Feature selection based on combined Doppler and range information improves fall detection and enables better discrimination against similar high Doppler non-rhythmic motions, such as sitting. A fall is typically characterized by an extension in range beyond that associated with sitting, which is determined by the seat horizontal depth. In this paper, we demonstrate, using time-frequency (TF) spectrograms, that range-Doppler radar plays a fundamental and important role in motion classification for assisted living applications. It reduces false alarms along with the associated cost in the unnecessary deployment of the first responders. This reduction is considered vital for the development of in-home radar monitoring and for casting it as a viable technology for aging-in-place.