Muse is a brain-sensing headband that helps you refocus during the day and recover overnight.
EEG-powered sleep tracking insights including sleep stage visualization, sleep position tracking, and a personalized sleep efficiency score.
Muse S helps you understand and track how well you focus, sleep, and recharge so you can refocus during the day and recover each night.
Muse connects to your mobile device via Bluetooth. Once connected, simply start the Muse Meditation app, put on your headphones, and close your eyes.
Once your session is complete, you can review your results and track your progress.
Muse is an EEG device widely used by neuroscience researchers around the world. It uses advanced signal processing to interpret your mental activity to help guide you. When your mind is calm and settled, you hear peaceful weather. Busy mind? As your focus drifts, you’ll hear stormy weather that cues you to bring your attention back to your breath.
Transforming Brain Signals Into Real-time Feedback
Muse detects a range of brain electrical activity and transforms it into easily understandable experiences. The Muse app transforms raw brain signals into many different components – noise, oscillations, non-periodic characteristics, and transient and event-related brain events. Signal processing and machine learning techniques are applied to the brain signal components to control the experience in real time.
If you are interested in recording, visualizing, and streaming EEG and movement sensor data with Muse – from raw data and band powers to head movement and rotation – the Muse headband can be used in combination with Muse Direct for iOS. Muse Direct can be used for applications like neurofeedback, research, art installations, education, and more!
Muse Translates Your Brainwaves Into the Guiding Sounds of Weather
Muse’s 7 finely calibrated sensors – 2 on the forehead, 2 behind the ears plus 3 reference sensors – detect and measure the activity of your brain.
The Muse app decomposes raw brainwave signals into their component oscillations, non-periodic characteristics, transient brain events, and noise, and uses techniques developed through machine learning to make the experience responsive, in real time.