Institute Mines-Télécom, France
University Montpellier 2, France
A*STAR Research Attachment Programme (ARAP)
- Jit Biswas: Information Systems Technology and Design, Science, Singapore University of Technology and Design, Singapore
- Zhang Haihong: Neural and Biomedical Technology Department, Institute for Infocomm Research, Singapore
- Mounir Mokhtari: Institut Mines-Télécom, France
In 2010, I received a B.Sc. in biomedical engineering from biomedical engineering dept., Helwan university, Egypt. In 2014, I received an Erasmus Mundus joint master degree in computer vision and robotics (VIBOT).
During my master, I've attended three different universities. i.e., university of burgundy (Dijon, France), university of Girona (Girona, Spain), and heriot watt university (Edinburgh, Scotland). I've done my master thesis at Le2i, UMR CNRS 6303, university of burgundy (Dijon, France).
I received the Robert F. Wagner All Conference Best student paper award for my paper "Automatic Discrimination of Color Retinal Images Using the Bag of Words Approach" published at SPIE medical imaging conference on computer aided diagnosis, February 2015. Orlando - Florida USA.
My PhD research work focuses on continuous and unobtrusive vital signs monitoring in ambient assisted living.
The idea is to measure human vital signs such as heart rate and respiratory rate using a mat with embedded microbend fiber optic sensors.
The microbend fiber optic sensor is a suitable candidate for noninvasive and unconstrained monitoring, because of its high sensitivity to the ballistic forces experienced by the body as the heart periodically expels blood into the aorta during the ventricular cycle. The sensor is also attractive because of its lower price.
Due to body movements, respiratory efforts, and environmental noise the signal quality might be disrupted. Therefore, the main objective of the work is to design a generic and robust signal processing tool to cancel related noise and thereafter to measure human vital signs.
- Biomedical Signal Processing, Medical Image Analysis, Machine Learning, Pattern Recognition
- Non-Invasive, Non-Wearable Sensors, Pervasive Computing
- Vital Signs, Monitoring, Ballistocardiogram, Denoising
- Novel Unobtrusive Mattress Sensor towards the Detection of Obstructive Sleep Apnoea – A Comparison with Home Sleep Apnoea Testing Devices