In this paper, we propose a robust environmental sound spectrogram classification approach. Its purpose is surveillance and security applications based on the reassignment method and log-Gabor filters. 
Besides, the reassignment method is applied to the spectrogram to improve the readability of the time-frequency representation, and to assure a better localization of the signal components. Our approach includes three methods. In the first two methods, the reassigned spectrograms are passed through appropriate log-Gabor filter banks and the outputs are averaged and underwent an optimal feature selection procedure based on a mutual information criterion. The third method uses the same steps but applied only to three patches extracted from each reassigned spectrogram. The proposed approach is tested on a large database consists of 1000 sounds belonging to ten classes. The recognition is based on Multiclass Support Vector Machines.

Certain aspects of balance control can be affected by some entries as vision, proprioception, direction, age, Gender, height and weight. The knowledge of the effects of these factors on postural equilibrium allows differentiating pathological and physiological postural aspects. The aim of this study is to define the effects of these entries on postural control by analyzing the parameters: mean velocity of CoP (center of pressure), RMS (root mean square) CoP of displacement, Range of COP, CEA (confidence ellipse area). We examined healthy subjects between 19-42 years of age during the quiet stance under static conditions: keeping foot outspread and opened eyes (PE_YO), tighten foot and opened eyes (PS_YO), outspread foot and closed eyes (PE_YF), tightened foot and closed eyes (PS_YF). 
Experimental results through all studied parameters permit to conclude that the lack of vision and the situation with tighten foot cause a degradation of balance maintaining. They indicate also that it is easier to maintain equilibrium on the anteroposterior direction than mediolateral direction. Results show also a less well-controlled posture for male related to female.
Results display also that the postural parameters studied failed to find significant effect of the height, weight and age on the postural stability.

This paper presents an analysis of stabilogram using the modified Principal Component Analysis (mPCA) decomposition which will be employed to highlight the effects of different aspects on the human postural stability.
The aim of this study is to analyze stabilogram center of pressure time series using the mPCA decomposition method. The mPCA is a decomposition method applied to a complex signal. It decomposes the stabilogram, considered as an additive model, into three components: trend, rambling and trembling. The study of the trace of analytic trembling (respectively of rambling) in the complex plan highlights a unique rotation center. So the phase is defined and two parameters are extracted: the area of the circle in which 95% of the trace's data points are located and the angular frequency. In this study 25 healthy volunteers (average age 31± 11 years) are required to stand upright on an electromagnetic platform either with eyes closed or open and with feet outspread or tighten.
Experimental results show the efficiency of the parameter area to identify the effect of visual, proprioceptive and directional entries on the postural stability. These results are able to discriminate between control and young groups and indicate a less well-controlled posture for control subjects (34.5± 7.5y) relatively to young subjects (22.5 ±2. 5y). Results serve also to display that female subjects are more stable than males, that fat subjects are more stable than thin and that tall subjects are more stable than small.