Faezeh Marzbanrad (Fae) joined Monash University in June 2016, after completing her PhD in Electrical and Electronic Engineering at the University of Melbourne. Her PhD was supported by IPRS and APA scholarships funded by Australian Government. During her PhD she received several awards including the Len Stevens scholarship from University of Melbourne in 2014, student paper award from IEEE Australia council in 2014, and the finalist award of the student paper competition at IEEE Engineering in Medicine and Biology Conference (EMBC 2014) in Chicago, IL, USA. She also received Mortara fellowship in September 2017 and honorable mention for Rosanna Degani Young Investigator Award in both 2015 and 2016, from Computing in Cardiology. In 2021, she was awarded the prestigious Veski Victoria Fellowship by the Victorian Government. She is also the winner of B&T Women Leading Tech Award 2022, in the Education/Research category. In 2022, Fae received the Dean's Award for Honours Supervision.

Her research interests include medical technology for health equity, biomedical signal processing and machine learning, artificial intelligence in health, affordable medical devices, mobile-health as well as fetal, maternal and neonatal healthcare technologies.

Academic Profile:

Research fellows:

1- Dr  Chiranjibi Sitaula (2021 - present)

2- Dr Yuxin Zhang (2021 - present)

3- Dr Fatemeh Babaeian (2020 - present)

4- Dr Jinyuan (Sam) He (2020)

PhD students:

1- Emma Perkins (2021 to present), "Detecting driver drowsiness using a hybrid detection scheme".

2- Ethan Grooby (2020 to present), "Affordable and portable audio-visual system for neonatal health
monitoring". (Monash-UBC PhD)

3- Yunzhi Ling (2016 to 2019 - graduated), "A flexible, transparent and multiple stimuli electronic skin consisting of nanopaper and nanocopper for physiological monitoing", Jointly supervised with Prof Wenlong Cheng (Monash Chem Eng).

Masters students:

1- Wenqi Cai (2017), "Automated diagnosis of digital breath sounds".

Undergraduate students (FYP)

30+ FYP students have been working in this research group on various projects, including smart wearable devices for physiological monitoring, drowsiness detection devices, interactive virtual reality-based systems and affordable mobile-health systems for cardiovascular and mental health, etc.


  • Sasha Jain and Merry Le won the runner-up award at SPARK Night 2017 for their outstanding work: "DriveMate: A drowsiness detection and alert system for drivers"..

Research interns:

  1. Julie Kiewsky (Jun-Sep 2019), ENSEIRB-MATMECA, France, "Analysis of breath sounds in preterm neonates with respiratory distress syndrome".
  2. Davood Fattahi (Mar-Sep 2019), Shiraz University, Iran, "Analysis and characterisation of chest sounds for cardio-respiratory monitoring of preterm neonates".
  3. Mathieu Acchiardi (Jun-Sep 2018), ENSEIRB-MATMECA, France, "Automated assessment of neonatal breath sound".
  4. Benjamin Wu (Nov 2017- Feb 2018), summer research intern, Monash University.
    • Benjamin received People's Choice Award at the faculty-wide competition, for his outstanding work and presentation: "Touching the Sound: Sensory Substitution Rings for the Hearing Impaired".
  5. Negin Yaghmaei (Jul-Sep 2017), Sharif University of Technology, Iran, "Automated Quality Assessment of Physiological Signals".
  6. Matthieu Da Silva Filarder (Feb-Jul 2017), ENSEIRB-MATMECA, France, "Detecting Atrial Fibrillation from a Short Single Lead ECG Recording".

Open PhD positions:

I am looking for high calibre engineering students to join our team. Applicants must meet the university’s academic and English language requirements to apply for the PhD program. If eligible and interested, you are encouraged to complete the Expression of Interest(EOI) form.


Recent Publications

Book Chapter:

  1. F. Marzbanrad, Y. Kimura, M. Palaniswami, et al., ”Fetal Heart Rate Variability”. ECG Time Series Variability Analysis: Engineering and Medicine, 18, CRC Press, ISBN 9781482243475, 2017.

