Traffic accidents and mental stress are strongly correlated. Drivers under pressure are more easily to cause accidents. A system which could describe the mental state of a driver would be helpful to avoid such accidents. Multiple indices derived from analysis of heart rate variability (HRV) could be used in the estimation of mental state in humans; moreover, recent years, methods of non-contact heart rate estimation have been well studied and reached high accuracy. Based on both, we developed a real-time driver monitoring system which could not only estimate heart rate of the driver, but also indicate whether he is under pressure or not. This system delivers 2 outputs: heart rate(HR) and mental stress level (stress index). We utilized an 18-bit camera to grab frontal facial frames and independent component analysis (ICA) to extract haemoglobin signal from each frame. After temporal filtering and peak detection, R-R interval(RRI) will be obtained and HR measured. Mental stress estimation will start 30 seconds after we get the first RRI data, then a power spectrum analysis method will be applied to all of the HRV data within 30 seconds to generate powers of Low-Frequency and High-Frequency band data. The ratio of the powers in both bands, so called LF-HF ratio (LF/HF), will be delivered as a stress index to quantify the degree of mental stress. Finally, the validity of stress index is verified over arithmetic calculation and a number of driving-simulating scenarios.