Abstract
In this chapter, a novel algorithm for predicting ventricular arrhythmia (VA) is presented. It utilizes a unique set of ECG features with LDA classifier. These features are extracted from two consecutive heartbeats. The proposed method achieves a capability of predicting the arrhythmia up to 3 h before the onset with an accuracy of 99.1\(\%\) sensitivity of 98.95\(\%\) and precision of 98.39\(\%\).
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Acknowledgements
This work has been supported by the Semiconductor Research Corporation (SRC) under the Abu Dhabi SRC Center of Excellence on Energy-Efficient Electronic Systems (\(ACE^{4}S\)), Contract 2013 HJ2440, with funding from the Mubadala Development Company, Abu Dhabi, UAE.
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Tekeste, T., Saleh, H. (2019). Efficient Algorithm for VT/VF Prediction for IoT SoCs. In: Elfadel, I., Ismail, M. (eds) The IoT Physical Layer. Springer, Cham. https://doi.org/10.1007/978-3-319-93100-5_13
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DOI: https://doi.org/10.1007/978-3-319-93100-5_13
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