EEG & Biofeedback Research from Muse

MUSE RESEARCH

Featured research with Muse

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.

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Research Projects Involving Muse

Attentional and Affective Consequences of Technology Supported Mindfulness: a Randomised Trial

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.

Read the Paper in BMC Psychology >

Characterizing Population EEG Dynamics throughout Adulthood

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.

Read the Paper in eNeuro >

Novel Speed-of-Learning Effects Detected in Neurofeedback

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).

Read the Paper in PLOS One >

Neuroscientists Study Meditation-Related Changes in Brain Performance

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.

Watch the video >

Identifying Pain with an Adaptive Brainwave Learning System

Researchers at MIT and Harvard used machine learning to detect and distinguish signals associated with pain when participants wore Muse.

See paper 1 >
See paper 2 >

Using Muse to Measure Event-Related Potentials Outside of the Lab.

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.

Read in Frontiers in Neuroscience >

Watch the video >

Identifying Mental States with Machine Learning

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.

Read the preprint on ArXiv >

Vigilance Lapse Identification With Muse

Researchers from McMaster University used EEG machine learning tools to detect lapses in vigilance (sustained attention) state of participants wearing Muse.

Read the paper on IEEE Xplore >

Integration of Muse with Virtual Reality

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.

Research Resource Identifier (RRID)

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).

Learn More >