Key result
Proposed PPG signal quality module achieves ~95% sensitivity with extremely low energy overhead.
Why the study?
Continuous vital sign monitoring via wearable PPG sensors imposes challenging constraints on battery life, requiring efficient on-chip signal quality evaluation.
A novel on-chip signal quality assessment algorithm for PPG sensors demonstrates high accuracy with minimal energy overhead, potentially improving wearable device efficiency.
May extend wearable PPG battery life via efficient analog front-ends; leaves open clinical validation before practice change.
The growing demand for reliable wearable devices that can continuously monitor vital signs and track health under various conditions imposes challenging constraints on battery life. Wearable devices typically include a Photoplethysmogram (PPG) sensor, which is used for various applications such as monitoring heart rate (HR) and blood oxygenation (SpO2). The efficiency of these applications depends on the quality of the PPG sensor, which acquires raw data through the analog front-end and transmits it externally. This paper presents a digital block that evaluates the quality of the PPG signal directly within the ASIC. The proposed Signal Quality Assessment (SQA) module is derived from post-processing algorithms and translated into a real-time, single-sample evaluation approach, providing significant benefits at both the sensor and system levels. The proposed solution achieves performance comparable to state-of-the-art methods, with a sensitivity of 95.2%, a specificity of 88.1%, and an accuracy of 89.52%, while introducing an extremely low energy overhead equal to 5.38J.
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Basile et al. (2026) studied this question. Signal Quality Assessment (SQA) module vs. state-of-the-art methods was evaluated on Signal quality assessment performance (sensitivity, specificity, accuracy). The proposed Signal Quality Assessment module achieved a sensitivity of 95.2%, specificity of 88.1%, and accuracy of 89.52% with an extremely low energy overhead of 5.38J.
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