Advances in Automatic Sleep Analysis

Abstract

In this paper we investigate the innovative spectral analysis techniques that have been used in sleep analysis with some success. A comparative analysis of these proposed classification techniques have been presented and the findings discussed. The paper identifies the problems faced in interpreting published results and performs an accurate comparison of different proposed systems. Future strategies to improve the performance of sleep analysis algorithms and novel signal processing tools suitable for sleep analysis are proposed.