Abstract
Accurate R peaks detection in electrocardiogram (ECG) is an important process to assess the cardiovascular health of an individual (e.g. heart arrhythmia, heart rate variability, etc.). Many studies have presented various methods to detect R peaks in ECG using single physiological signal (i.e. ECG) and are highly subjective to the quality of the ECG signal. In this paper, an accurate R peaks detection algorithm is proposed based on the use of electro-mechanical physiological signals (i.e. ECG and photoplethysmography (PPG)). Concurrent processing of both ECG and PPG is able to reduce the need to have high quality ECG and allows the use of simple signal processing algorithms to identify the locations of R peaks in ECG signals. The flexibility of our method was demonstrated through concurrent implementation on a low cost platform (i.e. BeagleBone Black (BBB)) and FPGA platform (i.e. myRIO from National Instrument), achieving respective accuracy of 96% and 98%, using physiological signals acquired in real-time. The accuracy provided by our method is able to be applied on wearables and supports accurate real-time assessment of cardiovascular health.
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Delrieu, A., Hoël, M., Phua, C.T., Lissorgues, G. (2017). Multi physiological signs model to enhance accuracy of ECG peaks detection. In: Goh, J., Lim, C., Leo, H. (eds) The 16th International Conference on Biomedical Engineering. IFMBE Proceedings, vol 61. Springer, Singapore. https://doi.org/10.1007/978-981-10-4220-1_12
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DOI: https://doi.org/10.1007/978-981-10-4220-1_12
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