Recently, we have faced on the problem such as increasing elderly people who have occurred accidents including solitary death and falling and so on at their houses. To deal with these problems, many researchers and companies are proposing and releasing the systems monitored by sensors for keeping them safety. However, conventional systems using sensors including cameras and microphones give little privacy. In order to solve the problems, we proposed and discussed the falling discrimination using sound information for watching elderly people. Proposed system expects the falling discriminations using acoustic features extracted from sound. For discrimination accurately, we focused on Spectrum gravity between subjects/things and flooring styles. The feature characterized and modeled as Spectrum ratio of delta power as dynamic parameter. Finally, experiments of two-class discriminations using feature parameters achieved to 96.83 % with dataset of unspecific conditions.