Brain-Machine Neurofeedback: Robotics or Electrical Stimulation?

Influence of Temporal and Frequency Selective Patterns Combined with CSP Layers on Performance in Exoskeleton-Assisted Motor Imagery Tasks

“…In this context, we hypothesized that the use of a robotic arm exoskeleton at different speeds could enhance cortical rhythms which could facilitate the classification of upper limb KMI tasks. An adequate classification score and False Positive Rate were found, considering the literature reports [31][32][33]36]. Considering the working principle of CSPbased methods [19], our results suggest that information in the time domain cannot be fully discriminatory when the KMI is under different conditions, which is a limitation for spatial filtering methods.…”

“…This proposal also used constant velocity during the protocol, which may limit the scope. Guggenberg et al implemented a strategy to classify KMI from EEG signals in a protocol that employed a robotic hand orthosis and a functional electrical stimulator [36]. This approach reached an accuracy rate above 0.6 using information from the Beta (β) band.…”

“…The second is that the use of sensory feedback during MI can re-activate pathways associated with the mechanoreceptors of limbs that have been affected after neurological trauma. This is associated with neural biomarkers [34], which have gained recognition because this information may be used as neurofeedback that can play an important role in induction of neuroplasticity and improvement of proprioception [36,37]. The exploration of cortical behaviors has been presented using hand orthosis [36], arm exoskeletons [34], and robotic gloves [35,37].…”

“…This is associated with neural biomarkers [34], which have gained recognition because this information may be used as neurofeedback that can play an important role in induction of neuroplasticity and improvement of proprioception [36,37]. The exploration of cortical behaviors has been presented using hand orthosis [36], arm exoskeletons [34], and robotic gloves [35,37]. However, these works have been focused on binary conditions, such as rest and motion classification, whose limitations are explained above.…”

Non-invasive brain-spine interface: Continuous control of trans-spinal magnetic stimulation using EEG

“…Non-invasive brain-machine interfaces (BMIs) allow the transmission of volitional cortical commands to control rehabilitative devices ( Wolpaw et al, 2002 ; López-Larraz et al, 2018b ; Guggenberger et al, 2020 ). For instance, there is ample evidence demonstrating contingent EEG control of robotic exoskeletons with patients ( Ramos-Murguialday et al, 2013 ; López-Larraz et al, 2018a ).…”