IoT-Powered Mental Healthcare: Sleep State Analyzing and Monitoring Based on EEG Signals

Abstract

Nowadays, people frequently suffer from sleep deficiency. When this state continues for a long time, it undermines their physical health and mental health. With recent advancement in Internet of Thing (IoT), artificial intelligence (AI), and neuroscience, there is more room for developing efficient healthcare systems. In this paper, we propose an architecture for effectively building a mental healthcare system to analyze and monitor users' sleep states, from which their mental health can be protected. The architecture consists of three main components, Edge Device, Cloud Server, and UI Application. The Edge Device is responsible for tracking electroencephalogram (EEG) signals, i.e., brainwave signals. The Cloud Server is employed to process the collected EEG signals and relies on various modern AI models to analyze and predict EEG activities and sleep stages. The UI Application allows the users to access and interact with the results of their mental health. The proposed architecture under the support of IoT and AI has successfully demonstrated its efficiency, accuracy, and convenience through a prototype system.