Abstract
In this study, we used a commercial BCI device, the Emotiv EPOC, which is a high-resolution wireless neuroheadset for EEG signal acquisition, to develop a intelligent pattern detection tool parallel to the developer's one to implement an application that combines Augmented Reality (AR). The application was developed as a possible treatment of phantom limb pain (PLP) in amputees patients. The classification engine development has allowed greater control over processing parameters and signal pattern detection, which yielded up to 82.1% of classification. These detected neural signals from a subject, were used to decode its intention of closing or opening a virtual model of a hand or prosthesis attached to the real stump through the AR environment, providing visual feedback to the patient. This, would neurologically help reduce the PLP.
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