EEG-to-Text
A method to transcribe brainwaves into readable text using AI.
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EEG-to-text is an advanced application of Artificial Intelligence (AI) and Machine Learning (ML) that involves transcribing electrical brain activity, specifically electroencephalogram (EEG) readings, directly into text. This cutting-edge technology works by using ML algorithms to analyze and interpret patterns in EEG data, then convert these patterns into corresponding text. The goal of EEG-to-text technology is to help augment human-computer interaction, with particularly important implications in assistive technologies for individuals with neurological disorders or speech and mobility impairments.
While the technology is in its nascent stages, groundbreaking research began making significant strides in the late 2010s. In 2020, a study published in Nature Neuroscience, reported that scientists were able to develop a technology that converted EEG readings from a person thinking about handwriting into actual sentences, marking a key moment for EEG-to-text in AI.
While the field of Brain-Computer Interfaces and neurotechnology involves several researchers globally, groups such as the NeuroLex Laboratories and researchers such as Francis Willett (author of the aforementioned 2020 study) are at the frontier of EEG-to-text technology. Their continued work holds the potential to revolutionize how humans and machines interact.