Fundamental movement skills (FMSs) are considered to be one of the essential phases of motor skill development. The proper development of FMSs allows children to participate in more advanced forms of movements and sports. To be able to perform an FMS correctly, children need to learn the right way of performing it. By making use of technology, a system can be developed that can help facilitate the learning of FMSs. The objective of the research was to propose an effective natural user interface (NUI) architecture for detecting FMSs using the Kinect. In order to achieve the stated objective, an investigation into FMSs and the challenges faced when teaching them was presented. An investigation into NUIs was also presented including the merits of the Kinect as the most appropriate device to be used to facilitate the detection of an FMS. An NUI architecture was proposed that uses the Kinect to facilitate the detection of an FMS. A framework was implemented from the design of the architecture. The successful implementation of the framework provides evidence that the design of the proposed architecture is feasible. An instance of the framework incorporating the jump FMS was used as a case study in the development of a prototype that detects the correct and incorrect performance of a jump. The evaluation of the prototype proved the following: - The developed prototype was effective in detecting the correct and incorrect performance of the jump FMS; and - The implemented framework was robust for the incorporation of an FMS. The successful implementation of the prototype shows that an effective NUI architecture using the Kinect can be used to facilitate the detection of FMSs. The proposed architecture provides a structured way of developing a system using the Kinect to facilitate the detection of FMSs. This allows developers to add future FMSs to the system. This dissertation therefore makes the following contributions: - An experimental design to evaluate the effectiveness of a prototype that detects FMSs - A robust framework that incorporates FMSs; and - An effective NUI architecture to facilitate the detection of fundamental movement skills using the Kinect.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:nmmu/vital:21055 |
| Date | January 2015 |
| Creators | Amanzi, Richard |
| Publisher | Nelson Mandela Metropolitan University, Faculty of Science |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis, Masters, MSc |
| Format | x, 112 leaves: some colour illustrations, pdf |
| Rights | Nelson Mandela Metropolitan University |
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