This Application Note explains how to optimize ECG R-R interval data for Heart Rate Variability studies by using a template matching approach. It also explains how to identify erroneous R-R interval values caused by signal artifact and shows methods for correcting the errors by using the tools in the AcqKnowledge software. The note explains how to:
A. Record good ECG data B. Prepare data for the tachogram
1. Filter the ECG data 2. Transform the data using Template Correlation function
C. Create a tachogram D. Identify problems with the tachogram data E. Correct tachogram data
Recording good data is essential for performing HRV analysis. The protocol outlined for data acquisition, filtering, artifact detection and correction results in great improvements in HRV analysis.
“Results reveal that even a single heart period artifact, occurring within a 2-min recording epoch, can lead to errors of estimate heart period variability that are considerably larger than typical effect sizes in psychophysiological studies.” —Berntson & Stowell, 1998
For the Application Note detailing HRV Calculations, see Application Note 129 – Heart Rate Variability. For an automated HRV script, see Script 056: Calculating HRV Statistics.
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The autonomic nervous system (ANS) is responsible for regulating the functions of all the body’s organs. Take a look at this month’s citations to see how to apply BIOPAC’s tools and learn techniques for ANS research… Comparable responses to a wide range of olfactory stimulation in women and men. Scientific Reports, 13(1), 9059. Lillqvist, M., Claeson, […]
BIOPAC tools are used for studies in a variety of different fields and disciplines. AcqKnowledge software is one of our universally applicable tools, used by thousands of labs around the world and cited in thousands of peer reviewed publications, such as the following studies… The psychophysiology of guilt in healthy adults. Cognitive, Affective, & Behavioral Neuroscience, 1-18. […]