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This work proposes a novel methodology for the detection of the intention to change the direction during gait based on event-related desynchronization (ERD). Frequency and temporal features of the electroencephalographic (EEG) signals are characterized. Then, a selection of the most influential features and electrodes to differentiate the direction change intention from the walking is carried out. Best results are obtained when combining frequency and temporal features with an average accuracy of [Formula: see text]%, which are promising to be applied for future BCIs. <\/jats:p>","DOI":"10.1142\/s0129065721500155","type":"journal-article","created":{"date-parts":[[2021,2,27]],"date-time":"2021-02-27T03:20:16Z","timestamp":1614396016000},"source":"Crossref","is-referenced-by-count":5,"title":["Detection of the Intention of Direction Changes During Gait Through EEG Signals"],"prefix":"10.1142","volume":"31","author":[{"given":"Paula","family":"Soriano-Segura","sequence":"first","affiliation":[{"name":"Brain-Machine Interface Systems Lab, Miguel Hern\u00e1ndez University of Elche, Avda. de la, Universidad S\/N, Ed. Innova, Elche, Alicante, 03202, Spain"}]},{"given":"Eduardo","family":"I\u00e1\u00f1ez","sequence":"additional","affiliation":[{"name":"Brain-Machine Interface Systems Lab, Miguel Hern\u00e1ndez University of Elche, Avda. de la, Universidad S\/N, Ed. 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