Journal Papers:

  1. C. Sitaula, J. He, A. Priyadarshi, M. Tracy, O. Kavehei, M. Hinder, A. Withana, A. McEwan, F. Marzbanrad, "Neonatal Bowel Sound Detection Using Convolutional Neural Network and Laplace Hidden Semi-Markov Model",  IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2022.
  2. D. Fattahi, R. Sameni, E. Grooby, K. Tan, L. Zhou, A. King, A. Ramanathan, A. Malhotra and F. Marzbanrad, "A Blind Filtering Framework for Noisy Neonatal Chest Sounds" IEEE Access, 2022.
  3. S. Gong, L.W. Yap, Y. Zhang,J. He, J. Yin, F. Marzbanrad, D.M. Kaye, and W. Cheng "A gold nanowire-integrated soft wearable system for dynamic continuous non-invasive cardiac monitoring" Biosensors and Bioelectronics, 205, p.114072, 2022.
  4. E. Grooby, C. Sitaula, D. Fattahi, R. Sameni, K. Tan, L. Zhou, A. King, A. Ramanathan, A. Malhotra, GA. Dumont, F. Marzbanrad "Real-Time Multi-Level Neonatal Heart and Lung Sound Quality Assessment for Telehealth Applications" IEEE Access, 2022.
  5. C. Sitaula, T. Bahadur Shahi, S. Aryal, and F. Marzbanrad. "Fusion of multi-scale bag of deep visual words features of chest X-ray images to detect COVID-19 infection" Scientific reports 11, no. 1: 1-12, 2021.
  6. A. Adami, R. Boostani, F. Marzbanrad, P.H. Charlton "A New Framework to Estimate Breathing Rate From Electrocardiogram, Photoplethysmogram, and Blood Pressure Signals" IEEE Access, 9, 45832-45844, 2021.
  7. A. H. Khandoker, H. M. Al-Angari, F. Marzbanrad, Y. Kimura "Investigating myocardial performance in normal and sick fetuses by abdominal Doppler signal derived indices" Current Research in Physiology, 4, 29-38, 2021.
  8. E. Grooby, J. He, J. Kiewsky, D. Fattahi, L. Zhou, A. King, A. Ramanathan,A. Malhotra, G. A. Dumont, F. Marzbanrad "Neonatal heart and lung sound quality assessment for robust heart and breathing rate estimation for telehealth applications" IEEE Journal of Biomedical and Health Informatics, Accepted, Dec 2020.
  9. A. C. Kevat, F. Marzbanrad, R. Roseby "Making digital auscultation accessible and accurate" Pediatric Pulmonology, 2020.
  10. F. Marzbanrad, N. Yaghmaie, and H. F. Jelinek "A framework to quantify controlled directed interactions in network physiology applied to cognitive function assessment." Scientific Reports 10.1: 1-13, 2020.
  11. C. E. Valderrama, N. Katebi, F. Marzbanrad, P. Rohloff, and G. D. Clifford. "A review of fetal cardiac monitoring, with a focus on low-and middle-income countries." Physiological Measurement, 2020.
  12. N. Katebi, F. Marzbanrad, L. Stroux, C. E. Valderrama, and G. D. Clifford. "Unsupervised hidden semi-Markov model for automatic beat onset detection in 1D Doppler ultrasound." Physiological Measurement 41, no. 8: 085007, 2020.
  13. C. E. Valderrama, F. Marzbanrad, M. Juarez, R. Hall-Clifford, P. Rohloff and G. D. Clifford, "Estimating birth weight from observed postnatal weights in a Guatemalan highland community", Physiological Measurement,  2020.
  14. L. Zhou, F. Marzbanrad, A. Ramanathan, D. Fattahi, P. Pharande and A. Malhotra, "Acoustic analysis of neonatal breath sounds using digital stethoscope technology", Pediatric Pulmonology,  2020.
