Filtering scope - Revision history

Harald at 13:23, 4 May 2021

2021-05-04T13:23:14Z

Harald at 13:22, 4 May 2021

2021-05-04T13:22:33Z

Mateusz at 08:57, 3 February 2021

2021-02-03T08:57:39Z

Mateusz at 08:35, 3 February 2021

2021-02-03T08:35:19Z

Mateusz at 08:33, 3 February 2021

2021-02-03T08:33:45Z

Mateusz at 08:33, 3 February 2021

2021-02-03T08:33:05Z

Harald at 17:30, 2 February 2021

2021-02-02T17:30:21Z

Mateusz at 16:17, 2 February 2021

2021-02-02T16:17:06Z

Mateusz at 16:15, 2 February 2021

2021-02-02T16:15:28Z

Mateusz at 16:15, 2 February 2021

2021-02-02T16:15:15Z

@@ Line 5: / Line 5: @@
 }}
 ==Overview==
-In EEG/MEG data analysis frequency filtering is one of the most basic and at the same time important operations. In BESA Research filtering is implemented as a linear operation so it is interchangeable in the processing pipeline - it can be changed at every processing step in almost all situations. There are however some moments that filtering cannot be applied in a strictly linear manner - e.g. averaging in the presence of slow drifts. In general, due to the linear nature of filtering we recommend not to apply filtering in the pre-averaging processing stage (apart from high pass to reduce drifts) as it can still be applied afterwards. You will be prompted by the application if you encounter this type of situation in data analysis:
+In EEG/MEG data analysis frequency filtering is one of the most basic and at the same time important operations. In BESA Research filtering is implemented as a linear operation so it is interchangeable in the processing pipeline - it can be changed at every processing step in almost all situations. There are however some situations where filtering cannot be applied in a strictly linear manner - e.g. averaging in the presence of slow drifts. In general, due to the linear nature of filtering we recommend not to apply filtering in the pre-averaging processing stage (apart from high pass to reduce drifts) as it can still be applied afterwards. You will be prompted by the application if you encounter this type of situation in data analysis:
 [[File:Filter_notification.jpg]]

