Abstract: The existing ultrasonic gesture recognition methods are usually vulnerable to invalid gestures and hardly to identify wrong classified gestures in real time.This paper presents a context-aware information based ultrasonic gesture recognition method.This method extracts effective gesture features using fast Fourier transform.Then the confidence of gestures is calculated by using extreme learning machine algorithm and softmax function.Context-aware information is transformed into gesture’s context confidence by the defined probability transformation function simultaneously.Both gesture confidence and gesture’s context confidence are combined to yield satisfactory recognition results by filtering invalid gestures and correcting wrong classified gestures finally.The results of extensive experiments show that the recognition accuracy of this method could reach94.7%,which is33.2%higher than the ultrasonic gesture recognition methods without context information.