摘要：In this preliminary work, we presented an effective and efficient algorithm on adaptive thresholds to automatically recognize falls from acceleration signals collected by a single tri-axial accelerometer in a mobile phone. Initial thresholds depend mainly on their carrying position of mobile phones, and then are adjusted automatically by a self-learning process and a classification module. Our researches are designed for carrying phones in casual ways which has not been done in previous researches. An android-based software is designed for experiments and the results show the efficiency of our method and improvements have been made on detection accuracy after having the learning process.
