Abstract
Cardiechema is a way to reflect cardiovascular disease where the doctor uses a stethoscope to help determine the heart condition with a sound map. In this paper, phonocardiogram (PCG) is used as a diagnostic signal, and a deep learning diagnostic framework is proposed. By improving the architecture and modules, a new transfer learning and boosting architecture is mainly employed. In addition, a segmentation method is designed to improve on the existing signal segmentation methods, such as R wave to R wave interval segmentation and fixed segmentation. For the evaluation, the final diagnostic architecture achieved a sustainable performance with a public PCG database.
Original language | English |
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Article number | 127 |
Journal | Biosensors |
Volume | 11 |
Issue number | 4 |
DOIs | |
Publication status | Published - Apr 2021 |
Keywords
- Biosignal diagnosis
- Phonocardiogram
- Transfer learning
ASJC Scopus subject areas
- Clinical Biochemistry