Improving Human Performance via Biomechanics, Robotics, Virtual Reality and More!
In the Human Performance and Robotics Laboratory, we focus our research in biomechanics, robotics, virtual reality and haptics*. The lab’s current main project is designing a full-body suit that tracks human motion and muscle activity, while providing motion-optimizing feedback.
The purpose of this project is to create a suit that can be used in possible applications such as: correcting posture while walking or running, providing guidance for blind people, and rehabilitation.
The lab also features other exciting projects that are being worked on by our graduate students. One such project is a generic, multibody simulation framework that can track and analyze human motion in real-time. The main advantage of this framework, compared to other existing simulation software, is the fact that it was built on top of a widely-supported game engine.
This means that the framework can easily be integrated with a plethora of technologies, such as: virtual reality, haptic feedback systems, and markerless motion capture.
Moreover, since the framework is generic by design, it can be used by other developers to create applications that use motion analysis . . . applications that can potentially be used towards human rehabilitation and training!
Speaking of human rehabilitation, another active project in our lab is a virtual reality simulation of a soccer environment that provides psychological rehabilitation for athletes who have suffered a traumatic injury on the field.
The project incorporates marker-based motion capture to track the athlete’s motion and control the simulation’s character in real-time. Athletes within the simulation will experience haptic feedback similar to kicking a soccer ball. Simulations such as this one can be used to provide physical/psychological rehabilitation in a control setting. Future applications of this project can include specific sport-related training.
One other interesting ongoing project is on optimization of running strategies. In this project we record the movement data and physiological data from human subjects while running. This data will be analyzed later using deep learning algorithms. This method returns useful information on the most important characteristics of a professional runner. These results are important for designing personalized training and rehabilitation plans.
Finally, the most recent project in our lab focuses on incorporating haptics* in a human robot collaborative manufacturing process to increase efficiency and task focus. The goal of this research project is to test the feasibility of incorporating haptic feedback as an alternative feedback method for robot-human collaboration, with a focus on manufacturing. As part of this project a haptic interface glove and arm sleeve will be designed to give haptic feedback to a user collaborating with a robot to complete a simulated manufacturing task.
* science of applying touch (tactile) sensation and control to interaction with computer applications
