"PERSON" project (FSC 2007-2013 Regional Technology Cluster – PERvasive game for perSOnalized treatment of cognitive and functional deficits associated with chronic and Neurodegenerative diseases) is a Regional Cluster.
Research field: Bio-Engineering, EEG Processing, BCI
Partners:see all the partners
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Remote Neuro-Cognitive Impairment Monitoring based on P300 Spatio-Temporal Characterization
Part of the project is the development of a novel mobile healthcare solution for remotely monitoring neuro-cognitive efficiency. The method is based on the spatio-temporal characterization of a specific Event-Related Potential (ERP), called P300, induced in our brain by a target stimulus. P300 analysis is used as a biomarker: the amplitude and latency of the signal are quality indexes of the brain activity. Up to now the P300 characterization has been performed in hospital through EEG analysis and it has not been experimented an algorithm that can work remotely and learn from the subject performance. The proposed m-health service allows remote EEG monitoring of P300 through a ‘plug and play’ system based on the video game reaction of the subject under test. The signal processing is achieved by tuned Residue Iteration Decomposition (t-RIDE). The improvement achieved by the proposed algorithm respect the state of the art is higlighted through a comparison between t-RIDE, Independent component analysis (ICA) approaches and grand average method. t-RIDE and ICA analysis report the same results (0.1% deviation) using the same dataset (game with a detection of 40 targets). Nevertheless, t-RIDE is 1.6 times faster than ICA since converges in 79 iterations (i.e. t-RIDE: 1.95s against ICA: 3.1s).
- D. De Venuto, V. F. Annese and G. Mezzina, "Remote Neuro-Cognitive Impairment Sensing Based on P300 Spatio-Temporal Monitoring," in IEEE Sensors Journal, vol. 16, no. 23, pp. 8348-8356, Dec.1, 2016. doi: 10.1109/JSEN.2016.2606553
- D. D. Venuto, V. F. Annese, G. Mezzina, M. Ruta and E. D. Sciascio, "Brain-computer interface using P300: a gaming approach for neurocognitive impairment diagnosis," 2016 IEEE International High Level Design Validation and Test Workshop (HLDVT), Santa Cruz, CA, 2016, pp. 93-99.
- V. F. Annese, G. Mezzina and D. De Venuto, "Towards mobile health care: Neurocognitive impairment monitoring by BCI-based game," 2016 IEEE SENSORS, Orlando, FL, 2016, pp. 1-3.