User Tutorial:Data Analysis - Revision history

Mellinger: /* Custom Data Analysis */

2022-06-08T15:20:55Z

Custom Data Analysis

← Older revision		Revision as of 15:20, 8 June 2022
Line 31:		Line 31:
	BCI2000 data files can be loaded, read, and analyzed in both Matlab and Python. For users who wish to go beyond the constraints of the analysis procedures in the tutorials, the following resources may be useful:		BCI2000 data files can be loaded, read, and analyzed in both Matlab and Python. For users who wish to go beyond the constraints of the analysis procedures in the tutorials, the following resources may be useful:

			* The [[User_Reference:BCI2000Analysis\|BCI2000Analsyis tool]] may be used to create filter graphs from BCI2000 processing steps offline in a GUI, and to train classifiers.
	* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.		* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.
	* The [[User_Reference:BCI2000Analysis\|BCI2000Analsyis tool]] may be used to create filter graphs from BCI2000 processing steps offline in a GUI, and to train classifiers.
	* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.		* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.
	** BCI2000 Data can be converted and analyzed using [[User Reference:Matlab MEX Files\|Matlab MEX Files]]		** BCI2000 Data can be converted and analyzed using [[User Reference:Matlab MEX Files\|Matlab MEX Files]]

Mellinger: /* Custom Data Analysis */

2022-06-08T15:20:25Z

Custom Data Analysis

← Older revision		Revision as of 15:20, 8 June 2022
Line 32:		Line 32:

	* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.		* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.
			* The [[User_Reference:BCI2000Analysis\|BCI2000Analsyis tool]] may be used to create filter graphs from BCI2000 processing steps offline in a GUI, and to train classifiers.
	* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.		* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.
	** BCI2000 Data can be converted and analyzed using [[User Reference:Matlab MEX Files\|Matlab MEX Files]]		** BCI2000 Data can be converted and analyzed using [[User Reference:Matlab MEX Files\|Matlab MEX Files]]

Emilycohen: /* Custom Data Analysis */

2022-04-20T16:02:21Z

Custom Data Analysis

← Older revision		Revision as of 16:02, 20 April 2022
Line 33:		Line 33:
	* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.		* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.
	* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.		* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.
	** ~~Converting and Analyzing~~ BCI2000 Data ~~with~~ [[User Reference:Matlab MEX Files\|Matlab MEX Files]]		** BCI2000 Data can be converted and analyzed using [[User Reference:Matlab MEX Files\|Matlab MEX Files]]
	* ~~Analyze~~ BCI2000 Data in Python with [https://github.com/neurotechcenter/BCI2kReader BCI2k Reader]		* Another option is to analyze BCI2000 Data in Python with [https://github.com/neurotechcenter/BCI2kReader BCI2k Reader]

	==See also==		==See also==

Emilycohen at 16:01, 20 April 2022

2022-04-20T16:01:36Z

← Older revision		Revision as of 16:01, 20 April 2022
Line 1:		Line 1:
	There is a number of data analysis tutorials provided. These show how to analyze some sample data that is included with ''BCI2000''.		There is a number of data analysis tutorials provided. These show how to analyze some sample data that is included with ''BCI2000''.

	~~==Getting Started: Reading BCI2000 Data Files==~~
	~~BCI2000 data files can be loaded, read, and analyzed in both Matlab and Python. Tools to do this can be found at the links below:~~
	* Converting and Analyzing BCI2000 Data with [[User Reference:Matlab MEX Files\|Matlab MEX Files]]
	* Analyze BCI2000 Data in Python with [https://github.com/neurotechcenter/BCI2kReader BCI2k Reader]

	==Mu Rhythm/SMR Data Analysis==		==Mu Rhythm/SMR Data Analysis==
Line 34:		Line 29:
	==Custom Data Analysis==		==Custom Data Analysis==

