论文信息 - Towards mobile health care: Neurocognitive impairment monitoring by BCI-based game

Towards mobile health care: Neurocognitive impairment monitoring by BCI-based game

A mobile-health solution for neuro-cognitive impairment monitoring based on P300 spatio-temporal characterization achieved by tuned Residue Iteration Decomposition (t-RIDE) is here presented. It allows remote monitoring of neuro-cognitive impairment through a domestic game-test by physician which can interact with it. Data collection is allowed by cloud bridging. It has been validated on 10 subjects: P300 amplitude and latency ranges are 2.8pV-8pV and 300ms-410ms (on Pz, Fz, Cz, EEG electrodes) in total agreement with the medical references. The methodology shows fast diagnosis of cognitive deficit, including mild and heavy cognitive impairment: t-RIDE convergence is reached in 79 iteration (i.e. 1.95s) giving 80% accuracy in P300 amplitude evaluation with only 13 trials on a single EEG channel.

V. F. Annese | D. De Venuto | G. Mezzina

[1] Alberto L. Sangiovanni-Vincentelli,et al. Designing a Cyber–Physical System for Fall Prevention by Cortico–Muscular Coupling Detection , 2016, IEEE Design & Test.

[2] Frank Padberg,et al. Value of event-related P300 subcomponents in the clinical diagnosis of mild cognitive impairment and Alzheimer's Disease. , 2002, Psychophysiology.

[3] Joav Merrick,et al. Neurological Disorders: Public Health Challenges , 2007 .

[4] Giovanni Mezzina,et al. Remote Neuro-Cognitive Impairment Sensing Based on P300 Spatio-Temporal Monitoring , 2016, IEEE Sensors Journal.

[5] Daniela De Venuto,et al. Fall-risk assessment by combined movement related potentials and co-contraction index monitoring , 2015, 2015 IEEE Biomedical Circuits and Systems Conference (BioCAS).

[6] Daniela De Venuto,et al. Combined EEG/EMG evaluation during a novel dual task paradigm for gait analysis , 2015, 2015 6th International Workshop on Advances in Sensors and Interfaces (IWASI).

[7] Daniela De Venuto,et al. FPGA based architecture for fall-risk assessment during gait monitoring by synchronous EEG/EMG , 2015, 2015 6th International Workshop on Advances in Sensors and Interfaces (IWASI).

[8] Werner Sommer,et al. A toolbox for residue iteration decomposition (RIDE)—A method for the decomposition, reconstruction, and single trial analysis of event related potentials , 2015, Journal of Neuroscience Methods.