Problem description: How can we design an effective tool to help physiotherapists prescribe exercises?
Work done: We gathered 12 physiotherapists in a group and moderated a discussion on how we could improve the way they prescribe exercises.
Results: The group insights allowed the exploration of several innovative prototypes that made their work more efficient, informed, and personalised.
Related project: FallSensing
Problem description: We needed to understand the best way to visually represent finance-related concepts to use as icons in a finances’ application.
Work done: We developed two sets of cards: one with the financial words and another one with a set of icons that could visually represent the concepts. We presented both sets to the users and asked them to make a connection between words and images.
Results: By using an almost gamelike method, we were able to find the best visual representations for harder to explain concepts. The method is quick and fun to apply, which means that we can easier reach a great number of users. We are more certain that most users will be able to understand the icons, thus improving the system’s usability.
Related project: Smart Companion
Problem description: We wanted to understand what kind of cognitive games users were most attracted to, so that we could develop a digital version of them.
Work done: We developed a small book with different cognitive games and gave them to participants. Then, we asked them to refer to that book whenever they wanted and engage in the games they were most interested in.
Results: By understanding which games were most appealing to our users we developed a gaming platform that had more potential to be successful among the target audience.
Related project: Cogniplay
Problem description: Which button should we use to guarantee that users can turn on/off the settings without any difficulty?
Work done: We created several different options for an on/off switch button. We then tested three options with 9 users. According to the first results we made a second iteration and based on the first three designs we created five different options that were variations of previous ones. These were tested with 12 more users.
Results: We were able to reach a solution that the target group of our application will be able to use without any challenges.
Related project: Smart Companion
Problem description: Understand the challenges faced by seniors when interacting with mobile keyboards in order to design a customised one.
Work done: We asked 13 participants to test the three main available solutions on the market. The same task was replicated on the three options and metrics for effectiveness, efficiency and satisfaction were collected.
Results: We identified the most common difficulties faced by the users, as well as the most effective, efficient and preferred solution for our target group. Therefore, when we developed a custom keyboard, we already knew the tasks that needed to be easier to perform, and we had an available example to use as a starting point.
Related project: Smart Companion
Problem description: Are users capable of using this contacts application?
Work done: We used paper prototypes to simulate the screens of the application and asked users to perform the necessary tasks to guarantee that they would be able to operate the application, e.g.: identify favourite contacts, search, see contact details, call, send SMS, add or edit contact.
Results: By measuring effectiveness (completion rate, errors, assists) during the test, we were able to identify all the usability problems that would prevent the app from being used by the target group.
Related projects: LIFANA | Clockwork | MASPARK
Problem description: What minimum font size should we use in a mobile application for seniors?
Work done: We performed tests with 73 senior users, asking them to read a text in a smartphone, using different sizes. We included seniors with different vision impairments at different stages of evolution and asked them to perform the evaluation with and without seeing aids.
Results: We are now able to indicate the minimum font size to accommodate most senior users, considering their impairments, their stage and if it is information that they should be able to see without glasses or contact lenses.
Related project: Smart Companion
Problem description: We needed our mobile application to be customisable depending on the users’ experience with smartphones.
Work done: We created three different UIs for the main menu of our application:
> A launcher with bigger buttons
> A launcher with smaller buttons
> A non-launcher mode
Results: By providing different options, novice users will be able to use the solution with ease, expert users will not feel stigmatised by a novice interface and the interface will be able to evolve together with its users.
Related project: Smart Companion
Problem description: How can we use our expertise to identify usability issues and offer proper solutions to our clients’ systems?
Work done: Five researchers measure the usability of the interface using Nielsen’s Usability Heuristics, identifying issues and their severity.
Results: After their individual analysis, they discussed all issues together, defining the most critical problems and suggesting alternatives to the design and development team.
Related project: INNOVASmartInnovation (project for client)
Problem description: How do we help our international clients to test and validate their digital solutions in site?
Work done: We designed a test protocol, describing all the requirements – setting, technology used, participants and metrics - needed to conduct a usability test protocol with local participants. All tests were recorded in order to be analysed and reported by our team of experts.
Results: We streamlined the process of requesting documents in public services, minimising the number of steps to request a specific document, via smartphone, and avoiding unnecessary trips and cues in public services.
Problem description: How can we design a technology that supports people’s healthy eating?
Work done: We asked participants (11 non-professionals and one expert) to interview and observe them in their homes to learn about the way they made food choices, how they managed grocery shopping and how they cooked.
Results: We designed a nutrition application to support people’s current practices in choosing what food to cook, arranging their items for shopping and sharing their cooking experiences with others.
Related project: Clockwork
Problem description: How can we trust if the new diagnostic test is valid?
Work done: We conducted a clinical study using eye fundus images of people with diabetes mellitus which were classified by a panel of 3 ophthalmologists. This classification was used as the gold standard to compare the results provided by the decision-support system.
Results: We validated the decision-support system as a diagnostic test for screening for DR of people with diabetes mellitus.
Related project: DEMEyeFundusScope
Fraunhofer Center for Assistive Information and Communication Solutions – AICOS