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Develop your own app using Muse’s SDK—handling Bluetooth connectivity, async data, and raw EEG/PPG/accelerometer streams. Includes .muse file support, simulated playback, and logging tools.

Available for iOS & Android; Windows, Unity & Unreal coming soon.

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CONDUCTING RESEARCH WITH MUSE?

Researchers: request access to our validated, peer-reviewed EEG tools and study protocols.

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THE POWER OF EEG TECHNOLOGY

EEG tracks electrical brain activity in real time, revealing patterns linked to consciousness, sleep, cognition, and neurological health. Once lab-bound, this tech is now portable and accessible for clinical and field research.

ACCURACY AT SCALE

Muse delivers research-grade EEG validated in applications like stress, anxiety, stroke, MCI, and sleep. Trusted by clinicians and scientists globally.

Stress

Anxiety

Sleep

Mild cognitive impairment

Stroke

BIOFEEDBACK TRAINING MEETS MEDITATION

Biofeedback training, especially when linked with meditation, is an effective method that helps users gain more control over their body’s and brain’s functions and responses.

Here's how it works: Muse gives users real-time audio feedback on their brain activity to reinforce an optimal meditative state. Muse measures the user's brainwave patterns, heart rate, and breathing then gives them real-time audio.

Feedback on their mental state to let them know when they’re in the zone.

Over time, this can improve their ability to focus, reduce stress, and enhance self-awareness.

AI-ENHANCED SLEEP DIAGNOSTICS

Advancing Sleep Research with Foundation Model EEG

Validated sleep staging (Cohen’s Kappa: 0.76)
Applications in long COVID, migraine, and cognitive aging
Introduction to Alpha Peak, Brain Recharge & AI-driven sleep metrics
Athena enables real-time, in-home trials using multimodal data streams

RESEARCH HIGHLIGHTS

Muse is featured in 200+ peer-reviewed studies on:

Stress & Anxiety (EEG classifiers, LSTM models)
PTSD & OCD (neurofeedback, mindfulness)
Cognitive Fatigue (rapid ERP, N200 amplitude)
Stroke & MCI (early detection, intervention support)

Stress

Classification of Perceived Mental Stress Using A Commercially Available EEG Headband

Human stress classification using EEG signals in response to music tracks

Stress Classification Using Brain Signals Based on LSTM Network

Mindfulness Using a Wearable Brain Sensing Device for Health Care Professionals During a Pandemic: A Pilot Program

Use of a Wearable EEG Headband as a Meditation Device for Women With Newly Diagnosed Breast Cancer: A Randomized Controlled Trial

Electroencephalographic monitoring of brain wave activity during laparoscopic surgical simulation to measure surgeon concentration and stress: Can the student become the master?

Human stress classification during public speaking using physiological signals

Perceived Stress Detection through EEG Data Segmentation and Classification

Anxiety

A study on multi-class anxiety detection using wearable EEG headband.

A scalable and robust system for audience EEG recordings

Day-to-day individual alpha frequency variability measured by a mobile EEG device relates to anxiety

Mobile Quantitative EEG Assessment and Children’s Preoperative Anxiety: a Psychometric and Feasibility Study

PTSD

The Effectiveness of Using Neurofeedback in the Treatment of Post-Traumatic Stress Disorder: A Systematic Review

A Randomized Controlled Study of Neurofeedback for Chronic PTSD

Cognitive Fatigue / Impairment

Using Muse: Rapid Mobile Assessment of Brain Performance

Classification of Cognitive Fatigue with EEG Signals

Eliciting brain waves of people with cognitive impairment during meditation exercises using portable electroencephalography in a smart-home environment: a pilot study

Supporting Mindfulness Practices with Brain-Sensing Devices. Cognitive and Electrophysiological Evidences

Classification of Cognitive Fatigue with EEG Signals

Screening for Mild Cognitive Impairment with Speech Interaction Based on Virtual Reality and Wearable Devices

