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• W3045195655 abstract "• Compressive Sampling of electrocardiographic signals. • Signal-adapted sensing matrix. • Low computational complexity on the acquisition node. • Reduced data rate to be transmitted. • Accurate reconstruction of the signal waveform. The paper presents a novel method for the compressed acquisition of electrocardiographic (ECG) signals. The proposed method is intended to be applied to Internet-of-Medical-Things (IoMT) acquisition nodes (i.e. wearable measurement systems) as they can benefit from a reduction of the signal data rate to be transmitted, and the consequent reduction of energy consumption. Being based on Compressive Sampling (CS), the proposed method presents a very low computational complexity on the acquisition node. Moreover, since the sensing matrix is adapted to the acquired signal, it allows achieving a better reconstruction performance compared with the other CS-based methods available in literature." @default.
• W3045195655 created "2020-07-29" @default.
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• W3045195655 date "2021-01-01" @default.
• W3045195655 modified "2023-10-06" @default.
• W3045195655 title "A novel compressive sampling method for ECG wearable measurement systems" @default.
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• W3045195655 doi "https://doi.org/10.1016/j.measurement.2020.108259" @default.
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