Robust Heartbeat Detection from Multimodal Data via CNN-based Generalizable Information Fusion

Bollepalli, Sandeep Chandra and Sastry, Challa Subrahmanya and Jana, Soumya (2018) Robust Heartbeat Detection from Multimodal Data via CNN-based Generalizable Information Fusion. IEEE Transactions on Biomedical Engineering. ISSN 0018-9294

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Objective: Heartbeat detection remains central to cardiac disease diagnosis and management, and is traditionally performed based on electrocardiogram (ECG). To improve robustness and accuracy of detection, especially, in certain critical-care scenarios, the use of additional physiological signals such as arterial blood pressure (BP) has recently been suggested. There, estimation of heartbeat location requires information fusion from multiple signals. However, reported efforts in this direction often obtain multimodal estimates somewhat indirectly, by voting among separately obtained signal-specific intermediate estimates. In contrast, we propose to directly fuse information from multiple signals without requiring intermediate estimates, and thence estimate heartbeat location in a robust manner. Method: We propose as a heartbeat detector, a convolutional neural network (CNN) that learns fused features from multiple physiological signals. This method eliminates the need for hand-picked signal-specific features and ad hoc fusion schemes. Further, being data-driven, the same algorithm learns suitable features from arbitrary set of signals. Results: Using ECG and BP signals of PhysioNet 2014 Challenge database, we obtained a score of 94%. Further, using two ECG channels of MITBIH arrhythmia database, we scored 99.92%. Both those scores compare favorably with previously reported database-specific results. Also, our detector achieved high accuracy in a variety of clinical conditions. Conclusion: The proposed CNN-based information fusion (CIF) algorithm is generalizable, robust and efficient in detecting heartbeat location from multiple signals. Significance: In medical signal monitoring systems, our technique would accurately estimate heartbeat locations even when only a subset of channels are reliable.

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IITH CreatorsORCiD
Sastry, Challa SubrahmanyaUNSPECIFIED
Item Type: Article
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: Team Library
Date Deposited: 19 Jul 2018 11:36
Last Modified: 19 Jul 2018 11:36
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