Recent research:
This portfolio consolidates a multidisciplinary program at the intersection of Biomedical Engineering, Rehabilitation, Prosthetics & Neurotechnology, and intelligent sensing. Across several studies, the author develops and evaluates Brain-Computer Interface (BCI)–driven neurorehabilitation protocols for post-stroke patients, integrating Motor Imagery (MI), Action Observation (AO), Neurofeedback (NFB), and non-invasive stimulation approaches (csDCS, tACS). Robotic augmentation (gloves, monocycle, orthoses) and low-cost EEG/sEMG sensing accompany these protocols to decode neural intentions, track progress with clinical scales (FMA, FIM, NIHSS, MBT, TUG, 10MWT, etc.), and monitor muscle activity. Several works employ advanced signal processing (CSP, FBCSP, RG, PWFP) and classifiers (LDA, SVM, kNN) to achieve robust MI recognition and hand/finger movement control, with notable effectiveness in upper- and lower-limb rehabilitation. Additional projects broaden impact beyond neurorehabilitation: low-cost sensorized systems for vertical jump analysis in sports; integrated portable medical assistants (IPMA) combining ML for worker health surveillance; and evaluative studies of robotic orthoses/exoskeletons using kinematic and sEMG metrics, plus user-satisfaction assessments. A recurring theme is real-time, multimodal data fusion (EEG, sEMG, kinematics, HR, SpO2) and the translation of these signals into assistive interventions, with emphasis on accessibility, usability, and scalability. Overall, the research demonstrates a coherent trajectory toward practical, low-cost, user-centered BCIs and robotic rehabilitation tools that enhance motor recovery, daily functioning, and safety in clinical and athletic contexts. The impact lies in advancing robust, adaptable neurorehabilitation pipelines, validating them across multiple cohorts and settings, and informing clinical adoption through standardized metrics and usability outcomes.
Key Topics:

• Biomedical Engineering, Rehabilitation, Prosthetics & Neurotechnology
• Robotics, Autonomous Systems & Control
• Sensors, Instrumentation & Measurement Systems
• Artificial Intelligence, Machine Learning & Data Science
• BCI/MI/AO/NF for neurorehabilitation
• Non-invasive brain stimulation (csDCS, tACS)
• Lower- and upper-limb rehabilitation robotics
• Clinical evaluation metrics and usability
• Low-cost sensing and accessibility in rehabilitation
• Sports science sensing and performance analytics