@@ Line 5: / Line 5: @@
 }}
 ==Overview==
-In EEG/MEG data analysis frequency filtering is one of the most basic and at the same time important operations. In BESA Research filtering is implemented as a linear operation so it is interchangeable in the processing pipeline - it can be changed at every processing step in almost all situations. There are however some moments that filtering cannot be applied in a linear manner - i.e. averaging. In general, we recommend not to apply filtering during such types of operations (apart from high pass to reduce drifts) as it can still be applied afterwards. You will be prompted by the application if you encounter this type of situation in data analysis:
+In EEG/MEG data analysis frequency filtering is one of the most basic and at the same time important operations. In BESA Research filtering is implemented as a linear operation so it is interchangeable in the processing pipeline - it can be changed at every processing step in almost all situations. There are however some moments that filtering cannot be applied in a strictly linear manner - e.g. averaging in the presence of slow drifts. In general, due to the linear nature of filtering we recommend not to apply filtering in the pre-averaging processing stage (apart from high pass to reduce drifts) as it can still be applied afterwards. You will be prompted by the application if you encounter this type of situation in data analysis:
 [[File:Filter_notification.jpg]]
@@ Line 16: / Line 16: @@
 ! style="font-weight: bold;" | Averaged buffer
 ! style="font-weight: bold;" | FFT
-! style="font-weight: bold;" | lienear corelation / regression
+! style="font-weight: bold;" | lienear correlation / regression
 ! style="font-weight: bold;" | Combine Conditions
 ! style="font-weight: bold;" | ERP
@@ Line 26: / Line 26: @@
 |  style="font-weight: bold;" | Low/High pass
 |  style="background: #F2D16B" |Main
-| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px,   #BA9588 10px,   #BA9588 20px);"| Main / can be redefine to default values(2-35Hz)
+| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px,   #BA9588 10px,   #BA9588 20px);"| Main / can be redefined to default values(2-35Hz)
 |  style="background: #BA9588" |as used during buffer creation
 |  style="background: #F2D16B" |Main
@@ Line 39: / Line 39: @@
 |  style="font-weight: bold;" | Notch
 |  style="background: #F2D16B" |Main
-| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px,   #BA9588 10px,   #BA9588 20px);"| Main / can be redefine to default values(2-35Hz)
+| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px,   #BA9588 10px,   #BA9588 20px);"| Main / can be redefined to default values(2-35Hz)
 |  style="background: #BA9588" |as used during buffer creation
 |  style="background: #F2D16B" |Main
@@ Line 52: / Line 52: @@
 |  style="font-weight: bold;" | Bandpass
 |  style="background: #F2D16B" |Main
-| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px,   #BA9588 10px,   #BA9588 20px);"| Main / can be redefine to default values(2-35Hz)
+| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px,   #BA9588 10px,   #BA9588 20px);"| Main / can be redefined to default values(2-35Hz)
 |  style="background: #BA9588" |as used during buffer creation
 |  style="background: #F2D16B" |Main
@@ Line 65: / Line 65: @@
 |  style="font-weight: bold;" | Polygraphic
 |  style="background: #F2D16B" |Main*
-|  style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px,   #BA9588 10px,   #BA9588 20px);"| Main* / can be redefine to default values(2-35Hz)
+|  style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px,   #BA9588 10px,   #BA9588 20px);"| Main* / can be redefined to default values(2-35Hz)
 |  style="background: #BA9588" |as used during buffer creation
 |  style="background: #F2D16B" |Main*
@@ Line 78: / Line 78: @@
 |  style="font-weight: bold;" | artifact correction
 |  style="background: #F2D16B" |Main
-| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px,   #BA9588 10px,   #BA9588 20px);"| Main / can be redefine to default values(2-35Hz)
+| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px,   #BA9588 10px,   #BA9588 20px);"| Main / can be redefined to default values(2-35Hz)
 |  style="background: #BA9588" |as used during buffer creation
 |  style="background: #F2D16B" |Main
@@ Line 101: / Line 101: @@
 ==Specific Source Analysis settings==
-For source analysis (SA), if you press '''ESI/MSI''' button on the toolbar ribbon ''Main'' filter settings will be used. Filters for SA can be set during sending a block of data to Source Analysis (right-click on the highlighted block and select '''Source Analysis''').
+For source analysis (SA), if you press the '''ESI/MSI''' button on the toolbar ribbon ''Main'' filter settings will be used. Filters for SA can be set during sending a block of data to Source Analysis (right-click on the highlighted block and select '''Source Analysis''').
 [[File:filter_SA.jpg]]
-In case of enabled artifact correction, you will be prompted just before averaging if you want to average artifact corrected data or not. The detailed description of difference in both approaches can be found [[Using BESA to correct blink and EKG artifacts in MEG data#Averaging the raw data|here]]
+In case of enabled artifact correction, you will be prompted just before averaging if you want to average artifact corrected data or not. The detailed description of difference in both approaches can be found [[Using BESA to correct blink and EKG artifacts in MEG data#Averaging the raw data|here]].
 ==Notch filter==

@@ Line 101: / Line 101: @@
 ==Specific Source Analysis settings==
-For source analysis (SA), if you press '''ESI/MSI''' button on the toolbar ribbon ''Main'' filter settings will be used.) Filters for SA can be set during sending a block of data to Source Analysis (right-click on the highlighted block and select '''Source Analysis''').
+For source analysis (SA), if you press '''ESI/MSI''' button on the toolbar ribbon ''Main'' filter settings will be used. Filters for SA can be set during sending a block of data to Source Analysis (right-click on the highlighted block and select '''Source Analysis''').
 [[File:filter_SA.jpg]]

