Test instrument for early diagnosis of Alzheimer’s disease

Frei, Jan and Wehli, Cedric (2019) Test instrument for early diagnosis of Alzheimer’s disease. Student Research Project thesis, HSR Hochschule für Technik Rapperswil.

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The team of the Memory Clinic located in the Felix Platter hospital for elderly people in Basel has developed a test instrument for early diagnosis of Alzheimer’s disease. This diagnosis consists of three computer-assisted tests where the test persons answer memory related questions. Those were created on the basis of a proprietary platform.

To make this tool available for other clinics and experts the goal was to recreate these tests without the need to license an expensive software as well as improve the usability for the operator's needs in the clinic's daily business.

To create a software that runs the specified tests on all major desktop operating systems (Linux, Mac, Windows) in just three months with an intuitive user interface we decided to create an electron app on the basis of the following electron react boilerplate: https://electron-react-boilerplate.js.org

To comply with the legal requirements of FPS we split our application into a generic test execution shell that is able to read test specifications from JSON files and the specific configuration files with their Alzheimer’s diagnosis tests. This allowed us to extract any external intellectual property into the configuration files which were handed to our client while the test execution shell could be published under the MIT open source license.
With this approach it is possible to expand the program or write similar experiments on the basis of the experiment execution shell by simply changing or creating JSON experiment configuration files.

Item Type: Thesis (Student Research Project)
Subjects: Topics > Software > Testing and Simulation
Topics > User Interface Design
Area of Application > Healthcare, Medical Sector
Technologies > Programming Languages > Java Script
Divisions: Bachelor of Science FHO in Informatik > Student Research Project
Depositing User: OST Deposit User
Thesis advisor
Stolze, Markus
Date Deposited: 09 Apr 2020 12:43
Last Modified: 09 Apr 2020 12:43
URI: https://eprints.ost.ch/id/eprint/840

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