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.

Planned secondments: AAU (SD, M12-M12): Signals and applications for neuro-business; UPISA (EP, M15-M18): Integration and analysis of fNIRS data, multivariate modelling and real-time processing; GTEC (BO, M22-M22): Design of wearable systems, mountings and compatibility; SKU (MG, M30-M33): Application of neural network models.

Sofia Sappia


Sofía completed her Bachelor’s and Master’s Degrees in Biomedical Engineering at Universidad Nacional de Córdoba, Argentina.

She participated on different projects on signal processing and integrated the R&D group of OTTAA Project, an Argentinean startup devoted to the development of Augmentative and Alternative Communication Systems. There, she participated in the development of a Brain Computer Interface, working actively on the signal classification module and applying machine learning algorithms to the analysis and classification of EEG signals. Her research interests include neuroscience, biomedical signal processing and machine learning.




Novel metrics for fNIRS in neuro-business (WP1-WP5)


  • Model describing the relation between hemodynamic brain signals, systemic factors, mental state and decision processes
  • Neuro-business NIRS device and software prototype.