Abstract
Although heartbeat segmentation can be done very well in ECG signals for arrhythmia detecting, there’re short of techniques for detecting heartbeat part from ECG images. We apply the powerful Faster R-CNN detector here, and achieves accurate detecting results. Along with the improved patch-sampling mechanism in training, detection results are more precise. The high evaluation metric on validation data and demo of real scenes demonstrate the effectiveness of our method.
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Acknowledgement
This work was supported by the National Key R&D Program of China (No. 2016QY03D0501), by the National Natural Science Foundation of China (No. U1636220, NO. 61876183), by the Beijing Natural Science Foundation (No. 4172063).
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He, Z., Niu, J., Ren, J., Shi, Y., Zhang, W. (2020). A Deep Learning Method for Heartbeat Detection in ECG Image. In: Deng, Z. (eds) Proceedings of 2019 Chinese Intelligent Automation Conference. CIAC 2019. Lecture Notes in Electrical Engineering, vol 586. Springer, Singapore. https://doi.org/10.1007/978-981-32-9050-1_41
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DOI: https://doi.org/10.1007/978-981-32-9050-1_41
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