Localized tissue bioimpedance is being widely investigated as a technique to identify physiological features in support of health focused applications. In support of this method being translated into wearable systems for continuous monitoring, it is critical to not only collect measurements but also evaluate their quality. This is necessary to reduce errors in equipment or measurement conditions from contributing data artifacts to datasets that will be analyzed. Two methods for artifact identification in resistance measurements of bioimpedance datasets are presented. These methods, based on thresholding and trend detection, are applied to localized knee bioimpedance datasets collected from two knee sites over 7 consecutive days in free-living conditions. Threshold artifacts were identified in 0.04% (longitudinal and transverse) and 0.69% (longitudinal) /3.50% (transverse) of the total data collected.