All About EDA Part 3: Data Editing

Now that we recognize the components of the EDA waveform, it is important to differentiate between actual response and fluctuations in the signal which are in fact artifacts. It is important to prevent artifact from occurring as much as possible by using quality electrodes and following best practices for data acquisition, […]

All About EDA Part 2: Components of Skin Conductance

Last time we talked about the significance of measuring electrodermal activity, and how it is collected. Now we can start looking at the resulting waveform and how to extract meaningful information from it.   Scaling EDA to Microsiemens MindWare applications expect incoming data to be in volts (with the exception […]

All About EDA Part 1: Introduction to Electrodermal Activity

All About Electrodermal Activity EDA stands for Electrodermal Activity, and is the measurement of changes in the electrical properties of the skin. When a person sweats, the conductivity of their skin changes, and activation of eccrine sweat glands is an established indicator of sympathetic nervous system arousal. Therefore, by measuring […]

Improving Data Quality: ECG

Before reading this article, check out these basic guidelines for ensuring good data collection which are universally applicable. Now we will get a bit more focused, and talk about signal specific data quality issues that can arise and how to deal with them. Disclaimer: Labeling data “good” or “bad” is […]

Improving Data Quality: EDA

Before reading this article, check out these basic guidelines for ensuring good data collection which are universally applicable. Now we will get a bit more focused, and talk about signal specific data quality issues that can arise and how to deal with them. Disclaimer: Labeling data “good” or “bad” is […]

Improving Data Quality: Cardiac Impedance

Before reading this article, check out these basic guidelines for ensuring good data collection which are universally applicable. Now we will get a bit more focused, and talk about signal specific data quality issues that can arise and how to deal with them. Disclaimer: Labeling data “good” or “bad” is […]

Improving Data Quality: General Guidelines

Collecting good quality data is fundamental to every study. Poor data quality can result in hours of additional work in post processing and, in the worst case scenario, the need to discard an entire epoch/session/subject. Discarding a subject often means not only lost data, but also lost time and financial […]

All About HRV Part 5: Data Editing

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 of Artifact on RSA It is critical that […]

All About HRV Part 4: Respiratory Sinus Arrhythmia

Last time we talked about how the IBI series is transformed from the time-domain to a frequency-domain representation. This is done to isolate specific frequency ranges of variability. One of the frequency bands, named the High Frequency (HF) band, is influenced predominantly by a phenomenon known as respiratory sinus arrhythmia. […]