Robjona Toska
Postgraduate Research Fellow
Politecnico di Torino,
Control and Computer Engineering Department
Robjona Toska was a Postgraduate Research Fellow at the Department of Control and Computer Engineering (DAUIN) of Politecnico di Torino.
Her research focused on analyzing inertial sensor data to quantitatively assess motor symptoms in Parkinson’s disease, combining biomedical signal processing and data analysis. Her work aimed to develop objective, technology-based markers for clinical evaluation.
Bachelor and Master
Robjona Toska obtained her B.Sc. (2019-2022) and M.Sc. (2022–2025, cum laude) degrees in Biomedical Engineering from Politecnico di Torino, specializing in Biomedical Instrumentation. Throughout her studies, she developed a strong interest in biomedical signal processing, machine learning, and neurotechnology applications. She was passionate about developing translational tools that bridge clinical and engineering research, ultimately improving patients’ quality of life.
Her Master’s thesis, “Visual Adaptation Strategies under Simulated Central Vision Loss using Eye-Tracking in Augmented Reality”, explored compensatory oculomotor mechanisms under simulated central scotoma. She designed and implemented an augmented reality application for Microsoft HoloLens 2 to induce gaze-contingent visual distortions and developed experimental tasks to assess reading and visual search performance. The study combined hardware–software integration, eye-tracking analysis, and experimental validation on 33 participants.
Working Experience and Research Activities
Robjona was a Postgraduate Research Fellow at the Department of Control and Computer Engineering (DAUIN) of Politecnico di Torino, in collaboration with Molinette Hospital. Her research focused on analyzing inertial sensor signals from Parkinson’s disease patients during motor tasks. The project aimed to investigate correlations between clinical scales and quantitative motion features derived from accelerometers and gyroscopes, employing signal fusion and filtering techniques to robustly extract features.
Robjona is an inducted member of the IEEE-HKN Mu Nu Chapter.