Author: Allison Peng
What are BCIs, and how do they work? Brain-computer interfaces allow for humans to interact with machines in real time using brain waves. After brief training periods that associate brain signals with user intent, computers are able to determine user intent in different tasks using brain signal data. BCIs can be independent, where users only interact with machines with brain signals, or dependent, where some slight movements from the user, such as changing eye gaze direction.
Signaling methods and types of signals The most common signaling methods used with BCIs include EEG, ECoG, and MEG, which vary in spatial and temporal resolution, making them suited to different types of BCI.
EEG data can be analyzed for various types of signals, which help computers decode user intent. Many of these signals are sensory evoked potentials or event-related potentials, which are detailed below.
Uses of BCI Although widespread everyday use of BCI is not yet possible, due to interference, high numbers of artifacts, and variability, these are some goals for the development of brain-computer interfaces.
Check out this document to learn more about BCIs!
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