Auscultation is one of the essential skills for clinical examination, in particular, of the respiratory system. Sparse modeling is one innovative technology for discovering components of biological signals including auscultatory signals, of which characteristics and irregurity can be interpreted as redundancy or sparsity of their features. This article explains and demonstrates how to apply the sparse modeling techniques to biological signals, showing lung sound separation as an example.
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