Pedro M. Rodrigues has a B.Sc., M.Sc. and Ph.D. degrees in biomedical engineering. He is currently an assistant professor at the Faculty of Biotechnology - Universidade Católica Portuguesa (ESB-UCP) and an integrated member of the Centre for Biotechnology and Fine Chemistry (CBQF-UCP). He lectures Bioengineering / Biomedical disciplines in digital signal processing, digital electronics, computer programming and machine learning areas at ESB-UCP. His research areas focus on digital signal processing and artificial intelligence applied to the diagnosis of neurodegenerative, cardiac and speech diseases.

Publications

Rodrigues, P.M. (*), Bispo, B. C., Garrett, C., Alves, D., Teixeira, J. P. and Freitas, D. “Lacsogram: a New EEG Tool to Diagnose Alzheimer’s Disease”, IEEE Journal of Biomedical and Health Informatics, 2021 (In press, available online), doi: 10.1109/JBHI.2021.3069789

Alves, M., Silva, G., Bispo, B. C., Dagjer, M. and Rodrigues, P.M (*). “Voice Disorders Detection Through Multiband Cepstral Features of Sustained Vowel, Elsevier Journal of Voice, 2021 (In press, available online), doi: https://doi.org/10.1016/j.jvoice.2021.01.018

Bispo, B. C., Yamamura, C.F, Nogueira, W. M. S., Theodoro, E. A. R. and Rodrigues, P. M. (*), “Analysis of Acoustic Feedback Cancellation Systems based on Direct Closed-Loop Identification”, Journal of Communication and Information Systems, 35(1), pp. 217-229, 2020, doi:10.14209/jcis.2020.24

Pereira, R. M., Bispo, B.C. and Rodrigues, P. M. (*), “Evaluation of Lead I ECG Features Discriminant Power for Cardiac Diseases Identification”. Journal of Engineering, 10(4), pp. 1-8, 2020, ISSN:2278-8719.               

Silva, G., Alves, M., Cunha, R., Bispo, B.C. and Rodrigues, P. M. (*) “Parkinson Disease Early Detection using EEG Channels Cross-Correlation.” International Journal of Applied Engineering Research, 15(3), pp. 197-203, 2020, ISSN 0973-4562

Rodrigues, P. M. (*), Freitas, D. R., Teixeira, J. P., Bispo, B., Alves, D. and Garrett, C..  “Electroencephalogram Hybrid Method for Alzheimer Early Detection”, Elsevier Procedia Computer Science, 138, pp. 209-214, 2018, doi: 10.1016/j.procs.2018.10.030

Academic CV