Single Channel EEG for Near Real-Time Sleep Stage Detection

Sleep disorders are considered as one of the major human life issues in the recent years. Therefore, efficient and automated systems that can differentiate sleep stages and assist physicians/neurologists in the diagnosis and treatment of sleep-related disorders, are highly on demand. The present paper is devoted to developing an easy-to-implement sleep stage classification algorithm that works fast (near real-time) in a proficient way. The proposed algorithm is based on two statistical features applied to single-channel EEG signals. We examined the effectiveness of our technique by building a near real-time detection system using the Neurosky's Mindwave Mobile device, an affordable wireless EEG headset, to obtain EEG signals. The system is one-way without feedback loops. The results of analyzing our algorithm show that the run-time performance of this detection technique is quasi-linearly proportional to the size of the input samples and the execution time is fast, regardless of the time recording the data.

I. Introduction

Sleep is the primary function of the brain and plays an essential role in an individual's performance, learning ability and physical movement [1], [2]. Recently, sleep disorders are indicated as one of the main causes that severely affect human physical health and daily life [3]–[5]. According to a survey, an estimated 50–70 million adults in the United States have a sleep disorder [6], [7]. Sleep issues may cause sleepiness, depression or even death [8], [9]. Moreover, police reports indicate that up to 3% of road traffic accidents and 4% of fatalities are attributed to sleep-related causes [10], [11]. Consequently, there is a need to develop a real-time, easy-to-use, and economical device for automatically detecting and analyzing sleep patterns to classify sleep-related conditions including fatigue, drowsiness, or sleep disorders, such as apnea, insomnia or narcolepsy. Sleep stage classification can be automatically identified using a single EEG channel. Several methods have been proposed using available electrodes with sophisticated headset devices that are directly attached to a subject to acquire the EEG signals [12]–[14]. One such device is the NeuroSky Mindwave Mobile device, which is one of the most obtainable, smallest and affordable EEG headsets that gathers the user's mind waves [15], released by NeuroSky, Inc. Neurosky Mindset is categorized as an electrode-based and an appropriate device that can read EEG signals from the human brain, as illustrated in Figure 1 [16] [17]. Figure 1.

Neurosky mindwave mobile device