Brain Computer Interface (BCI) technology is an alternative/ augmentative communication channel, based on the interpretation of the user’s brain activity, who can then interact with the environment without relying on neuromuscular pathways. Such technologies can act as alternative HCI devices towards AAL (Ambient Assisted Living) systems, thus opening their services to people for whom interacting with conventional interfaces could be troublesome, or even not viable. A complete BCI implementation is presented and discussed, briefly introducing the customized hardware and focusing more on the signal processing aspects. The BCI is based on SSVEP signals, featuring self-paced calibration-less operation, aiming at a “plug&play” approach. The signal processing chain is presented, introducing a novel method for improving accuracy and immunity to false positives. The results achieved, especially in terms of false positive rate containment (0.16 min−1) significantly improve over the literature. In addition, a possible integration of EMG signals in a hybrid-BCI scheme is discussed, serving as a binary switch to turn on/off the EEG-based BCI section (and the flashing stimuli unit). This can have positive impact on both the user’s comfort as well as on the resilience towards false positives. Preliminary results for jaw clench recognition show good detectability, proving that such integration can be implemented.

Hybrid BCI systems as HCI in ambient assisted living scenarios / Mora, Niccolò; De Munari, Ilaria; Ciampolini, Paolo. - 9738(2016), pp. 434-443. [10.1007/978-3-319-40244-4_42]

Hybrid BCI systems as HCI in ambient assisted living scenarios

MORA, Niccolo';DE MUNARI, Ilaria;CIAMPOLINI, Paolo
2016

Abstract

Brain Computer Interface (BCI) technology is an alternative/ augmentative communication channel, based on the interpretation of the user’s brain activity, who can then interact with the environment without relying on neuromuscular pathways. Such technologies can act as alternative HCI devices towards AAL (Ambient Assisted Living) systems, thus opening their services to people for whom interacting with conventional interfaces could be troublesome, or even not viable. A complete BCI implementation is presented and discussed, briefly introducing the customized hardware and focusing more on the signal processing aspects. The BCI is based on SSVEP signals, featuring self-paced calibration-less operation, aiming at a “plug&play” approach. The signal processing chain is presented, introducing a novel method for improving accuracy and immunity to false positives. The results achieved, especially in terms of false positive rate containment (0.16 min−1) significantly improve over the literature. In addition, a possible integration of EMG signals in a hybrid-BCI scheme is discussed, serving as a binary switch to turn on/off the EEG-based BCI section (and the flashing stimuli unit). This can have positive impact on both the user’s comfort as well as on the resilience towards false positives. Preliminary results for jaw clench recognition show good detectability, proving that such integration can be implemented.
Hybrid BCI systems as HCI in ambient assisted living scenarios / Mora, Niccolò; De Munari, Ilaria; Ciampolini, Paolo. - 9738(2016), pp. 434-443. [10.1007/978-3-319-40244-4_42]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11381/2820551
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