In this paper, we present experiments on the design of a novel movement analysis system for real-time balance assessment in the frail elderly. Using the Microsoft Kinect sensors, we capture TUG (Timed Up and Go) tests and analyze mainly the transfer from sitting-to-standing and back-to-sitting which represent two of the most commonly executed human movements. Nine spatio-temporal parameters were extracted from recorded joint positions by 3D skeletal sequence processing. In order to validate and evaluate the developed system, practical test experiences have been performed on ten healthy young subjects, who were asked to realize the TUG in three different conditions: normal, cognitive and motor. Obtained results showed good measurement reliability and reproducibility with important precision. In addition, we observed that even for young healthy subjects, there is a significant difference of movement parameter between normal condition and cognitive condition, which represents a stimulating result in the dual task paradigm field. This preliminary study opens a new research and development way for economic geriatric health which implies multiple aspects: user-friendly, hygiene, low-cost, home-based environment, and automatic autonomy assessment.