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Comparing Recalibration Strategies for Electroencephalography-Based Decoders of Movement Intention in Neurological Patients with Motor Disability.
López-Larraz, Eduardo; Ibáñez, Jaime; Trincado-Alonso, Fernando; Monge-Pereira, Esther; Pons, José Luis; Montesano, Luis.
Afiliação
  • López-Larraz E; 1 Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Silcherstr. 5, 72076, Tübingen, Germany.
  • Ibáñez J; 2 Instituto de Investigación de Ingeniería de Aragón (I3A), Departamento de Informática e Ingeniería de Sistemas, University of Zaragoza, María de Luna 1, 50015, Zaragoza, Spain.
  • Trincado-Alonso F; 3 Sobell Department of Motor Neuroscience, Institute of Neurology, University College London, 3rd Floor, Clinical Neurosciences Building, 33, Queen Square, London, WC1N 3BG, UK.
  • Monge-Pereira E; 4 Neural Rehabilitation Group, Cajal Institute, Spanish National Research Council (CSIC), Av Doctor Arce, 37, 28002 Madrid, Spain.
  • Pons JL; 5 Biomechanics and Technical Aids Unit, Hospital Nacional de Parapléjicos, Finca La Peraleda s/n, 45071 Toledo, Spain.
  • Montesano L; 6 Departamento de Fisioterapia, Terapia Ocupacional, Rehabilitación y Medicina Física, Facultad de CC de la Salud, Universidad Rey Juan Carlos, Av. de Atenas, s/n, 28922, Alcorcón, Spain.
Int J Neural Syst ; 28(7): 1750060, 2018 Sep.
Article em En | MEDLINE | ID: mdl-29463157
ABSTRACT
Motor rehabilitation based on the association of electroencephalographic (EEG) activity and proprioceptive feedback has been demonstrated as a feasible therapy for patients with paralysis. To promote long-lasting motor recovery, these interventions have to be carried out across several weeks or even months. The success of these therapies partly relies on the performance of the system decoding movement intentions, which normally has to be recalibrated to deal with the nonstationarities of the cortical activity. Minimizing the recalibration times is important to reduce the setup preparation and maximize the effective therapy time. To date, a systematic analysis of the effect of recalibration strategies in EEG-driven interfaces for motor rehabilitation has not yet been performed. Data from patients with stroke (4 patients, 8 sessions) and spinal cord injury (SCI) (4 patients, 5 sessions) undergoing two different paradigms (self-paced and cue-guided, respectively) are used to study the performance of the EEG-based classification of motor intentions. Four calibration schemes are compared, considering different combinations of training datasets from previous and/or the validated session. The results show significant differences in classifier performances in terms of the true and false positives (TPs) and (FPs). Combining training data from previous sessions with data from the validation session provides the best compromise between the amount of data needed for calibration and the classifier performance. With this scheme, the average true (false) positive rates obtained are 85.3% (17.3%) and 72.9% (30.3%) for the self-paced and the cue-guided protocols, respectively. These results suggest that the use of optimal recalibration schemes for EEG-based classifiers of motor intentions leads to enhanced performances of these technologies, while not requiring long calibration phases prior to starting the intervention.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Intenção / Eletroencefalografia / Interfaces Cérebro-Computador / Reabilitação Neurológica / Atividade Motora / Transtornos dos Movimentos Tipo de estudo: Etiology_studies / Guideline Limite: Adult / Aged / Humans / Male / Middle aged Idioma: En Revista: Int J Neural Syst Assunto da revista: ENGENHARIA BIOMEDICA / INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Intenção / Eletroencefalografia / Interfaces Cérebro-Computador / Reabilitação Neurológica / Atividade Motora / Transtornos dos Movimentos Tipo de estudo: Etiology_studies / Guideline Limite: Adult / Aged / Humans / Male / Middle aged Idioma: En Revista: Int J Neural Syst Assunto da revista: ENGENHARIA BIOMEDICA / INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Alemanha