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Early detection of Alzheimer s and Parkinson´s disease based on eye-tracking and AI

Reference number
Coordinator Optolexia AB
Funding from Vinnova SEK 1 924 000
Project duration June 2017 - April 2019
Status Completed
Venture Digital health

Purpose and goal

In this project, we have implemented a test protocol for eye movement measurement that has been evaluated on patients with Altzheimer´s and Parkinson´s disease compared to healthy control subjects. Through the project we have been able to show that the technology is possible to use in a clinical environment and that it provides data that are useful for applications based on artificial intelligence. Furthermore, we have within the project investigated regulatory and intellectual property issues related to commercialization.

Expected results and effects

Preliminary results show that the method we have developed can yield eye movement patterns that can be used to classify disease states by on artificial intelligence. Furthermore, the technique has been appreciated by both patients and investigators, as the method has proven to be easy to use and the test can be carried out quickly. The surveys regarding regulatory conditions and protection of intellectual rights show low thresholds for commercialization.

Planned approach and implementation

The approach of using eye movement measurement on patients has worked well when the technique itself worked and that both investigators and patients estimate that the test protocol is easy to implement. However, implementing the system in the patient flow for Altzheimers took a very long time, which means that the part of the data collection was not completed within the project period. This is not so much the technology as it has been difficult to coordinate the work with preparations. Overall, however, the project has resulted in methods, results and experiences that have been valuable.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 8 January 2019

Reference number 2017-02317

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