Preventing human falls is an essential part of healthcare. Nowadays there is a strong interest in human falling detection systems. Recent publications use different cameras and sensor combination to detect falls. Unfortunately, the comparison and evaluation of different systems remains challenging. This master thesis proposes that the evaluation of falling detection systems can be effectively done through a virtual environment. Therefore, the transition between normal and falling behaviour is modelled kinematically. For modelling the virtual environment, data is obtained through a motion capture system. The system uses reflecting markers for joint detection. Thus, the position and rotation of body segments can be analysed. The thesis concludes that the models of the lower body are accurate. The upper body shows discrepancies compared to the motion capture data. The discrepancies accrue due to different movements betweenthe participants while capturing the same falling type.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hh-34931 |
| Date | January 2017 |
| Creators | Strasser, Rafaela |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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