Research Areas
My research is often cross-disciplinary human- and health-related, typically with an innovation mindset and a view to the overall user experience and the human-computer interaction.
My interests include:
- User Experience
- Human-Computer Interaction
- Human-Centered Artificial Intelligence
- Applied Machine Learning
- Capturing and Analysing Human-Related Data Traces
- Eye Tracking and Pupillometry
- Physiological Measurements / Biometric Sensors
- Combining Interaction Traces and Physiological Measurements
- Human Mobility
- Cognition
- Modelling User Behaviour and State of Mind
- Cognitive Information Processing
- Cognitive Neuroscience
- Cognitive Load
- Digital Media
I am interested in how digital systems can benefit our lives and assist us in better doing the things we care about.
I’m also part of the CACHET team.
MSc Thesis projects that address some of the topics above and perhaps relate to one of the following projects will often be prioritized (partly due to time and resource constraints).
Current Projects
In addition to the following short descriptions, follow the links or see further below
Reading the Reader
Imagine reading a text that knows you are looking at it – imagine reading a text that adapts to how you read it and supports you as you read. How we read today has changed little since the invention of printing.
However, new technologies can make it possible to identify individual reading patterns and adjust the reading material according to the reader, making reading easier and more accessible also for reading impaired to improve comprehension.
This project develops a robust set of machine learning methods that integrate and classify features from complex, noisy, multimodal data of biological origin in real-time.
The description above was done in collaboration with Sofie Beier
Who are involved
At DTU, also Chaudhary Muhammad Aqdus Ilyas (Postdoc) and Ashkan Tashk (Postdoc) are employed with the project.
In collaboration with Royal Danish Academy of Architecture, Design and Conservation: Sofie Beier (Professor MSO, Head of Centre for Visibility Design) and Bart Cooreman (Postdoc)
Also in collaboration with the University of Copenhagen, Department of Clinical Medicine / Rigshospitalet: Michael Larsen (Clinical Professor, Ophtalmology).
Funding
Funded by Novo Nordisk Data Science Foundation.
Anxiety Detection and Reduction in Childrens’ Emergency Care
After being triaged in the hospital emergency department, a procedure that takes approximately 10 minutes, children are typically transferred to a single patient waiting room. Here they spend between two to six hours before receiving treatment.
Often, children become anxious, and that can complicate the medical intervention that is required.
Being able to assess their anxiety, in some parts through collecting biometric data or observing their interaction with their surroundings, could help to evaluate whether they are ready for a medical intervention or perhaps need mitigating actions to address their anxiety.
This project aims at creating tools and mitigating actions that can help, and may involve biometric data recording and analysis, machine learning, creating e.g. games or other intervention strategies, performing testing with the target group etc in order to improve the overall patient experience (UX).
The description above was done in collaboration with Michael Deininger
Who are involved
At DTU, also Michael Deininger (Associate Professor, Department of Civil and Mechanical Engineering Engineering Design and Product Development) is involved strongly with the project and co-supervise.
In collaboration with Herlev Hospital, Pediatrics: Gitte Maria Flyger Würz (Nurse and PhD within the project at Herlev and Gentofte Hospital, Pediatrics), Hanne Konradsen (Clinical Professor, Department of Clinical Medicine / Herlev and Gentofte Hospital, Gastroenterology) and Jesper Johannesen (Associated professor, MD, DMSc, Herlev and Gentofte Hospital, Paediatrics, Herlev and Gentofte Hospital, Copenhagen Diabetes Research Center (CPH-DIRECT), Chief Consultant, Steno Diabetes Center Copenhagen)
Funding
Internal funding from Herlev Hospital.
EyeKnow
Using a custom-made eye-tracking module to detect and diagnose dizziness/vertigo.
Who are involved
In collaboration with Zealand University Hospital, Department of Ear, Nose and Throat Surgery / Radiology: Bjarki Ditlev Djurhuss (Clinical Research Associate Professor), Anders Ohlhues Baandrup (Associate Professor, MSc Engineering) and Casper Grønlund Larsen (PhD Student, M.D.). In addition, DTU students Oskar Hibbert and Jacopo Ceccuti work as assistants in the project.
Funding
Some parts funded by EU / Interreg.
Eye Tracking and Pupillometry
I have a strong interest in eye tracking and pupillometry, and normally have several ongoing ideas for research in this area, including using machine learning to analyse or classify time-series of eye related data, or modelling user emotional or cognitive state(s) based on eye data.
This may also extend to other biometric data.
Past Projects
Personalized micro-intervention technology for diabetes self-management
Imagine, you had to change your lifestyle radically tomorrow! What would you do? – How would you do it? Why would you do it?
For many people ‘why’ they would change their lifestyle is simple, they do not have a choice. Type 2 diabetes (T2DB) is a chronic disease that effects a significant number of people and if left untreated has a significant number of complications, such as damage to eyes. However, some of these can be avoided or delayed by adherence to a healthy lifestyle and medicine.
In recent years, a large number of mobile health (mHealth) applications have sprung up to support different uses, such as long-term chronic illnesses in this case T2DB. Many applications are focused on tracking health data, however tracking alone often does not provide enough feedback to sustain long term user engagement and to achieve user health goals.
The description above is courtesy of Dan Roland Persson
Also involved at DTU: Persson, D. R., Bardram, J. E. & Nørgaard, K.
Funded through the project iPDM-GO and CACHET.
Visual Aids for Visually Impaired using Mixed Reality
Also involved at DTU: Hou, B.J., Mulvey, F., Sadowski, M.
Funded by SYNOPTIK Fonden.
PUPILS (Eye Tracking Cognitive Load in Hearing Care)
Also involved at DTU: Iborra, H. R., Dau, T., Wenn, D. & Bækgaard, P. et al.
Funded by Oticon Fonden.
LINC
Also involved at DTU: Persson, D.R., Rich, J., Valentino, S. et al.
An EU project.
Systematic Mathematical Modeling for Agile Development of Model Based Medical Control Systems
Also involved at DTU: Reenberg, A. T., Jørgensen, J. B., Nørgaard, K. & Boiroux, D.
Digital Business Model Innovations in Nordic Small and Medium-Sized Firms
Also involved at DTU: Trischler, M., Li-Ying, J.
Neoro-adaptive Digital Learning
Also involved at DTU: Ioannou, C., Saqid, S., Kindler, E. & Weber, B.
In collaboration with University of Queenland.
Communication keyboards for people with special needs
Also involved at DTU: Bafna, T., Hansen, J. P., Puthusserypady, S.
Funded by the Bevica Foundation.
Design Toolbox for Personal Health Technology
Also involved at DTU: Maharjan, R., Bardram, J. E.
Funded by CACHET.