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Automated Workflow Detection for the Evaluation of Product Usability using Eye Tracking
Today, medical devices are required to run usability testing before they can hit the market. However, traditional usability testing is subjective and not transparent.
The goal is therefore to develop and validate an automated method, which allows an objective evaluation of product usability.
In order to validate functionality and to improve customer satisfaction of a product usability testing is indispensable. However, traditional usability testing, in the form of interviews, observations and questionnaire, can only provide limited and often subjective insights.
Eye Tracking Technology allows to recreate human gaze patterns during usability studies, so that the cognitive processes of each participant can be understood.
Leveraging this data can lead the way for an automatically generated, objective usability evaluation.
The goal of this project is to find and validate characteristic behavioral patterns, using data from real usability studies. This should be applied to newly acquired data, in order create an automated evaluation method for product usability
The student will have the opportunity to work in an unique environment which combines medical technology, usability testing and eye tracking technology.
In order to validate functionality and to improve customer satisfaction of a product usability testing is indispensable. However, traditional usability testing, in the form of interviews, observations and questionnaire, can only provide limited and often subjective insights.
Eye Tracking Technology allows to recreate human gaze patterns during usability studies, so that the cognitive processes of each participant can be understood. Leveraging this data can lead the way for an automatically generated, objective usability evaluation.
The goal of this project is to find and validate characteristic behavioral patterns, using data from real usability studies. This should be applied to newly acquired data, in order create an automated evaluation method for product usability
The student will have the opportunity to work in an unique environment which combines medical technology, usability testing and eye tracking technology.
- Review on the state of the art
- Improvement of an existing algorithm to extract characteristic process sequences based on real world data
- Development and Execution of suitable Eye
Tracking studies.
- Providing innovative approaches to the problems at hand
- Possibility to work with an industry partner
- Review on the state of the art - Improvement of an existing algorithm to extract characteristic process sequences based on real world data - Development and Execution of suitable Eye Tracking studies. - Providing innovative approaches to the problems at hand - Possibility to work with an industry partner
- Experience in programming (MATLAB or python) helpful - Interested in human behavior and Product Usability - A good technical understanding - Creativity and like hands-on work - Systematic approaches to problems - Highly Motivated and independent
The chair of Product Development
and Engineering Design at the
ETH Zurich considers itself a center
for system-oriented product
development and innovation. Our
aspiration consists on the one hand
of the advancement and investigation
of methods and processes of
product development and on the
other hand of the development of
new technical systems. The purpose
of our daily work is to contribute
to the innovative ability and
competitiveness of Switzerland.
The chair of Product Development and Engineering Design at the ETH Zurich considers itself a center for system-oriented product development and innovation. Our aspiration consists on the one hand of the advancement and investigation of methods and processes of product development and on the other hand of the development of new technical systems. The purpose of our daily work is to contribute to the innovative ability and competitiveness of Switzerland.
Semester /Master Thesis Technical Background
Felix Wang (PhD Candidate)
**wangfe@ethz.ch
**LEE O 221
Leonhardstrasse 21, 8092 Zürich
Felix Wang (PhD Candidate) **wangfe@ethz.ch **LEE O 221 Leonhardstrasse 21, 8092 Zürich