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. 2022 Mar 17;13:791768. doi: 10.3389/fpsyg.2022.791768

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Copyright © 2022 Amores, Dotan and Maes.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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The system reads brain activity signals and sends this information from the EEG to the smartphone via Bluetooth Low Energy (BLE). The app integrates a pre-trained machine learning model that takes 30 s worth of data from the EEG and predicts a sleep stage with a given accuracy. The user or experimenter can customize the duration and frequency of the olfactory stimulation in certain sleep stages using the smartphone app. Scent can be activated manually using a button, or automatically based on physiological signals, such as heart rate and breathing rate. The system can also release scent based on the user's sleep stage, or based on time, e.g., 20 min after going to sleep.