An enhanced respiratory rate monitoring method for real tracheal sound recordings

This paper addresses the problem of non-invasive respiratory rate (RR) monitoring using single channel tracheal sound (TS) recordings. We have recently developed a robust respiratory phase segmentation method based on genetic algorithm (GA) which works well only for preprocessed clean TS. Therefore, an enhanced respiratory phase monitoring method is proposed in this paper by exploiting the signal redundancy to our existing method. In this context, appropriate overlapping windows have been applied to ensure sufficient redundancy of TS signals. The performance of the enhanced method is analyzed for different types of real TS and standard preprocessed TS. The average accuracy of respiratory phase segmentation found for real TS is comparable to that of the standard preprocessed data by our proposed method.