Study Findings on Information Technology Are Outlined in Reports from Dongguan University of Technology (Unsupervised Framework for Single Channel Heart and Lung Sounds Separation In Data Constrained Environments).

The article presents a new unsupervised framework for separating heart and lung sounds from single-channel recordings, aiming to improve cardiopulmonary disease screening. Topics include the use of minima-controlled recursive algorithms and non-negative matrix factorization for sound separation, the challenges of data constraints in real-world applications, and the robustness of the proposed framework compared to existing methods.