Abstract
With the development of wearables and artificial intelligence, developing a non-invasive heart sound recognition system via the machine listening theory becomes a vital research topic. Nevertheless, a standard publicly accessible heart sound corpus is urgently lacking in the current studies. In addition, low reproducibility, subject-dependency, and inconsistent evaluation metrics prevail in the existing reported results. To this end, we introduce a most recent standard heart sound corpus, the Heart Sounds Shenzhen (HSS) database. We discuss the state-of-the-art methods and the baseline as featured in an official competition, and indicate the opportunities and challenges. We hope this contribution can attract more attention and further studies to this relevant area.
Translated title of the contribution | Opportunities and Challenges for Heart Sound Recognition: A Brief on the Heart Sounds Shenzhen Corpus |
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Original language | Chinese (Traditional) |
Pages (from-to) | 354-359 |
Number of pages | 6 |
Journal | Journal of Fudan University (Natural Science) |
Volume | 59 |
Issue number | 3 |
State | Published - Jun 2020 |
Externally published | Yes |
Keywords
- artificial intelligence
- heart sound recognition
- machine listening
- medical healthcare
- smart wearables