View source for Using stock devices for unobtrusive fall detection

{{StudentProjectTemplate
|Summary=The core research question is to whether stock devices can be used to effectively detect fall events in the home.
|Programme=EIS Masters 15hpc
|Keywords=Smart homes, pervasive computing, DiaSuite
|TimeFrame=6 months
|References=Please see text below
|Prerequisites=DA8003 Cyber-Physical Systems
|Supervisor=Walid Taha
|Examiner=Antanas Verikas
|Level=Master
|Status=Ongoing
}}
The core research question is to whether stock devices can be used to effectively detect fall events in the home.
This project will be aligned with ongoing work at Charles Consel's research group at INRIA Bordeaux, France.
The research question involves primarily building a fall detection system using readily available components using the DiaSuite platform, and then evaluating it effectiveness at detecting falls.
The first component of the work is learn how DiaSuite works and make an installation at the HH smart home environment.
The second component is to identify a base line fall detection device that can be used for comparing the new solution.
The third component is a state of the art review.
The fourth is to use DiaSuite to explore multiple options for detecting falls, including smart phones, basic motion sensors, specialized motion sensors (such as the kinect), and others.
The fifth component is the evaluation of detection methods that have been developed in the project. This involves using the models to test the tools to see if they are able to produce the expected results in a satisfactory manner.
The sixth component is writing up the results of the work.
References:
- https://hal.inria.fr/hal-00702909/file/diasuite.pdf
- https://www.ncbi.nlm.nih.gov/pubmed/21096573
- http://subs.emis.de/LNI/Proceedings/Proceedings208/1456.pdf
- http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6610594
- http://link.springer.com/chapter/10.1007%2F978-3-642-40261-6_55