freeMind
Link to the freeMind Github Project
17 million people in the United States are affected by depression each year. While there are many anti-depressants that work, less than a third of the people who use them get the right one on the first try. It takes any time from weeks, up to a year for patients to know if the antidepressants are working. freeMind is a tool that assists healthcare professionals in identifying depression, as well as predicting whether or not anti-depressant drugs will succeed for participants. This product is a combination of the Muse Brain Sensing Headband, Indico Machine Learning API, Facebook's Javascript SDK, and Firebase's Real Time Databases.
Brain Waves The brain is composed of billions of neurons, which communicate with eachother using electricity. When we look at the big picture, all of the electric signals combine into brain waves. Brain waves can be categorized through five bandwidths: Delta, Theta, Alpha, Beta, and Gamma (in order of rising frequency). Delta and Theta waves are typically emitted during sleeps states. Alpha waves are most prominent during states of daydreaming and meditation. Beta waves are emitted when people are deep in thought and trying to solve problems. Gamma waves are emitted when different areas of the brain are simultaneously processing information.
Brain Waves, Mental Illness, and Remission Prediction According to the Journal of Neuroscience, an increased amount of alpha waves and decreased amount of beta waves help to reduce anxiety and panic attacks. When alpha waves are prominent, the mind is more clear of unwanted thoughts. By measuring the brain waves of a patient throughout a week, it is possible to generate relatively accurate predictions of whether or not the patient will go into remission with their current antidepressant. While the patient is using the antidepressant, the ratios of the alpha vs delta and theta waves are measured. If alpha waves are increasing relative to delta and theta waves, the drug is working properly. If the delta and theta waves increase with respect to the alpha waves, the drug might not be the right one for the patient.
How freeMind Works In the healthcare professional's office, the patient will put on the Muse Brain Sensing Headband, which in turn measures the patient's brain waves. The separate waves will be recorded into the Firebase Database. The participant will then log in to answer eight questions about their lives. The answers that the participants type are analyzed using Indico's Machine Learning API for general sentiment and emotions. The results are run through freeMind's algorithm and provides a general trend of their sentiment and emotions, in addition to the trends in alpha, beta, delta, theta, and gamma waves. This information combined will offer advice to healthcare professionals to make the correct decisions. Another feature of freeMind is that participants can connect their Facebook accounts for the Indico Machine Learning API to determine a general trend of the sentiment and emotions through their post histories. By aiding healthcare professionals in making correct decisions, freeMind is setting a path towards a future without mistaken prescriptions for mental illnesses.
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