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|Title:||Tool for extracting and visualizing travel patterns||Authors:||Chan, Nathaniel Ming Kong||Keywords:||DRNTU::Engineering||Issue Date:||2013||Abstract:||The number of people with dementia is rising over the years and will triple from the current number of 35.6 million by 2050. There is currently no known cure for dementia as the brain is such a complex organ and thus extensive research should be carried out on attempting to find a cure for dementia. To aid research on dementia, a tool that can provide a graphical visualisation on the travel patterns could be created. It would allow researchers to observe patterns of the elderly and the difference in cognitive behaviour in the elderly. After observing and identifying the patterns, researchers could then possibly identify the link between the different types of dementia and which area the brain is affected by it. The purpose of this project is to investigate the existing situation of dementia, smart homes and tools available in aiding the research of dementia to create a tool that would aid and possibly further research done in this area. Through investigation of the current situation, a better understanding of how dementia and smart homes play a part in two areas – allowing the elderly to remain independent while being monitored by loved ones and collecting data on the cognitive of elderly suffering from dementia over time. Finally, a new tool was proposed to further aid researchers in determining a difference in cognitive and possibly identify the areas of the brain is affected by a particular strain of dementia. The tool was developed to be easily used across different platforms and made simple to use for researchers that are not IT savvy. The tool visualises the subject’s behaviour patterns from a data format to a visual format. It takes data provided from smart homes and draws out the movement patterns for various tasks that the subject performs. This would allow researchers to have an easier understanding of how the subject functions over time while coping with different types of dementia. Patterns could then be drawn out and researchers could identify changes in those patterns and link them to how different types of dementia affect the brain. In conclusion, the tool created provided a platform for researchers to work on and possibly further their research. However the tool requires further refinements and additional features such as having the ability to process different types of data sets. The core features of the tool such as the processing of data, setting up the framework for future works and animation of paths in accordance to real time will be explained in this paper.||URI:||http://hdl.handle.net/10356/55068||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SCSE Student Reports (FYP/IA/PA/PI)|
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