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 here.

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
;

The following table shows the command parameters seen above and their descriptions:

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

The dialog box allows you to assign values to the command parameters outlined above.

Determining the energy contributions of different joints during locomotion can be integral (no pun intended) to understanding the gait cycle and comparing one trial to another. Some subjects may rely more heavily on ankle propulsion, while others may see more energy production from their knees and hips as a result of factors like age or imbalances.

Here we use Automatic Gait Events and Metric Integrate to compare the work done by a subject's right and left knees while running on a treadmill.

First, define important gait events using Automatic Gait Events.

Automatic_Gait_Events
! /FRAME_WINDOW=8
! /USE_TPR=TRUE
! /TPR_EVENT_INSTANCE=1
;

Next we will compute the work done by the left and right knees by integrating knee power with respect to time.

Metric_Integrate
! /RESULT_METRIC_FOLDER=PROCESSED
/RESULT_METRIC_NAME=R_Knee_Work
! /APPLY_AS_SUFFIX_TO_SIGNAL_NAME=FALSE
/SIGNAL_TYPES=LINK_MODEL_BASED
! /SIGNAL_FOLDER=ORIGINAL
/SIGNAL_NAMES=RKneePower
/COMPONENT_SEQUENCE=X
/EVENT_SEQUENCE=RHS+RTO
/EXCLUDE_EVENTS=
/SEQUENCE_PERCENT_START=
/SEQUENCE_PERCENT_END=
! /GENERATE_MEAN_AND_STDDEV=TRUE
! /GENERATE_MEAN_AND_STDDEV_ACROSS_SUBJECTS=FALSE
! /APPEND_TO_EXISTING_VALUES=FALSE
;

Metric_Integrate
! /RESULT_METRIC_FOLDER=PROCESSED
/RESULT_METRIC_NAME=L_Knee_Work
! /APPLY_AS_SUFFIX_TO_SIGNAL_NAME=FALSE
/SIGNAL_TYPES=LINK_MODEL_BASED
! /SIGNAL_FOLDER=ORIGINAL
/SIGNAL_NAMES=LKneePower
/COMPONENT_SEQUENCE=X
/EVENT_SEQUENCE=LHS+LTO
/EXCLUDE_EVENTS=
/SEQUENCE_PERCENT_START=
/SEQUENCE_PERCENT_END=
! /GENERATE_MEAN_AND_STDDEV=TRUE
! /GENERATE_MEAN_AND_STDDEV_ACROSS_SUBJECTS=FALSE
! /APPEND_TO_EXISTING_VALUES=FALSE
;

6 new metrics have now been computed, the work, mean work, and standards deviation of work done for the left and right knees. Comparing the work done in each stride and mean work done for the left and right sides will help to identify any asymmetry between sides.

The results should look something like this:

• Impulse
• Joint_Work

NOTE: When using the Metric_Integrate dialog box, don't forget to Import the desired signals.