Technology scaling enables today the design of ultra-low cost wireless body sensor networks for wearable biomedical monitors. These devices, according to the application domain, show greatly varying tradeoffs in terms of energy consumption, resources utilization and reconstructed biosignal quality. To achieve minimal energy operation and extend battery life, several aspects must be considered, ranging from signal processing to the technological layers of the architecture. The recently proposed Rakeness-based Compressed Sensing (CS) expands the standard CS paradigm deploying the localization of input signal energy to further increase data compression without sensible RSNR degradation. This improvement can be used either to optimize the usage of a non volatile memory (NVM) to store in the device a record of the biosignal or to minimize the energy consumption for the transmission of the entire signal as well as some of its features. We specialize the sensing stage to achieve signal qualities suitable for both Healthcare (HC) and Wellness (WN), according to an external input (e.g. the patient). In this paper we envision a dual-operation wearable ECG monitor, considering a multi-core DSP for input biosignal compression and different technologies for either transmission or local storage. The experimental results show the effectiveness of the Rakeness approach (up to ≈ 70% more energy efficient than the baseline) and evaluate the energy gains considering different use case scenarios.

An ultra-low power dual-mode ECG monitor for healthcare and wellness / Bortolotti, Daniele; Mangia, Mauro; Bartolini, Andrea; Rovatti, Riccardo; Setti, Gianluca; Benini, Luca. - STAMPA. - 2015-:(2015), pp. 7092651.1611-7092651.1616. (Intervento presentato al convegno 2015 Design, Automation and Test in Europe Conference and Exhibition, DATE 2015 tenutosi a Alpexpo Congress Center, Grenoble - Francia nel 9-13 Marzo 2015) [10.7873/date.2015.0784].

An ultra-low power dual-mode ECG monitor for healthcare and wellness

MANGIA, MAURO;BARTOLINI, ANDREA;ROVATTI, RICCARDO;BENINI, LUCA
2015

Abstract

Technology scaling enables today the design of ultra-low cost wireless body sensor networks for wearable biomedical monitors. These devices, according to the application domain, show greatly varying tradeoffs in terms of energy consumption, resources utilization and reconstructed biosignal quality. To achieve minimal energy operation and extend battery life, several aspects must be considered, ranging from signal processing to the technological layers of the architecture. The recently proposed Rakeness-based Compressed Sensing (CS) expands the standard CS paradigm deploying the localization of input signal energy to further increase data compression without sensible RSNR degradation. This improvement can be used either to optimize the usage of a non volatile memory (NVM) to store in the device a record of the biosignal or to minimize the energy consumption for the transmission of the entire signal as well as some of its features. We specialize the sensing stage to achieve signal qualities suitable for both Healthcare (HC) and Wellness (WN), according to an external input (e.g. the patient). In this paper we envision a dual-operation wearable ECG monitor, considering a multi-core DSP for input biosignal compression and different technologies for either transmission or local storage. The experimental results show the effectiveness of the Rakeness approach (up to ≈ 70% more energy efficient than the baseline) and evaluate the energy gains considering different use case scenarios.
2015
Proceedings -Design, Automation and Test in Europe, DATE
1611
1616
An ultra-low power dual-mode ECG monitor for healthcare and wellness / Bortolotti, Daniele; Mangia, Mauro; Bartolini, Andrea; Rovatti, Riccardo; Setti, Gianluca; Benini, Luca. - STAMPA. - 2015-:(2015), pp. 7092651.1611-7092651.1616. (Intervento presentato al convegno 2015 Design, Automation and Test in Europe Conference and Exhibition, DATE 2015 tenutosi a Alpexpo Congress Center, Grenoble - Francia nel 9-13 Marzo 2015) [10.7873/date.2015.0784].
Bortolotti, Daniele; Mangia, Mauro; Bartolini, Andrea; Rovatti, Riccardo; Setti, Gianluca; Benini, Luca
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/554666
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