Surgeons representing a number of domains, including endovascular surgery, have expressed a desire for objective performance measures and feedback mechanisms as a means to improve training and assessment of skill. Metrics that quantify smoothness of tool movements have recently been shown to exhibit strong correlations with endovascular surgical skill. This thesis explores the applicability and implementation of two of these smoothness metrics as a method for providing real-time performance feedback via a haptic interface. The algorithms for spectral arc length and submovement count are modi ed for near real-time computation. They are then mapped to vibrotactile cues to serve as a feedback when subjects complete a dexterous, mirror tracing task. This task is developed and veri ed as a suitable proxy task for endovascular surgery and serves as a platform to test performance assessment and feedback based on movement smoothness analysis. Submovement count is shown to have limited viability as it is constrained by its computationally expensive nature. However, spectral arc length based feedback is shown to have a substantial positive e ect on performance in terms of both accuracy and completion time.