Pervasive Cardiovascular and Respiratory Monitoring Devices

Miodrag Bolic received his Ph.D. degree in electrical engineering from Stony Brook University, US, in 2004. Since 2004 he has been with the University of Ottawa, Canada where he is Professor with the School of Electrical Engineering and Computer Science. He is a Director of the Computational Analysis and Health Devices research groups. His current research interests include physics based machine learning and uncertainty quantification for biomedical and autonomous vehicles applications. He has published about 80 journal papers and has 5 patents. He teaches at the graduate level courses on biomedical instrumentation and uncertainty quantification in engineering and machine learning. Prof. Bolic worked on cardiorespiratory monitoring for the last 12 years including both the design of devices and development of signal processing/machine learning algorithms. His work on wearable devices include ECG-assisted oscillometric and BCG-assisted cuffless blood pressure monitoring. His work on contactless monitoring includes breathing and heart rate estimation and breathing pattern classification using RGB, thermal and 3D cameras as well as radars.

Preface Acknowledgments Overview of biomedical instrumentation and devices

1. Concepts in performance evaluation and uncertainty analysis 2. Transducers 3. Electronics 4. Modelling and simulation of biomedical systems 5. Devices based on Oscillometric Signal: Blood pressure 6. Devices based on photoplethysmogram and pulse oximetry 7. Devices based on ECG Signal 8. Devices based on Time Difference between Signals: Continuous Blood Pressure Measurement 9. Continuous monitoring of breathing 10. Wearable devices 11. Conclusions and research Directions: beyond wearable devices