Measuring heart rate variability is an important component of developing human monitoring systems for soldiers of the next century. Unfortunately, even the best sensors are prone to error in active situations. We have developed a system that detects and corrects errors in interbeat interval data in real time. A six to ten second buffer is used to provide context for a set of rules designed to simulate the way a human expert corrects data offline.
Interbeat interval data was gathered from a pool of eighteen subjects with three detection devices used on each subject. Results of the automated correction were compared with human experts to determine the validity of the method. As expected, success varied based on the number of errors in a neighborhood. Isolated errors were corrected with high accuracy, while severely damaged data streams were totally unrecoverable by human or machine. This technique could serve as a crucial component of interbeat interval based monitoring technologies.