The problem of motion artifacts that contaminate the physiological signals like the electrocardiography and the photoplethysmography in wearable vital signs monitoring is an issue of particular interest because the increased interest in wearables like diagnostic tools. Currently, devices that allow the measurement of vital signs ambulatory have been develop by researchers and companies. However, measures delivered by these devices are significantly affected by motion artifacts, which has led the development of motion artifacts reduction methods. Because that, deep knowledge concerning the way of these artifacts affect the physiological signals became a clue for the use of wearables in medical diagnosis. In this paper, a method of characterization of electrocardiographic and photoplethysmographic signals in daily life situations is proposed, the signals characterization in time and frequency domains was performed using energy of signals in interest's frequencies. The results of this characterization is presented highlighting the non-stationarity of the signals and the significant differences that exist between the acquired signals at rest and the signals acquired during motion.