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Sleep Stage Classification Using DWT and Dispersion Entropy Applied on EEG Signals
Published in Varun Bajaj, G.R. Sinha, Computer-aided Design and Diagnosis Methods for Biomedical Applications, 2021
Rajeev Sharma, Sitanshu Sekhar Sahu, Abhay Upadhyay, Rishi Raj Sharma, Ajit Kumar Sahoo
We used a six-class classification, considering classes S1 to S4, W, and REM as suggested by the R&K standard, which has also been used in previous studies [11,19,20]. The newly proposed AASM standard suggests the use of a five-class classification, obtained by combining the S3 and S4 stages into a single class. Therefore, we considered a five-class classification as the most important type of classification. The sleep stages S1 and S2 can be combined as they are known as shallow sleep [20,35]. Further, the combination of S1 and S2 as a single class gives rise to a four-class classification. The S1, S2, S3, and S4 stages fall into non-REM categories. The classification between W, REM, and non-REM sleep stages can be helpful for the diagnosis of REM-sleep-related disorders [36,37]. Sometimes it is of interest to separate EEG signals related to sleep and awake conditions; therefore, we also studied a two-class classification. Figure 2.1 depicts an example of the 30-sec epochs of the different sleep stages of 3000 samples. Table 2.1 includes the total number of epochs which were used in this study.
Sleep and Fatigue
Published in Roger G Green, Helen Muir, Melanie James, David Gradwell, Roger L Green, Human Factors for Pilots, 2017
Roger G Green, Helen Muir, Melanie James, David Gradwell, Roger L Green
As the person starts to fall asleep alpha activity gives way to small, rapid irregular waves and the EOG shows slow rolling eye movements. This is Stage 1 sleep, a transitional phase between waking and sleeping (see Figure 3b.4). As sleep progresses the EEG contains increasing amounts of low frequency, high voltage activity (delta activity). Sleep stages 2-4 are largely defined by the amount of delta activity recorded, with the deeper stages of sleep (stages 3 and 4) having increasing amounts. Stages 3 and 4 are often referred to as slow wave sleep. The remaining stage of sleep is called rapid eye movement (REM) sleep, when this occurs the EEG becomes irregular (desynchronized), the EOG shows the eyes rapidly darting back and forth, and the EMG becomes silent indicating muscle relaxation (see Figure 3b.5). This sleep is sometimes termed 'paradoxical' sleep because of the EEG becoming similar to that of somebody who is awake.
Protocol and Process of EEG Data Acquisition
Published in Narayan Panigrahi, Saraju P. Mohanty, Brain Computer Interface, 2022
Narayan Panigrahi, Saraju P. Mohanty
The EEG signal is closely related to the level of consciousness of the person. As the activity increases, the EEG shifts to a higher dominating frequency and lower amplitude. When the eyes are closed, the alpha waves begin to dominate the EEG. When the person falls asleep, the dominant EEG frequency decreases. In a certain phase of sleep, rapid eye movement (REM), the person dreams and has active movements of the eyes, which can be seen as a characteristic EEG signal. In deep sleep, the EEG has large and slow deflections called delta waves. No cerebral activity can be detected from a patient with complete cerebral death. An example of each of the mentioned waveforms is depicted in Figure 5.2.
Analyzing the dynamics of sleep electroencephalographic (EEG) signals with different pathologies using threshold-dependent symbolic entropy
Published in Waves in Random and Complex Media, 2021
Lal Hussain, Saeed Arif Shah, Wajid Aziz, Syed Nadeem Haider Bukhari, Kashif Javed Lone, Quratul-Ain Chaudhary
Sleep is characterized by reduced sensory activity, reduced responsiveness to stimuli, and conscious awareness in comparison to the wakefulness [1]. A sleep-wake transition [2] concept can describe the basic model of sleep homeostasis. In humans, the sleep stages are conventionally classified as wake, rapid eye movement (REM) sleep, and non-REM sleep based on electroencephalographic (EEG) patterns, consisting of about 80% for entire sleep [3]. These sleep stages are dynamic transitions between various physiological states switching between the dual stable and unstable conditions to permit the environmental adaptations and to achieve the mental and physical restoration [4]. By employing the analysis of electroencephalography (EEG) signal, the quantification of sleep stages has always remained a challenge for the researchers for years. Visual sleep stage scoring does not fully capture the intrinsic dynamics of EEG activity [5].
Towards Patient-centered Diagnosis of Pediatric Obstructive Sleep Apnea—A Review of Biomedical Engineering Strategies
Published in Expert Review of Medical Devices, 2019
EOG is principally used as an adjunct to EEG and EMG to identify sleep staging. Both full montage and single-channel EEG may identify sleep state and transitions from REM to non-REM sleep. Standalone sleep staging using either surrogate channels such as electrocardiography (ECG) or the use of a subset of EEG channels has been shown to be useful in a small number of studies. For example, Berthomier et al. reported the use of a single channel EEG platform for the automated detection of sleep staging [27]. Conversely, two other studies investigated the use of 1–2 channels of EOG alone for sleep-wake identification [28,29]. However, the principal limitation is the reduced agreement with manual scoring in children with increasing severity of OSA.
Impact of shift work on sleep and fatigue in Maritime pilots
Published in Ergonomics, 2021
Jamie L. Tait, Timothy P. Chambers, Regan S. Tait, Luana C. Main
In addition to the aforementioned long working hours, maritime pilots are subject to ‘on-call’ work scheduling, with data indicating that pilots may spend up to 60% of their working time on-call (Nicol and Botterill 2004). In this format workers either sleep on site, or can remain at home, but must be available to work at short notice at all times of the day or night (Hall et al. 2017; Nicol and Botterill 2004). On-call maritime pilots may have the option of either sleeping locations. This form of occupational scheduling is known to impair workers’ sleep and stress physiology, ability to fall and stay asleep, and leads to a reduction in sleep duration. For example, increased stress caused by having to wake suddenly at unexpected times can stimulate the physiological stress system (i.e. the hypothalamic-pituitary axis). The resulting activation can lead to increased sleep fragmentation, light sleep, and reduced time in REM sleep, and a decrease in sleep duration and efficiency (Born et al. 1989; Buckley and Schatzberg 2005; Holsboer et al., 1988). Further, poor sleep can have a negative effect on the functioning of this axis (Balbo, Leproult, and Van Cauter 2010; Meerlo et al. 2002). Previous research in the fields of engineering, aviation, medicine, emergency services, and sailing have demonstrated that the quality and quantity of sleep is poorer when on-call compared to not-on call (Ernst et al. 2014; Hall et al. 2017; Lockley et al. 2004; Nicol and Botterill 2004; Pilcher and Coplen 2000; Torsvall and Åkerstedt 1988; Torsvall et al. 1987). For instance, total sleep time was 1 h shorter when on-call and sleeping at home in railroad engineers, compared to regular work assignments (Pilcher and Coplen 2000). Total sleep time was reduced by 132 min per night when on-duty and on-call, compared to when off-roster, in helicopter pilots on duty for emergency medical services (Samel, Vejvoda, and Maass 2004). On-call work was also associated with diminished mental health and well-being, increased stress, and a disturbance of social functioning and activities (Hall et al. 2017; Nicol and Botterill 2004), which may collectively compromise physical health. Despite this research, it is unclear as to what extent on-call work may affect sleep quality and quantity in maritime pilots.