Discipline: Technology and Engineering
Subcategory: Biomedical Engineering
Vicente J. Munguia - California State University, Los Angeles
Co-Author(s): Samuel Landsberger, California State University, Los Angeles
Children and adults with physical disabilities benefit from functional therapy. Functional therapy employs active problem solving to develop meaningful skills such as dressing. My work focuses on developing a simple yet versatile simulated zero-gravity Universal Exercise Unit, wherein a patient is supported by manifold adjustable springs. The objective is to minimize the impediment of body and promoting range of motion within a safe environment that can accommodate various levels of capacity and several exercises that are functionally therapeutic. Evaluation of the Mark I prototype have been promising and generated a demand for a home unit. Quantifying and recording motion and progress towards therapeutic goals is important. Therefore, our work has two principal objectives: (i) modifying the equipment, (ii) and adding joint-angle measurement capabilities. Our aims are to reduce the weight, maximize portability, and standardize the use of the equipment. To measure the joint-angles without expensive instrumentation, the motion sensing of the low-cost Microsoft Xbox One Kinect™ Video-Game Platform will be leveraged. Tracking individual joint angles will allow therapist to more closely monitor progress.
The hardware modifications have resulted in a second-generation prototype meeting specifications: weight under 15lbs, area under 16ft2, and height under 6.5ft. This design has been analyzed and verified using both SolidWorks and experimentation. Furthermore, the suspension cords have been calibrated to ensure a consistent and adjustable level of support and resistance to motions. This first stage has demonstrated that a home unit is feasible.
The goal is now to develop a joint-angle extraction algorithm that harness the three-dimensional depth-mapping capabilities of the Kinect. The Kinect’s built-in skeletal tracking algorithm can track estimated wrist, elbow, and spine locations. These markers can be used to generate estimates of joint angles. Microsoft Software Development Kit, KinectHacks, LabVIEW Hacker, and MATLAB will be employed to develop appropriate algorithms. For validation of accuracy, our system will be compared against a multi-camera Vicon system, the gold standard in motion tracking instrumentation. Preliminary results have shown successful raw depth value extraction from the Kinect sensor, whose output is a 3-D point cloud. The quality of data suggests it is suitable for static measurement testing yet further development remains.Not Submitted
Funder Acknowledgement(s): CSULA LSAMP-BD Cohort XI is supported by the NSF via Grant # HRD-1363399. Special thanks to Dr. Samuel Landsberger and laboratory members. Dr. Margaret Jefferson, Dr. Katrina Yamazaki, and the LSAMP Organization.
Faculty Advisor: Samuel Landsberger, firstname.lastname@example.org