Developing Low-cost Electroencephalography-based Sleep Monitoring System with Neurosky's Think Gear ASIC Module

Insomnia is the most common sleep disorder and etiology for a series of health problems. Researchers indicated that environmental factors negatively influence sleep, including environmental noise and indoor light intensity. To explore the relationship between these factors and sleep, low-cost Internet of Things (IoT) systems were developed for monitoring environmental data related to sleep quality. In this study, we created an IoT system based on Electroencephalography (EEG) signals for monitoring sleep quality. The suggested system detects indoor environment variables during sleep, such as color temperature, air quality, and sound noise level. Additionally, we collected environmental and brainwave data for sleep with LINE notifications. In the proposed system, we deployed with Neurosky's Think Gear Asic module (TGAM)-based chip to acquire human brainwaves for determining sleep states. At the same time, we employed a Node-rapid event developer (RED) platform to display sensor data. Finally, the proposed system can effectively work over Raspberry Pi.