	For users who wish to go beyond the constraints of the analysis procedures in the tutorials, the following resources may be useful:		BCI2000 data files can be loaded, read, and analyzed in both Matlab and Python. For users who wish to go beyond the constraints of the analysis procedures in the tutorials, the following resources may be useful:

	* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.		* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.
	* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.		* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.
			** Converting and Analyzing BCI2000 Data with [[User Reference:Matlab MEX Files\|Matlab MEX Files]]
			* Analyze BCI2000 Data in Python with [https://github.com/neurotechcenter/BCI2kReader BCI2k Reader]

	==See also==		==See also==

Emilycohen at 15:48, 20 April 2022

2022-04-20T15:48:07Z

← Older revision		Revision as of 15:48, 20 April 2022
Line 1:		Line 1:
	There is a number of data analysis tutorials provided. These show how to analyze some sample data that is included with ''BCI2000''.		There is a number of data analysis tutorials provided. These show how to analyze some sample data that is included with ''BCI2000''.

			==Getting Started: Reading BCI2000 Data Files==
			BCI2000 data files can be loaded, read, and analyzed in both Matlab and Python. Tools to do this can be found at the links below:
			* Converting and Analyzing BCI2000 Data with [[User Reference:Matlab MEX Files\|Matlab MEX Files]]
			* Analyze BCI2000 Data in Python with [https://github.com/neurotechcenter/BCI2kReader BCI2k Reader]

	==Mu Rhythm/SMR Data Analysis==		==Mu Rhythm/SMR Data Analysis==

Mellinger: /* P300/ERP Data Analysis */

2012-11-23T18:19:18Z

P300/ERP Data Analysis

← Older revision		Revision as of 18:19, 23 November 2012
Line 24:		Line 24:
	:will guide you through a time-domain offline analysis using some sample ECoG data included with ''BCI2000''		:will guide you through a time-domain offline analysis using some sample ECoG data included with ''BCI2000''

	*[[User_Reference:P300Classifier#Tutorial:Using the P300Classifier tool]]		*[[User_Reference:P300Classifier#Tutorial\|Using the P300Classifier tool]]
	:will show you how to train a classifier, and to obtain a set of configuration parameters, from data recorded with [[User Reference:StimulusPresentationTask\|StimulusPresentation]] or [[User Reference:P3SpellerTask\|P3Speller]] application modules.		:will show you how to train a classifier, and to obtain a set of configuration parameters, from data recorded with [[User Reference:StimulusPresentationTask\|StimulusPresentation]] or [[User Reference:P3SpellerTask\|P3Speller]] application modules.

Mellinger: /* P300/ERP Data Analysis */

2012-11-23T18:19:03Z

P300/ERP Data Analysis

← Older revision		Revision as of 18:19, 23 November 2012
Line 25:		Line 25:

	*[[User_Reference:P300Classifier#Tutorial:Using the P300Classifier tool]]		*[[User_Reference:P300Classifier#Tutorial:Using the P300Classifier tool]]
	:will show you how to train a classifier, and to obtain a set of configuration parameters, from data recorded with [[User Reference:StimulusPresentationTask StimulusPresentation]] or [[User Reference:P3SpellerTask P3Speller]] application modules.		:will show you how to train a classifier, and to obtain a set of configuration parameters, from data recorded with [[User Reference:StimulusPresentationTask\|StimulusPresentation]] or [[User Reference:P3SpellerTask\|P3Speller]] application modules.

	==Custom Data Analysis==		==Custom Data Analysis==

Mellinger: /* P300/ERP Data Analysis */

2012-11-23T18:17:19Z

P300/ERP Data Analysis

← Older revision		Revision as of 18:17, 23 November 2012
Line 25:		Line 25:

	*[[User_Reference:P300Classifier#Tutorial:Using the P300Classifier tool]]		*[[User_Reference:P300Classifier#Tutorial:Using the P300Classifier tool]]
	:will show you how to train a classifier, and to obtain a set of configuration parameters, from data recorded with [[User Reference:StimulusPresentation]] or [[User Reference:P3Speller]] application modules.		:will show you how to train a classifier, and to obtain a set of configuration parameters, from data recorded with [[User Reference:StimulusPresentationTask StimulusPresentation]] or [[User Reference:P3SpellerTask P3Speller]] application modules.

