Static posturography possesses a significant, although undiscovered to date, diagnostic potential hidden in the subtle oscillations which represent individual muscle contractions regulating body balance when standing still. This paper presents the principles of a new approach to posturographic signal analysis. First, the Center of Mass path (xCoM) is estimated from Center of Pressure (xCoP) signal using digital filtering. The difference xCoPM = xCoP − xCoM approximately corresponds to the corrective muscle impulses. Then, the velocities and accelerations of xCoM and xCoPM paths (vCoM, aCoM, vCoPM, aCoPM) are calculated. Next, 8 phases of body balance regulation are defined based on the combination of instantaneous signs of vCoM, aCoM and vCoPM. Finally, 16 phase transitions are defined which represent different special instants of body balance regulation. They may be divided into 3 main types: Zero Crossing (ZC), Turning Back (TB) and Impulse Extremum (IE). They can be subsequently divided into Forward and Backward subtypes.Based on the presented decomposition 822 new parameters have been analyzed. The exemplary analysis including 23 young healthy subjects (eyes open vs. eyes closed condition) indicated that a number of new parameters showed a higher discrimination power than the standard parameters analyzed to date. Advanced big data methods, such as neural networks or decision trees, should be applied in the future to the extracted parameters in order to evaluate the possible diagnostic potential of the new method of analysis.