Several attempts have been made to achieve a quantitative analysis of lung sounds mainly for two purposes: a) an understanding of their genesis, and b) an insight of their changes with pathologies for medical diagnosis. Early studies involved the collection of acoustic information at several positions on the thoracic surface or at the extra-thoracic trachea with one up to four microphones, but with a non-simultaneous acquisition. However, an increment for simultaneous acquisition points has been suggested; for example, as a consequence of multichannel acquisition acoustic visualization through computerized interpolation has emerged being helpful to analyze lung sounds (LS) origin, distribution, and relation to ventilation. Nevertheless, quantitative analysis of lung sounds requires eliminating interference signals prior to the extraction of relevant features. The acquired signals not only contain LS but also heart sounds (HS) among other interferences. HS are unavoidable and sometimes represent severe disturbing interference. This paper proposes a HS cancellation scheme as an extension of a previous effort using the Empirical Mode Decomposition (EMD) and a combination of time warping with linear adaptive FIR filtering. Simulated signals are used to evaluate the performance of the proposed scheme under known and controlled scenarios.