  15. A. Ramanathan, F. Marzbanrad, K. Tan, F.T. Zohra, M. Acchiardi, R. Roseby, A. Kevat and A. Malhotra "Assessment of breath sounds at birth using digital stethoscope technology", European Journal of Pediatrics, 1-9,  2020.
  16. S. Gong, L.W. Yap, B. Zhu, Q. Zhai, Y. Liu, Q. Lyu, K. Wang, M. Yang, Y. Ling, D.T. Lai, F. Marzbanrad and W. Cheng "Local Crack‐Programmed Gold Nanowire Electronic Skin Tattoos for In‐Plane Multisensor Integration", Advanced Materials 31 (41), 1903789,2019.
  17. A. King, D. Blank, R. Bhatia, F. Marzbanrad and A. Malhotra, "Tools to assess lung aeration in neonates with respiratory distress syndrome", Acta Paediatrica,2019.
  18. A. Ramanathan, L. Zhou, F. Marzbanrad, R. Roseby, K. Tan, A. Kevat and A. Malhotra, "Digital stethoscopes in paediatric medicine", Acta Paediatrica, 108(5), pp.814-822, 2019.
  19. C. E. Valderrama, L. Stroux, N. Katebi, E. Paljug, R. Hall-Clifford, P. Rohloff, F. Marzbanrad and G. D. Clifford, "An open source autocorrelation-based method for fetal heart rate estimation from one-dimensional Doppler ultrasound", Physiological measurement, 40(2), p.025005, 2019.
  20. N. Yaghmaie, M. A. Maddah-Ali, H. F. Jelinek and F. Mazrbanrad, "Dynamic signal quality index for electrocardiograms", Physiological measurement, 39(10), p.105008, 2018.
  21. F. Marzbanrad, L. Stroux, and G. D. Clifford. "Cardiotocography and beyond: a review of one-dimensional Doppler ultrasound application in fetal monitoring." Physiological measurement 39.8 (2018): 08TR01.*Featured article*
  22. A. H. Khandoker, F. Marzbanrad, and Y. Kimura. "Recent Advances in Doppler Signal Processing and Modelling Techniques for Fetal Monitoring." Frontiers in Physiology 9 (2018): 691.
  23. C. V. Cuadros, F. Marzbanrad, L. Stroux, et al., “Template-based Quality Assessment of the Doppler Ultrasound Signal for Fetal Monitoring”, Frontiers in Physiology , 8: 511, 2017.
  24. F. Marzbanrad, A. H. Khandoker, Y. Kimura, et al., “Assessment of Fetal Development Using Cardiac Valve Intervals”, Frontiers in Physiology, 8:313, 2017.
  25. F. Marzbanrad, A. Khandoker, B. Hambly, et al., “Methodological comparisons of heart rate variability analysis in genotyped diabetic patients”, IEEE Journal of Biomedical and Health Informatics, vol.20, no.1, pp.55-63, 2016.
  26. A. Khandoker, F. Marzbanrad; A. Voss, et al., “Analysis of Maternal-Fetal Heart Rate Coupling Directions with Partial Directed Coherence”. Journal of Biomedical Signal Processing and Control, 30, pp. 25-30, 2016.
  27. F. Marzbanrad, Y. Kimura, M. Palaniswami, et al., “Quantifying the Interactions between Maternal and Fetal Heart Rates by Transfer Entropy”. PLoS One, 10.12, 2015.
  28. F. Marzbanrad, Y. Kimura, K. Funamoto, et al., “Model based Estimation of Aortic and Mitral valves Opening and Closing Timings in Developing Human Fetuses”. IEEE Journal of Biomedical and Health Informatics, vol.20, no.1, pp.240-248, 2014.
  29. F. Marzbanrad, Y. Kimura, K. Funamoto, et al., “Automated estimation of fetal cardiac timing events from Doppler ultrasound signal using hybrid models,” IEEE Journal of Biomedical and Health Informatics, vol.18, no.4, pp.1169-1177, 2013. *Featured article*

