Recent research:
The research focuses on the intersection of biomedical engineering, signal processing, and clinical diagnostics. A significant portion of the work involves computational modeling of cardiac electrophysiology, specifically investigating how anatomical remodeling—such as that induced by intrauterine growth restriction (IUGR)—affects ECG biomarkers and ventricular arrhythmia risk. This includes the development of realistic biventricular models to correlate geometric changes with electrical depolarization and repolarization patterns.

Parallel to cardiac studies, the research explores the processing and analysis of biosignals, including EEG and EMG. This involves evaluating digital filter performance, the impact of audiovisual stimulation on neural oscillations, and the influence of posture and support surfaces on electromyographic recordings in clinical populations, such as those with cerebral palsy. Furthermore, the work emphasizes the development of embedded systems and wearable technology for biomechanical monitoring in sports, such as race walking and weightlifting, as well as the design of mechatronic solutions for upper-limb prosthetics.

Finally, the research addresses the operational reliability of medical technology. This includes establishing methodologies for medical equipment maintenance management, quality control planning, and assessing the impact of equipment downtime in clinical settings. Educational tools and graphical interfaces are also developed to facilitate the study of biosignals and FPGA-based embedded system design.

Key Topics:

• Cardiac Electrophysiology and Computational Modeling
• Biosignal Processing (EEG/ECG/EMG)
• Medical Equipment Maintenance and Reliability
• Wearable Sensors and Biomechanical Monitoring
• Neuromodulation and Cognitive Learning
• Mechatronic Prosthetic Design