@@ Line 4: / Line 4: @@
 |version = 6.1 or higher
 }}
+==Overview==
 In EEG/MEG data analysis frequency filtering is one of the most basic and at the same time important operations. In BESA Research filtering is implemented as a linear operation so it is interchangeable in the processing pipeline - it can be changed at every processing step in almost all situations. There are however some moments that filtering cannot be applied in a linear manner - i.e. averaging. In general, we recommend not to apply filtering during such types of operations (apart from high pass to reduce drifts) as it can still be applied afterwards. You will be prompted by the application if you encounter this type of situation in data analysis:

@@ Line 101: / Line 101: @@
 ==Specific Source Analysis settings==
-For source analysis (SA), if you press ''''ESI/MSI''' button on the toolbar ribbon ''Main'' filter settings will be used.) Filters for SA can be set during sending a block of data to Source Analysis (right-click on the highlighted block and select '''Source Analysis''').
+For source analysis (SA), if you press '''ESI/MSI''' button on the toolbar ribbon ''Main'' filter settings will be used.) Filters for SA can be set during sending a block of data to Source Analysis (right-click on the highlighted block and select '''Source Analysis''').
 [[File:filter_SA.jpg]]

@@ Line 105: / Line 105: @@
 [[File:filter_SA.jpg]]
 ==Notch filter==
@@ Line 116: / Line 117: @@
 [[File:filter_poly.jpg]]
 [[Category:Preprocessing]]

@@ Line 5: / Line 5: @@
 }}
-In EEG/MEG data analysis frequency filtration is one of the most basic and at the same time important operations. In BESA Research filtration is implemented as a linear operation so it is interchangeable in the processing pipeline - it can be changed at every processing step in almost all situations. There are however some moments that filtration cannot be applied in a linear manner - i.e. averaging. In general, we recommend not apply filtration during such types of operations as it can be replied afterward. You will be prompted by the application if you encounter such a moment in data analysis:
+In EEG/MEG data analysis frequency filtering is one of the most basic and at the same time important operations. In BESA Research filtering is implemented as a linear operation so it is interchangeable in the processing pipeline - it can be changed at every processing step in almost all situations. There are however some moments that filtering cannot be applied in a linear manner - i.e. averaging. In general, we recommend not to apply filtering during such types of operations (apart from high pass to reduce drifts) as it can still be applied afterwards. You will be prompted by the application if you encounter this type of situation in data analysis:
 [[File:Filter_notification.jpg]]
-Also at some stages of the data processing, the filtration is of major importance, therefore we made it more accessible and you can easily redefine it. Please have a look at the table below:
+Also at some stages of the data processing, filtering is of major importance, therefore we made it more accessible and you can easily redefine it. Please have a look at the table below:
 {| class="wikitable" style="text-align:center;"
 ! style="font-weight: bold;" | Filter type
@@ Line 96: / Line 96: @@
 ==Specific ERP settings==
-The ERP filter settings can be set during paradigm definition. Note that there are two different settings - for artifact scan and for averaging
+The ERP filter settings can be set during paradigm definition. Note that there are two different settings - for artifact scan and for averaging.
 [[File:filter_ERP.jpg]]
@@ Line 107: / Line 107: @@
 ==Notch filter==
-Note that because of its generic nature - power line artifact removal - notch filter is treated differently. The notch filter value populates from ''Main'' setting to all subsequent applications.
+Note that because of its generic nature - power line artifact removal - the notch filter is treated differently. The notch filter value populates from ''Main'' setting to all subsequent applications.
 ==Bandpass filter==
-Bandpass filter is complementary to high/low pass filter combination. For convenience, it is treated differently and also populates to all subsequent applications from ''Main'' setting.
+The bandpass filter is complementary to the high/low pass filter combination. For convenience, it is treated differently (it also has different filter characteristics) and also populates to all subsequent applications from ''Main'' setting.
 ==Polygraphic filter==

@@ Line 1: / Line 1: @@
 {{BESAInfobox
 |title = Module information
-|module = BESA Research Basic or higher
+|module = BESA Research
 |version = 6.1 or higher
 }}