Key result
A wearable ECG processor using a short-term autocorrelation algorithm for robust instantaneous heart rate monitoring consumed 13.7 μA for heart rate logging applications.
The development of a low-power (13.7 μA) noise-tolerant ECG processor enables more efficient wearable bio-signal monitoring systems for daily life.
May enable extended wearable HR monitoring; leaves open clinical validation studies.
To prevent lifestyle diseases, wearable bio-signal monitoring systems for daily life monitoring have attracted attention. Wearable systems have strict size and weight constraints, which impose significant limitations of the battery capacity and the signal-to-noise ratio of bio-signals. This report describes an electrocardiograph (ECG) processor for use with a wearable healthcare system. It comprises an analog front end, a 12-bit ADC, a robust Instantaneous Heart Rate (IHR) monitor, a 32-bit Cortex-M0 core, and 64 Kbyte Ferroelectric Random Access Memory (FeRAM). The IHR monitor uses a short-term autocorrelation (STAC) algorithm to improve the heart-rate detection accuracy despite its use in noisy conditions. The ECG processor chip consumes 13.7 μA for heart rate logging application.
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Izumi et al. (2014) studied this question. Wearable ECG processor with STAC algorithm was evaluated on Power consumption and heart-rate detection accuracy. A wearable ECG processor using a short-term autocorrelation algorithm for robust instantaneous heart rate monitoring consumed 13.7 μA for heart rate logging applications.
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