Name
Abstract | ||
|---|---|---|
Localization of exact positions of the fundamental heart sounds (FHS) is an essential step towards automatic analysis of heart sound phonocardiogram (PCG) recordings, the automatic segmentation allows for data-driven classification of heart pathological events. Current approach using probabilistic models such as hidden Markov models (HMMs) has improved accuracy of heart sound segmentation. In this paper, we propose a switching linear dynamic system (SLDS) of piece-wise stationary autoregressive (AR) processes for segmenting the heart sounds into four fundamental components with distinct second order structure (auto-correlation). The SLDS is able to capture simultaneously both the continuous state-space in the hidden dynamics in PCG, and the regime switching in the dynamics using a discrete Markov chain. This overcomes limitation of HMMs which is based on a single-layer of discrete states. Compared to AR processes, the Gaussian mixture densities in HMM do not account for the temporal autorrelation structure in PCG which has one-to-one correspondence to frequency content a distinctive feature of HS components. We introduce three schemes for model estimation: (1) switching Kalman filter (SKF) model. (2) refinement by switching Kalman filter (SKS), and (3) fusion of SKF and the duration-dependent Viterbi algorithm (SKF-Viterbi). Results on a large PCG dateset of Physionet/Challenge 2016 shows SKF-Viterbi significantly outperforms SKF by improvement of segmentation accuracy from 71% to 84.2%. |
Year | Venue | Keywords |
|---|---|---|
2017 | IEEE Global Conference on Signal and Information Processing | Segmentation,Kalman filter,state-space models,Viterbi algorithm |
Field | DocType | ISSN |
Phonocardiogram,Autoregressive model,Pattern recognition,Segmentation,Computer science,Markov chain,Kalman filter,Artificial intelligence,Hidden Markov model,Viterbi algorithm,Heart sounds | Conference | 2376-4066 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fuad Numan | 1 | 0 | 0.34 |
| S. Hussain | 2 | 47 | 9.46 |
| Chee-Ming Ting | 3 | 72 | 13.17 |
| Hadri Hussain | 4 | 0 | 0.34 |