The segmentation of sensor data plays an important role in the Recognition of the activities of daily living. In this paper, we summarize the state of the art of data stream segmentation in the past five years and divide them into four categories, i.e., change point detection based method, semantics based method, window based method, and deep learning-based methods. The summary shows that there are relatively few studies on segmentation using deep learning methods. Besides, there is a lack of a general platform, which can be used in comparing different methods.