Development of EEG-based technologies for the characterization and treatment of neurological diseases a ecting the motor function

  1. Ibáñez Pereda, Jaime
Dirigida por:
  1. María Dolores del Castillo Sobrino Director/a
  2. José Ignacio Serrano Moreno Director/a
  3. Javier Mínguez Zafra Director/a

Universidad de defensa: Universidad de Zaragoza

Fecha de defensa: 30 de octubre de 2014

Tribunal:
  1. Ramón Ceres Ruiz Presidente/a
  2. Luis Montesano del Campo Secretario/a
  3. Roberto Hornero Sánchez Vocal

Tipo: Tesis

Resumen

This thesis presents a set of studies applying signal processing and data mining techniques in real-time working systems to register, characterize and condition the movement-related cortical activity of healthy subjects and of patients with neurological disorders affecting the motor function. Patients with two of the most widespread neurological affections impairing the motor function are considered here: patients with essential tremor and patients who have suffered a cerebro-vascular accident. The different chapters in the presented thesis show results regarding the normal cortical activity associated with the planning and execution of motor actions with the upper-limb, and the pathological activity related to the patients' motor dysfunction (measurable with muscle electrodes or movement sensors). The initial chapters of the book present A) a revision of the basic concepts regarding the role of the cerebral cortex in the motor control and the way in which the electroencephalographic activity allows its analysis and conditioning, B) a study on the cortico-muscular interaction at the tremor frequency in patients with essential tremor under the effects of a drug reducing their tremor, and finally C) a study based on evolutionary algorithms that aims to identify cortical patterns related to the planning of a number of motor tasks performed with a single arm. In the second half of the thesis book, two brain-computer interface systems to be used in rehabilitation scenarios with essential tremor patients and with patients with a stroke are proposed. In the first system, the electroencephalographic activity is used to anticipate voluntary movement actions, and this information is integrated in a multimodal platform estimating and suppressing the pathological tremors. In the second case, a conditioning paradigm for stroke patients based on the identification of the motor intention with temporal precision is presented and tested with a cohort of four patients along a month during which the patients undergo eight intervention sessions.