5 accepted papers
Camera-based pulse measurements from remote photoplethysmography (rPPG) have rapidly improved over recent years due to innovations in video processing and deep learning. However, modern data-driven solutions require large training datasets collected under diverse conditions. Collecting such training…
Camera-based respiratory monitoring is contactless, non-invasive, unobtrusive, and easily accessible compared to conventional wearable devices. This paper presents a novel multimodal approach to estimating breathing rate based on tracking the movement and color changes of the face through an RGB cam…
The accurate estimation of peripheral capillary oxygen saturation (SpO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> ) is vital for monitoring respiratory health, with applications spanning medical diagnostics and fitness tracking. Remote phot…
This paper presents algorithms to improve the estimation of heart rate (HR) and heart rate variability (HRV) from smartphone video. The remote photoplethysmogram (rPPG) signals are first extracted from the videos recorded. Next, we proposed an rPPG filter adaptively tuned by HR and respiratory rate…
Lung health assessment is traditionally done mainly through X-ray images and spirometry tests which are time-consuming, cumbersome, and costly. In this paper, we investigate the potential of passively recordable contents such as speech, cough and heart signal for such an assessment. Our regression m…