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Computational Intelligence and Neuroscience
Volume 2017 (2017), Article ID 1512504, 9 pages
Research Article

Selection of the Optimal Algorithm for Real-Time Estimation of Beta Band Power during DBS Surgeries in Patients with Parkinson’s Disease

1Laboratory of Rehabilitation Engineering, National University of Entre Ríos, Oro Verde, Argentina
2Group for Digital Design and Processing (GDDP), ETSE, Department of Electronic Engineering, University of Valencia, Valencia, Spain
3Functional Neurosurgery Unit, La Fe Hospital, Valencia, Spain

Correspondence should be addressed to Alfredo Rosado Muñoz

Received 31 August 2017; Accepted 29 November 2017; Published 24 December 2017

Academic Editor: Plácido R. Pinheiro

Copyright © 2017 Ángeles Tepper et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Deep Brain Stimulation (DBS) is a surgical procedure for the treatment of motor disorders in patients with Parkinson’s Disease (PD). DBS involves the application of controlled electrical stimuli to a given brain structure. The implantation of the electrodes for DBS is performed by a minimally invasive stereotactic surgery where neuroimaging and microelectrode recordings (MER) are used to locate the target brain structure. The Subthalamic Nucleus (STN) is often chosen for the implantation of stimulation electrodes in DBS therapy. During the surgery, an intraoperative validation is performed to locate the dorsolateral region of STN. Patients with PD reveal a high power in the band (frequencies between 13 Hz and 35 Hz) in MER signal, mainly in the dorsolateral region of STN. In this work, different power spectrum density methods were analyzed with the aim of selecting one that minimizes the calculation time to be used in real time during DBS surgery. In particular, the results of three nonparametric and one parametric methods were compared, each with different sets of parameters. It was concluded that the optimum method to perform the real-time spectral estimation of beta band from MER signal is Welch with Hamming windows of 1.5 seconds and 50% overlap.