<p> Human upper limb motion analysis with sensing by way of consumer-off-the-shelf (COTS) devices presents a rich set of scientific, technological, and practical implementation challenges. The need for such systems is motivated by the popular trend toward the development of home based rehabilitative motor therapy systems in which patients perform therapy alone while a technological solution connects the patient to a therapist by performing data acquisition, analysis, and the reporting of evaluation results remotely. The choice to use COTS devices mirrors the reasons why they have become universally accepted in society in recent times. They are inexpensive, easy to use, manufactured to be deployable at large scale, and satisfactorily performant for their intended applications. These claims for the use of COTS devices also resound with requirements that make them suitable for use as low-cost equipment in academic research.</p><p> The focus of this work is on the development of a proof of concept human upper limb motion capture system using Myo and Sphero. The end-to-end development of the motion capture system begins with developing the software that is required to interact with these devices in MATLAB. Each of Myo and Sphero receive a fully-featured device interface that’s easy to use in native MATLAB m-code. Then, a theoretical framework for upper limb motion capture and analysis is developed in which the devices’ inertial measurement unit data is used to determine the pose of a subject’s upper limb. The framework provides faculties for model calibration, registration of the model with a virtual world, and analysis methods that enable successful validation of the model’s correctness as well as evaluation of its accuracy as shown by the concrete example in this work.</p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10255111 |
| Date | 17 March 2017 |
| Creators | Tomaszewski, Mark |
| Publisher | State University of New York at Buffalo |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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