Health & Wellbeing

The health and wellbeing theme involves a wide diversity of researchers from the Faculty of EEMCS. Their involvement ranges from microelectronic devices for human organ and disease models to mathematical biophysics, and from implantable medical devices to genomic data analysis and visualization. The theme Health and Wellbeing is well embedded into the TU Delft DRI “Medical Delta”, and many regional (LDE) and national (NKI, VUMC, Hubrecht Institute, Dutch Burn Centre, LUMC, 4TU) collaborations exist. The aim is to contribute to faster and more accurate diagnostics, advanced therapy, improved health-related quality of life (also for healthy people, to improve productivity and overall societal participation), and better prevention, care and cure, at reduced cost. In microelectronics, the design and implementation of biomedical microsystems address challenges such as high-quality signal modeling, miniaturization, accuracy and reliability, energy efficiency, biocompatibility, manufacturability and cost. Research encompasses material and technology, device and circuit design, signal processing, system implementation and software design. In mathematics and computer science, models and algorithms are being designed that advance health cure and care. The central challenges are the analysis of massive volumes of health, treatment, and genomics data, including personal lifestyle data, medical imaging data, and a range of multi-modal molecular data as well as the (cyber)security and privacy aspects of health data.


Scientific challenges

  • Extreme miniaturization, energy efficiency, flexibility and closed-loop control of implantable devices and ultrasound catheters and probes. 
  • Flexible and customized organ-on-a-chip platforms.
  • Reverse-engineering the brain: brain signal processing (hardware emulation, i.e. computational neuroscience/bio-inspired circuits and algorithms), understanding molecular processes. 
  • Single-cell analysis: finding spatio-temporal patterns, capturing lineages and (tissue) heterogeneity.
  • Data integration (across several modalities) and knowledge discovery.
  • Mathematical modeling of biological phenomena.
  • Mental health computing and behavior change support systems using virtual health agents. 
  • Cybersecurity and protection of privacy-sensitive information in biomedical devices, services and data.

Societal & industrial challenges

  • Reduce costs and time of drug development.
  • Optimize use of available resources, e.g. limited number of ambulances.
  • Reduce hospital/care costs by minimally invasive medicine; living longer at home.
  • Address ethical and privacy implications of medical technological innovations.
  • Contribute to the HPTC research programmes.