New Deep Learning Discovery Paves Way for AI Interpretation of Brainwave Data
Summary
Machine learning has the potential to relieve some of this burden, but EEG data is extremely multidimensional and can be expensive, and time-consuming to annotate. This means there are typically not enough labelled examples for supervised deep neural networks to learn from in order to create an efficient AI. This has potential to improve the performance of algorithms used in everything from consumer sleep and wellness support tools like Muse S, to swifter diagnosis of neurological disorders. • Research institutions using Muse®: The Mayo Clinic, NASA, Harvard, MIT, U of T, UCL, UCSD, Inria, UVic, UBC, and many more. • Meditating with Muse® works: A recent study at the Catholic University of Milan showed that four weeks with Muse® significantly reduced stress as well as potentially influenced beneficial neuroplastic changes in users’ brains, compared to controls.