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Welcome to the OpenSense documentation! To complete this example, you will need to download OpenSim 4.1 or later. If you try the example and software, please send any issues or feedback to opensim@stanford.edu. Note that the functionality has been improved in later versions including the introduction of visualization tools for IMU data in version 4.2. |
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OpenSense is a new workflow for analyzing movement with inertial measurement unit (IMU) data. In the page below, we introduce you to the tool, show you how to get started, and describe how to use the software to compute and analyze gait kinematics through a hands-on example.
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OpenSense provides an interface to associate and register each IMU sensor with a body segment of an OpenSim model (as an IMU Frame). We provide a basic calibration routine in which the first time step of IMU data is registered to the default pose of the model. You change the registration pose by changing the default coordinate values of the model. You can also write your own calibration procedures in Matlab, Python, etc. to optimize the initial pose of the model for calibration using other data sources (markers, goniometer, etc). Read more about these steps in our User's Guide chapter on the IMU Placer tool.
Computing Inverse Kinematics
An inverse kinematics method is used to compute the set of joint angles at each time step of a motion that minimizes the errors between the experimental IMU orientations and the model’s IMU Frames. The angles can then be used as inputs to other OpenSim tools and analyses or you can visualize these angles in the OpenSim GUI. The OpenSense capabilities are available through the command line and through scripting (Matlab or Python). As of OpenSim 4.2, the calibration and inverse kinematics steps are also available through the OpenSim GUI. The resulting Model and Motion can be loaded, visualized, and analyzed in the OpenSim GUI. In the future, we will also provide a direct GUI-based tool to run IMU-based kinematics. Read more about this step in the User's Guide chapter on IMU Inverse Kinematics.
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How to Setup the OpenSense Tools
The OpenSense workflow is available as of OpenSim 4.1. To get started, you will first need to download and install the latest OpenSim version (minimum version is 4.1). OpenSense can be downloaded from SimTK, with both Windows and Mac builds available. You can perform the OpenSense workflow on Mac or Windows through:
- Matlab scripting: To use OpenSense in Matlab, follow the Matlab scripting setup instructions.
- Python scripting: To use OpenSense in Python, follow the Python scripting setup instructions.
- Command line: To use OpenSense from the command line, read about the Command Line Utilities
- GUI: To use OpenSense tools from the application GUI (version 4.2 and later). The setup files are included under the "Models\Rajagopal_OpenSense" folder included with the distribution.
As with OpenSim, the OpenSense tools use XML settings files to specify the details of your workflow.
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Running OpenSense to Compute Gait Kinematics
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- Step One: Collect and Prepare IMU Data
- Step Two: Read Your Data into OpenSense
- Step Three: Calibrate an OpenSim Model
- Step Four: Perform IMU Sensor Tracking
- Step Five: Visualize the Results of IMU Tracking
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We use Xsens sensor data in this example, but all the steps for using APDM sensors are identical except for data reading. Read how to import APDM sensor data in the section below. Please note that the data in this example is for illustrative purposes and not intended for research use.
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Once you have collected and pre-processed your data, you must convert it to OpenSim's file format and associate it with an OpenSim model. Data from IMUs can be in various formats: a single file with numbered sensor names (e.g., APDM) or multiple files with sensor-specific numbering (e.g., Xsens). Upon import, OpenSim will create a single, time synced, Storage (.sto) file format for orientations, converting the rotation matrices into quaternions.
In this example, we will be using data from an Xsens system that has been pre-processed (e.g., time-syncing and sensor fusion has been performed) and exported to an Xsens text format. You can find this data in the IMUData folder. Each Xsens sensor is represented by a single text (.txt) file with time histories of the internal sensor data. We assume the data reported by the IMU system to include orientations (in the case of XSens these are assumed to be direction-cosine-matrices).
To read your data, you first need to create a file that lets OpenSense know which sensor is associated with which body segment in the Model. In our example, this file is called myIMUMappings.xml. You can open and edit this file in any text editor. In this settings/XML file you specify the following information:
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The next step is to calibrate the IMUs to an OpenSim model. The OpenSense Calibration step takes an OpenSim Model and the IMU calibration data and finds the initial orientations of the IMU Frames (i.e. offsets) relative to the OpenSim body segments. We provide a basic algorithm for calibration or you can also create your own methods of calibration by developing your own algorithms (in C++ or via scripting) to compute a default pose and/or the transforms of the IMU sensors.
