Key result
A sensor IC featuring a sparse sampling algorithm reduced system power consumption by ~70% while achieving less than 1 bpm and 1% mean absolute errors for HR and SpO2 compared to a clinical reference.
Why the study?
Continuous PPG health monitoring requires low-power sensors to preserve battery life, but conventional LEDs and flexible organic devices demand high power consumption.
A novel sensor IC with sparse sampling reduces power consumption by ~70% while maintaining high accuracy for continuous SpO2 and heart rate monitoring.
Organic PPG sensors may boost wearability and cut fabrication costs; leaves open clinical validation for continuous monitoring.
Photoplethysmography (PPG) is an attractive method to acquire vital signs such as heart rate and blood oxygenation and is frequently used in clinical and at-home settings. Continuous operation of health monitoring devices demands a low power sensor that does not restrict the device battery life. Silicon photodiodes (PD) and LEDs are commonly used as interface devices in PPG sensors; however, using of flexible organic devices can enhance the sensor conformality and reduce the cost of fabrication. In most PPG sensors, most of system power consumption is concentrated in powering LEDs, traditionally consuming mWs. Using organic devices further increases this power demand since these devices exhibit larger parasitic capacitances and typically need higher drive voltages.This work presents a sensor IC for continuous SpO₂and HR monitoring that features an on-chip reconstruction-free sparse sampling algorithm to reduce the overall system power consumption by~70% while maintaining the accuracy of the output information. The designed frontend is compatible with a wide range of devices from silicon PDs to organic PDs with parasitic capacitances up to 10 nF. Implemented in a 40 nm HV CMOS process, the chip occupies 2.43 mm²and consumes 49.7μW and 15.2μW of power in continuous and sparse sampling modes respectively. The performance of the sensor IC has been verified in vivo with both types of devices and the results are compared against a clinical grade reference. Less than 1 bpm and 1% mean absolute errors were achieved in both continuous and sparse modes of operation.
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Alamouti et al. (2022) studied Continuous SpO2 and HR monitoring. Sensor IC with on-chip reconstruction-free sparse sampling algorithm vs. Clinical grade reference was evaluated on Mean absolute errors for heart rate and SpO2. A sensor IC featuring a sparse sampling algorithm reduced system power consumption by ~70% while achieving less than 1 bpm and 1% mean absolute errors for HR and SpO2 compared to a clinical reference.
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