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Heart rate signal decomposition and evaluation from brow area

Patients present abnormal heart rhythm due to cholesterol clogging, heart attack and enlargement of one side of the heart. To diagnose the fault in heart rate of a person, an Electrocardiogram is taken using Electrocardiograph. In order to measure the heart rate, non-contact technique is used. The input data is a video clip captured from human face brow area using a camera. Reflectance signal shows the change in blood volume of the face blood vessels. The oxygenated haemoglobin in the blood absorbs only the green light component. Hence, the green channel of the video signal is taken for decomposition. From the input video, the green channel and reflected intensity signal are extracted. The reflectance signal strength is calculated by observing the variation in blood volume and haemoglobin absorptivity. The Hilbert Huang transform (HHT) uses enhanced empirical mode decomposition to split the reflectance signal into various intrinsic mode functions (IMF). The regression model provides the relationship among variables for monitoring heart rate signal. A Neural Network is used to detect abnormal and normal heart rhythms using IMF. The blood pressure of a person is also found from IMF.