PulseCam: high-resolution blood perfusion imaging using a camera and a pulse oximeter

Photoplethysmographic Imaging of Hemodynamics and Two-Dimensional Oximetry

The review of recent papers devoted to actively developing methods of photoplethysmographic imaging (the PPGI) of blood volume pulsations in vessels and non-contact two-dimensional oximetry on the surface of a human body has been carried out. The physical fundamentals and technical aspects of the PPGI and oximetry have been considered. The manifold of the physiological parameters available for the analysis by the PPGI method has been shown. The prospects of the PPGI technology have been discussed. The possibilities of non-contact determination of blood oxygen saturation SpO2 (pulse saturation O2) have been described. The relevance of remote determination of the level of oxygenation in connection with the spread of a new coronavirus infection SARS-CoV-2 (COVID-19) has been emphasized. Most of the works under consideration cover the period 2010-2021.

Using High-Fidelity Avatars to Advance Camera-based Cardiac Pulse Measurement

Non-contact physiological measurement has the potential to provide low-cost, non-invasive health monitoring. However, machine vision approaches are often limited by the availability and diversity of annotated video datasets resulting in poor generalization to complex real-life conditions. To address these challenges, this work proposes the use of synthetic avatars that display facial blood flow changes and allow for systematic generation of samples under a wide variety of conditions. Our results show that training on both simulated and real video data can lead to performance gains under challenging conditions. We show strong performance on three large benchmark datasets and improved robustness to skin type and motion. These results highlight the promise of synthetic data for training camera-based pulse measurement; however, further research and validation is needed to establish whether synthetic data alone could be sufficient for training models.

PulseCam: a camera-based, motion-robust and highly sensitive blood perfusion imaging modality

Blood carries oxygen and nutrients to the trillions of cells in our body to sustain vital life processes. Lack of blood perfusion can cause irreversible cell damage. Therefore, blood perfusion measurement has widespread clinical applications. In this paper, we develop PulseCam - a new camera-based, motion-robust, and highly sensitive blood perfusion imaging modality with 1 mm spatial resolution and 1 frame-per-second temporal resolution. Existing camera-only blood perfusion imaging modality suffers from two core challenges: (i) motion artifact, and (ii) small signal recovery in the presence of large surface reflection and measurement noise. PulseCam addresses these challenges by robustly combining the video recording from the camera with a pulse waveform measured using a conventional pulse oximeter to obtain reliable blood perfusion maps in the presence of motion artifacts and outliers in the video recordings. For video stabilization, we adopt a novel brightness-invariant optical flow algorithm that helps us reduce error in blood perfusion estimate below 10% in different motion scenarios compared to 20-30% error when using current approaches. PulseCam can detect subtle changes in blood perfusion below the skin with at least two times better sensitivity, three times better response time, and is significantly cheaper compared to infrared thermography. PulseCam can also detect venous or partial blood flow occlusion that is difficult to identify using existing modalities such as the perfusion index measured using a pulse oximeter. With the help of a pilot clinical study, we also demonstrate that PulseCam is robust and reliable in an operationally challenging surgery room setting. We anticipate that PulseCam will be used both at the bedside as well as a point-of-care blood perfusion imaging device to visualize and analyze blood perfusion in an easy-to-use and cost-effective manner.