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Adapting smartphone-based photoplethysmograpy to suboptimal scenarios

Photoplethysmography (PPG) is an optical technique used to measure the heart rate (HR) and other cardiovascular variables by analyzing volume changes in the microvascular bed of tissue. At the moment, smartphone users can already measure their HR using PPG applications that use the smartphone’s built-in camera. However, available applications are unreliable when artifacts are present, such as those caused by movement, finger pressure, or ambient light changes. This contribution aims to analyze the limitations of a smartphone-based PPG algorithm capable of measuring N–N intervals when such artifacts are present by comparing it to a 2-lead electrocardiography (ECG). By using a Bandpass filter and a zero-crossing detection algorithm on a PPG signal captured at 800  ×  600 pixels and 30 Hz, we have designed an approach capable of assessing N–N intervals when movement artifacts are present. An evaluation performed on n  =  31 users shows our algorithm is capable of measuring N–N intervals with an average relative error of 9.23 ms, when compared to a 2-lead ECG. Our approach proves the reliability of smartphone-based photoplethysmography to measure N–N intervals, even under the presence of movement artifacts, and opens the door for its future use in remote diagnosis scenarios.