High Sampling Rate Smartphone-PPG via Built-in Rolling Shutter Image Sensor

Abstract

Recent advancement of CMOS camera image sensor (CIS) on smartphone brings a significant improvement to the IoT-based mobile healthcare technology in the form of CIS-photoplethysmography (CPPG). Nevertheless, most of the available smartphone is equipped with a limited sampling rate (Fs), typically 30 frame per second (fps), thus often resulting in a distorted CPPG signal acquisition. This distorted signal is hard to be utilized for different types of advanced photoplethysmography (PPG)-derived physiological analysis, and only useful in a simple pulse rate monitoring system. In this article, the rolling-shutter camera mechanism has been exploited to extract CPPG data points from CIS-pixel rows, thus allowing high-Fs CPPG signal extraction from a common built-in, low-fps smartphone CIS. Multiple experiments were conducted to prove the reliability of rolling-shutter CPPG (RSCPPG) signal. First, we conduct iterative experiments with different CIS parameters to find their correlation to the acquired RSCPPG signal quality. Results indicate that the short exposure time produces a high-SNR CPPG signal up to 25 ± 2.38 dB, and highly correlated signal morphology (average <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${r}$ </tex-math></inline-formula> = 0.95) compared to the reference PPG signal. Then, we also demonstrated the proposed RSCPPG algorithm allowing a high CPPG data sampling with Fs = 150 Hz (that is ≥ 5 times CIS fps). Finally, a feasibility study has been conducted on multiple features extracted from RSCPPG that are potentially implemented for further physiological analysis application. These findings suggest that the proposed RSCPPG algorithm is a reliable bio-signal acquisition technique in smartphone-based healthcare technology.