A system to detect a man down situation using intra-aural inertial measurement units is disclosed. The system comprises an earpiece having an inertial measurement unit (IMU) adapted to capture acceleration and rotation speed of the earpiece. The method comprises a training phase to characterize statistical distribution models of extreme values of feature signals, segmented by their respective optimally-sized time windows and to merge the detection probability provided by the statistical model of the feature signals. The method further comprises a prediction phase. The prediction phase comprises applying the detection strategy on independent data, based on the critical states obtained from the characterization. The data from the said inertial measurement of the MEMS are used for the detection of full (F), immobility (I) and down on the ground (D) states.