MOVING: a Multi-MOdal dataset of EEG signals and VIrtual Glove hand trackING
DOI10.5281/zenodo.12804784Zenodo12804784MaRDI QIDQ6704881
Dataset published at Zenodo repository.
Author name not available (Why is that?)
Publication date: 24 July 2024
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A new Multi-modal dataset comprising neural EEG signals and kinematic data associated with three hand movements open/close, finger tapping, and wrist rotation along with a rest period. The dataset, obtained from eleven subjects using a 32-channel dry wireless EEG system, also includes synchronized kinematic data captured by a Virtual Glove (VG) system equipped with two orthogonal Leap Motion Controllers. The use of these two devices allows for fast assembly (~ 1 minute) while introducing more noise than the gold standard devices for data acquisition. The data set, obtained from 11 subjects using a 32-channel dry wireless EEG system, also includes synchronized kinematic data captured by a Virtual Glove (VG) system equipped with two orthogonal Leap Motion Controllers. For citation please refer to the paper:Mattei, E.; Lozzi, D.; Di Matteo, A.; Cipriani, A.; Manes, C.;Placidi, G. MOVING: A Multi-Modal Dataset of EEG Signals and Virtual Glove Hand Tracking. Sensors 2024,24, 5207. https://doi.org/10.3390/s24165207 References: Placidi, Giuseppe. "A smart virtual glove for the hand telerehabilitation." Computers in Biology and Medicine 37.8 (2007): 1100-1107. Placidi, Giuseppe, et al. "Measurements by a LEAP-based virtual glove for the hand rehabilitation." Sensors 18.3 (2018): 834. Placidi, Giuseppe, et al. "Patienttherapist cooperative hand telerehabilitation through a novel framework involving the virtual glove system." Sensors 23.7 (2023): 3463.
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