Investigating the Accuracy of Sleep Stage Classification in Pediatrics: A Comprehensive Review

Getting sufficient sleep is a crucial component of maintaining overall wellness for human beings. The quality of one's sleep has a direct impact on it. In order to understand the problems related to sleep, it is important to study sleep stages. In this fast-paced world challenges can be both physically and mentally and quality of sleep is as essential to lead a healthy life. The process of categorizing sleep stages is arduous and requires a significant amount of time. There have been numerous automatic techniques devised to tackle this issue. Deep learning algorithms like CNN, RNN and machine learning algorithms which include SVM, RF, LSTM, KNN, which are implemented over sleep recordings like PSG, EEG etc, despite the prevalence of adult sleep stage classification methods, there is a need to create pediatric sleep stage classification methods since sleep problems in children are significantly more widespread than in adults. This study discusses many pediatric sleep stage categorization approaches that have been proposed in recent years and their analysis.