EEG based interpretation of human brain activity during yoga and meditation using machine learning: A systematic review.
Complementary Therapies in Clinical Practice February 14, 2021 Padmavathi Kora, K. Meenakshi, K. Swaraja et al.
A systematic review of 120 articles examined how machine learning methods classify brain waves (EEG) recorded during yoga and meditation. The review found that various meditation styles—Zen, CHAN, mindfulness, TM, Rajayoga, Kundalini, and yoga—produce distinct EEG patterns. Classification algorithms including KNN, SVM, random forest, fuzzy logic, neural networks, and convolutional neural networks have been used to identify different mental states. Yoga practice may serve as an effective adjunctive treatment for clinical and aging populations. The authors conclude that more research is needed to reliably classify EEG signatures for different mental states.