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.
Electrodermal Activity (EDA) is an objective index for understanding emotional states. Researchers measure EDA to gain insights on psychological or physiological response, leading them down the path of scientific discovery. Because EDA is so important to research, BIOPAC has created tools to optimize event-related EDA analysis. Topics include: how to identify skin conductance responses, convert stim events from E-Prime SuperLab, Presentation, Vizard, etc., into AcqKnowledge events that can used for analysis, and score skin conductance responses using the AcqKnowledge automated EDA analysis tool.
NIRS and CNAP—Pairing great tools for great data Cerebral hemoglobin concentration (blood mass in the brain) is frequently measured in the prefrontal cortex, and systemic arterial blood pressure is known to be a variable factor based on the hemoglobin concentration. A leg pressure cuff was used to constrict and release blood flow to create a […]
BIOPAC’s just released Introductory ECG Guide addresses fundamental to advanced concerns to optimize electrocardiography data recording and analysis. Topics include: ECG Complex; Electrical and Mechanical Sequence of a Heartbeat; Systole and Diastole; Configurations for Lead I, Lead II, Lead III, 6-lead ECG, 12-lead ECG, precordial leads; Ventricular Late Potentials (VLPs); ECG Measurement Tools; Automated Analysis Routines […]