ICIEA 2026 Special Session
SS42: Control, Systems, and Signal Processing for Biomedical Applications
Organized by:
Organizer 1: Nacira Laamiri
Email: laamiri.nacira@cck.rnu.tn; naciralaamiri@yahoo.fr
Affiliation: Mohamed Taher Maamouri University Hospital, Tunisia
Organizer 2: Lotfi Chaouech
Email: lotfi.chaouech@essths.u-sousse.tn
Affiliation: University of Tunis, Tunisia
Organizer 3: Jaouher Ben Ali
Email: benali.jaouher@essths.u-sousse.tn
Affiliation: University of Tunis, Tunisia
Advances in control theory, dynamical systems modeling, and signal and information processing are playing a transformative role in modern biomedical research and healthcare technologies. From physiological signal analysis and medical imaging to closed-loop therapeutic systems and intelligent monitoring platforms, system-level approaches are enabling more precise, adaptive, and reliable healthcare solutions. The rapid advancement of control systems, signal processing, and computational intelligence has significantly influenced the evolution of modern biomedical research and healthcare technologies. Biological systems are inherently complex, nonlinear, and dynamic, requiring sophisticated modeling, estimation, and control strategies to better understand physiological mechanisms and improve clinical outcomes. At the same time, the increasing availability of high-resolution biomedical signals and medical imaging data has created new opportunities for data-driven and system-theoretic approaches. The session will encourage submissions that integrate computational intelligence, control theory, and signal processing to address real-world healthcare challenges. Each paper will be evaluated on scientific merit, methodological rigor, and potential clinical impact.
This special session aims to bring together researchers and practitioners working at the intersection of control systems, signal processing, computational intelligence, and biomedical engineering. The session will explore novel methodologies for modeling biological systems, analyzing complex biomedical signals, designing robust control strategies for medical devices, and integrating AI-driven information processing techniques into healthcare applications.
By fostering interdisciplinary collaboration, this session seeks to highlight innovative frameworks that bridge engineering methodologies with biomedical applications, ultimately contributing to safer, smarter, and more personalized healthcare systems.
Recent developments in machine learning and AI have further enhanced the ability to extract meaningful information from complex biomedical datasets. However, many healthcare challenges still require robust control frameworks, interpretable models, real-time processing capabilities, and reliable system integration. Bridging control theory, systems engineering, and signal and information processing with biomedical applications is therefore essential for developing safe, adaptive, and clinically deployable solutions.
This special session is justified by the growing demand for interdisciplinary platforms that connect researchers in control, signal processing, AI, and biomedical engineering. It aims to foster collaboration, highlight methodological innovations, and address practical challenges in translating theoretical advances into impactful healthcare technologies. By providing a focused forum on this intersection, the session will contribute to advancing next-generation intelligent biomedical systems.
The proposed special session will feature high-quality research papers focusing on the intersection of control systems, signal processing, and biomedical applications. The session will include contributions that highlight both theoretical innovations and practical implementations in healthcare, medical devices, and biological research.
Expected topics include, but are not limited to: