
This article provides the key steps for data analysis with Lasa software and data export to Excel. The Excel file containing the physiological variables calculated for several animals studied can be used to draw initial conclusions or to prepare the data for import into advanced statistical software (Graphpad prism, R, Python...).
a. Principle
The aim of this article is to illustrate the procedure to be followed to analyze the data acquired with DECRO. In the software, analysis and export are performed in the SESSION section of your study.
b. Learning case (Study example)
A learning case will be used to illustrate the steps of the analysis process in LASA software:
A gavage protocol was carried out in a group of 3 rats with a saline solution in
order to quantify the stress effect of handling on cardio-respiratory
variables.
Several
steps must be followed in the software to process the physiological data and
obtain an export of all physiological variables for several individuals in an Excel file .
2. DETECTION
The first step is DETECTION.
a. Launch DETECTION
DETECTION enables you to
position the various events (R peaks, Vmax and Vmin) on the recorded raw signal
using algorithms, in order to automatically obtain the evolution of
physiological variables over time.
When you clik on DETECT button, default detection parameters are available on the DETECT CONFIG LASA VIEW. These have been carefully defined for each species (DETECT CONFIG LASA VIEW), so simply launch detection with these predefined parameters to visualize and export the evolution of physiological variables over time.
adjustable DETECTION parameters values in the DETECT CONFIG LASA VIEW

DETECTION PARAMETERS VALUES are available in the DETECT CONFIG pop-up and can be adjusted as needed, for each physiological function.
The theorical definition of each parameter can be found in the
USER GUIDE "part 6.3 : setup the parameters for the automatic detection" available in each DECRO system with the question mark button

.
The first DETECTION step gives access to the MERGE button with the evolution of physiological variables over time, the visualization of physiological signals, the export of raw data and the possibility of calibrating the respiratory signal.
SOFTWARE : For each acquisition session (for ex. WEEK1-CRTL-RAT1), simply click on the corresponding "DETECTION" button (individually) in order to open the previous DETECT CONFIG and validate to launch the algorithms. You can also choose to launch several detection with the "DETECT" button at the top of the session home page : its then possible to launch a detection on all sessions, those identified by a TAG, or only those not yet detected.
In our learning case, we are using the
DETECTION default parameters. To perform a DETECTION, follow the steps in the video below :
In the case of the first DETECTION, the "DETECT" button is GREEN and the MERGE, "T0" ,"ANALYZE" and "Download" buttons are not displayed. After detection, this button turns ORANGE.
b. Access to post-detection visualisation
In our learning case, by clicking on the MERGE session, a new page opens by default with the evolution of heart rate, respiratory rate and activity level (ALL IN ONE view : average over 10 seconds to simplify data display). Markers created (Treatment) during acquisition are positioned at the corresponding time.
Other variables and physiological signals can be viewed using the wheel available above the ALL IN ONE view.

The identification of events by the algorithms can be seen in the screening of individual signals by the positioning of crosses on those events (R peak, Vmin and Vmax) that fall within the detection parameter ranges defined in the software's DETECT CONFIG window. The values of the predefined parameters are based on feedback from several studies and are adapted to several scientific cases.
On the other hand, the software doesn't include in the results, signal portions that don't correspond to the predefined range, and therefore cycles that you the user does not consider physiological.
In the individual view, several editing parameters are displayed at the top of merge page :
1- Scrolling mode: After zooming in, you can load and display signals and/or evolution of physiological parameters over time by scrolling the time scale. (ALL VIEWS)
2- Cycles management : You can show (Magnifying glass) and edit (Pencil) cycles from the MERGE. (SIGNAL VIEWS ONLY)

If certain cycles are not taken into account by the software algorythms, but you wish to integrate them into the results, it is possible to manually adjust the existing detection, with the "MOVE EVENT" function. This function lets you add, delete or move events and cycles on an existing merge session detection. An automatic, adjustment of the calculated parameters will be made once the modification has been validated.
There are two ways of editing cycles :
- Directly with cardiac or respiratory "SIGNAL VIEW" (ECG or RIP displayed) : The "Show cycle" and "Edit" buttons are used to display and modify cycles directly.
- In the calculated physiological parameter view (e.g. CR, RRi, etc.), you can click on an averaged point, and display the portion of the signal used to calculate it and edit it if necessary. The “Show cycle” and “Modify” buttons are also available in the corresponding pop-up windows.
3- Markers management : You can place markers manually (arrow associated with the + button) or by entering a set duration (calendar associated with the + button). (ALL VIEWS)
To delete a marker, simply click on the marker name, a page open and you click on "DELETE".
3. LASA ANALYSIS
The second step is the analysis. It involves identifying zones of interest called TIMEFRAME, defining a T0 to realign the data over time, and choosing the type of data calculation.
a. Timeframe of interest
To facilitate analysis in the Excel export, it is possible to identify areas of interest directly on the MERGE session. To do this, we will use tool named TIMEFRAME. This step is recommended, but it is not mandatory to access the next analyse step or analyzed export file.
In our learning case, we want to compare a control state before gavage with the state of the animal immediately after the manipulation. We will therefore add colored TIMEFRAMEs on the MERGE in order to find them later in the Excel export file and facilitate analysis.
In first, it is necessary to define the different TIMEFRAMEs in the TIMEFRAME button at the top of the SESSION home page, so that they are available later in the corresponding list in MERGE visualisations.
We will therefore place two TIMEFRAMEs directly on the MERGE as described in the video. We
place the "Baseline" TIMEFRAME and the "Handling" TIMEFRAME. Areas of spontaneous animal ACTIVITY were also identified.
Repeat this step for each MERGE session