To calibrate your model, you first need a setup file that stores information about the model, orientations file, and some settings to be used during the calibration procedure. In our example, this file is called myIMUPlacer_Setup.xml. You can open and edit this file in any text editor. In this settings/XML file you specify the following information:
- <model_file> To use OpenSense's calibration, you must provide an OpenSim Model in the calibration step. In our example, we are using the Rajagopal (2015) model. As noted above, on data read, your Model should have IMU Frames attached that correspond to the name_in_model specified in Step Two, or if you use our assumed naming convention (<bodyname>_imu), the calibrate step will add IMU Frames to the model as long as there is a corresponding body segment with a matching <bodyname>.
OpenSense calibration assumes that the pose of the subject in the calibration data matches the default pose of the model. In our example, the calibration pose is with the pelvis, hip, knee, and ankle at neutral, so we did not need to make any adjustments to the model's default pose. If you use a different pose, you can edit the pose of the input in the OpenSim GUI, through scripting, or in XML (see Coordinate Controls and Poses to learn how to edit the default pose through the OpenSim GUI).
<orientation_file_for_calibration> You must next provide the calibration data. OpenSense assumes the first time point corresponds to the calibration pose. If you have a trial where the calibration pose is performed at some time other than the first time row, you must edit your orientations file (or make a new one) where the first time row best corresponds to the calibration pose.
- <sensor_to_opensim_rotations> You must also provide the rotation needed to convert the IMU world Frame (typically Z up, Y to the left) to the OpenSim world Frame (Y up, Z to the right).
You can also specify optional arguments that enable OpenSense to correct or adjust for the overall difference in the heading (forward direction) of the IMU data versus that of the OpenSim model. Typically, an OpenSim model is facing in the positive X direction of the ground Frame in the initial pose, but the base IMU (e.g., on the pelvis or torso) can have any initial heading. To perform heading correction update the following settings:
- <base_imu_label> This is the label that identifies the base IMU in the provided orientation data. The default is no base_imu_label provided, and thus no heading correction will be performed.
- <base_heading_axis> This is the axis of the base IMU that represents its heading direction. The axis can be 'x', '-x', 'y', '-y', 'z' or '-z'.
An example setup file is shown below:
OpenSense will compute the angular offset between the two poses and use it to rotate all the orientation data so that the heading of the base IMU is now directed along the X-axis of the OpenSim ground reference Frame (same as the model). In our example, the pelvis_imu is set as the base IMU and z is the axis of the base IMU that corresponds to its heading, If either <base_imu_label> or <base_heading_axis> are not provided, then no heading correction is performed.
- <output_model_file> The output of the calibration step is a calibrated model, where each IMU is registered to the OpenSim model. This setting allows you to specify the output model file name.
The image below shows our example subject with IMU's on the pelvis, trunk, thighs, shanks, and feet segments and the corresponding OpenSim model with the matching pose.
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| A visualizer window will appear, showing the calibrated model. The pose of the model is determined by the model's default pose and will not change from one calibration to the next (unless you edit the model's default pose). What will change is the orientation of the sensors attached to each body. You can zoom in on the sensors, represented as small orange bricks located at the COM of each body. Note: You can close the visualizer window, when selected, by using the keyboard shortcut of ctrl-Q (command-Q on Mac). |
| You will see a print out the calibration offset for each IMU. This is the transform between the model body and the IMU sensor. To continue the calibration, and print the calibrated model to file, select the visualizer window and press any key to continue. The Calibrated Model is written to file and will have the postfix '' added (i.e., if the input Model file is called model.osim, the output calibrated model file will be named model_calibrated.osim). |
Using the OpenSim
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Application (GUI)
As of version 4.2 you can execute this step from the OpenSim application by invoking Tools→IMU Placer and loading the settings from the file myIMUPlacer_Setup.xml created above, or entering the data manually in the dialog as shown below, then hitting the Run button. After you run the tool, a new model with IMUs placed on it will appear in the application.
