A deep learning approach for analyzing brainwave signals during audio meditation in expectant mothers: variational mode decomposition with a CNN-BiLSTM model.
Biomedical physics & engineering express March 31, 2026 Daisy Das, Nabamita Deb, Saswati Sanyal Choudhury
Brief audio meditation measurably alters brain activity in pregnant women. EEG signals recorded during resting, meditation, and post-meditation states were analyzed using Variational Mode Decomposition and a hybrid deep learning model combining CNNs and Bidirectional LSTM networks. The model classified the three mental states with 94.79% test accuracy, demonstrating that short-term cognitive modulation can be detected reliably. The findings provide an objective framework for evaluating meditation's neural effects during pregnancy, supporting its potential as a non-pharmacological intervention for stress, anxiety, and depression in maternal care.