Abstract
In this study, an automatic sleep-stage determination system with the capacity for artifact detection was developed. The methodology was based on the conditional probability of the knowledge base of an expert visual inspection. Expert visual inspection was the manual scoring of sleep stages and artifacts by a qualified clinician. The knowledge base consisted of probability density functions of characteristic parameters for stages and artifacts. Automatic sleep-stage determination and artifact detection were carried out based on a value of conditional probability. The total overnight bioneurological signals under the usual recording conditions with the artifacts of four subjects were analyzed. The results of automatic sleep-stage determination showed a close agreement with the expert visual inspections. In addition, an artifact can be detected at the same time by using the same method. With the capacity for artifact detection, the proposed automatic sleep-stage determination system can be adapted for real clinical applications.
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Wang, B., Wang, X., Zou, J. et al. Automatic determination of sleep stage through bio-neurological signals contaminated with artifacts by a conditional probability of the knowledge base. Artif Life Robotics 12, 270–275 (2008). https://doi.org/10.1007/s10015-007-0480-6
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DOI: https://doi.org/10.1007/s10015-007-0480-6