Joseph AZAR : "Data compression and deep learning for IoT healthcare applications based on physiological signals"

PhD works of Joseph Azar : "Data compression and deep learning for IoT healthcare applications based on physiological signals"

Abstract : In recent years, Internet of Things (IoT) technology has gained tremendous attention for its ability to relieve the burden on healthcare caused by an aging population and the increase in chronic disease. IoT technology facilitates the tracking of
patients with different conditions and the processing of vast volumes of data, of which a substantial part of this data are physiological signals. Physiological signals are an invaluable source of data which helps to diagnose, rehabilitate, and treat diseases. The signals come from a Wireless Body Sensor Network or wearable devices placed on a patient's body. There are many difficulties in IoT-healthcare systems, such as data collection and processing especially that (1) wireless sensor nodes
have limited energy, processing and memory resources, (2) the quantity of data collected periodically is enormous, (3) thequality of the data collected is not always satisfactory, and that such data are highly likely to include noisy or unreliable areas,
and (4) the manual feature extraction process from the physiological signals requires significant human intervention and medical expertise. Firstly, an energy-efficient data compression technique is being proposed in this dissertation. The proposed
scheme is based on an error-bound lossy compressor originally designed for high-performance computing applications and has been adapted for IoT devices that are resource constrained. The proposed solution is an easy-to-implement algorithm, which
could reduce energy consumption by as much as 2.5 times. It also reduces the processing/transmission time by compressing large batches of data before their transfer from the IoT to the edge.. [...]

Jury Composition : 

1. Raphaël COUTURIER PR, Université Bourgogne - Franche-Comté, PhD Director
2. Abdallah MAKHOUL Professeur, Université Bourgogne - Franche-Comté, PhD Co-director
3. Germain FORESTIER Professeur, Université de Haute-Alsace – Mulhouse, Reporter
4. David ELIZONDO Professeur De Montfort University – Leicester, Reporter
5. Mme Amal EL FALLAH SEGHROUCHNI, Professeur, Sorbonne Université – Paris, Reviewer
6. Jacques DEMERJIAN, Professeur, Université Libanaise, Reviewer
7. Christophe GUYEUX, Professeur des Universités, Université Bourgogne Franche-Comté, Reviewer

Localization : Amphithéâtre 4 - IUT Belfort-Montbéliard - 19, Avenue du Maréchal Juin - 90000 Belfort