Inspect3D Overview
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Inspect3D. Analytics and Data Exploration for Biomechanics.
Visual3D is an incredibly accurate, flexible, and useful tool to process motion capture data.
However, it is primarily session based and users often assume the responsibility of grouping data and calculating metrics. This is where Inspect3D comes in - it allows users to easily group and plot data, exclude "bad" cycles of data, and export metrics.
The video above describes how to load an existing CMO library, normalize all signals in the Link Model Based folder (ex. Joint Angles, Moments, etc.), average left and right sides together, then calculate, plot and export the mean data, all done in under five minutes.
Loading Data: CMO Library
Inspect3D uses the CMO Library to read data. So each subject/session should have a CMZ file created by Visual3D, and Inspect3D should point to the root directory.
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Manually Grouping Data
Once the CMO Library path is defined, you can define groups to indicate what signals you want to analyze, and how you want them grouped (ex. average all right/left sagittal ankle angles for treadmill trials). Data can be grouped based on tags, events, signals or expressions.
Examples of common groupings are:
- Right & Left signals (ex. control data base)
- Right Ankle Angle + Left Ankle Angle
- Affected/Unaffected
- Affected Right Ankle Angle + Affected Left Ankle Angle vs Unaffected Right Ankle Angle + Unaffected Left Ankle Angle
- Pitching
- Pitching Side vs Non pitching side
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Plotting and Inspecting Data
Once you have defined the signals you are interested in viewing, you can plot them easily as individual traces, workspace means, or group means. You can click on specific cycles and choose to exclude them from analysis.
This is an incredibly important quality assurance step.
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Exporting Data
Normalized signal data or metrics such as max/min can be exported to a text file. Text data can be exported in the default Visual3D text file format, but other formats are available as well.
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Autogenerating Groups
Defining the signals you are interested in analyzing may be tedious, so an automatic signal generation tool is available. Group names can be modified or removed after they've been defined.
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Working with Metrics
Inspect3D also allows you to view and analyze metric data calculated in Visual3D on bar charts.
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Inspect3D and the Visual3D CMO Library
The Inspect3D program accesses Visual3D's CMO library directly, and is thus ideal for exploring large amounts of data from the library. Visual3D tends to be a "session based" analysis tool, and is used to process data from one (or a few) data collection sessions, rather than a project based tool. Inspect3D was created to bridge the gap between the biomechanical analysis of the Motion Capture data collected from a single subject to the scientific enterprise of trying to make sense of data from a group or population.
The CMO Library (more...) | ||
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Grouping Data
Grouping Data (more....) | ||
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Exporting Data
Inspect3D lets you export average normalized signals, metrics (max/min), or PCA values to the default Visual3D text file format, or to several other text file formats.
Exporting Data (more...) | ||
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Quality Assurance
During the development of Inspect3D we discovered that it was incredibly useful for exploring data quickly, and its role in "Quality Assurance" dominated our early use of the tool. Many research studies involve data collected by multiple investigators from multiple labs - differences that are liable to lead to artifact. The Quality Assurance function of Inspect3D is particularly helpful for lab managers (or supervisors of students) who may not be familiar with the raw data, or for collaborators that were not involved in the data collection process. For instance, Inspect3D allows the user to check the force assignments of all their files at once, and then easily correct any artifacts that are found.
Thanks to [XKCD.com]
Most, if not all, Motion Capture data contains artifact of some sort, and it is a nuisance, at best, and a catastrophe, at worst, if these affect the statistical analysis, and consequent interpretation of data. Inspect3D's ability to provide a straightforward way to examine all data used in any statistical analysis has generated considerable interest with academic and industrial researchers, during many discussions we have held at various conferences and lab visits, all over the world, this year.
These two figures contain data from the same cmo library. Several of the signals in the left figure were artifacts that were removed from the analysis by Inspect3D. Each signal can be traced back to its source data file to verify that there was something wrong, or that the problem was correctable (e.g. Motion Capture markers may have been mislabeled). Clearly stats performed on the left graph will be different that the same stats on the right graph.
Inspect3D takes a necessary chore that may take hours using other software into a streamlined process that takes minutes to perform.
Data Quality Assurance (more....) | ||||||||
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If an errant signal is found in these other packages, it can be both difficult and time consuming to trace the issue back to a cmo file and individual trial. Inspect3D is tightly coupled with the cmo library.
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Biomechanical Waveform Data.
Many biomechanical signals (eg. joint angles or joint moments) are represented by a time series of data and should be compared statistically as time series.
Zero dimensional analyses of one dimensional signals (more....) |
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Each of the signals in the figure is time normalized to 101 points (common in most gait studies), resulting in more than 10,000 data points in this figure. In the figure there is data from two groups of subjects. Identifying differences between groups (typically an important statistical goal) is challenging because of the substantial variability within each group. The challenge is to identify the most salient features of the data that discriminate the two groups without removing important information.
Principal Component Analysis.
The original intention of Inspect3D was actually to perform waveform based Principal Component Analysis (PCA). PCA was developed in Collaboration with Dr. Kevin Deluzio at Queen's University, and follows the explanation of the analysis described in Research methods in Biomechanics.
Principal Component Analysis (more....) | ||
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For a step-by-step example of how to use Inspect3D PCA see our Principal Components Analysis Tutorial.
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