Continuous versus discrete robotic feedback for brain-computer interfaces aimed for neurorehabilitation - Carino-Escobar, Ruben I.; Rodríguez-García, Martín E.; Carrillo-Mora, Paul; Valdés-Cristerna, Raquel; Cantillo-Negrete, Jessica (Frontiers in Neurorobotics, 2023)
Brain-Computer Interfaces (BCI) can allow control of external devices using motor imagery (MI) decoded from electroencephalography (EEG). Although BCI have a wide range of applications including neurorehabilitation, the low spatial resolution of EEG, coupled to the variability of cortical activations during MI, make control of BCI based on EEG a challenging task. For this reason, two different feedback timing strategies were compared, comprised by passive hand movement provided by a robotic hand orthosis. One of the timing strategies, the continuous, involved the partial movement of the robot immediately after the recognition of each time segment in which hand MI was performed. The other feedback, the discrete, was comprised by the entire movement of the robot after the processing of the complete MI period. Twelve healthy subjects performed two sessions of BCI training and testing, one with each feedback. Significantly higher BCI performance (65.05%±17.80% with continuous and 60.41%±17.99% for discrete feedback) and pronounced bilateral alpha and beta cortical activations were observed with the continuous feedback. It was hypothesized that these effects, although heterogenous across subjects, were caused by the enhancement of attentional and closed-loop somatosensory processes. This is important, since a continuous feedback timing could increase the number of BCI users that can control a MI-based system or enhance cortical activations associated with neuroplasticity, important for neurorehabilitation applications.