Step Four: Perform IMU Sensor Tracking Anchor stepfour stepfour
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Now that you have read in your data and calibrated your model, you can use OpenSense's Inverse Kinematics to track Orientation data from IMU sensors. The Inverse Kinematics step finds the pose of the model at each time-step that minimizes, in the least-squares sense, the difference between the orientation data from the IMU sensors and the IMU Frames on your calibrated model. The computed kinematics depend on both the calibrated model and the sensor data. Thus to perform inverse kinematics tracking of orientation data you need (i) a Calibrated Model (.osim), (ii) an orientations file (as quaternions), and (iii) an Inverse Kinematics Setup file (.xml). Using the calibrated model we generated in the previous section, we will track orientation data for walking that we read in during Step Two.
In a text editor— such as Notepad++, SublimeText, Atom, or Matlab— open the myIMUIK_Setup.xml file. The setup file stores properties that tell OpenSense how to run the Inverse Kinematics simulation. In the setup file, you specify:
<time_range> The time range for the inverse kinematics tracking (in seconds). In our example, we use data between 7.25 and 15 seconds.
- <sensor_to_opensim_rotations> The rotation needed to convert the IMU world Frame (typically Z up, Y to the left) to the OpenSim world Frame (Y up, Z to the right).
- <model_file_name> The name/path to the calibrated model file (.osim) to be used in tracking. In our example, this is the Rajagopal_2015_calibrated.osim file that was the output of Step Three.
- <orientations_file_name> The name/path to a .sto file of sensor Frame orientations (as quaternions) that will be tracked. In our example, this is the MT_012005D6_009-001_orientations.sto we created in Step Two.
- <results_directory> The directory where the results will be printed to file.
An example setup file is shown below.
For now, leave these settings as they are. This settings file can be copied and edited for your own workflow.
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To perform Inverse Kinematics with OpenSense from the command line, use the following steps.
The output motion file is written to file and will have the prefix 'ik_' added (i.e., if the input orientations file is called MT_012005D6_009-001_orientations.sto, the output motion file will be named IKResults/ik_MT_012005D6_009-001_orientations.mot) |
Using the OpenSim
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Application (GUI)
As of version 4.2 you can execute this step from the OpenSim application by invoking Tools→IMU Inverse Kinematics and loading the settings from the file imuInverseKinematics_Setup.xml created above, or entering the data manually in the dialog as shown below, then hitting the Run button, the . The IK problem will be solved and the solution will be animated in the application.
Step Five: Visualize the Results of IMU Tracking Anchor visualizeResults visualizeResults
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To view the Inverse Kinematics results:
- Open the OpenSim 4.1 application application.
- Open the model: calibrated_Rajagopal_2015.osim
- Load the motion you created in Step Four: IKResults/ik_MT_012005D6_009-001_orientations.mot. Since the IMUs cannot track global translations, only relative orientations, the model appears to rotate about a single place.
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- In the taskbar, select Tools → Plot.
- Select Y-Quantity→ Load File, and select IKResults/MT_012005D6_009-001_orientations.sto
- Select the hip_flexion_r, knee_angle_r, & ankle_angle_r coordinates.
- Select X-Quantity→ Time.
- Select Add
Customizing the OpenSense Workflow via Matlab Scripting Anchor matlabscripting matlabscripting
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We ran the OpenSense through the Matlab scripting environment in a simplified manner in the steps above. The Matlab interface provides additional tools to customize your workflow.
Example Matlab scripts to compute gait kinematics
We have provided a set of scripts to run through the workflow from the example above in Matlab.
Matlab scripting to create an orientations file from IMU sensor data
You can read your IMU data into OpenSense through the Matlab scripting interface. Note that, as in the example above, we will still use the myIMUMappings.xml file to define the mappings from IMU sensor to OpenSim model. A feature of the scripting interface is that you can also read and export the IMU accelerations, magnetometer, and gyro data to file.
- Launch Matlab and navigate to the OpenSenseExample folder.
- Open and run the OpenSense_IMUDataConverter.m script.
- Run the script. This will generate an orientations file, MT_012005D6_009-001_orientations.sto, as well as _acceleration, _magnetometer, and _gyro data files.
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To use the OpenSense APDM command-line tool to read in the APDM data and export an orientations .sto file to use in OpenSense, you would use the below call.
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>> opensense -ReadAPDM exampleAPDM_Data.csv exampleAPDM_Settings.xml |
Future Work
The current version of OpenSense is our first step in bringing IMU-based biomechanics to the research community. We plan several additional enhancements and new features in future releases, for example:
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