Contactless Cardiac Activity Detection Based on Head Motion Magnification

The aim of this study is to remotely measure cardiac activity (heart pulse, total cycle length and pulse width) from videos based on a head motion at different positions of the head (front, back and side). As the head motion resulting from the cardiac cycle of blood from the heart to the head via the carotid arteries is not visible to the naked eye and to preserve the signal strength in the video, we used wavelet decomposition and a Chebychev filter to develop a standard Eulerian video magnification in terms of noise removal and execution time. We used both magnification systems to measure cardiac activity and statistically compare the results using Bland-Altman method. Also, we proposed a new video quality system based on fuzzy interface system to select which magnification system has better magnification quality and gives better results for the heart pulse rate. The experimental results on several videos captured from 10 healthy subjects show that the proposed contactless system of heart pulse has an accuracy of 98.3% when magnified video based on the developing magnification system was used and an accuracy of 97.4% when magnified video based on Eulerian magnification system was used instead. The proposed system has low computational complexity, making it suitable for advancing health care applications, mobile health applications and telemedicine.