• Deepak Antony J N
• Kirubakaran S
• Kowsik S
• Logeshwaran S
• Anila S

With the rapid pace of modern life, millions of people suffer from sleep problems. Music therapy, as a non-medication approach to mitigating sleep problems, has attracted increasing attention recently. Sleep disorders, affecting up to 30% of adults, are a common health problem in our society and may result in fatigue, depression, and problems in daytime functioning EEG-based sleep quality recommendation system music therapy offers an alternative healing method, which improves sleep quality by playing back music at bed time. EEG signal of the subject is recorded using the Thought Evoked Potential paradigm. The proposed system automatically sends an alert message to the subject stating that his sleep quality is poor when the power delta value falls less than 5µV2 and recommends a music playlist which improves the sleep quality of the subject. The process is repeated continuously till the sleep quality is improved and the power delta value is changed to 140 µV2.The process repeats continuously till the sleep quality is improved A conclusion is obtained from the standard dataset of 50 trials in the proposed system. The acquired data set is preprocessed to eliminate signal artifacts and the Features are extracted by Fast Fourier Transform to get a conclusive result. Twilio API is used to send alert message to the subject. From the observations made, the results show mixed sleep quality attainment. Among the subjects tested, 16.7% attained good sleep quality within two iterations of playlist shuffle, 66.7% of the subjects required 10 playlist shuffles to attain good sleep quality. The remaining 16.7% of the subjects couldn’t attain good sleep quality even after 20 playlist shuffles which implies, they require serious medical attention and they are recommended for medical consultation.

"An EEG Based Sleep Quality Analysis and Music Recommendation System for Insomnia Patients", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 1, page no.a230-a234, January-2022, Available :http://www.jetir.org/papers/JETIR2201029.pdf

"An EEG Based Sleep Quality Analysis and Music Recommendation System for Insomnia Patients", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 1, page no. ppa230-a234, January-2022, Available at : http://www.jetir.org/papers/JETIR2201029.pdf