Conference Papers:

  1. E. Grooby, C. Sitaula, K. Tan, L. Zhou, A. King, A. Ramanathan, A. Malhotra, G.A. Dumont, and F. Marzbanrad. "Prediction of Neonatal Respiratory Distress in Term Babies at Birth from Digital Stethoscope Recorded Chest Sounds." International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, 2022.
  2. E. Grooby, J. He, D. Fattahi, L. Zhou, A. King, A. Ramanathan, A. Malhotra, GA. Dumont, and F. Marzbanrad. "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, 2021.
  3. CE. Valderrama, F. Marzbanrad, L. Stroux, et al., "Improving the Quality of Point of Care Diagnostics with Real-Time Machine Learning in Low Literacy LMIC Settings", ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS), 2018.
  4. F. Marzbanrad, G. Clifford, “Analyzing Fetal and Maternal Cardiorespiratory Interactions During Labor”, Computing in Cardiology Conference (CinC), 2017.
  5. R. Whitsed, A. Horta, F. Marzbanrad, et al., “Spatial Characterization of Hypertension Clusters using a Rural Australian Clinical Database”, Computing in Cardiology Conference (CinC), 2017.
  6. R. Allami, A. Stranieri, HF. Jelinek, F. Marzbanrad, et al., “Atrial Fibrillation Analysis for Real Time Patient Monitoring”, Computing in Cardiology Conference (CinC), 2017.
  7. M. Da Silva--Filarder, F. Marzbanrad, “Combining Template-based and Feature-based Classification to Detect Atrial Fibrillation from a Short Single Lead ECG Recording”, Computing in Cardiology (CinC ), 2017.
  8. S. Maleki, F. Marzbanrad, P. Warner and HF. Jelinek, "Use of Heart Rate Variability Infographics in Identification of Depression Status Complementing the Patient Health Questionnaire-9", IEEE Life Sciences Conference (LSC), 2017.
  9. F. Marzbanrad, C. Karmakar, A. Khandoker, et al., “The Influence of Pharmacological Autonomic Blockades on Multi-Scale Measures of Heart Rate Variability”. European Medical and Biological Engineering Conference (EMBEC), 2017.
  10. A. Khandoker, H. Alangari, F. Marzbanrad, et al., “Investigating fetal myocardial function in heart anomalies by Doppler myocardial performance indices”. IEEE Engineering in Medicine and Biology Society Conference (EMBC), 2017.
  11. F. Marzbanrad, A. H. Khandoker, Y. Kimura, et al., ”Estimating Fetal Gestational Age Using Cardiac Valve Intervals”. Computing in Cardiology Conference (CinC), 11-14 Sep 2016.
  12. A. H. Khandoker, F. Marzbanrad, Y. Kimura, et al., ”Assessing the development of fetal myocardial function by a novel Doppler myocardial performance index”. IEEE Engineering in Medicine and Biology Society Conference (EMBC), 2016.
  13. F. Marzbanrad, M. Endo, Y. Kimura,  et al.,  “Transfer Entropy Analysis of Maternal and Fetal Heart Rate Coupling”, IEEE  Engineering in Medicine and Biology Conference EMBC 2015.
  14. F. Marzbanrad, A. Khandoker, et al., “Classification of Doppler Ultrasound Signal Quality for the Application of Fetal Valve Motion Identification”, Computing in Cardiology (CinC), 2015.
  15. F. Marzbanrad, A. Khandoker, M. Endo, et al., “A Multi-dimensional Hidden Markov Model Approach to Automated Identification of Fetal Cardiac Valve Motion”, IEEE Engineering in Medicine and Biology Conference EMBC 2014, pp.1885-1888.
  16. F. Marzbanrad, Y. Kimura, M. Palaniswami, et al., “Application of Automated Fetal Valve Motion Identification to Investigate Fetal Heart Anomalies”. IEEE EMBS Healthcare Innovation Conference (HIC), 2014 IEEE , vol., no., pp.243-246, 2014. doi: 10.1109/HIC.2014.7038920
  17. F. Marzbanrad, Y. Kimura, M. Endo, et al., “Automated measurement of fetal Isovolumic Contraction Time from Doppler ultrasound signal without using fetal electrocardiography”, Computing in Cardiology Conference (CinC), 2014 , vol., no., pp.485-488, 2014.
  18. F. Marzbanrad, B. Hambly, E. Ng, et al., “Relationship Between Heart Rate Variability and Angiotensinogen Gene Polymorphism in Diabetic and control individuals”, IEEE  Engineering in Medicine and Biology Conference EMBC 2014, pp. 6683-6686.
  19. F. Marzbanrad, Y. Kimura, K. Funamoto, et al., “Development of fetal cardiac intervals throughout 16 to 41 weeks of gestation,” In Computing in Cardiology (CinC), 2013.
  20. F. Marzbanrad, HF. Jelinek, E. Ng, et al., “The effect of automated preprocessing of RR interval tachogram on discrimination capability of Heart Rate Variability parameters,” In Computing in Cardiology Conference (CinC), 2013, pp. 483-486. IEEE, 2013.
  21. F. Marzbanrad, A. H. Khandoker, K. Funamoto,  et al., “Automated Identification of fetal cardiac valve timings,” In Engineering in Medicine and Biology Society (EMBC), 35th Annual International Conference of the IEEE, pp. 3893-3896. IEEE, 2013.
  22. Q. Wang, A. H. Khandoker, F. Marzbanrad, et al., “Investigating the beat by beat phase synchronization between maternal and fetal heart rates,” In Engineering in Medicine and Biology Society (EMBC), 35th Annual International Conference of the IEEE, pp. 3821-3824. IEEE, 2013.

Contact us

For any inquiries please contact Dr Faezeh Marzbanrad at:

+61 3 9905 1893

Room 225, 14 Alliance Lane, Clayton 3800 VIC

Department of Electrical and Computer Systems Engineering

Monash University