Paradigms

A paradigm defines how the raw data will be converted to trials ready to be processed by a decoding algorithm. This is a function of the paradigm used, i.e. in motor imagery one can have two-class, multi-class, or continuous paradigms; similarly, different preprocessing is necessary for ERP vs ERD paradigms.

Motor Imagery Paradigms

MotorImagery([n_classes])

N-class motor imagery.

LeftRightImagery(**kwargs)

Motor Imagery for left hand/right hand classification

FilterBankLeftRightImagery(**kwargs)

Filter Bank Motor Imagery for left hand/right hand classification

FilterBankMotorImagery([n_classes])

Filter bank n-class motor imagery.

P300 Paradigms

SinglePass([fmin, fmax])

Single Bandpass filter P300

P300(**kwargs)

P300 for Target/NonTarget classification

SSVEP Paradigms

SSVEP([fmin, fmax])

Single bandpass filter SSVEP

FilterBankSSVEP([filters])

Filtered bank n-class SSVEP paradigm

Base & Utils

motor_imagery.BaseMotorImagery([filters, …])

Base Motor imagery paradigm.

motor_imagery.SinglePass([fmin, fmax])

Single Bandpass filter motot Imagery.

motor_imagery.FilterBank([filters])

Filter Bank MI.

p300.BaseP300([filters, events, tmin, tmax, …])

Base P300 paradigm.

ssvep.BaseSSVEP([filters, events, …])

Base SSVEP Paradigm

base.BaseParadigm()

Base Paradigm.