Teaching in courses:
Research Group
Personalized Health Technology
Group leader: Jakob E. Bardram
Personalized Health Technology is basic to creating the 21st century healthcare delivery model which is participatory, personalized, predictive, and preventive.
The Digital Health section researches digital technologies for health, healthcare, life science, and society, in order to enhance the efficiency of healthcare delivery and make healthcare more personalized and precise. As an interdisciplinary scientific discipline, Digital Health involves the use of information and communication technologies to address the health problems and challenges faced by patients and society in general.
The section works with a wide range of both hardware and software technologies, including wearable medical devices, biomedical signal processing, brain-computer interfaces, human-computer interfaces, artificial intelligence, machine learning, mobile & wearable sensing, personalized health technology, telemedicine, remote health monitoring, clinical support systems, and large-scale health data science infrastructures for collection, management, and analysis of health and well-being data.
The section addresses advances in diagnostics, treatment, and monitoring of a wide range of health and well-being domains, including psychiatry (e.g., depression and bipolar disorders), cognitive declined (e.g., dementia), neurological disorders (e.g., epilepsy and Parkinson's), cardiovascular diseases, and diabetes.
The section works with a wide range of both hardware and software technologies, including wearable medical devices, biomedical signal processing, brain-computer interfaces, human-computer interfaces, artificial intelligence, machine learning, mobile & wearable sensing, personalized health technology, telemedicine, remote health monitoring, clinical support systems, and large-scale health data science infrastructures for collection, management, and analysis of health and well-being data.
The section addresses advances in diagnostics, treatment, and monitoring of a wide range of health and well-being domains, including psychiatry (e.g., depression and bipolar disorders), cognitive declined (e.g., dementia), neurological disorders (e.g., epilepsy and Parkinson's), cardiovascular diseases, and diabetes.
The group work with a wide range of companies and healthcare organizations, such as the hospital in the Copenhagen area as well as the City of Copenhagen. Our research is supported by a number of funding agencies, as shown below.
Research
The group works within a set of core computer science research topics, builds and supports a set of research software technologies and applications, and is involved in a wide range of research projects.
The group's research is focused on what we have chosen to call "Personalized Health Technology" [3], but this line of research has also be labeled as Pervasive Healthcare [1,2], Personal Health Informatics, Digital Health, Mobile Health (mHealth), or Health IoT (Internet-of-Things). These names overlap and more or less refers to the same. Our definition of personalized health technology is;
"...a generic class of pervasive computing technologies that uses personal mobile devices and back-end servers for health- and behavior-related data sampling, processing, visualization, and feedback." [3, p. 70]
A very generic software architecture for such system are shown below (from [3]).
The group works in a set of core computer science research topics as well as in more health-application oriented research topics, including:
- Ubiquitous Computing, including Mobile and Wearable Sensing and Context-aware Computing
- Distributed Software Architectures for data collection, management, security, and privacy
- Feature Modelling and Machine Learning for behavior and disease modelling
- Human-Computer Interaction for the design of easy-to-use personal health technology
- Health-specific application development for e.g. psychiatry, neurology, diabetes, cardio-vascular diseases, and cancer.
The group builds and maintains a set of software tools for own and general use. Most of this is open source and is available from the CACHET github. These tools include:
- Open mHealth schema support for Flutter.
- CARP Mobile Sensing – a mobile and wearable sensing framework for Flutter
- CARP Cloud – a cloud-based RESTfull web service platform for collection, storage, and analysis of collected beharioral and health data. Implements the Open mHealth API.
The groups is involved in a range of research projects, which all takes place as part of the Copenhagen Center for Health Technology (CACHET), including:
- RADMIS – Reducing the rate and duration of readmission among patients with unipolar and bipolar disorder using smartphone-based monitoring and treatment.
- REACH – Responsive Engagement of the Elderly promoting Activity and Customized Healthcare
- REAFEL – Reaching the Frail Elderly Patient for optimizing diagnosis of atrial fibrillation
- BHRP – Biometric Healthcare Research Platform for research in psychiatric and neurological diseases using sensor technologies
- Phy-Psy Trial – A cluster randomised, parallel-group, 5-year trial of coordinated, co-produced care to reduce the excess mortality of patients with severe mental illness by improving the treatment of their comorbid physical conditions.
- TEAM – Technology Enabled Mental Health for Young People
- Bardram, J. E. (2008). Pervasive healthcare as a scientific discipline. Methods of information in medicine, 47(03), 178-185.
- Arnrich, B., Mayora, O., Bardram, J., & Tröster, G. (2010). Pervasive healthcare. Methods of information in medicine, 49(01), 67-73.
- Bardram, J. E., & Frost, M. (2016). The Personal Health Technology Design Space. IEEE Pervasive Computing, 15(2), 70-78.
Group Leader
Jakob Eyvind Bardram Head of Sections, Professor Department of Health Technology Phone: +45 45255311 Mobile: +45 25550446 jakba@dtu.dk
