There are over three million wheelchair users within the United States and that number is growing. This paper is concerned with improving the safety of wheelchair operation by the on-line estimation of tire slip. Wheelchair tire slip is a result of icy or low friction surfaces, often representative of dangerous conditions. In this research, wheel slip is detected by estimating the instantaneous center of rotation (ICR) locations of wheelchair wheels relative to the ground surface. Any departure of the estimated ICR positions from the wheel contact point indicates slippage is occurring. An Extended Kalman Filter (EKF) algorithm uses inputs of position and orientation obtained via map-based localization to detect changes in wheelchair ICR location estimates. The ICR EKF algorithm is verified in simulation. A robotic wheelchair is used for testing the presented algorithms under conditions inducing tire slip. The results show that the ICR locations do not vary significantly when the wheelchair is operated under normal conditions, i.e. low slip surfaces; however, they change significantly under slip conditions. Implementing this method with electric wheelchairs can improve the prediction of wheelchair motion on slippery surfaces, enabling warning systems and safe operational modes that can enhance the safety of wheelchair users.