Physiological indexes, such as blink frequency and heart rate, express the physical and mental state of a human. This paper presents an algorithm for simultaneous detection of eye blink and heart rate using multi-channel ICA. Video sequences captured from smart phones are used in which subjects are requested to sit without big motion. Statistic information from the R, G and B components of eyes and their surrounding facial region is explored to discriminate the different sources that mixed in each image. The proposed algorithm extracts both eye blink and cardiac signal as different sources at the same time by 6-channel SOBI without any other complex processing. Meanwhile, a kurtosis based method is proposed to automatically select blink and cardiac signals from the output separations. Different ICA algorithms and channel numbers as well as a series of head moving modes are employed to test the robustness and accuracy of the algorithm. Experiments on twenty subjects show that multi-channel ICA is capable of precisely separating the eye blink and cardiac signals in a less complex way.