Multimodal Cardiovascular and Motor Assessment in Parkinson's Disease

Speaker:  Prof. Guadalupe Dorante Mendez

15 Aprile 2026 | 17:30
DEIB, Sala Seminari "A. Alario" (Ed. 21)

Contatti: Prof. Manuela Ferrario

Sommario

On April 15^th, 2026, at 5:30 pm Prof. Guadalupe Dorante Mendez, will give a seminar on "Multimodal Cardiovascular and Motor Assessment in Parkinson's Disease" in DEIB “Alessandra Alario” Seminar Room (Building 21).

Parkinson’s disease (PD) is a degenerative disorder of the nervous system, which involves motor and non-motor disturbances. Non-motor alterations are important because they may appear in the early stages of PD, even decades before the motor alterations. Therefore, its evaluation offers the possibility of early diagnosis and adequate monitoring of the disease. In addition, motor alterations affect gait according to the progression of PD and can be used by experts in movement disorders to rate the severity of the disease. However, this rating depends on the expertise of the clinical specialist. In this talk will be presented approaches used to classify Parkinson’s disease patients using vertical ground reaction force (VGRF) signals with PD gait severity classification, triaxial accelerometer signals, and heart rate variability features.

Biografia

Guadalupe Dorantes-Méndez is Full Professor in Biomedical Engineering at the Faculty of Science of the Autonomous University of San Luis Potosí (UASLP), she is a member of the Postgraduate Programs in Electronic Engineering and Life Sciences. She holds a Bachelor’s and Master’s in Biomedical Engineering from Autonomous Metropolitan University (Mexico) and a Ph.D. in Bioengineering from the Polytechnic University of Milan, Italy. She has the recognition of Researcher Level I in Mexico’s National Research System (SNI), she is the leader of the academic group of Biomedical Engineering in the UASLP, and she is an associate editor of IEEE Latin America Transactions. Her research focuses on biomedical signal processing, physiological interactions, multivariate techniques, artificial intelligence, and biomedical instrumentation.