Coronary Artery Disease Classification from Photoplethysmographic Signals-Reference-Cited by-同舟云学术

Coronary Artery Disease Classification from Photoplethysmographic Signals

Published:2020-08-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 4th International Conference on Medical and Health Informatics
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Author:

Banerjee Shibabroto¹,Sood Pourush²,Ghose Sujoy¹,Das Partha Pratim¹

Affiliation:

1. Computer Science and Engineering, Indian Institute of Technology, Kharagpur West Bengal, India

2. Electronics and Electrical, Communication Engineering, Indian Institute of Technology, Kharagpur West Bengal, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3418094.3418116

Reference18 articles.

1. Reduction of motion artifacts from photoplethysmographic recordings using a wavelet denoising approach

2. Maik Pflugradt Kai Geissdoerfer Matthias Goernig and Reinhold Orglmeister. 2017. A Fast Multimodal Ectopic Beat Detection Method Applied for Blood Pressure Estimation Based on Pulse Wave Velocity Measurements in Wearable Sensors. Sensors 17 1 Article 158 (2017). Maik Pflugradt Kai Geissdoerfer Matthias Goernig and Reinhold Orglmeister. 2017. A Fast Multimodal Ectopic Beat Detection Method Applied for Blood Pressure Estimation Based on Pulse Wave Velocity Measurements in Wearable Sensors. Sensors 17 1 Article 158 (2017).

3. Lenn Drijkoningen etal 2014. Validation of a smartphone based photoplethysmographic beat detection algorithm for normal and ectopic complexes. Computing in Cardiology (2014) 845--848. Lenn Drijkoningen et al. 2014. Validation of a smartphone based photoplethysmographic beat detection algorithm for normal and ectopic complexes. Computing in Cardiology (2014) 845--848.

4. Feature Extraction for Photoplethysmographic Signals using PWA

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