Education

University of Patras, Greece – Vrije Universiteit Brussels, Belgium

Joint Ph.D. candidate • 12/2017 — Present

Thesis title: «Multi-Channel EMG Pattern Classification based on Deep Learning»

University of Patras, Greece

MSc Degree in Biomedical Engineering • 10/2015 — 6/2017

Thesis title: «Smartphone-based fall detection system for the elderly»

Grade: 9.02/10

University of Patras, Greece

Diploma in Electrical and Computer Engineering • 10/2010 — 10/2015

Thesis title: «Transmission of biomedical signals using a wireless sensor network»

Grade: 8.31/10

Publications

P. Tsinganos, B. Cornelis, J. Cornelis, B. Jansen and A. Skodras, “The Effect of Space-filling Curves on the Efficiency of Hand Gesture Recognition Based on sEMG Signals”, International Journal of Electrical and Computer Engineering Systems, 12(1), 2021.

P. Tsinganos, B. Cornelis, J. Cornelis, B. Jansen and A. Skodras, “Data Augmentation of Surface Electromyography for Hand Gesture Recognition”, Sensors, MDPI, 20(17), 4892, 2020.

P. Tsinganos, B. Cornelis, J. Cornelis, B. Jansen and A. Skodras, “Hilbert sEMG data scanning for hand gesture recognition based on deep learning”, Neural Computing and Applications, Springer, 2020.

P. Tsinganos, B. Cornelis, J. Cornelis, B. Jansen and A. Skodras, “Hand Gesture Recognition Based on EMG Data: A Convolutional Neural Network Approach”, Physiological Computing Systems. PhyCS 2016, PhyCS 2017, PhyCS 2018. Lecture Notes in Computer Science, , A. Holzinger, A. Pope and H. Plácido da Silva, Springer, Cham, 2019, pp. 180-197.

P. Tsinganos, B. Cornelis, J. Cornelis, B. Jansen and A. Skodras, “A Hilbert Curve Based Representation of sEMG Signals for Gesture Recognition”, 2019 International Conference on Systems, Signals and Image Processing (IWSSIP), Osijek, Croatia, 2019, pp. 201-206.

P. Tsinganos, B. Cornelis, J. Cornelis, B. Jansen and A. Skodras, “Improved Gesture Recognition Based on sEMG Signals and TCN”, 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, 2019, pp. 1169–1173.

P. Tsinganos, A. Skodras, B. Cornelis and B. Jansen, “Deep Learning in Gesture Recognition Based on sEMG Signals”, Learning Approaches in Signal Processing, 1st ed., F. Ring, W.-C. Siu, L.-P. Chau, L. Wang and T. Tang, Eds. Pan Stanford Publishing, 2018, pp. 471.

P. Tsinganos, B. Cornelis, J. Cornelis, B. Jansen and A. Skodras, “Deep Learning in EMG-based Gesture Recognition”, 5th International Conference on Physiological Computing Systems (PhyCS), Seville, Spain, 2018, pp. 107–114.

P. Tsinganos and A. Skodras, “A Smartphone-based Fall Detection System for the Elderly”, 10th International Symposium on Image and Signal Processing and Analysis (ISPA), Ljubljana, Slovenia, 2017, pp. 53-58.

Skills

Programming languages

C/C++, Python, Android, Matlab, HTML, JavaScript

Signal Processing

Image and Signal Processing, Biomedical Signals

Machine Learning

Udacity AI for Healthcare Nanodegree, Data Mining, Artificial Neural Networks, Deep Learning

Web Development

Udacity Full Stack Developer Nanodegree, Flask, React, REST API, Auth0

Embedded Programming

Experience in ARM Cortex M3 and RTOS

Communication protocols

TCP/IP, GSM, MQTT

Recognition

Best Student Paper

IEEE, EURASIP, University of Osijek, FERIT • 2019

Awarded for the paper with title “A Hilbert Curve Based Representation of sEMG Signals for Gesture Recognition” presented in IWSSIP 2019 Osijek, Croatia.