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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
This person shows a lot of unrelated SCRs.
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Declining responses
This dataset shows an extremely strong response at the onset of the task without any breathing related events (no sharp peaks or troughs in the respiration channel). In addition to several unrelated SCRs, the first sigh elicits an SCR followed by more unrelated SCRs and another one that may be too close to the sigh signal onset to really be related to anything. You see that after that, the SCRs decline and remain absent until the end.
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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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Artifacts that 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.
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