Classification of mild cognitive impairment based on handwriting dynamics and qEEG

Feasibility of Wearable Sensors to Assess Cognitive Load During Clinical Performance: Lessons Learned and Blueprint for Success

Low global frontal brain activity is associated with non-planned or impulsive suicide attempts. A preliminary study

Other Medical Applications

Technology supported mindfulness for obsessive compulsive disorder: Self-reported mindfulness and EEG correlates of mind wandering

Predicting stroke severity with a 3-min recording from the Muse portable EEG system for rapid diagnosis of stroke

Application of the Muse portable EEG system to aid in rapid diagnosis of stroke

Stroke identification using a portable EEG device – A pilot study

Choosing MUSE: Validation of a low-cost, portable EEG system for ERP research

Characterizing population EEG dynamics throughout adulthood

Validating the wearable MUSE headset for EEG spectral analysis and Frontal Alpha Asymmetry

Automated Sleep Staging on wearable EEG enables Sleep Analysis at scale

Do try this at home: Age prediction from sleep and meditation with large-scale low-cost mobile EEG

Wearable Technologies for Mental Workload, Stress, and Emotional State Assessment during Working-Like Tasks: A Comparison with Laboratory Technologies

Regulation of brain cognitive states through auditory, gustatory, and olfactory stimulation with wearable monitoring

Trait mindful awareness predicts inter-brain coupling but not individual brain responses during naturalistic face-to-face interactions

Exercising is good for the brain but exercising outside is potentially better

EEG-Based Emotion Classification Using Stacking Ensemble Approach

High-intensity interval exercise impairs neuroelectric indices of reinforcement-learning

Chasing the zone: Reduced beta power predicts baseball batting performance

Robust learning from corrupted EEG with dynamic spatial filtering

Uncovering the structure of clinical EEG signals with self-supervised learning

Deep learning-based electroencephalography analysis: a systematic review

A deep evolutionary approach to bioinspired classifier optimisation for brain-machine interaction

Evaluating the feasibility of a consumer-grade wearable EEG headband to aid assessment of state and trait mindfulness

Using portable EEG to assess human visual attention

EEG-based classification of imagined digits using a recurrent neural network

Brain-EE: Brain enjoyment evaluation using commercial EEG headband

A personalized reading coach using wearable EEG sensors: A pilot study of brainwave learning analytics

A Short Virtual Reality Mindfulness Meditation Training For Regaining Sustained Attention

Conscious, Pre-Conscious and Unconscious Mechanisms in Emotional Behaviour. Some Applications to the Mindfulness Approach with Wearable Devices

Player Engagement Classification in Mobile Games Using MUSE Headband

Evaluation of the User Adaptation in a BCI Game Environment

Machine Learning-based Approach for Stroke Classification using Electroencephalogram (EEG) Signals

A predictive method for emotional sentiment analysis by deep learning from EEG of brainwave dataset

A Comparative Analysis of Machine and Deep Learning Techniques for EEG Evoked Emotion Classification

Mindfulness Meditation and Interprofessional Cardiopulmonary Resuscitation: A Mixed Methods Pilot Study

Modulation of Neural Activity during Guided Viewing of Visual Art

Sans Tracas: A Cross-platform Tool for Online EEG Experiments.

Dementia Digital Neuro-biomarker Study from Theta-band EEG Fluctuation Analysis in Facial and Emotional Identification Short-term Memory Oddball Paradigm

Using a Wearable Brain Activity Sensing Device in the Treatment of Long COVID Symptoms in an Open-Label Clinical Trial

NeuroChat: A Neuroadaptive AI Chatbot for Customizing Learning Experiences

RAPID FATIGUE DETECTION

In a 1,000-participant ERP study, Muse assessed cognitive fatigue in under 7 minutes via N200 signals—linking mental load to error rates and real-world risk. A breakthrough in scalable brain-state assessment.