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Standing Balance Experiment with Long Duration Random Pulses Perturbation

<p>Standing balance experiment and the measured data-set are fundamental for identifying postural feedback controllers. As the generalized feedback controllers can only be identified from long duration balance data (under random external perturbations), a standing balance experiment is conducted and the long duration motion data&nbsp;was recorded. The data-set includes the perturbation reaction data from eight subjects. Each subject performed four experiment trials, including two quiet standing and two perturbed trials. Each trial lasted five minutes. A total of 80 minutes quiet standing and 80 minutes perturbed standing data are included in this&nbsp;data-set. Recorded information including three dimensional trajectories of thirty-two&nbsp;markers (27 on subjects&#39; trunk and legs and 5 on the treadmill frame), six dimensional ground reaction forces, and nine Electromyography signals (EMGs, on subjects&#39; right leg). In addition, joint angles and torques were calculated using a human body model and inverse dynamics. Basic statistical analysis of the data is also included.</p> <p>Measured raw data for each subject in each experimental trial includes three files:</p> <ol> <li>Mocapxxxx.txt: contains motion capture marker data, ground reaction force, and 76 analog channels. Data was recorded at 100 Hz sampling rate.</li> <li>Mocapxxxx_Motion Analysis_analog.txt: contains 76 high sampling rate (1000Hz) analog channels&#39; data. Analog data is consisted of&nbsp;the analog singal from the froce sensor on the treadmill,&nbsp;EMG signals in the Delsys EMG sensors,&nbsp;and 3 axises acceeleration signals of the Delsys EMG sensors.</li> <li>Recordxxxx.txt: contains the sway motion data of treadmill and the three-axis acceleration data of two Xsens MTi-10 series sensors.</li> </ol> <p>Measured raw data also includes two&nbsp;files of the unloaded trial, which is used for the inertia compensation.</p> <ol> <li>Mocap0000.txt: contains motion capture marker data (5 markers on the treadmill frame) and ground reaction forces.</li> <li>Record0000.txt: contains the treadmill sway motion data and the acceleration data (three-axis) of two Xsens MTi-10 series sensors.</li> </ol> <p>Processed data of each subject in each experimental trial contains four files:</p> <ol> <li>Mocapxxxx.txt: contains the gap filled motion capture marker data and the inertia compensated ground reaction force data.</li> <li>Motionxxxx.txt: contains the calculated the trajectories of&nbsp;three joints&#39; (hip, knee, and ankle) angles, angular velocities, moments, and joint contact forces.</li> <li>Data_infoxxxx.txt: contains the quality of recorded raw marker data (percentage and biggest duration of missing marker data), and the percentage of removed inertia artifacts in ground reaction forces</li> <li>MotionAnalysis.fig: shows the mean and standard deviation of three joints&#39; trajectories in four experimental trials.</li> </ol> <p>There are two more plots in the processed data folder which shows the joint motion/moment and the raw/compensated ground reaction forces of one example experimental trial (subject 07 trial 03).</p> <p>The processed data was generated using the code in the &#39;Processing_Code&#39; folder. The code was wrote using Matlab and the&nbsp;main function is &quot;Data_Processing_Main.m&quot;</p> <p>More details of the standing balance experiment can be found in the document &#39;Standing_Balance_Experiment_with_Long_Duration_Random_Pulses_Perturbation.pdf&#39;</p>

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44/100

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These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
8

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