Key result
Non-Nyquist sampling-based event-triggered systems and knowledge-based adaptive sampling strategies applied to electrocardiograms result in an order of magnitude reduction in sampling rates.
Non-Nyquist event-triggered sampling can significantly reduce sampling rates and energy consumption in cardiovascular monitoring IoT devices.
May reduce energy demands in ECG IoT monitoring; leaves open clinical validation of diagnostic accuracy.
Editor's notes: Non-Nyquist sampling-based event-triggered systems can enable adaptive sampling of IoT nodes resulting in large energy savings. This article reviews introductory concepts and building blocks of non-Nyquist sampling for cardiovascular monitoring systems. It further analyzes the performance of a knowledge-based adaptive sampling strategy applied to biophysiological signals such as electrocardiogram resulting in the order of magnitude reduction in sampling rates. -Subhanshu Gupta, Washington State University.
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Surrel et al. (2019) conducted a review in Cardiovascular monitoring. Non-Nyquist sampling-based event-triggered systems was evaluated. Non-Nyquist sampling-based event-triggered systems and knowledge-based adaptive sampling strategies applied to electrocardiograms result in an order of magnitude reduction in sampling rates.
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