Malte Kirst

Reliable motion artifact detection for ECG monitoring systems with dry electrodes

Reliable signals are the basic prerequisite for most mobile ECG monitoring applications. Especially when signals are analyzed automatically, capable motion artifact detection algorithms are of great importance. This article presents different artifact detection algorithms for ECG systems with dry electrodes. The algorithms are based on the measurement of additional parameters that are correlated with the artifacts. We describe a mobile measurement system and the procedure used for the evaluation of these algorithms. The algorithms are assessed based upon their effect on QRS detection. The best algorithm improved sensitivity (Se) from 98.7% to 99.8% and positive predictive value (+P) from 98.3% to 99.9%, while 15% of the signal was marked as artifact. This corresponds to a decrease in false positive and false negative detected beats by 89.9%. Different metrics to evaluate the performance of an artifact detection algorithm are presented.

An approach to reliable motion artifact detection for mobile long-term ECG monitoring systems using dry electrodes

The authors present a research project aiming to develop a context-aware cardiac permanent monitoring system. A significant challenge addressed by this project is to acquire reliable ECG signals with dry electrodes in order to do an automatic analysis und alerting. A method to detect motion artifacts by the simultaneous measurement of electrode/skin-impedance is proposed. Investigations of the correlation of motion artifacts and impedance signal are presented. Results of applying an impedance signal based artifact detection algorithm on QRS detection is shown.

Using DWT for ECG motion artifact reduction with noise-correlating signals

Dealing with motion artifacts in long-term ECG recordings is a big issue. The frequency spectrum of motion artifacts is similar to the frequencies of the QRS complex — the wanted signal in the ECG. The deletion of motion artifacts often leads to a deformation of QRS complexes, too. These risks can be minimized by using a noise-correlating signal as a second channel for artifact reduction. This paper presents an approach using the electrode-skin impedance as a second channel for the reduction of motion artifacts. Using the discrete wavelet transform, motion artifacts can be deleted time and frequency selective. This filter approach leads to an improvement of the automatic QRS detection and decreases the number of false detections by 35 %.

Mobile patient simulator for resuscitation training with automatic external defibrillators.

Resuscitation training has to be performed under most realistic conditions. This includes both usual CPR measures (breathing and chest compressions) and advanced measures, e.g. the usage of an Automatic External Defibrillator (AED). Almost all currently available simulators for ECG signals used in such trainings have a rather limited variety of available ECG signals. The trainer also has to change between different rhythms manually, resulting in a less realistic training environment. The development will result in mobile ECG simulator which can automatically react to events in the resuscitation process according to pre-programmed scenarios. It also has potential to simulate other physiological parameters like thorax impedance in the future.