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--- visual3d:documentation:pipeline:metric_commands:metric_event_sequence_count [2024/07/16 19:29] – created sgranger
+++ visual3d:documentation:pipeline:metric_commands:metric_event_sequence_count [2025/09/24 14:26] (current) – [Example: Time_Interval] wikisysop
@@ Line 1: / Line 1: @@
-====== Metric_Event_Sequence_Count ======
+====== Metric Event Sequence Count ======
-Creates a metric containing the number of Event Sequences.
+====Overview====
-|<code>\\ Metric_Event_Sequence_Count\\ ! /RESULT_METRIC_FOLDER=The resulting folder of the metric \\ /RESULT_METRIC_NAME= The resulting name of the metric \\ ! /TIME_INTERVAL= The number of event sequences which occur\\   within a time interval\\ /EVENT_SEQUENCE= The event sequence to search for and count \\ /EXCLUDE_EVENTS= Don't count a sequence that contains this \\  event \\ ! /GENERATE_COUNT_TOTAL_IN_GLOBAL= Create a global count\\   over the active files\\ ;\\ </code>  |  {{EventsSequenceCountDlg.png}}|
+**Metric Event Sequence Count** Creates a metric containing the number of Event Sequences. When a movement or series of movements (like a jump) is defined by an event sequence this command can be used to count the number of repetitions of that movement. The command can be found within the **Pipeline Workshop** under **Metric**.
-\\
+====Pipeline Command====
-\\
+<code>
+Metric_Event_Sequence_Count
+! /RESULT_METRIC_FOLDER=The resulting folder of the metric
+/RESULT_METRIC_NAME= The resulting name of the metric
+/TIME_INTERVAL= The number of event sequences which occur within a time interval
+/EVENT_SEQUENCE= The event sequence to search for and count
+/EXCLUDE_EVENTS= Don't count a sequence that contains this event
+! /GENERATE_COUNT_TOTAL_IN_GLOBAL=
+;
+</code>
-==== Time_Interval ====
+====Command Parameters====
-**The Time_Interval parameter can be used to count the number of events that occur within a specific interval.**
+The following table shows the command parameters and descriptions:
+|**RESULT_METRIC_FOLDER**|**The resulting folder of the metric**|
+|**RESULT_METRIC_NAME**|**Information about Parameter**|
+|**TIME_INTERVAL**|**The number of event sequences which occur within a time interval**|
+|**EVENT_SEQUENCE**|**The event sequence to search for and count**|
+|**EXCLUDE_EVENTS**|**Don't count a sequence that contains this event**|
+|**GENERATE_COUNT_TOTAL_IN_GLOBAL**|**Create a global count over the active files**|
+====Dialog====
+The command can be edited in a text editor or in a dialog form. To edit in the dialog pop up form either click on the **Edit** button in the pipeline workshop or double-click on the pipeline command. The dialog is shown below.
+{{:EventsSequenceCountDlg.png}}
+The dialog box allows you to assign values to the command parameters outlined above.
+====Example: Time_Interval ====
+The **Time_Interval** parameter can be used to count the number of events that occur within a specific interval.
 === Command Setup ===
-**If a trial is 20 seconds long, and a 5.0 second interval is specified, the result will be 4 metrics. Each metric will contain the number of event sequences which occur within each 5.0 second window.**
+If a trial is 20 seconds long, and a 5.0 second interval is specified, the result will be 4 metrics. Each metric will contain the number of event sequences which occur within each 5.0 second window.
