Multidimensional Video-based Contactless Infant Seizure Monitoring
Developed a real-time monitoring and prediction algorithm for infant seizures in collaboration with a a leading tertiary hospital in Guangzhou, aiming to establish a low-cost, contactless detection system to mitigate resource limitations and inconsistencies in seizure diagnosis quality.
Preprocessed raw ECG signals to extract heart rate and calculate heart rate variability (HRV).
Utilized remote photoplethysmography (rPPG) to extract heart rate and HRV from video data for non-invasive physiological monitoring.
Applied optical flow techniques to analyze global and skin-region motion in vEEG videos.
Deployed open-source human pose estimation tools to detect infant keypoints and compute motion intensity.
Analyzed limb movement intensity using cross-correlation and Pearson correlation coefficients to integrate motion and physiological signals.
Introduced a camera-based solution for NICU settings, enabling contactless monitoring of infant motion and vital signs with improved precision and efficiency.
Apr 1, 2024
