A WiSARD Network Approach for a BCI-Based Robotic Prosthetic Control
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A WiSARD Network Approach for a BCI-Based Robotic Prosthetic Control Mariacarla Staffa1
· Maurizio Giordano2
· Fanny Ficuciello3
Accepted: 3 July 2019 © Springer Nature B.V. 2019
Abstract There are significant research efforts underway in the area of automatic robotic-prosthesis control based on brain–computer interface aiming at understanding how neural signals can be used to control these assistive devices. Although these approaches have made significant progresses in the ability to control robotic manipulators, the realization of portable and easy of use solutions is still an ongoing research endeavor. In this paper, we propose a novel approach relying on the use of (i) a Weightless Neural Network-based classifier, whose design lends itself to an easy hardware implementation; (ii) a robotic hand designed in order to fit with the main requirements of these kind of technologies (such as low cost, high performance, lightness, etc.) and (iii) a non-invasive light-weight and easy-donning EEG-helmet in order to provide a portable controller interface. The developed interface is connected to a robotic hand for controlling open/close actions. The preliminary results for this system are promising in that they demonstrate that the proposed method achieves similar performance with respect to state-of-the-art classifiers by contemporaneously representing a most suitable and practicable solution due to its portability on hardware devices, which will permit its direct implementation on the helmet board. Keywords Automatic robotic prosthetic control · Weightless neural network · Brain computer interface · EEG-signal processing
1 Introduction In the last years, we witnessed a great interest in the field of brain–computer interface (BCI) based control of robotic devices, with particular focus on health-related applications, where the adoption of BCI-based control of prosthetic devices aims at increasing the quality of life for patients with diseases causing temporary or permanent paralysis or, in the
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Mariacarla Staffa [email protected] Maurizio Giordano [email protected] Fanny Ficuciello [email protected]
1
Department of Physics “E. Pancini”, University of Naples Federico II, Via Cinthia, 21, 80126 Napoli, Italy
2
High Performance Computing and Networking Institute, National Research Council of Italy, Via Pietro Castellino 111, Naples, Italy
3
Department of Electrical Engineering and Information Technologies, University of Naples Federico II, via Claudio, 21, 80125 Napoli, Italy
worst case, the lost of limbs [14]. Diseases causing temporary or permanent paralysis are many and very often it is difficult or even impossible to restore lost of limbs or basic functions (e.g., ALS (Amyotrophic Lateral Sclerosis) patients who progressively lose the use of the limbs in relation to the disease course). In most cases, the brain continues to perform its activity even if the body does not respond to stimuli as it should. For this reason, the research has focused on the study of cognitive processes that
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