====== Metric Interquartile====== =====Overview===== The **Metric Interquartile** command is used to find the range of the middle 50% of datapoints within a set. A quartile is a statistical measure that divides a data set into four equal parts, with each part representing 25% of the observations. There are three quartile values: the first quartile (Q1), which marks the 25th percentile; the second quartile (Q2), which is the median; and the third quartile (Q3), which marks the 75th percentile. The **interquartile range** can be defined as Q3-Q1 and can be helpful when analyzing the variability of data and/or identifying outliers. Read more [[https://en.wikipedia.org/wiki/Interquartile_range|here]]. =====Pipeline Command===== The command can be found in the **Pipeline Workshop** under **Metric** as so: Metric_Interquartile ! /RESULT_METRIC_FOLDER=PROCESSED /RESULT_METRIC_NAME= ! /APPLY_AS_SUFFIX_TO_SIGNAL_NAME=FALSE /SIGNAL_TYPES= ! /SIGNAL_FOLDER=ORIGINAL ! /SIGNAL_NAMES= ! /COMPONENT_SEQUENCE= /EVENT_SEQUENCE= /EXCLUDE_EVENTS= ! /GENERATE_MEAN_AND_STDDEV=TRUE ! /GENERATE_MEAN_AND_STDDEV_ACROSS_SUBJECTS=FALSE ! /APPEND_TO_EXISTING_VALUES=FALSE ; ====Command Parameters==== The following table shows the command parameters seen above and their descriptions: |**RESULT_METRIC_FOLDER**|**The name of the result signal folder**| |**RESULT_METRIC_NAME**|**The name of the result signal**| |**APPLY_AS_SUFFIX_TO_SIGNAL_NAME**|**Specify the metric name to be the ORIGINAL signal plus a SUFFIX**| |**SIGNAL_TYPES**|**Specify the signal type**| |**SIGNAL_FOLDER**|**Specify the origin folder**| |**SIGNAL_NAMES**|**Specify the Signal to be used**| |**COMPONENT_SEQUENCE**|**Specify the Signal components to be used (e.g. X + Y + Z or 0 + 1 + 2 etc)**| |**EVENT_SEQUENCE**|**A list of events (separated by "+" signs). For example, LHS+RTO**| |**EXCLUDE_EVENTS**|**If this event occurs before the first and last event, do not computed a metric**| |**GENERATE_MEAN_AND_STDDEV**|**Generate the mean and standard deviation of this metric**| |**GENERATE_MEAN_AND_STDDEV_ACROSS_SUBJECTS**|**Generate the mean and standard deviation of this metric across ranges and files**| |**APPEND_TO_EXISTING_VALUES**|**Add these metric values to an existing metric**| ====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: {{:interquartile_dlg.png}} The dialog box allows you to assign values to the command parameters outlined above. ==== Example: COFP Range for balance trial ==== Here the **Metric Interquartile** command is used to analyze center of foot pressure data during a standing trial and compare the ranges computed for a subject's left and right sides. The command for the right side looks like this: Metric_Interquartile ! /RESULT_METRIC_FOLDER=PROCESSED /RESULT_METRIC_NAME=COFP_RIGHT_INTER ! /APPLY_AS_SUFFIX_TO_SIGNAL_NAME=FALSE /SIGNAL_TYPES=COFP ! /SIGNAL_FOLDER=ORIGINAL /SIGNAL_NAMES=FP3 /COMPONENT_SEQUENCE=ALL /EVENT_SEQUENCE=START+END /EXCLUDE_EVENTS= ! /GENERATE_MEAN_AND_STDDEV=TRUE ! /GENERATE_MEAN_AND_STDDEV_ACROSS_SUBJECTS=FALSE ! /APPEND_TO_EXISTING_VALUES=FALSE ; COFP is a 2 dimensional signal, with the X and y components representing the medial/lateral and anterior/posterior directions respectively. The resulting metrics contain an x value and a y value indicating the variation in pressure for each direction during the trial. A larger range indicates greater variation in the COFP value during the trial and a less consistent balance point. The results for this trial show a larger range for the right side than left and a greater range in the Y direction than X for both sides. {{:cofp_left.png}}{{:cofp_right.png|}} ====Example: Comparing Interquartile Ranges for joints==== In this example **Metric Interquartile** is used to compare the left and right ankle angles of subjects running on a treadmill. First, **Automatic Gait Events** is used to define key events that will define the following commands: Automatic_Gait_Events ! /FRAME_WINDOW=8 ! /USE_TPR=TRUE ! /TPR_EVENT_INSTANCE=1 ; Next, the **Interquartile** command is used to identify the middle 50% range of ankle angle values for both sides between toe and heel strikes. Metric_Interquartile ! /RESULT_METRIC_FOLDER=PROCESSED /RESULT_METRIC_NAME=RANKLE_INTER ! /APPLY_AS_SUFFIX_TO_SIGNAL_NAME=FALSE /SIGNAL_TYPES=LINK_MODEL_BASED ! /SIGNAL_FOLDER=ORIGINAL /SIGNAL_NAMES=RAnkleAngle ! /COMPONENT_SEQUENCE= /EVENT_SEQUENCE=RHS+RTO /EXCLUDE_EVENTS= ! /GENERATE_MEAN_AND_STDDEV=TRUE ! /GENERATE_MEAN_AND_STDDEV_ACROSS_SUBJECTS=FALSE ! /APPEND_TO_EXISTING_VALUES=FALSE ; Metric_Interquartile ! /RESULT_METRIC_FOLDER=PROCESSED /RESULT_METRIC_NAME=LANKLE_INTER ! /APPLY_AS_SUFFIX_TO_SIGNAL_NAME=FALSE /SIGNAL_TYPES=LINK_MODEL_BASED ! /SIGNAL_FOLDER=ORIGINAL /SIGNAL_NAMES=LAnkleAngle ! /COMPONENT_SEQUENCE= /EVENT_SEQUENCE=LHS+LTO /EXCLUDE_EVENTS= ! /GENERATE_MEAN_AND_STDDEV=TRUE ! /GENERATE_MEAN_AND_STDDEV_ACROSS_SUBJECTS=FALSE ! /APPEND_TO_EXISTING_VALUES=FALSE ; The results for this trial show that the subjects on average exhibited a larger interquartile range for flexion of their left ankles than right. {{:lankle_inter.png|}}{{:rankle_inter.png|}}