TY - GEN
T1 - Automatic segmentation of heart sound signals using hidden Markov models
AU - Ricke, A. D.
AU - Povinelli, R. J.
AU - Johnson, M. T.
PY - 2005
Y1 - 2005
N2 - The monitoring of respiration rates using impedance plethysmography is often confused by cardiac activity. This paper proposes using the phonocardiogram as an alternative, since the process of respiration affects heart sounds. As part of this research, a technique is developed to segment heart sounds into its component segments, using Hidden Markov Models. The heart sounds data is preprocessed into feature vectors, where the feature vectors are comprised of the average Shannon energy of the heart sound signal, the delta Shannon energy, and the delta-delta Shannon energy. The performance of the segmentation system is validated using eight-fold cross-validation.
AB - The monitoring of respiration rates using impedance plethysmography is often confused by cardiac activity. This paper proposes using the phonocardiogram as an alternative, since the process of respiration affects heart sounds. As part of this research, a technique is developed to segment heart sounds into its component segments, using Hidden Markov Models. The heart sounds data is preprocessed into feature vectors, where the feature vectors are comprised of the average Shannon energy of the heart sound signal, the delta Shannon energy, and the delta-delta Shannon energy. The performance of the segmentation system is validated using eight-fold cross-validation.
UR - http://www.scopus.com/inward/record.url?scp=33847098808&partnerID=8YFLogxK
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U2 - 10.1109/CIC.2005.1588266
DO - 10.1109/CIC.2005.1588266
M3 - Conference contribution
AN - SCOPUS:33847098808
SN - 0780393376
SN - 9780780393370
T3 - Computers in Cardiology
SP - 953
EP - 956
BT - Computers in Cardiology, 2005
T2 - Computers in Cardiology, 2005
Y2 - 25 September 2005 through 28 September 2005
ER -