We began by defining the long-term goal of helping vulnerable individuals by improving communication in emergencies to reduce harm, anxiety, and risk. We developed sprint questions from possible ways of failure, mapped user interactions, and conducted interviews with caretakers and elderly individuals, uncovering key insights. These insights revealed that elderly people often resist welfare technology due to confusion, embarrassment, and fear of new technology, despite the significant risk of unattended fall injuries.

From the observations we could conclude that fall alert detectors rely on batteries and may generate false alarms or struggle to distinguish normal activities from actual falls, leading to potential reliability issues. Many users find them uncomfortable, forget to wear them, or worry about privacy, reducing their effectiveness. Caregivers appreciate devices like smartwatches and Life Alert for safety, but concerns about user compliance, battery management, and communication persist.

On the second day of the Sprint, we have focused on sketching concrete ideas for the product using techniques like Lightning Demos to research similar technologies and broaden our perspective. We drew inspiration from devices like the Apple Watch and explored functionalities outside the Welfare Technology sector to enhance our solution. Each of us created and shared our “Big Idea” through the Four Step Sketch process, presenting a final solution sketch to the group.

The third day of the Sprint was the Decision Day. Here, we were able to gather all of our ideas from the previous day and display them to the whole team. So, we had the opportunity to review and vote on the strongest ideas as a team and leave the final decision to the Decider. To make the best decisions, we focused on the long-term goal (Help people who are in need/vulnerable by preventing further harm, decreasing anxiety and potentially minimising risk of dying through providing better communication in emergency situations), as well as made use of structured processes.

The technique that helped us in the decision process was “The sticky decision”. The process consisted of 5 steps as follows: Art museum, Heat map, Speed critique, Straw pool and Supervote. By the end of “The Sticky Decision” process, we were able to decide as a team on our final solution and move to the Storyboard. The idea of the Storyboard was to sketch the whole user journey through our final product in a detailed way, so each of the participants understands entirely what the prototype will look like.

On this day we have also created an in-depth user flow to streamline the path care takers will take in the app to support their elderly or in other ways vulnerable stakeholders.

We started our fourth day of Sprint by revisiting the Storyboard. The Prototyping day was spent by discussing the user journey and dividing the steps in an equal way. Because our product is meant to be a digital interface, we have decided that the best tool to create our prototype would be Figma. The process continued with each of the participants focusing on their parts. To ensure design consistency, we had several check-ins, where we displayed our work and made decisions together. 

On the final day of the Sprint week we have dedicated a whole day on testing the solution with probable users, listening to their needs and finding new ways how we can adapt our solution to them. We have built an interview/task guide by using the technique of the Five Act-interview to make sure our users feel comfortable to answer our questions. We have tested on 5 interviewees as according to Jacob Nielsen 85 percent of the problems in a presented prototype can be observed after interviewing just five people. During the interviews we took notes of any likes, dislikes, questions or ideas that our users had and put it onto a whiteboard.

After the interviews we came back to the whiteboard and looked for patterns. We have found out that users felt like the onboarding could be more intuitive, that there should be a bigger emphasis that the app’s main purpose is fall detection rather than health statistics and that the switching between different care receivers was confusing and not emphasized enough. The rest of the day was spent generating new ideas and readjusting the design to fit the user’s needs.