Outliers in graph data—such as noise or other signal artifact—may result in the unwanted or inaccurate placement of event marks during automated analysis routines that use Find Cycle and have peak tracking enabled.
Any unusual area in the data that contains a major jump can throw off the Find Cycle algorithm tracking the threshold and skew the results. Should this occur, this workaround using some basic AcqKnowledge software tools will prove helpful for extracting statistics from relevant data while excluding noise or other unwanted artifacts. These artifacts will be replaced by inputting values into the graph. Ultimately, the values inputted into the graph must fall within the lowest and highest points of the cycles. To accomplish this, follow the below example (which uses a noninvasive blood pressure graph):
After processing all “bad” areas, analyses that use Find Cycle (such as ABP Classifier) should yield the proper results.