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Great signals and easy interpretability
The following example shows the co-occurrence of spikes in the respiration and the EDA signal. Channel 8 reflects the onset and offset of the signal to take a deep breath. We also see a deeper breath (possibly speech) before the onset of the sigh task and smaller SCRs after the end of the sigh task.
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Unmatched SCRs
In this example, we see some “unmatched” SCRs: while SCRs occur with each sigh, there are also some SCRs that occur shortly before the second sigh and a few seconds after the third SCR. Unmatched means that it is unlikely that these occurred due to the event (sigh signal in channel 8, reflected by the light bulbs in the global channel).
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Unmatched but somewhat related SCRs
Below we see an SCR right before the onset of the 4th sigh. You can see from the respiration signal that the participant took a longer breath around the same time. Therefore, this might mean that the SCRs are related to deeper breaths, but deeper breath can also occasionally happen without a signal to do so. This depends on the participant. For example, the person might yawn, sneeze or cough. We should not count these unrelated SCRs but they are useful in understanding that the SCRs might be related to breathing events and not solely to the stimulus on the screen.
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Similar examples of more unrelated SCRs
Absence of SCRs
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Absence of SCRs during events but unrelated SCR in the middle
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Exclude this subject from analysis
Define a period of time during which we investigate the SCRs and ignore everything that’s outside that range.
CURRENTLY DO NOT HAVE AN ANSWER
FIND OUT WHAT HAPPENED AT THE REST5 SECTION
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How do I know the data have sufficient quality to analyze?
In this example, the range of the signal is small (ca. 1.75-2.25 microsiemens for the visible signal range - compare to subject above peaking above 9 micro siemens). Remember, in the EDA preferences, you selected a baseline, threshold and a rejection percentage of amplitude height that will all determine whether a peak qualifies as an SCR. Therefore, we leave it up to the software to decide whether the fluctuations are large enough to report as an SCR. It is important to apply the same threshold to all subjects and data.
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Artifact, can be removed
Artifacts can be brief signal spikes on the EDA signal that are clearly not part of the signal pattern. To remove the artifact, select the area around it (as tightly as possible), then select the EDA channel you want the signal to be removed from, then click Transform → Math functions → Connect endpoints.
This means that everything in the selection area will be flattened to connect the beginning point of the selection with the end point of the selection. This will not happen in your original EDA channel. Instead, a new EDA channel will be created that is now lacking that particular artifact.
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Partly usable with effort
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This is the same file, just zoomed in around “Sigh2”
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