A proposal of the Signal Processing Group has been selected by the “Fundación para la Innovación y la Prospectiva en Salud en España (FIPSE)”

The proposal EVIDENCE-BASED BEHAVIOUR of the GTS Group has been selected by the “Fundación para la Innovación y la Prospectiva en Salud en España” (FIPSE), a Spain-based nonprofit foundation dedicated to advancing new healthcare technologies. This proposal was submitted in response to the “Call for funding feasibility studies in health innovation projects” that was published by FIPSE on October 2016.

Project Summary

Mental diseases bring together a huge burden in terms of human suffering and economic cost (greater than cancer, cardiovascular diseases and diabetes together). Typically of chronic nature, they may cause a poor ability to function in many areas of the subject’s life (social interactions, work, ability to live by their own …). Evaluation and monitoring of patients is performed by questionnaires and interviews along the time, which entails two main drawbacks: subjectivity (and bias) of the information obtained, and long unsupervised periods of time between interviews.

The goal of this project is the development of a behavioural-monitoring system for psychiatric patients, based on the use of mobile devices (smart phones and wearable devices) that send in real time information from sensors and device’s use to a central server, which stores and process such information, and provides medical stuff and caregivers with statistical analysis about the subject’s behaviour. Such analysis provides information on 1) sudden changes in the subject’s behaviour pattern, and 2) evaluation of the subject’s functionality (to allow quicks follow-ups by psychiatrics).

The main advantage of the proposed system is an objective characterization of the subject’s behaviour (through physical measurements that contain information on the behaviour). The procedure is automatic, as no intervention from the subject is required, continuous along time, and non-invasive.

Aside the above advantages, the core of the project is at the statistical processing of the psychiatric information gathered at the central server through advanced machine learning techniques, and the behaviour characterization in an objective and personalized manner. The group I lead is a pioneer in the application of machine learning to psychiatry, combining expertise from both engineers and psychiatrists in a multidisciplinary work atmosphere.

Principal Investigator: Antonio Artés Rodríguez.

  • E-mail: antonio -at- tsc.uc3m.es
  • Phone: +34 916248741.