<p>This is a submitted draft of a paper on the design and validation of a Torso-dynamics Estimation System (TES). The TES consisted of a Force Sensing Seat (FSS) and an inertial measurement unit (IMU) that measured the kinetics and kinematics of the subject's torso motions. The FSS estimated the 3D forces, 3D moments, and 2D COPs while the IMU estimated the 3D torso angles. To validate the TES, the FSS and IMU estimates were compared to gold standard research equipment (AMTI force plate and Qualisys motion capture system, respectively).</p> <p>Potential applications of the TES include physical human-robot interaction (pHRI) for navigating riding or remote robots.</p> <p>The data and data processing code from this study are open source and can be found via the following links:</p> <ul> <li>IEEE DataPort with data: https://ieee-dataport.org/documents/validation-study-torso-dynamics-estimation-system-tes-hands-free-physical-human-robot </li> <li>GitHub repository with code: https://github.com/ssong47/TorsodynamicsEstimationSystem </li> </ul> <p><br></p>
The article presents the development process of the video game Huni Kuin: Yube Baitana (The ways of the boa constrictor) created by a group of Brazilian anthropologists with a Huni Kuin indigenous community from Acre, Brazil. Understood from a perspective in which video games must be taken seriously, a reflection is made on how the game Huni Kuin: Yube Baitana is inserted in the discussions and productions arising from multimodal anthropology.
<p>This is a submitted draft of a paper on the design and validation of a Torso-dynamics Estimation System (TES). The TES consisted of a Force Sensing Seat (FSS) and an inertial measurement unit (IMU) that measured the kinetics and kinematics of the subject's torso motions. The FSS estimated the 3D forces, 3D moments, and 2D COPs while the IMU estimated the 3D torso angles. To validate the TES, the FSS and IMU estimates were compared to gold standard research equipment (AMTI force plate and Qualisys motion capture system, respectively).</p> <p>Potential applications of the TES include physical human-robot interaction (pHRI) for navigating riding or remote robots.</p> <p>The data and data processing code from this study are open source and can be found via the following links:</p> <ul> <li>IEEE DataPort with data: https://ieee-dataport.org/documents/validation-study-torso-dynamics-estimation-system-tes-hands-free-physical-human-robot </li> <li>GitHub repository with code: https://github.com/ssong47/TorsodynamicsEstimationSystem </li> </ul> <p><br></p>
<p>This is a submitted (IEEE RO-MAN 2023) draft of a paper on the testing of a hands-free human-robot interaction for navigating a ballbot in a virtual environment. In this study, able-bodied users and manual wheelchair users controlled a virtual ballbot using a hands-free (HF) lean-to-steer control concept that uses torso motions. A custom sensor system (i.e., Torso-dynamics Estimation System (TES)) was utilized to measure and convert the dynamics of the rider’s torso motions into commands to provide HF control of the robot. A simulation study was conducted to explore the efficacy of the HF controller compared to a traditional joystick (JS) controller, and whether there were differences in performance by manual wheelchair users (mWCUs), who may have reduced torso function, compared to able-bodied users (ABUs). Twenty test subjects (10 mWCUs + 10 ABUs) used the subject-specific adjusted TES while wearing a virtual reality headset and were asked to navigate a virtual human rider on the ballbot through obstacle courses replicating seven indoor environment zones. </p>
<p>This is a submitted draft of a paper on the design and validation of a Torso-dynamics Estimation System (TES). The TES consisted of a Force Sensing Seat (FSS) and an inertial measurement unit (IMU) that measured the kinetics and kinematics of the subject's torso motions. The FSS estimated the 3D forces, 3D moments, and 2D COPs while the IMU estimated the 3D torso angles. To validate the TES, the FSS and IMU estimates were compared to gold standard research equipment (AMTI force plate and Qualisys motion capture system, respectively).</p> <p>Potential applications of the TES include physical human-robot interaction (pHRI) for navigating riding or remote robots.</p> <p>The data and data processing code from this study are open source and can be found via the following links:</p> <ul> <li>IEEE DataPort with data: https://ieee-dataport.org/documents/validation-study-torso-dynamics-estimation-system-tes-hands-free-physical-human-robot </li> <li>GitHub repository with code: https://github.com/ssong47/TorsodynamicsEstimationSystem </li> </ul> <p><br></p>
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