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The main goal of this paper is to simultaneously decode movement velocity of both hand and elbow from electroencephalography (EEG) signals. The result can support motor rehabilitation using a robotic arm and assist people with disabilities to control an upper limb neuroprosthesis in natural movement. In recent works, researchers have estimated hand movement velocity from EEG signals. However, such studies are insufficient to apply motor rehabilitation, since they only considered hand movement trajectory. Sometimes patients take wrong elbow movement in motor rehabilitation even though their hand movements are correct. In this study, we explore to decode not only hand but also elbow velocity from EEG signals when subjects move upper limb.
David Atienza Alonso, José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola, Ping-Keng Jao
Michael Herzog, Maya Roinishvili, Ophélie Gladys Favrod, Patricia Figueiredo, Janir Nuno Ramos Antunes Da Cruz