Camera-Based Photoplethysmography for Measuring Heartbeat Intervals During General Anesthesia

Photoplethysmography has been used to assess vital signs since the late 19th century. Recently, camera-based photoplethysmography systems have gained attention due to their noninvasive nature. However, challenges such as low perfusion, motion artifacts, and ambient light interference limit their use during surgical anesthesia. This study evaluated the efficacy of a camera-based system (FaCare) compared with that of a conventional contact monitor (GE HealthCare CARESCAPE B850 patient monitor) in measuring heartbeat intervals during various stages of surgical anesthesia.

Thirty patients undergoing video-assisted thoracic surgery were included. Data were collected using a webcam and FaCare software at 4 stages: preanesthesia, postanesthesia, postanesthesia with a shadowless lamp, and postsurgery. Six remote photoplethysmography techniques using artificial intelligence algorithms processed the data.

The results demonstrated a high level of agreement between the FaCare and GE HealthCare monitor. Pearson correlation analysis, Bland-Altman plots, and Welch's t test indicated that 88.1% of the heart rate correlation coefficients between the 2 devices were >0.8. Furthermore, their heartbeat interval measurements showed strong agreement in the Bland-Altman plots. FaCare showed comparable functionality, offering a noninvasive alternative suitable for operating rooms.

This study evaluated the FaCare camera-based photoplethysmography system, integrating 6 remote photoplethysmography techniques with artificial intelligence algorithms, and compared it to a conventional contact monitor for measuring heartbeat intervals during surgical anesthesia. The results showed strong consistency between FaCare and the GE contact monitor across different anesthesia stages. These findings indicate that the noninvasive FaCare system reduces infection risks and improves patient comfort. Future research is recommended to optimize artificial intelligence algorithms, data synchronization, and sampling frequency to enhance its clinical application.