Tesis (Ingeniero Biomédico)

Stroke is one of the leading causes of motor and cognitive disability in the world. Despite the
existence of various conventional therapies that seek to maximize the recovery of patients,
Brain-Computer Interfaces (BCI) are tools to integrate the central nervous system in the
rehabilitation process to empower the recovery. Technologies based on the acquisition of
EEG signals seeking to complement existing therapies with exoskeletons present enormous
potential. The T-FLEX is an active ankle orthosis that has shown efficiency in recovering
patients with disabilities in the lower limb. This project presents the preliminary integration
of T-FLEX and a BCI system based on EEG signals with validation in post-stroke patients.
Initially, a theoretical framework based on Motor Imagination (MI) principles were implemented, specifically in the Event-Related Synchronization (ERS) of the beta frequency band
in the central zone of the cerebral cortex. In this sense, a local server was designed, which
worked as a communication bridge between the designed BCI and the T-FLEX device using
different data sending protocols.
In the experimental study, the BCI system was analyzed with five post-stroke patients
with external stimuli facilitating the MI generation. These were visual and visual with tactile
stimuli. Significant differences were found in the accuracy, which concluded greater accuracy
in the ability of the BCI to detect MI with visual and tactile stimulation with an increase of
13.3% to 20%.
Significant differences were found in the Power Spectral Density (PSD) related to the
tests performed with visual and tactile stimulation in the Cz, C2 and Cpz channels vs. the
therapy mode of the T-FLEX device, in which the patient was not required to generate MI.
In the same way, the subjective perception of the patients was evaluated through a QUEST
2.0 questionnaire. The results showed that the preliminary integration of this technology is
viable for future studies in the medium and long term.