Algorithm development and AI

Within Mobilab & Care, we formulate answers to concrete healthcare-related questions from the professional field on the basis of real recorded data. We develop and validate new algorithms that use existing Machine Learning (ML) or Artificial Intelligence (AI) methodologies. We translate those techniques into applications in healthcare.

It is essential to start with real-life data to develop new insights or answers with those techniques. Over the years, Mobilab & Care has built up a lot of experience in collecting data using different types of sensors and measurement systems.

Within our applied scientific research, we build technological innovations in the form of prototypes that open up additional possibilities and provide additional support to the existing care and welfare offerings.

In addition to the development and validation of prototypes, we support business innovations for the healthcare sector and transfer new knowledge and insights to education.

Projects

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Researchers

Marc Mertens

Kris Cuppens

Glen Debard

Hajar Ghaem

Bert Bonroy

Kurt De Wit

Kurt De Wit

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What can we do for you?

Mobilab & Care strives to maximize the flow of our expertise to businesses and organizations.

  • Problem identification and system requirements
  • Advice on data collection using sensors, measurement systems,…
  • Advice on usable AI/ML techniques
  • Possibilities with existing datasets
  • Evaluation of existing systems, (scientific) validation

    Feel free to contact us!
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Infrastructure

We have:

  • Extensive range of wearables to measure physiological signals
  • Monitoring systems for contactless monitoring of persons in the home situation
  • Experience lab where sensor systems can be deployed and evaluated in a simulated home and care environment
  • Motion lab for measuring movement , muscle activity…
  • Extensive collection of 3D scanners
  • Several VR glasses
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Publications

Mertens M. , Raepsaet J., Debard G., Mondelaers M., Vanrumste B. and Davis J. (2019) USE OF WEARABLE TECHNOLOGY TO QUANTIFY FALL RISK IN PSYCHOGERIATRIC ENVIRONMENTS: A FEASABILITY STUDY In 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Berlin, 2019