Kaha Data Files and Resources
Example Rat Data Files
The files below contain short segments of data recorded in LabChart from conscious rats using the Kaha Sciences telemeter model listed.
The macro feature of LabChart can be used to automate repetitive tasks. These macros are provided as examples that may be useful to telemetry users. Please see below for more details on the specific macros.
When to use?
Automatic file saving in LabChart
When recording data from telemetry studies the files can get very large, very quickly. The problem with large files is that they can be slow to work with and analyze in LabChart. A macro can be used to automatically record data for a set period of time (e.g. 12 hours), save the data and create a new file before starting a new recording.
The zip files available for download contain LabChart settings files (which include file saving macro) and instructions for setting up the macro. Two versions are available depending on whether you are recording video in LabChart or not.
Automating hourly averages of multiple files in LabChart
Analyzing data from chronic telemetry experiments can be time consuming. The file telemetry analysis macros.zip contains instructions, an example LabChart data file, and required additional files to automatically calculate hourly averages from batch of LabChart files.
It can be difficult to determine if you have a good sympathetic nerve activity (SNA) signal. One of the hallmarks of SNA is that it contains bursts that are in time with the cardiac cycle (arterial pulse). This is not always obvious just by viewing the signal. One method of determining if the bursts are occurring at the same time in the cardiac cycle is to average the signal with respect to the systolic peak in the arterial pressure signal. This method was described in Guild et al. 2010. Instructions (Tech note) for how to perform this analysis in LabChart and an example LabChart data file are available for download using the links above.
Guild et al. “Quantifying sympathetic nerve activity: problems, pitfalls and the need for standardization.“ Experimental Physiology 95(1), 41-50, 2010. https://doi.org/10.1113/expphysiol.2008.046300