| Literature DB >> 25609212 |
Gianluca Borghini1,2,3, Pietro Aricò4,5, Ilenia Graziani4, Serenella Salinari5, Yu Sun6, Fumihiko Taya6, Anastatios Bezerianos6, Nitish V Thakor6,7, Fabio Babiloni8.
Abstract
Generally, the training evaluation methods consist in experts supervision and qualitative check of the operator's skills improvement by asking them to perform specific tasks and by verifying the final performance. The aim of this work is to find out if it is possible to obtain quantitative information about the degree of the learning process throughout the training period by analyzing neuro-physiological signals, such as the electroencephalogram, the electrocardiogram and the electrooculogram. In fact, it is well known that such signals correlate with a variety of cognitive processes, e.g. attention, information processing, and working memory. A group of 10 subjects have been asked to train daily with the NASA multi-attribute-task-battery. During such training period the neuro-physiological, behavioral and subjective data have been collected. In particular, the neuro-physiological signals have been recorded on the first (T1), on the third (T3) and on the last training day (T5), while the behavioral and subjective data have been collected every day. Finally, all these data have been compared for a complete overview of the learning process and its relations with the neuro-physiological parameters. It has been shown how the integration of brain activity, in the theta and alpha frequency bands, with the autonomic parameters of heart rate and eyeblink rate could be used as metric for the evaluation of the learning progress, as well as the final training level reached by the subjects, in terms of request of cognitive resources.Keywords: Cognitive learning; ECG; EEG; EOG; Perceived workload; Training
Mesh:
Year: 2015 PMID: 25609212 DOI: 10.1007/s10548-015-0425-7
Source DB: PubMed Journal: Brain Topogr ISSN: 0896-0267 Impact factor: 3.020