Abstract
This paper describes an ultra-low power yet robust photoplethysmographic (PPG) readout exploiting various mixed-signal processing techniques. Firstly, compressive sampling (CS) enables to reduce the LED driver power consumption by up to 30x. Feature extraction is performed in the compressed domain, using a Lomb-Scargle periodogram (LSP) to extract the average heart rate and variability, without requiring complex signal reconstruction techniques. Secondly, we demonstrate, in simulations, increased robustness through digital motion artifact reduction for PPG signals, using a spectral subtraction technique. Finally, simulations show further signal enhancement through sensor fusion, enabling electrocardiogram (ECG)-assisted PPG acquisition for cuffless blood pressure (BP) monitoring. The power consumption gains of compressive sampling and feature extraction directly from the compressed domain are demonstrated through a 172 μW compressive sampling PPG acquisition ASIC fabricated in a 0.18 μm CMOS process. The ASIC achieves up to 30x reduction in LED driver power consumption while extracting heart rate with an accuracy conforming to ANSI-AAMI standards.
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Notes
- 1.
The benefits of CS encoding and decoding, followed by feature extraction, all on the sensor node, over the conventional approach of performing feature extraction on the Nyquist rate sampled signal might not be obvious. CS-based approach can be useful in cases where high-power stimulation is involved, as in the case with PPG acquisition as well as in the cases where the maximum achievable sampling frequency of the ADC is limited [15].
Fig. 8.4 
Various possible CS-based acquisition systems in context of BAN. (a) Signal acquisition is performed at the sensor node, while reconstruction and feature extraction are performed at the base station. (b) Both CS encoding and decoding are performed on the signal node followed by feature extraction. (c) Feature extraction is performed on the sensor node directly from the CS data
- 2.
Standard database [19] PPG signals lack annotations and hence sinusoidal modulation is chosen.
- 3.
The LED driver power consumption is measured while acquiring the PPG signal of a healthy individual. At the reported power levels, the resulting photocurrent is measured to have an AC component of 45 nApp, while the DC component is measured to be 1.6 μA.
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Pamula, V.R., Van Hoof, C., Verhelst, M. (2018). An Ultra-low Power, Robust Photoplethysmographic Readout Exploiting Compressive Sampling, Artifact Reduction, and Sensor Fusion. In: Harpe, P., Makinwa, K., Baschirotto, A. (eds) Hybrid ADCs, Smart Sensors for the IoT, and Sub-1V & Advanced Node Analog Circuit Design. Springer, Cham. https://doi.org/10.1007/978-3-319-61285-0_8
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