Muse is a powerful, compact electroencephalography (EEG) system. By leveraging improvements in dry sensor technology, Bluetooth and battery life, as well as significant advances in digital signal processing, Muse makes it easy to access and use brainwave data, inside and outside the laboratory and in real-world environments.
Dr. Norman Farb’s laboratory at the University of Toronto showed that six weeks’ regular use of Muse in healthy adults resulted in improvements in attention, as well as reduced somatic symptoms (headaches, pain, discomfort, etc.) on the Brief Symptom Inventory.
A study by researchers at McMaster University involving more than 6000 participants found population-level effects in brain data related to age and gender, giving scientists unparalleled resolution into how EEG brain dynamics change with age.
A study by Dr. Randy McIntosh’s lab at the Rotman Research Institute demonstrated previously unreported speed-of-learning effects in MyVirtualDream, a virtual neurofeedback environment powered by Muse. This effect, being subtle, was detectable only using a technology capable of testing a very large number of people (600) in a short time (twelve hours).
Neuroscientists at the University of Victoria and the University of British Columbia use Muse in their field work in Nepal to study the brains of Buddhist monks, who are highly expert meditators, to better understand how training affects the way the brain makes decisions.
Researchers at MIT and Harvard used machine learning to detect and distinguish signals associated with pain when participants wore Muse.
At the University of Victoria, in Canada, scientists are using Muse to measure event-related potentials (ERPs) in cognitive tasks. This research is also being applied to measure changes in decision making in response to fatigue – in ER doctors in the Emergency Room.
Researchers at the University of Memphis and IBM Watson Research Center found that by using machine learning to analyse brainwave signals from Muse, while participants watched different videos, they could determine what type of content (emotional or educational) each participant was seeing.
Researchers from McMaster University used EEG machine learning tools to detect lapses in vigilance (sustained attention) state of participants wearing Muse.
Students, scientists, and makers from around the world use Muse to create engaging and immersive experiences. One great example is PsychicVR, a virtual reality experience powered by Muse, that was created by Judith Amores Fernandez, Pattie Maes, and Xavier Benavides Palos, which won a Fast Innovation Company by Design award.
If you’re publishing research papers with Muse, make them more easily identifiable to other scientists through the Research Resource Identifier (RRID) initiative. Don’t forget to insert Muse’s unique identifier in your paper’s methods section when you first mention Muse, like this: Muse (SCR_014418).
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Researchers using Muse can access the same professional tools as clinicians through the Muse Professionals Program.
For questions or help using Muse in your research, or education program - please contact us!
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