Novel low-voltage, low latency, non-volatile memory (NVM) technologies allow long-term wearable biomedical monitors to benefit from large storage capability, avoiding costly wireless transmissions and enabling, along with proper signal processing and architectural optimization, minimal energy operations and extended battery life. The recently proposed rakeness-based Compressed Sensing (RCS) offers high compression rate with an associated low computational power. This allows an energy trade-off between the compression stage and the storage stage. In this paper we introduce a novel approach, namely zeroing CS, which reduces RCS computational requirements to extremely low levels. The new energy trade-off is analyzed, considering a suitable multi-core DSP and different NVM technologies for local storage. According to our analysis, the proposing zeroing approach is up to 80% more efficient than a standard CS solution and 70% w.r.t. RCS when overall energy requirement is not dominated by storage.

Novel low-voltage, low latency, non-volatile memory (NVM) technologies allow long-term wearable biomedical monitors to benefit from large storage capability, avoiding costly wireless transmissions and enabling, along with proper signal processing and architectural optimization, minimal energy operations and extended battery life. The recently proposed rakeness-based Compressed Sensing (RCS) offers high compression rate with an associated low computational power. This allows an energy trade-off between the compression stage and the storage stage. In this paper we introduce a novel approach, namely zeroing CS, which reduces RCS computational requirements to extremely low levels. The new energy trade-off is analyzed, considering a suitable multi-core DSP and different NVM technologies for local storage. According to our analysis, the proposing zeroing approach is up to 80% more efficient than a standard CS solution and 70% w.r.t. RCS when overall energy requirement is not dominated by storage.

Long-Term ECG monitoring with zeroing Compressed Sensing approach / Mangia, M.; Bortolotti, D.; Bartolini, A.; Pareschi, F.; Benini, L.; Rovatti, R.; Setti, G.. - ELETTRONICO. - (2015), pp. 1-4. (Intervento presentato al convegno Nordic Circuits and Systems Conference (NORCAS) tenutosi a Oslo (Norway) nel October 26-28, 2015) [10.1109/NORCHIP.2015.7364394].

Long-Term ECG monitoring with zeroing Compressed Sensing approach

Pareschi F.;Setti G.
2015

Abstract

Novel low-voltage, low latency, non-volatile memory (NVM) technologies allow long-term wearable biomedical monitors to benefit from large storage capability, avoiding costly wireless transmissions and enabling, along with proper signal processing and architectural optimization, minimal energy operations and extended battery life. The recently proposed rakeness-based Compressed Sensing (RCS) offers high compression rate with an associated low computational power. This allows an energy trade-off between the compression stage and the storage stage. In this paper we introduce a novel approach, namely zeroing CS, which reduces RCS computational requirements to extremely low levels. The new energy trade-off is analyzed, considering a suitable multi-core DSP and different NVM technologies for local storage. According to our analysis, the proposing zeroing approach is up to 80% more efficient than a standard CS solution and 70% w.r.t. RCS when overall energy requirement is not dominated by storage.
2015
Novel low-voltage, low latency, non-volatile memory (NVM) technologies allow long-term wearable biomedical monitors to benefit from large storage capability, avoiding costly wireless transmissions and enabling, along with proper signal processing and architectural optimization, minimal energy operations and extended battery life. The recently proposed rakeness-based Compressed Sensing (RCS) offers high compression rate with an associated low computational power. This allows an energy trade-off between the compression stage and the storage stage. In this paper we introduce a novel approach, namely zeroing CS, which reduces RCS computational requirements to extremely low levels. The new energy trade-off is analyzed, considering a suitable multi-core DSP and different NVM technologies for local storage. According to our analysis, the proposing zeroing approach is up to 80% more efficient than a standard CS solution and 70% w.r.t. RCS when overall energy requirement is not dominated by storage.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2696674