Feature extraction and calibration of EEG signals in sitting and walking meditation
International Conferences on Knowledge Innovation and Invention July 1, 2019 Min Huang, Junze Chen, Changle Zhou
Meditation benefits physical and mental health, but walking meditation is understudied. This work recorded EEG signals from 7-Day Zen participants in four states: sitting around, strolling, sitting meditation, and walking meditation. Rhythm-based EEG features were extracted and calibrated to classify the states. Personalized calibration methods effectively addressed individual differences in EEG signals, and the system identified the four states with high accuracy, offering insight into neural activity during different meditation forms.