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--- tools [2022/06/26 20:45]
154.54.249.194 alte Version wiederhergestellt (2022/05/04 23:23)
+++ tools [2024/04/26 19:38] (aktuell)
37.187.73.123 alte Version wiederhergestellt (2023/11/13 17:13)
@@ Zeile 1: / Zeile 1: @@
+======Dataminer======
+The datamining tool determines and extracts specific defined parameters (single values) from timeseries data, e.g. maximum, minimum or mean values of specific phases or at specific positions (events). Details are described in the [[http://nimue-platform.de/doku.php?id=analysistools:motiondataminer|Dataminer platform documentation]].
+=====Features=====
+For a long time in the Gaitlab Heidelberg the Matlab based tools "**GDMiner**" and "**Parametersuche**" are used. Last one is part of the Database "**HeiDataProVIT**". The Datmining functionality of the "**GaitlabHDApp**" is an alternative to these tools, with more flexibility and some advantages:
+  * It works for arbitrary filetypes, not only normalized data saved as [[http://nimue-platform.de/doku.php?id=fileformats:hdascii|HD-ASC]].
+  * The input-files with the paths to the input data are saved as XML.
+  * The legacy file type - ASCII tab-delimited format (e.g. created from the **Parametersuche** of **HeiDataProViT**) - can be imported. **No problems caused by unvisible/nonprintable characters any more**.
+=====Advantages in comparison to GDMiner=====
+   * **GDMiner** can work only with [[http://nimue-platform.de/doku.php?id=fileformats:hdascii|HD-ASC]] average files (gla) and it assumes, that all timeseries are time-normalized and have a prefix "Mean" or "Std". The dataminer tool of the Nimue-Platform can work with arbitrary file types: gla, glx, glm, c3d, d3d, ...
+   * It has its own robust [[http://nimue-platform.de/doku.php?id=generalfeatures:sessionsets|XML-file type to define path lists]]. **No problems with unvisible/nonprintable characters any more** (import function for csv-files are available)
+   * More flexibility in definition of phases: E.g. phases can start with "RTO" (This was needed for "Evas" project).
+===== Advantages in comparison to Parametersuche =====
+  * Multiple "Parametersuche" in one step.
+  * Calculation of data for both sides in one step.
+  * The data processing settings can be saved as an [[http://nimue-platform.de/doku.php?id=generalfeatures:sessionsets|XML-file]] for future use.
+  * Possibility to select multiple "gait phases" for calculations.
 ======Gait indizes======
 =====Gait profile score======
 =====Gait deviation index======
-======Generic data mining======
+======MoMo Integration======
-=====Advantages in comparison to GDMiner=====
+There are several tools which support legacy MoMo and Matlab Tools, described in the Nimue platform documentation, [[http://nimue-platform.motion-science.org/doku.php?id=glue:momo|here]].
-   * Its own robust xml-file with path lists, no problems with non printable characters (import function for old csv-file is available)
-   * More flexibility in definition of phases. Phases can start with RTO. This was needed for Evas project.
+The following tools are available:
-======Working with Session Sets======
-A Session Set defines a list of paths to data sessions and can include additional columns with allocated data. The data is organized as a table with rows and columns.
+==== Usage of Examination info files ====
-=====Import of csv-files======
+[[http://nimue-platform.motion-science.org/doku.php?id=glue:momo#examination_information|here]]
-A csv-file as it can be exported via Excel can be imported in a Nimue-Platform Project. It is saved as an xml-file in the subfoler "SessionSets" in the project.

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