22.4 A 172µW compressive sampling photoplethysmographic readout with embedded direct heart-rate and variability extraction from compressively sampled data.

2016 IEEE International Solid-State Circuits Conference (ISSCC)(2016)

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摘要
Heart rate (HR) and its variability (HRV) provide critical information about an individual's cardiovascular and mental health state. In either application, long-term observation is crucial to arrive at conclusive decisions and provide useful diagnostic feedback [1]. Photoplethysmographic (PPG) estimation of HR and HRV has emerged as an attractive alternative to ECG, as it provides electrode-free operation increasing patient comfort. However, PPG monitoring systems robust to low ambient light conditions and low perfusion conditions require a LED as a light source, which strongly dominates the power consumption of the complete system. Compressive sampling (CS) based PPG readouts promise to mitigate this LED power consumption [2], yet require large computational power to recover the signal, hindering real-time embedded processing on energy-scarce wearable devices. This paper presents a fully integrated, low-power PPG readout ASIC, completely integrating a single-channel readout front-end (AFE) and a 12b SAR ADC and a digital back-end (DBE) for embedded energy-efficient real-time information extraction, that advances the state-of-the-art on the following fronts: 1) By smartly duty-cycling all system components synchronously on a sparse non-uniform CS sampling pulse stream, the LED driver power is reduced up to 30x, without significant loss of information. 2) Moreover, the necessity of wireless off-loading, or for computationally intensive embedded signal reconstruction, is circumvented by enabling the direct extraction of HR and HRV information from the compressed data in real-time on the ASIC, while consuming only 172μW for the complete system.
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compressive sampling photoplethysmographic readout,embedded direct heart-rate variability extraction,cardiovascular health state,mental health state,ECG,electrode-free operation,PPG monitoring systems,low ambient light conditions,low perfusion conditions,light source,energy-scarce wearable devices,fully integrated low-power PPG readout ASIC,single-channel readout front-end integration,embedded energy-efficient real-time information extraction,LED driver power reduction,computationally intensive embedded signal reconstruction,power 172 muW
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