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32 termsExperimental setup in which trials with the same condition are presented consecutively before switching.
A direct communication pathway between the brain's neural activity and an external device. It functions by recording brain signals (often through electrodes), decoding those signals into commands using computer algorithms, and executing those commands to control a machine or prosthetic, often providing sensory feedback to the user to create a closed-loop system.
A brain-computer interface is a system that measures brain activity and converts it in (nearly) real-time into functionally useful outputs to replace, restore, enhance, supplement, and/or improve the natural outputs of the brain, thereby changing the ongoing interactions between the brain and its external or internal environments. It may additionally modify brain activity using targeted delivery of stimuli to create functionally useful inputs to the brain.
Non-contact EEG method utilizing capacitive sensors, enhancing user comfort and ease of setup.
Experimental design where subjects receive multiple interventions in a random sequence with washout periods.
A method for assessing long-range temporal correlations and self-similarity in non-stationary EEG signals.
Experimental design carried out in naturalistic, real-world settings rather than in controlled laboratories.
Invasive recording of brain activity from the cortical surface.
A graphic record of the variation with time of voltages taken from electrodes on the scalp, whose positions are specified according to a standard system.
A graphic record of the variation with time of voltages produced by the electrical activity of muscle fibers, recorded via electrodes placed on the skin or inserted into the muscle.
Technique for recording electrical activity in peripheral nerves, complementing central modalities.
Experiment where trials are randomized and interspersed, enabling analysis of transient responses to events.
An increase in oscillatory brain activity due to an external or internal event
Using extracted features to classify or decode the user's intent. It is typically the next step after feature extraction, using algorithms to categorize features into meaningful classes for BCI applications.
Automatic extraction of distinctive patterns from complex neural data.
Transforming time-domain signals into the frequency domain to analyse the signals' characteristics at different frequencies.
Systematic tuning of model parameters to achieve optimal neural decoding performance.
A statistical method used to separate a multivariate signal into its independent, constituent sources. In BCI, it is most commonly used for artifact removal, such as separating eye blinks and muscle noise from the underlying brain signals.
A graphic record of the variation with time of voltages taken from electrodes placed onto or deeply inserted into the brain to directly record electrical activities of the brain through sensors.
A subfield of AI focused on enabling machines to learn from data and improve performance on specific tasks without explicit programming.