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 […]

KB0073: Scaling EDA to Microsiemens (μS)

Electrodermal Activity (EDA) is typically viewed in microsiemens (μS). Depending on how the EDA was collected, the method of converting it from volts to μS will be different. This article details the various ways to scale data from volts to microsiemens in BioLab and the EDA Analysis application. If you […]

All About HRV Part 5: Data Editing

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 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. […]

All About HRV Part 3: Frequency Domain Analysis

Last time we talked about the IBI series and how it is built from the detected R peaks on the ECG signal. Time-domain HRV statistics can be derived directly from the IBI series, but further processing is needed to extract specific frequencies of beat-to-beat variation. Most notable of these frequencies […]