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The system has been funded by EU Horizon 2020 and is now distributed in the market in partnership between BrainSigns and Brain Products.

Applications

Aviation

Training and expertise are key aspects in aviation. A traditional way of evaluating operator (i.e. pilots, air traffic controllers) expertise is to measure performance output; however, this approach provides a narrow view of the operator’s capacity, especially with regard to the cognitive profile.

Automotive

The human element of driving remains the main cause of traffic accidents and fatalities. Real-time measurement of workload and vigilance provided by Mindtooth neurometrics enable better training and improved performance, thereby reducing the risk of accidents.

NeuroAesthetics

The Mindtooth system was validated through studies within the Accademia dei Lincei and the Basilica of San Pietro in Vincoli in Rome to measure the appreciation of various works of art: the recitation of passages from Dante’s Divine Comedy or the observation of the Moses statue by Michelangelo.

Virtual Reality Integration

The Mindtooth Touch headset can be worn together with head-mounted VR systems without inducing signal interference. The system has been tested by BrainSigns in a research study, which assessed workload and approach-withdrawal during VR in different scenarios. This solution is offered in collaboration with Myndek that developed an SDK for VR and Neurometrics integration.

Pietro Aricò

R&D Project Manager

Pietro Aricò BrainSigns

Professor Pietro Aricò got a PhD in Bioengineering at the University of Bologna “Alma Mater Studiorum”, and a Master Degree in Biomedical Engineering at the University of Rome “Sapienza”. He is currently project manager and senior team member of the R&D department of the company. 

foto Piero min

He is now Assistant Professor (RTD-B) at the Department of Computer, Control and Management Engineering, Sapienza University of Rome.

The activity of Professor Pietro Aricò focused on the integration of the technologies used in Brain Computer Interface systems in operational environments, in particular Artificial Intelligence (AI) approaches. By using such technology it is possible to classify particular components of the subject's biosignals in order to associate them with different mental and emotional states of the user or more in general human factor concepts, in particular attentional levels, training or mental workload.

The expertise of Professor Pietro Aricò, is focused on the analysis and processing of biosignals (Electroencephalography, Electrocardiogram, Galvanic Skin Response), with particular knowledge of different signal processing techniques (e.g. Wavelet analysis, Regressive algorithms, Independent Component Analysis, etc).

He is co-author of more than 50 scientific articles in peer-reviewed international journals and more than 50 scientific contributions in peer-reviewed national and international conferences (http://bit.ly/2vYhmac) and 1 patent (http://bit.ly/38WAJPp). 

Professor Aricò serves as reviewer for several peer-review journals, he is the Associate Editor for the International Journal of Bioelectromagnetism journal, and Guest Editor within many special issues on international journals, such as Frontiers in Human Neuroscience and Brain Sciences.

He teaches in the MSc programs in Biomedical Engineering and Medicine and Surgery HT (courses: Biosignal Processing - 6 CFU; Biosignal Processing and electromagnetic fields - 3 CFU). He is member of the board of the PhD programme in Control engineering, Bioengineering and Operations research at Sapienza University of Rome.

He was involved in several national and international projects, such as “TOBI - Tools for Brain-Computer Interaction” (Integrated Project) and “SM4All - Smart hoMes for All” (STREP), funded by the European Commission on the 7th framework and the project “NINA - Neurometrics INdicators for ATM”, founded by SESAR JU, “MOTO - the embodied reMOte Tower” and “STRESS - human performance neurometrics toolbox for highly automated systems design”.

 

Pietro Aricò on Linkedin