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## Parameters ##
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## Parameters ##
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When performing a fNIRS analysis, these parameters are some of the most important settings and it is crucial that they are correct for the study that is being performed. FLARES exposes most of the parameters needed for an analysis allowing for immense customizability. These parameters have been broken down into subcategories in an attempt to keep them simple. These parameters are also shown in the order that they will be applied, and logical values have been applied by default. Below is a list of the submenus:
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When performing a fNIRS analysis, these parameters are some of the most important settings and it is crucial that they are correct for the study that is being performed. FLARES exposes most of the parameters needed for an analysis allowing for immense customizability. These parameters have been broken down into subcategories in an attempt to keep them simple. These parameters are also shown in the order that they will be applied, and logical values have been applied by default. Below is a list of the submenus:
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- Preprocessing
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- [Preprocessing](https://git.research.dezeeuw.ca/tyler/flares/wiki#preprocessing)
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- Trimming
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- [Trimming](https://git.research.dezeeuw.ca/tyler/flares/wiki#trimming)
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- Verify Optode Placement
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- [Verify Optode Placement](https://git.research.dezeeuw.ca/tyler/flares/wiki#verify-optode-placement)
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- Heart Rate
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- [Short/Long Channels](https://git.research.dezeeuw.ca/tyler/flares/wiki#shortlong-channels)
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- Scalp Coupling Index
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- [Heart Rate](https://git.research.dezeeuw.ca/tyler/flares/wiki#heart-rate)
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- Signal to Noise Ratio
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- [Scalp Coupling Index](https://git.research.dezeeuw.ca/tyler/flares/wiki#scalp-coupling-index)
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- Peak Spectral Power
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- [Signal to Noise Ratio](https://git.research.dezeeuw.ca/tyler/flares/wiki#signal-to-noise-ratio)
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- Bad Channels Handling
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- [Peak Spectral Power](https://git.research.dezeeuw.ca/tyler/flares/wiki#peak-spectral-power)
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- Optical Density
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- [Coefficient of Variation](https://git.research.dezeeuw.ca/tyler/flares/wiki#coefficient-of-variation)
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- Temporal Derivative Distribution Repair filtering
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- [Median Absolute Deviation](https://git.research.dezeeuw.ca/tyler/flares/wiki#median-absolute-deviation)
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- Wavelet filtering
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- [Power Spectral Density Noise](https://git.research.dezeeuw.ca/tyler/flares/wiki#power-spectral-density)
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- Haemoglobin Concentration
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- [Channel Variance](https://git.research.dezeeuw.ca/tyler/flares/wiki#channel-variance)
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- Enhance Negative Correlation
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- [Bad Channels Handling](https://git.research.dezeeuw.ca/tyler/flares/wiki#bad-channels-handling)
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- Filtering
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- [Optical Density](https://git.research.dezeeuw.ca/tyler/flares/wiki#optical-density)
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- Short/Long Channels
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- [Temporal Derivative Distribution Repair filtering](https://git.research.dezeeuw.ca/tyler/flares/wiki#temporal-derivative-distribution-repair-filtering)
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- Extracting Events
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- [Wavelet filtering](https://git.research.dezeeuw.ca/tyler/flares/wiki#wavelet-filtering)
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- Epoch Calculations
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- [Haemoglobin Concentration](https://git.research.dezeeuw.ca/tyler/flares/wiki#haemoglobin-concentration)
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- Design Matrix
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- [Enhance Negative Correlation](https://git.research.dezeeuw.ca/tyler/flares/wiki#enhance-negative-correlation)
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- General Linear Model
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- [Filtering](https://git.research.dezeeuw.ca/tyler/flares/wiki#filtering)
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- Finishing Touches
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- [Extracting Events](https://git.research.dezeeuw.ca/tyler/flares/wiki#extracting-events)
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- Other
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- [Epoch Calculations](https://git.research.dezeeuw.ca/tyler/flares/wiki#epoch-calculations)
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- [Design Matrix](https://git.research.dezeeuw.ca/tyler/flares/wiki#design-matrix)
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- [General Linear Model](https://git.research.dezeeuw.ca/tyler/flares/wiki#general-linear-model)
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- [Finishing Touches](https://git.research.dezeeuw.ca/tyler/flares/wiki#finishing-touches)
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- [Other](https://git.research.dezeeuw.ca/tyler/flares/wiki#other)
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Information about the individual parameters can be found by chicking the "?" icon next to the respective parameter. There are more popups and menus that will appear after the analysis has completed. They will be discussed further down in the Analysis section.
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Information about the individual parameters can be found by chicking the "?" icon next to the respective parameter, or below in the Performing an Analysis section. There are more popups and menus that will appear after the analysis has completed. They will be discussed further down.
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# Performing an Analysis #
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# Performing an Analysis #
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Now that the app layout is understood, perfomring an analysis is simple. To start, open a file or a folder from the Navigation Bar. Once the file/files are loaded, ensure that the per-file and global parameters are correct for the study. Once you are satisfied with the parameters, click the "Process" button to start processing the files. This processing step will take some time, however you can validate progression visually by looking at the progress bars of the files in the [Loaded Files](https://git.research.dezeeuw.ca/tyler/flares/wiki/Home#loaded-files) area.
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Now that the app layout is understood, perfomring an analysis is simple. To start, open a file or a folder from the Navigation Bar. Once the file/files are loaded, ensure that the per-file and global parameters are correct for the study. Once you are satisfied with the parameters, click the "Process" button to start processing the files. This processing step will take some time, however you can validate progression visually by looking at the progress bars of the files in the [Loaded Files](https://git.research.dezeeuw.ca/tyler/flares/wiki/Home#loaded-files) area.
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@@ -184,7 +188,7 @@ Calculates the coefficient of variance of the participant. This quality metric i
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If CV is set to False, CV_THRESHOLD will be ignored.
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If CV is set to False, CV_THRESHOLD will be ignored.
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## Mean Absolute Deviation
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## Median Absolute Deviation
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Calculates the mean absolute deviation of the participant. This quality metric identifies outliers based on how much their signal swings compared to all other channels. If the entire channel averaged does not remain under the threshold value, then the channel will be marked as a bad channel.
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Calculates the mean absolute deviation of the participant. This quality metric identifies outliers based on how much their signal swings compared to all other channels. If the entire channel averaged does not remain under the threshold value, then the channel will be marked as a bad channel.
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**Parameters:**
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**Parameters:**
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Reference in New Issue
Block a user