To delete a Timeframe, simply click on it, a page open and then click on "
DELETE". You can also use the button in the views banner if you want to delete all the periods.
To perform an analysis, we have to
define a "T0" to access an analyzed export file (mandatory step for analysis).
You need to define a theoretical start of your recording, called T0, to realign data of several animals over time. For example, T0 can also be at the time of a treatment or at 0 (at the start of recording). This tool facilitates the visualization of an effect between subjects in the same experimental group.
Simply click on the button available under the MERGE banner.
SOFTWARE : In our learning case, we then choose to use a marker as T0 by
clicking on the marker list and selecting the "TREATMENT" marker.
Validate by clicking on “SET T0” button.
Define T0 for each session. In the case of the first T0 define, the button is first labelled “SET T0” then "Change T0".
To perform an analysis, in addition to defining a "T0", we have to perform calculations (mean, median or sum) on the raw data to access an analyzed export file of one or several subject.
Simply click on "ANALYSE". Then define fields in the analysis configuration pop-up window.
Once this is done, click on "Validate".
SOFTWARE : In our case, we'll calculate the average over 5 minutes. Of course, it
is possible to define different types of calculation and sampling
times for each physiological function. You can also choose the type of error you
wish to use, between Standard error or SEM.
You can repeat this step for each session or launch the same analysis for several sessions using the "ANALYSE" button at the top of the SESSION home page.4. EXCEL EXPORT
Once your results have been processed individually, you can bring them.
a. Tagging before export
To export several subject sessions, we have to placed TAG on each
previous analysis.
SOFTWARE : Before placing them, you must first define the different TAGs, using the "TAGS" button at the top of the SESSION home page, so that they are available later in the corresponding list.
In our case, we click on the menu available in front of the element to
be tagged (1) and select the tag “EXPORT 5 MIN” to assign to it (2).
The tag is displayed
in front of the element, just before the menu.
Repeat this step for each session
to be exported. (See example in video 6)

You can also add a tag directly during the analysis phase.
Tags at session name level only concern grouped detection (part 2.a : Launch DETECTION) or grouped analysis (part 3.c : Performing calculations (ANALYSE)). To export, the TAG must be placed on the corresponding analysis. b. Export
Once the different tags have been assigned for each ANALYSIS to be
exported, you just have to click on the "EXPORT" button at the top of session page (1). Then, choose your “EXPORT 5 MIN"tag and click on "Export"(2).
The
Excel format is proposed by default in this case. Finally, click on "GENERATE" and after on "DOWNLOAD".
The file is downloaded onto the computer…

> The software offers different file formats for exporting your data:
CSV / HDF5 = text files for exporting signals and metadata.
EDF = import signal into other signal processing software.
XLSX = perform initial group-averaged analysis and organize data before incorporating it into statistical software.
c. Data analysis in excel file
When several analyses are exported together, the file contains the corresponding data sets, metadata, and markers. Several spreadsheets are available :
All: Data set, including the following
- The characteristics of the session (Group, animal, sequence…)
- The time base (relative and absolute)
- The values of the recorded parameters and the percentage of signal exploitation
- Timeframes
Metas: Phase, session name, emitters used, and subjects recorded
Markers: Characteristics of the applied markers (Name, time, session …)
study: Characteristics of the data source study
The ALL spreadsheet, where the data is stored, is composed as follows:
SOFTWARE : In our case, to compare cardiorespiratory frequencies between the two states
(control vs. post-handling), the following steps were performed :
> Insert a pivot table in a new EXCEL page
by using “all” table
> In “Pivot
table fields", select the elements of interest and create table (e.g. time
frame, cardiac rate and respiratory rate)
> Generate graphics: in "Insert",
"Recommended chart", add in "Insert", click on
"Recommended graphics".

By doing the pivot table, you must remind few points :
-> Use the "Parameters_analyse" category to obtain the value of the parameter in the pivot table
-> The values are displayed summed automatically. Values must be averaged, to do this use the "Value Field Settings dialog box", by left-clicking on the parameter.
This file can be used to draw initial conclusions or to prepare data for import into advanced statistical software (Graphpad prism, R, python...).
To conclude this learning case, we can see here that on 3 individuals, the handling increased heart rate and respiratory rate by 13% and 30% respectively compared with control vales (HR=404 bpm and RR= 154 rpm).