Select analysis version to view the applicable content: We have now gone through the various statistics in the HRV application, how they are calculated, and what they infer. To ensure that these statistics are accurate, the R peaks on the ECG signal need to be checked for correctness. Effects […]
All About Cardiac Impedance Part 5: Data Editing
Select analysis version to view the applicable content: Now that we have talked about meaningful statistics in impedance cardiography and how they are calculated, we need to take a step back and make sure the data are clean and free of artifact. There are two steps for editing in impedance cardiography – […]
All About ECG Part 5: Identifying and Handling Cardiac Arrhythmia
As we continue our series on the ECG signal, we need to look at abnormal ECG signals and how to handle them in analysis. Diagnosis of specific conditions is best left to cardiologists and so we are not going to get deep into the identification of specific cardiac conditions (if you […]
All About ECG Part 4: Basic Artifact Correction
Select analysis version to view the applicable content: Last time we discussed what an artifact is, why it is important to correct artifact, and how artifact is identified in the MindWare analysis applications. The next step is actually dealing with that artifact. We are going to start with some examples […]
HRV vs. IMP : Why R We Editing Twice?
HRV vs. IMP : Why R We Editing Twice? Collecting and editing the ECG signal is crucial to performing heart rate variability (HRV) and impedance cardiography (IMP) analysis. In both of these cases it is necessary to identify a landmark on the ECG waveform to identify a beat. Using a […]