Novel metrics for fNIRS in neuro-business (WP1-WP5)
The main objective is the development of novel metrics derived from the analysis of functional Near Infrared Spectroscopy (NIRS) signals to access core cognitive processes in mixed reality. The goal of the ESR will be to develop a fully functional suite of software algorithms for an application of fNIRS as a neuro-business tool. In more detail, the work will consist of: 1) Extraction of artefacts and systemic factors of the NIRS signal using hemodynamic models, and non-parametric spectral estimation techniques such as Singular Spectrum Analysis and Empirical Mode Decomposition; 2) Evaluating psychological methods and tests to determine participant’s mental state and decision process; 3) Applying Machine Learning techniques such as Recurrent and Convolutional Neural Networks on multimodal ANS and NIRS features to infer the participant’s mental state and decision process; 4) Embedding above developed algorithms in a fNIRS software suite to be used in conjunction with an Artinis fNIRS neuro-business device.
Mohammad Shabakhti was born in Dezful, Iran, in 1990. He completed his B.Sc. in biomedical engineering at the Faculty of Engineering of the Islamic Azad University of Dezul in 2012. From 2014 to 2018, he worked as the head of the biomedical engineering department in Mehr Private Hospital, Ahwaz, Iran. In 2020, he gained the M.Sc. degree in biomedical engineering from Kaunas University of Technology (KTU), Kaunas, Lithuania. Presently, Mohammad is working as an early stage researcher at Artinis Medical Systems B.V., Elst, The Netherlands, where he conducts research towards the estimation of physiological parameters from fNIRS. His research interests include biomedical signal processing, sleep monitoring, and wearables.