Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction

• Published in: IEEE signal processing letters 2005-12, Vol.12 (12), p.812-815
• Main Authors: Ahlstrom, C., Liljefeldt, O., Hult, P., Ask, P.
• Format: Article
• Language: English
• Subjects: Bioacoustics; Detection algorithms; Error analysis; Frequency; Heart; heart sound (HS); lung sound (LS); Lungs; nonlinear prediction; Performance evaluation; recurrence time statistics; State-space methods; Statistics; TECHNOLOGY; TEKNIKVETENSKAP; Testing; Trajectory
• ISSN: 1070-9908; 1558-2361; 1558-2361
• DOI: 10.1109/LSP.2005.859528

Heart sounds (HS) obscure the interpretation of lung sounds (LS). This letter presents a new method to detect and remove this undesired disturbance. The HS detection algorithm is based on a recurrence time statistic that is sensitive to changes in a reconstructed state space. Signal segments that are found to contain HS are removed, and the arising missing parts are replaced with predicted LS using a nonlinear prediction scheme. The prediction operates in the reconstructed state space and uses an iterated integrated nearest trajectory algorithm. The HS detection algorithm detects HS with an error rate of 4% false positives and 8% false negatives. The spectral difference between the reconstructed LS signal and an LS signal with removed HS was 0.34/spl plusmn/0.25, 0.50/spl plusmn/0.33, 0.46/spl plusmn/0.35, and 0.94/spl plusmn/0.64 dB/Hz in the frequency bands 20-40, 40-70, 70-150, and 150-300 Hz, respectively. The cross-correlation index was found to be 99.7%, indicating excellent similarity between actual LS and predicted LS. Listening tests performed by a skilled physician showed high-quality auditory results.