Automatic fall detection is a major issue in taking care of the health of elderly people and has the potential of increasing autonomy and independence while minimizing the risks of living alone. It has been an active research area due to the large demand of the healthcare association for fall detection goods. Fortunately, due to the recent fast progression in sensing technologies, fall detection system becomes prospective. It permits to monitor elders and detect their falls, and consequently provides emergency support whenever needed. This paper describes the current work of detecting falls in independent living apartments using accelerometer concealed under tiles. We present the up-to-date advancement of data collection, feature extraction, feature selection, and signal changing detection, which are essential phases of this work.