Continuous Camera-Based Premature-Infant Monitoring Algorithms for NICU

Non-contact visual monitoring of vital signs in neonatology has been demonstrated by several recent studies in ideal scenarios where the baby is calm and there is no medical or parental intervention. Similar to contact monitoring methods (e.g., ECG, pulse oximeter) the camera-based solutions suffer from motion artifacts. Therefore, during care and the infants’ active periods, calculated values typically differ largely from the real ones. In this way, our main contribution to existing remote camera-based techniques is to detect and classify such situations with a high level of confidence. Our algorithms can not only evaluate quiet periods, but can also provide continuous monitoring. Altogether, our proposed algorithms can measure pulse rate, breathing rate, and to recognize situations such as medical intervention or very active subjects using only a single camera, while the system does not exceed the computational capabilities of average CPU-GPU-based hardware. The performance of the algorithms was evaluated on our database collected at the Ist Dept. of Neonatology of Pediatrics, Dept of Obstetrics and Gynecology, Semmelweis University, Budapest, Hungary

Respiratory rate monitoring by video processing using local motion magnification

Breathing monitoring by non-contact video processing has been the subject of recent research. This paper presents an advanced video processing algorithm for reliable Respiratory Rate (RR) monitoring based on the analysis of local video variations and a motion magnification method. This novel algorithm improves over the existing solutions in terms of estimation accuracy and excision of large body movements unrelated with respiration. Applications to adults and infants are presented to demonstrate the performance of the proposed algorithm and compare it with previous work