All About ECG Part 4: Basic Artifact Correction

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 which, while they may seem obvious, are important to […]

All About ECG Part 3: Identifying Artifact

Welcome to the third installation of the All About ECG series that is, as you might have guessed, an in-depth discussion on interpretation of the electrocardiogram, or ECG. We have gone through the basics in the first two blog posts, and now we can move on to a bit more interesting […]

All About ECG Part 2: ECG Component Identification

Welcome back to our blog series on analyzing the electrocardiogram, or ECG. Recall from last time the typical morphology of the ECG cycle: Today we are going to talk about how the MindWare applications identify two key components of the ECG waveform – the R peak and the Q point.   […]

All About ECG Part 1: Introduction to the Electrocardiogram

All About ECG The ECG, or electrocardiogram (also EKG), is a measure of the electrical activity of the heart. The recording and interpretation of the ECG signal yields several statistics that prove meaningful in the realm of psychophysiology. To examine activity in the parasympathetic nervous system, we can examine heart rate and […]

Smoothing Data with a Rolling Filter

“So… what does the Rolling Filter do?” If I had a dollar for every time I’ve been asked that, I would have a lot of money.  Unfortunately I don’t have all of that money, but what I do have is the sense that the Rolling Filter needs a bit more […]

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 […]