Título:
Near threshold pulse transit time processor for central blood pressure estimation.
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Autor:
Veirano Núñez, Francisco
Pérez-Nicoli, Pablo
Gammarano, Nicolás
Fierro, Germán
Silveira, Fernando
Pérez-Nicoli, Pablo
Gammarano, Nicolás
Fierro, Germán
Silveira, Fernando
Tutor:
Tipo de documento:
Preprint
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Palabras clave:
Heart rate
Power demand
Pulse measurements
Estimation
Electrocardiography
Signal processing
Blood pressure
ECG
Biomedical signals
Ultra-low power
Near-threshold
Power demand
Pulse measurements
Estimation
Electrocardiography
Signal processing
Blood pressure
ECG
Biomedical signals
Ultra-low power
Near-threshold
Descriptores:
Año de publicación:
2022
Contenido:
Resumen:
In this work a digital peripheral that can measure pulse transit time for central blood pressure estimation is presented. To do so, it processes ECG and BCG signals in real time by detecting the R-waves in the ECG and using this as time reference for measuring intervals of interest such as RJ, IJ and RR. The circuit was fabricated in a 180 nm process and experimental results are presented. The peripheral works at the near-threshold region and consumes 7 pJ/cycle with 0.43 V of supply voltage while operating at 8 kHz. We showed that state of the art performance can be achieved in the processing required for wearable estimation of central blood pressure while operating the digital circuit in the near-threshold region.
Descripción:
Presentado y publicado en 2022 IEEE 13th Latin America Symposium on Circuits and System (LASCAS), Puerto Varas, Chile, 01-04 mar 2022, pp. 1-4.
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EN:
Financiadores:
Agencia Nacional de Investigación e Innovación. ANII FMV 1 2017 1 136740
CSIC - Universidad de la República, Uruguay.
CSIC - Universidad de la República, Uruguay.
Citación:
Veirano Núñez, F., Pérez-Nicoli, P., Gammarano, N. y otros. Near threshold pulse transit time processor for central blood pressure estimation [Preprint]. Publicado en: 2022 IEEE 13th Latin America Symposium on Circuits and System (LASCAS), Puerto Varas, Chile, 01-04 mar 2022, pp. 1-4. DOI: 10.1109/LASCAS53948.2022.9789076
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https://ieeexplore.ieee.org/document/9789076
https://hdl.handle.net/20.500.12008/37219
https://hdl.handle.net/20.500.12008/37219
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Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| VPGFS22.pdf | Preprint | 645.69 KB | Adobe PDF |
