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.
A novel compressive sampling method for ECG wearable measurement systems / Picariello, F.; Iadarola, G.; Balestrieri, E.; Tudosa, I.; De Vito, L.. - In: MEASUREMENT. - ISSN 0263-2241. - 167:(2021), p. 108259. [10.1016/j.measurement.2020.108259]
A novel compressive sampling method for ECG wearable measurement systems
Iadarola G.Secondo
;
2021-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
