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Existing methods to assess mobility are either imprecise and subjective, or not convenient and not ecologically valid, such that there is a need for new solutions. Real-life mobility trackers offer this flexibility but first need to go through several validation steps to be used in clinical contexts. The first step is technical validation. There is a need to identify which among the existing algorithms is the most effective for assessing mobility from these sensors, relative to specific diseases. The data involved in the ranking consists of heterogeneous multivariate data in need of exploration. Such data complexity for exploration purposes consists a first data visualization challenge. The second aspect of this project is clinical validation. The gathered data need to be aggregated before their use by clinicians. Aggregation techniques for such complex data is another visualisation challenge. Finally, the project relies on patients’ participation whose engagement and involvement are mandatory for the success of the project. The project investigates how to give these patients access to their data considering accessibility and sharing restrictions.
This visualization project is part of the Mobilise-D project, and aims to design visualization to support these data exploration and validation steps.
Team
- Dr Alma Cantu (research associate), Newcastle University
- Dr Sara Johansson Fernstad (supervisor), Newcastle University
This work was supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No. 820820. This JU receives support from the European Union’s Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). Content in this page reflects the authors’ view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.