We have developed a slip sensor which is knitted by tension-sensitive electro-conductive yarns. When elongating this yarn, its resistance will drop remarkably. Because the yarn is mainly sensitive to deformation along its main axis, a special way to knit these yarns has been proposed to form a slip sensor. This sensor is used in detection of the human fingertip's slip during rubbing action on its surface. We found that, a simple derivative of the sensor's output was sufficient to detect slippage. However, in some cases, the sensor gets troublesome to distinguish between change of normal load and the occurrence of slip, since human implements their action without caring much about keeping the stable applied force on the sensor. Therefore, a well-known DWT (Discrete Wavelet Transform) method is employed to overcome this problem. As a result, depending on the purpose of the application, several data processing methods are employed to detect slippage of human's rubbing action, or robotic fingertip. Results in this paper promise an applicable sensory mean, which can be employed in haptic devices, teleoperation, or robotic skin.