Recent research:
Across publications, the author advances machine-assisted biomedical engineering and neurorehabilitation with a strong emphasis on practical instrumentation, electrophysiology, and computational modeling to understand and enhance human health and performance. Core work reveals how anatomical remodeling (notably in intrauterine growth restriction, IUGR) alters cardiac electrical patterns, such as QRS duration and T-wave intervals, and how these changes relate to ventricular arrhythmia risk through both clinical ECG analysis and in silico heart-torso models. Parallel efforts develop and validate maintenance and measurement frameworks for medical devices in clinical settings, highlighting operator training, incident analysis, and the deployment of standardized benchmarking to improve reliability and patient safety. Additional research demonstrates practical educational and rehabilitation tools: EEG-based learning modulation via binaural stimuli, Matlab-based biosignal analysis interfaces for students, embedded sensor systems for sport biomechanics (weightlifting and race walking), and cervical spine energy studies under varying support surfaces in cerebral palsy. Together, the work integrates data-driven analytics, embedded sensing, and computational simulations to inform clinical practice, education, and athletic training, with impact in cardiovascular risk assessment, equipment reliability, and performance monitoring.

Key Topics:

• Biomedical Engineering, Rehabilitation, Prosthetics & Neurotechnology
• Computer Vision, Medical Imaging & Signal Processing
• Sensors, Instrumentation & Measurement Systems
• Healthcare, Clinical Epidemiology & Public Health
• Standards, Validation, Benchmarks & Measurement Best-Practice
• Education, Pedagogy, Teacher Training & Inclusion
• Educational Technology, Gamification, XR & Learning Analytics