![]() Also, the patient benefits from this less intrusive method compared to PSG. Another advantage is that during the night, the ECG signal is relatively stable as movement artifacts are quite rare. The ECG signal on its own is easy to conduct, requiring only 2–3 electrodes which can be placed correctly even without being specially trained. It is obvious that there is a demand for a way of automatic (computer-assisted) sleep analysis that is cheaper, less obtrusive, and furthermore easy to be used by ordinary persons at home. Both the application of all the sensors beforehand as well as the evaluation of the acquired data is time consuming and has to be done by specialists in order to give correct results. Furthermore, he has to “suffer” extensive wiring which often disrupts or impedes sleep even more. The patient has to stay for several nights as most of the time, during the first night, his normal sleep cannot be observed because the environment is too unfamiliar. The use of 30-s windows is based on the fact that, when the body signal curves were printed to paper, one page equated to 30 s.īut PSG is extensive: It is an 8–12-h investigation, which requires the patient to stay at a special laboratory. Figure 1 shows an example of such a diagram. ![]() On the basis of these signals and of specific rules established by Rechtschaffen and Kales, a sleep structure curve, divided into 30-s windows (epochs), is provided. These signals are the electroencephalogram (EEG), electrocardiogram (ECG), electrooculography (EOG) or eye movement, pulse oximetry (SpO 2), and electromyography (EMG) as well as muscular activity. Multiple electrophysiological signals are recorded to determine the sleep stages. Up until today, the gold standard in sleep investigation is a sleep study or an overnight polysomnography (PSG). For the diagnosis of sleep disorders, the investigation of the sleep structure during the night is an important aspect. In our fast-paced, 24-h modern society, the amount of sleep-related disorders are increasing, amongst others because many people are not achieving the required amount of sleep they need (e.g., due to night shift work). Both quantity and quality of sleep are important to stay healthy. Not only is it the part of the day when the body rests and regenerates, sleep is also relevant for our physical and mental health in many ways. Sleep is an important part of our lives as we spend on average one third of it sleeping. With an agreement rate of 41.3%, this approach is a good foundation for future research. ECG data along with a hypnogram scored by professionals was used from Physionet database, making it easy to compare the results. ![]() From the heart rate, using the fast Fourier transformation (FFT), three parameters were calculated in order to distinguish between the different sleep stages. This would make it possible for sleep analysis to be performed at home, saving a lot of effort and money. In this paper, a sleep stage detection algorithm is proposed that uses only the heart rate signal, derived from electrocardiogram (ECG), as a discriminator. But the recording of the necessary electrophysiological signals is extensive and complex and the environment of the sleep laboratory, which is unfamiliar to the patient, might lead to distorted results. The gold standard in this domain is an overnight polysomnography (PSG). To evaluate the quality of sleep, it is important to determine how much time was spent in each sleep stage during the night. ![]()
0 Comments
Leave a Reply. |