Muammar Sadrawi, B.S., M.S., Ph.D.
Faculty of Bioinformatics
- Department of Bioinformatics
Research Interest
- Non-invasive signal generator
- Human-computer interaction
- Brain-heart interplay
Biography
Dr. Muammar Sadrawi, S.T., M.Sc. acquired his bachelor’s degree in the Department of Mechanical Engineering, Universitas Syiah Kuala, Indonesia, in 2009. He received his master’s and Ph.D. degrees in Mechanical Engineering at Yuan Ze University, Taiwan, in 2013 and 2018, respectively. Dr. Sadrawi has expertise in artificial intelligence (AI) and data science in sensing and condition monitoring systems.
Research Activity and Highlighted Project
| Year | Title | Partners |
|---|---|---|
|
2020-2021 |
Non-Invasive Cardiovascular and Cerebral Hemodynamics |
New Era AI Robotic Inc., Taipei, Taiwan |
|
2020 |
Continuous Blood Pressure Estimation Project |
New Era AI Robotic Inc., Taipei, Taiwan |
|
2016-2017 |
Arrhythmia Detection Development for Wearable System Project |
Kinpo Electronics, Inc., Taipei, Taiwan |
|
2015-2018 |
Emergency Medical Service Big Data Evaluation |
National Taiwan University Hospital (NTUH), Taipei, Taiwan |
|
2015 |
Anesthesia signal processing |
National Taiwan University Hospital (NTUH), Taipei, Taiwan |
Selected Publication
Sadrawi, M., Lin, Y. T., Lin, C. H., Mathunjwa, B., Hsin, H. T., Fan, S. Z., … & Shieh, J. S. (2021). Non-Invasive Hemodynamics Monitoring System Based on Electrocardiography via Deep Convolutional Autoencoder. Sensors, 21(18), 6264. |
Sadrawi, M., Lin, Y. T., Lin, C. H., Mathunjwa, B., Fan, S. Z., Abbod, M. F., & Shieh, J. S. (2020). Genetic deep convolutional autoencoder applied for generative continuous arterial blood pressure via photoplethysmography. Sensors, 20(14), 3829. |
Sadrawi, M., Sun, W. Z., Ma, M. H. M., Yeh, Y. T., Abbod, M. F., & Shieh, J. S. (2018). Ensemble genetic fuzzy neuro model applied for the emergency medical service via unbalanced data evaluation. Symmetry, 10(3), 71. |
Sadrawi, M., Lin, C. H., Lin, Y. T., Hsieh, Y., Kuo, C. C., Chien, J. C., … & Shieh, J. S. (2017). Arrhythmia evaluation in wearable ECG devices. Sensors, 17(11), 2445. |
Sadrawi, M., Fan, S. Z., Abbod, M. F., Jen, K. K., & Shieh, J. S. (2015). Computational depth of anesthesia via multiple vital signs based on artificial neural networks. BioMed research international, 2015. |
