Brain-computer interface

On the relationship between attention processing and P300-based brain computer interface control in amyotrophic lateral sclerosis

Our objective was to investigate the capacity to control a P3-based brain-computer interface (BCI) device for communication and its related (temporal) attention processing in a sample of amyotrophic lateral sclerosis (ALS) patients with respect to healthy subjects. The ultimate goal was to corroborate the role of cognitive mechanisms in event-related potential (ERP)-based BCI control in ALS patients. Furthermore, the possible differences in such attentional mechanisms between the two groups were investigated in order to unveil possible alterations associated with the ALS condition.

Adaptive learning in the detection of Movement Related Cortical Potentials improves usability of associative Brain-Computer Interfaces

Brain-computer interfaces have increasingly found applications in motor function recovery in stroke patients. In this context, it has been demonstrated that associative-BCI protocols, implemented by means the movement related cortical potentials (MRCPs), induce significant cortical plasticity. To date, no methods have been proposed to deal with brain signal (i.e. MRCP feature) non-stationarity.

Area-efficient low-power bandpass Gm-C filter for epileptic seizure detection in 130nm CMOS

A low-power 6th-order Butterworth bandpass filter has been designed for the front-end of an integrated neural recording system. The passband has been set to 250-500Hz to allow recording the fast ripple (FR) associated with epileptic seizure onset and filter out all other undesired components of the neural signals. The filter is composed of 3 Gm-C biquad stages. Low-power operation is achieved by biasing the MOS devices in the sub-threshold region, and using a dual power supply of ±0.5V.

Low power switched-resistor band-pass filter for neural recording channels in 130nm CMOS

In this work, we present a low-power 2nd order band-pass filter for neural recording applications. The central frequency of the passband is set to 375Hz and the quality factor to 5 to properly process the neural signals related to the onset of epileptic seizure, and to strongly attenuate all the out of band biological signals and electrical disturbances. The biquad filter is based on a fully differential Tow Thomas architecture in which high-valued resistors are implemented through switched high-resistivity polysilicon resistors.

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