-|<code>\\ Metric_Event_Sequence_Count\\ ! /RESULT_METRIC_FOLDER= PROCESSED\\ /RESULT_METRIC_NAME= LSWING_COUNT_INT\\ /TIME_INTERVAL= 5.0\\ /EVENT_SEQUENCE= The event sequence to search for and count \\ /EXCLUDE_EVENTS= Don't count a sequence that contains this \\  event \\ ! /GENERATE_COUNT_TOTAL_IN_GLOBAL= Create a global count\\   over the active files\\ ;\\ </code>  |  {{EventsSequenceCount_Interval.png}}|
+<code>
+Metric_Event_Sequence_Count
+! /RESULT_METRIC_FOLDER= PROCESSED
+/RESULT_METRIC_NAME= LSWING_COUNT_INT
+/TIME_INTERVAL= 5.0
+/EVENT_SEQUENCE= The event sequence to search for and count
+/EXCLUDE_EVENTS= Don't count a sequence that contains this event
+! /GENERATE_COUNT_TOTAL_IN_GLOBAL= Create a global count over the active files
+;
+</code>
+{{:EventsSequenceCount_Interval.png}}|
 === Result ===
-|**When using a 5 second interval on a 20 second trial, the result will be four metrics (20/5).**\\ \\ (1) The first metric will contain the number of times the sequence occurs during the first 5 seconds of the trial\\ (2) The second metric will contain the number of times the sequence occurs during the 5 - 10 second interval of the trial\\ (3) The third metric will contain the number of times the sequence occurs during the 10 - 15 second interval of the trial\\ (4) The fourth metric will contain the number of times the sequence occurs during the 15 - 20 second interval of the trial\\ \\ **NOTE:** If the event sequence occurs between two intervals (LTO occurs at 4 sec and LHS occurs at 6 sec), this sequence will be included in Interval 1.  |  {{EventsSequenceCount_Interval_Result.png}}|
+|**When using a 5 second interval on a 20 second trial, the result will be four metrics (20/5).**\\ \\ (1) The first metric will contain the number of times the sequence occurs during the first 5 seconds of the trial\\ (2) The second metric will contain the number of times the sequence occurs during the 5 - 10 second interval of the trial\\ (3) The third metric will contain the number of times the sequence occurs during the 10 - 15 second interval of the trial\\ (4) The fourth metric will contain the number of times the sequence occurs during the 15 - 20 second interval of the trial\\ \\ **NOTE:** If the event sequence occurs between two intervals (LTO occurs at 4 sec and LHS occurs at 6 sec), this sequence will be included in Interval 1.  |  {{:EventsSequenceCount_Interval_Result.png}}|
+====Complex Example: Approximating Strides Using Angular Velocity Thresholds====
+As a subject moves through the gait cycle the angular velocities of their joints and limbs follow a known sequence with each stride. For this example we will identify this sequence for the right shank and use **Metric Event Sequence Count** to approximate the number of strides in a trial.
+As a subject walks or runs their knees go through an alternating cycle of flexion and extension. This can be seen through many measurements, including the X component angular velocity of their shank. Here we use the **Event Threshold** command to identify each time that the angular velocity of the subject's right shank crosses 0 and goes from negative to positive or vice versa.
+<code>
+Event_Threshold
+/RESULT_EVENT_NAME=RSK_Positive
+/SIGNAL_TYPES=KINETIC_KINEMATIC
+/SIGNAL_FOLDER=RSK
+/SIGNAL_NAMES=AngVel
+/SIGNAL_COMPONENTS=X
+! /FRAME_OFFSET=0
+! /TIME_OFFSET=
+! /EVENT_SEQUENCE=
+! /EXCLUDE_EVENTS=
+! /EVENT_SEQUENCE_INSTANCE=0
+! /EVENT_SUBSEQUENCE=
+! /SUBSEQUENCE_EXCLUDE_EVENTS=
+! /EVENT_SUBSEQUENCE_INSTANCE=0
+! /EVENT_INSTANCE=0
+/THRESHOLD=0
+/ON_ASCENT=TRUE
+/ON_DESCENT=FALSE
+! /FRAME_WINDOW=8
+! /ENSURE_FRAMES_BEFORE=FALSE
+! /ENSURE_FRAMES_AFTER=FALSE
+;
+</code>
+<code>
+Event_Threshold
+/RESULT_EVENT_NAME=RSK_Negative
+/SIGNAL_TYPES=KINETIC_KINEMATIC
+/SIGNAL_FOLDER=RSK
+/SIGNAL_NAMES=AngVel
+/SIGNAL_COMPONENTS=X
+! /FRAME_OFFSET=0
+! /TIME_OFFSET=
+! /EVENT_SEQUENCE=
+! /EXCLUDE_EVENTS=
+! /EVENT_SEQUENCE_INSTANCE=0
+! /EVENT_SUBSEQUENCE=
+! /SUBSEQUENCE_EXCLUDE_EVENTS=
+! /EVENT_SUBSEQUENCE_INSTANCE=0
+! /EVENT_INSTANCE=0
+/THRESHOLD=0
+/ON_ASCENT=FALSE
+/ON_DESCENT=TRUE
+! /FRAME_WINDOW=8
+! /ENSURE_FRAMES_BEFORE=FALSE
+! /ENSURE_FRAMES_AFTER=FALSE
+;
+</code>
+Now, using these events we can use **Metric Event Sequence Count** to count the number of instances in which the right knee goes from flexing into extending and back again, with each of these representing one stride.
+<code>
+Metric_Event_Sequence_Count
+! /RESULT_METRIC_FOLDER=PROCESSED
+/RESULT_METRIC_NAME=RSK_flexion_extension
+! /TIME_INTERVAL=
+/EVENT_SEQUENCE=RSK_Positive+RSK_Negative
+/EXCLUDE_EVENTS=
+! /GENERATE_COUNT_TOTAL_IN_GLOBAL=TRUE
+;
+</code>
+A new folder should now be present in the **METRIC** folder containing a count of the event sequence. This number corresponds to the number of strides taken in a trial, which can be confirmed through further analysis or by watching the trial simulation.
+{{:visual3d:documentation:pipeline:metric_commands:rsk_count.png?500|}}