Browsing by Author "Bibian, Carlos"
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Item Evaluation of filtering techniques to extract movement intention information from low-frequency EEG activity(Institute of Electrical and Electronics Engineers Inc., 2017-09-13) Bibian, Carlos; Lopez-Larraz, Eduardo; Irastorza-Landa, Nerea; Birbaumer, Niels; Ramos-Murguialday, Ander; Medical TechnologiesLow-frequency electroencephalographic (EEG) activity provides relevant information for decoding movement commands in healthy subjects and paralyzed patients. Brainmachine interfaces (BMI) exploiting these signals have been developed to provide closed-loop feedback and induce neuroplasticity. Several offline and online studies have already demonstrated that discriminable information related to movement can be decoded from low-frequency EEG activity. However, there is still not a well-established procedure to guarantee that this activity is optimally filtered from the background noise. This work compares different configurations of non-causal (i.e., offline) and causal (i.e., online) filters to classify movement-related cortical potentials (MRCP) with six healthy subjects during reaching movements. Our results reveal important differences in MRCP decoding accuracy dependent on the selected frequency band for both offline and online approaches. In summary, this paper underlines the importance of optimally choosing filter parameters, since their variable response has an impact on the classification of low EEG frequencies for BMI.Item Influence of trans-spinal magnetic stimulation in electrophysiological recordings for closed-loop rehabilitative systems(Institute of Electrical and Electronics Engineers Inc., 2017-09-13) Insausti-Delgado, Ainhoa; Lopez-Larraz, Eduardo; Bibian, Carlos; Nishimura, Yukio; Birbaumer, Niels; Ramos-Murguialday, Ander; Medical TechnologiesRecent studies have shown the feasibility of spinal cord stimulation (SCS) for motor rehabilitation. Currently, there is an increasing interest in developing closed-loop systems employing SCS for lower-limb recovery. These closed-loop systems are based on the use of neurophysiological signals to modulate the stimulation. It is known that electromagnetic stimulation can introduce undesirable noise to the electrophysiological recordings. However, there is little evidence about how electroencephalographic (EEG) or electromyographic (EMG) activities are corrupted when a trans-spinal magnetic stimulation is applied. This paper studies the effects of magnetic SCS in EEG and EMG activity. Furthermore, a median filter is proposed to ameliorate the effects of the artifacts, and to preserve the neural activity. Our results show that SCS can affect both EEG and EMG, and that, while the median filter works well to clean the EEG activity, it did not improve the contaminations of the EMG activity. The obtained results underline the need of cleaning EMG and EEG signals contaminated by SCS, which is essential for optimal closed-loop rehabilitation.Item Stroke lesion location influences the decoding of movement intention from EEG(Institute of Electrical and Electronics Engineers Inc., 2017-09-13) Lopez-Larraz, Eduardo; Ray, Andreas M.; Figueiredo, Thiago C.; Bibian, Carlos; Birbaumer, Niels; Ramos-Murguialday, Ander; Medical TechnologiesRecent studies have demonstrated the efficacy of brain-machine interfaces (BMI) for motor rehabilitation after stroke, especially for those patients with severe paralysis. However, a cerebro-vascular accident can affect the brain in many different manners, and lesions in diverse areas, even from significantly different volumes, can lead to similar or equal motor deficits. The location of the insult influences the way the brain activates when moving or attempting to move a paralyzed limb. Since the essence of a rehabilitative BMI is to precisely decode motor commands from the brain, it is crucial to characterize how lesion location affects the measured signals and if and how it influences BMI performance. This paper compares the performances of an electroencephalography (EEG)-based movement intention decoder in two groups of severely paralyzed chronic stroke patients: 14 with subcortical lesions and 14 with mixed (i.e., cortical and subcortical) lesions. We show that the lesion location influences the performance of the BMI when decoding the movement attempts of the paretic arm. The obtained results underline the need for further developments for a better individualization of BMI-based rehabilitative therapies for stroke patients.