Performance challenges in current multi-lead QRS detection systems

Modern QRS detectors in patient monitoring systems must provide accurate results even when interfering noise is present. This task is complicated by the heterogeneous and non-uniform nature of the patient population. Certain beat morphologies demand a significant increase in the complexity of beat detection algorithms. At the same time, it is important to take a system-wide approach to the beat detection problem and include artifact rejection and baseline correction challenges. Here we emphasize the importance of such an approach to be able to successfully handle non-trivial input data. We also explain how this approach can improve the QRS detection performance in commercial patient monitoring systems. The performance benchmarks are presented by being tested on proprietary and public ECG databases.