Energy-Efficient Real-Time Heart Monitoring on Edge–Fog–Cloud Internet of Medical Things

نویسندگان

چکیده

The recent developments in wearable devices and the Internet of Medical Things (IoMT) allow real-time monitoring recording electrocardiogram (ECG) signals. However, continuous ECG signals is challenging low-power due to energy memory constraints. Therefore, this article, we present a novel energy-efficient methodology for continuously heart devices. proposed composed three different layers: 1) noise/artifact detection layer grade quality signals; 2) normal/abnormal beat classification detect anomalies 3) an abnormal diseases from Moreover, distributed multioutput convolutional neural network (CNN) architecture used decrease consumption latency between edge–fog/cloud. Our reaches accuracy 99.2% on well-known MIT-BIH Arrhythmia Data Set. Evaluation real hardware shows that our suitable having minimum RAM 32 kb. achieves $7\times $ more efficiency compared state-of-the-art works.

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ژورنال

عنوان ژورنال: IEEE Internet of Things Journal

سال: 2022

ISSN: ['2372-2541', '2327-4662']

DOI: https://doi.org/10.1109/jiot.2021.3138516