Key result
Novel near-threshold ECG processor reduces power consumption by ~63% compared to conventional designs.
Why the study?
Long-term cardiac monitoring requires ultra-low-power ECG signal processing to enable continuous real-time recording and diagnosis.
Answers are grounded in this paper and cite their sources.
May support extended ambulatory ECG monitoring; leaves open clinical validation before adoption.
A low-power multi-functional electrocardiogram (ECG) signal processor is presented in this paper. To enable long-term monitoring, several architecture-level power saving techniques are proposed, including global cognitive clocking, pseudo-downsampling wavelet transform, adaptive storing, and denoising-based run-length compression. An ultra-low-voltage ADC is designed for low-power signal digitization with adaptive clocking. Through these architecture-level techniques, the total power consumption can be significantly reduced by 63% as compared to the conventional design. Several circuit-level design techniques are also developed, including ultra-low-voltage operation and near-threshold level shifting, to further reduce the power consumption by 33%. In addition, a low-complexity cardiac analysis scheme is proposed to realize comprehensive on-chip cardiac analysis. Implemented in 0.18 µm CMOS process, the proposed cognitive ECG processor consumes only 457 nW at 0.5 V for real-time ECG recording and diagnosis.
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Zhou et al. (2014) studied Long-term cardiac monitoring. Cognitive Multi-Functional ECG Processor vs. Conventional design was evaluated on Power consumption. A near-threshold cognitive multi-functional ECG processor implemented in 0.18 µm CMOS process consumed only 457 nW at 0.5 V, reducing power consumption by 63% compared to conventional designs.
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