	==Custom Data Analysis==		==Custom Data Analysis==

Mellinger: /* P300/ERP Data Analysis */

2012-11-23T18:16:47Z

P300/ERP Data Analysis

← Older revision		Revision as of 18:16, 23 November 2012
Line 23:		Line 23:
	*[[User Tutorial:Performing a Time-Domain Offline Analysis of ECoG Data\|Performing a Time-Domain Offline Analysis of ECoG Data]]		*[[User Tutorial:Performing a Time-Domain Offline Analysis of ECoG Data\|Performing a Time-Domain Offline Analysis of ECoG Data]]
	:will guide you through a time-domain offline analysis using some sample ECoG data included with ''BCI2000''		:will guide you through a time-domain offline analysis using some sample ECoG data included with ''BCI2000''

			*[[User_Reference:P300Classifier#Tutorial:Using the P300Classifier tool]]
			:will show you how to train a classifier, and to obtain a set of configuration parameters, from data recorded with [[User Reference:StimulusPresentation]] or [[User Reference:P3Speller]] application modules.

	==Custom Data Analysis==		==Custom Data Analysis==

Jhill: /* Custom Data Analysis */

2012-01-28T02:50:47Z

Custom Data Analysis

← Older revision		Revision as of 02:50, 28 January 2012
Line 25:		Line 25:

	==Custom Data Analysis==		==Custom Data Analysis==

			For users who wish to go beyond the constraints of the analysis procedures in the tutorials, the following resources may be useful:

	* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.		* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.
	* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.		* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.


	==See also==		==See also==

← Older revision		Revision as of 15:20, 8 June 2022
Line 31:		Line 31:
	BCI2000 data files can be loaded, read, and analyzed in both Matlab and Python. For users who wish to go beyond the constraints of the analysis procedures in the tutorials, the following resources may be useful:		BCI2000 data files can be loaded, read, and analyzed in both Matlab and Python. For users who wish to go beyond the constraints of the analysis procedures in the tutorials, the following resources may be useful:

			* The [[User_Reference:BCI2000Analysis\|BCI2000Analsyis tool]] may be used to create filter graphs from BCI2000 processing steps offline in a GUI, and to train classifiers.
	* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.		* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.
	* The [[User_Reference:BCI2000Analysis\|BCI2000Analsyis tool]] may be used to create filter graphs from BCI2000 processing steps offline in a GUI, and to train classifiers.
	* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.		* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.
	** BCI2000 Data can be converted and analyzed using [[User Reference:Matlab MEX Files\|Matlab MEX Files]]		** BCI2000 Data can be converted and analyzed using [[User Reference:Matlab MEX Files\|Matlab MEX Files]]

← Older revision		Revision as of 15:20, 8 June 2022
Line 32:		Line 32:

	* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.		* The [[User_Reference:Command_Line_Processing\|BCI2000 command-line tools]] can be used to recreate a chain of BCI2000 processing steps offline, from a system command-line.
			* The [[User_Reference:BCI2000Analysis\|BCI2000Analsyis tool]] may be used to create filter graphs from BCI2000 processing steps offline in a GUI, and to train classifiers.
	* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.		* The Matlab function <tt>bci2000chain</tt>, part of BCI2000's suite of [[User_Reference:Matlab_Tools\|Matlab tools]], provides a convenient interface to this from within Matlab.
	** BCI2000 Data can be converted and analyzed using [[User Reference:Matlab MEX Files\|Matlab MEX Files]]		** BCI2000 Data can be converted and analyzed using [[User Reference:Matlab MEX Files\|Matlab MEX Files]]