Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction.
2005 (Swedish)In: Medicinteknikdagarna, 2005, Vol. 12, 812-815 p.Conference paper, Abstract (Other academic)
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 0 25, 0 50 0 33, 0 46 0 35, and 0 94 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.
Place, publisher, year, edition, pages
2005. Vol. 12, 812-815 p.
Bioacoustics, heart sound (HS), lung sound (LS), nonlinear prediction, recurrence time statistics.
Medical Equipment Engineering Signal Processing
IdentifiersURN: urn:nbn:se:liu:diva-122019DOI: 10.1109/LSP.2005.859528OAI: oai:DiVA.org:liu-122019DiVA: diva2:861256