Identifying skin conductance responses (SCRs) and extracting their main characteristics is a common practice in galvanic skin response (GSR) research. SCRs can be produced in response to a specific event (e.g., stimulus onset), known as event-related skin conductance responses (ER-SCR), or appear spontaneously with varying rates. This page will both explain Pro Lab’s procedure for identifying SCRs and ER-SCRs in a GSR signal, and describe the main SCR and ER-SCR characteristics that Pro Lab calculates.
Pro Lab GSR analysis is based on a three-step approach:
The GSR signal varies slowly in time and therefore, any rapid change in the GSR signal is considered external noise. In order to analyze the GSR data, it is important to remove first the most common types of noise or artifacts: high-frequency noise and rapid-transient artifacts. Pro Lab will remove these types of artifacts by applying a median filter with a time window of 500ms, followed by a mean filter with a time window of 1000ms.
After data filtering, Pro Lab applies a SCR detection algorithm to identify SCRs in the GSR data and calculate their main characteristics. Pro Lab follows these steps:
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