Heart rate variability (HRV), analysis gives an insight into the state of the autonomic nervous system which modulates the cardiac activity. Here a digital signal controller based handy device is developed which acquires the beat to beat time interval, processes it using techniques based on non-linear dynamics, fractal time series analysis, and information theory. The technique employed, that can give reliable results by assessing heart beat signals fetched for a duration of a few minutes, is a huge advantage over the already existing methodologies of assessing cardiac health, those being dependant on the tedious task of acquiring Electro Cardio Gram(ECG) signals, which in turn requires the subject to lie down at a stretch for a couple of hours. The sensor used, relies on the technique of Photoplethysmography, rendering the whole approach as noninvasive. The device designed, calculates parameters like, Largest Lyapunov Exponent, Fractal dimension, Correlation Dimension, Approximate Entropy and alpha-slope of Poincare plots, which based on the range in which they fall, the cardiac health condition of the subject can be assessed to even the extend of predicting upcoming disorders. The design of heart beat sensor, the technique used in the acquisition of heart beat data, the relevant algorithm developed for the analysis purpose, are presented here.