Assessment of patient’s therapy response based on smartphone data

Clinical trials are moving from the clinic towards inclusion of real-world data and measurements. This allows to study the effect of medication in a more continuous manner and also monitor objective aspects that were previously evaluated by structured interviews. The Centre for Human Drug Research (CHDR) has developed a platform that allows for monitoring of clinical trial subjects in the real-world collecting valuable information in relation to the effect of a drug in test. Numerous measurements are collected including steps, heart rate, and sound features that have the potential to be used for mood identification, user social profiling, and disease classification.

Assignment

It is well understood that diseases also affect the mood and behaviour of patients with serious consequences on their quality of life. It is the objective of this project to develop algorithms to monitor the users profile based on the persons smartphone use. More specifically, algorithms that can profile the users and that can help identify the diseases will be developed. These will be based on, for instance, the time a person is using their phone, what sort of app they are using and for how long, heart rate, and activity level using the number of steps, along with other variables that are monitored by the platform. It is expected that the student is performing the work at CHDR in Leiden, The Netherlands.

Requirements

- Matlab and/or python (python preferred) - Courses on Signals & Systems and on Machine learning

Contact

dr. Carolina Varon

Signal Processing Systems Group

Department of Microelectronics

Last modified: 2020-03-05