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Human sleep stages wring whole night are usually classified into six stages based on polysommnographic (PSG) record. Sleep state of human light sleep changes gradually and continuously. In this study, automatic judgment of light sleep state in PSG record was developed. Parameters for characterizing the PSG were calculated from the periodogram and the discriminant function was constructed by using...
Sleep apnea/hypopnea syndrome (SAHS) is one of serious sleep disorders. EEG arousals due to the apnea hypopnea are frequently appeared in polysomnographic (PSG) record in patients with SAHS. In this study, the method for detecting EEG arousals and apnea interval in PSG record was proposed for supporting visual inspection to classify respiratory levels and EEG arousals. Two threshold values were established...
In this study, the multivariate probability distribution was investigated to develop the expert knowledge-based automatic sleep stage determination technique. The ultimate purpose is to develop adaptive automatic sleep stage determination algorithm for clinical practice. Gaussian distribution was adopted to realize automatic parameter selection while Cauchy distribution was adopted to estimate the...
An automatic sleep stage determination system dealing with the sleep data contaminated by artifacts is developed, which is working on an expert knowledge-based multi-valued decision making method. The knowledge database is consisted of probability density functions of parameters for various sleep stages according to the visual inspection by a qualified clinician. The probability density functions...
This paper introduced an expert knowledge-based automatic sleep stage determination system working on statistical signal processing. The main methods included two processes. One was expert knowledge base construction, which was developed in terms of probability density functions (pdfs) of parameters for each sleep stage. Here, the visual inspection by a clinician was utilized rather than stage scoring...
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