Felix Beierle 
Ecological momentary assessments (EMAs) prompt users with a short questionnaire. One of the biggest challenges in such studies is the lack of adherence, i.e., users stop filling out the questionnaires. Being able to predict if a user will fill out a questionnaire could allow for specifically addressing those users, or for over-sampling populations at higher … Read more
Software Campus, a competitive program for future leaders in IT, funded my TYDR research project. In their news, they report about my stay at the National Institute of Informatics (NII) in Tokyo: LinkedIn (German), website (German), website (English).
Notifications are one of the most essential features of smartphones. App developers and researchers typically want to reach their audience at opportune times. We analyzed almost 10 million notifications collected from 922 users. Most notifications were logged in the late morning and late afternoon. Between 8 pm and 11 pm, the interaction delay (time between … Read more
Vision Transformers can outperform other methods like RNNs in classification tasks in the medical domain. MedMNIST (v2) is a collection of biomedical images, and contains eight 2D image datasets for a multi-class classification task. Using a pre-trained Vision Transformer model, and fine-tuning it for each dataset, we were able to outperform almost all of the … Read more
The COVID-19 pandemic not only affected the respiratory system, but, together with measures like social distancing, potentially affected the mental health of millions of people. What do Twitter (X) users talk about when they talk about #MentalHealth and #Depression? Did it change through the pandemic? We collected almost 3,000,000 tweets from more than 300,000 Twitter … Read more
How can mobile sensing, using the smartphone’s sensors for recording and storing data, help in personality science? Read our comprehensive book chapter on this topic. We cover an overview of related work and show the differences in researching personality traits vs. personality states with mobile sensing. We showcase a concrete mobile-sensing application and provide a … Read more
Today, I gave a presentation at an IEEE EMBS (Engineering in Medicine and Biology Society) event. My talk was about Predicting Adherence to Ecological Momentary Assessments, and I presented our findings about the predictability of users of a smartphone app filling out questionnaires. Based on smartphone sensor data, we utilized machine learning to try to … Read more
How well can we detect stress from sensor data from wearables? And how to develop systems for it fast? You can find the full project and code on GitHub and a paper here (PDF). Or just visit the interactive live demo showcasing the whole project right now!
At the beginning of the COVID-19 pandemic, with a lack of knowledge about the novel virus and a lack of widely available tests, getting first feedback about being infected was not easy. To support all citizens in this respect, we developed the mobile health app Corona Check. Based on a self-reported questionnaire about symptoms and … Read more
With about 300 million affected people, major depressive disorder (MDD) is one of the most common diseases worldwide. During the COVID-19 pandemic, the number of cases increased even further, by 28%. Many factors may be correlated with MDD, including the excessive use of social media apps. We investigated the relationship between the use of social … Read more
