Introduction. It seems that accelerometric variables play a vital role in evaluation of the locomotor system. Issues related to the direction and value of acceleration, as well as to the trajectory of movement in general, are related to energy transformations. Acceleration, as the principal factor in the force to inertia ratio, has the same direction and sense as the resultant of the acting forces. Changes in the parameters of the movement are related to energy transformations. Since in the locomotor system this process can be destructive, an analysis of such phenomena is justified. The objective of the study was to determine the patterns of trajectory parameters for selected points of the locomotor system in a selected population. The authors performed an evaluation of accelerometric and energy variables at various levels of the locomotor system. Research material and method. 20 healthy people aged between 19 and 23 took part in the research. Measurements were conducted using an ADXL acceleration sensor produced with MEMS technology. The sensor makes it possible to measure acceleration within a range of 0Hz to 3 kHz, at +/- 30m/s2. The sensor was connected to a data activation system with an NI DAQ9007 measurement card. Data activation was carried out by a dedicated programme, in which the sampling frequency was set to 50 Hz and the measurement range was +/- 25m/s2. The application performed online measurements, together with signal filtration and integration. The results of the measurements, in the form of phase charts for three axes, were displayed on a screen and the signal was saved to a file before filtration. The following were used in the programme: an inclination index, the course of measurement signals, results of signal integration (velocity, acceleration, dislocation) as well as phase charts for particular axes of the sensor. Results. Both quality variables illustrating movement trajectories in X, Y and Z planes, and statistical variables of accelerometric signals, are differentiated depending on the height of a given measurement. Their values also make it possible observe an asymmetry between the right and left side. Conclusions. 1. Energy estimates parameterised with a mean radius of the attractor in the phase space are connected with the degree of mechanical energy dissipation in the height function. 2. Transformation energy increases in the direction head to ground, reaching the highest values at the height of the heels. 3. Statistical estimates such as peak value and RMS value permit determination of asymmetries in the motion of the lower limbs.