The overall aim of the project is to develop an intelligent (self-)support system for patients suffering from depression. Such a system can only be effective if it will be accepted by the patient and perceived as useful. Hence, the system should be as unobtrusive as possible and should provide sensible support. This leads to the two most important aims the project: developing unnoticeable measurements of the behaviour of the patient and an intelligent analysis and communication of the progress. For the monitoring of activities, behaviour and state of the patient, a combination of novel techniques that all are beyond state of the art will be investigated.

First of all, software and the necessary hardware extensions will be developed to detect movements of a person and changes in his or her location using a cell-phone. This information will be used to derive conclusions about the activities a person is performing. Second, an unnoticeable electronic medicine monitoring system will be further developed and integrated in the system. This component will be able to detect medicine intake for different types of medication packaging relevant for depression (e.g. blisters, dose organizers, etc.) and communicate this information via Blue-tooth technology to a mobile phone. Third, wearable biosensors will be developed that, together with signal processing algorithms, will be able to measure several reactions of the body to emotional changes, such as changes in the body temperature, several variables extracted from the ECG, and the sympathetic response observed at the sudation level of the hands. These measurements are also wirelessly communicated to a mobile phone. Finally, the mobile phone itself will be used to prompt the patient for a self-assessment of his mood and feelings, using an intuitive (graphical) interface. Together, these measurements will give a wealth of information about the state of a patient. Which measurements are useful in which phase of the therapy is an important research question to be answered in the project. In order to use the measurements for assessing the progress of the therapy and providing appropriate support, an intelligent analysis of the data is needed. Reasoning techniques will be developed for each form of therapy (e.g. the aforementioned psychoeducation, cognitive and behavioural therapies) that have knowledge about the phases of the specific therapies, the main factors that influence the success or indicate problems, the foreseen changes in the state of the patient, and the common problems that people encounter in following the therapy. Based on this, it will be possible to assess the progress of the therapy partly automatically. A significant part of this is that the risk of relapse will be determined. The assessment of the therapy will be used in the (self-support) system by providing the patient with motivational messages, reminders (for scheduled activities or medicine intake), and feedback about the progress and mood. This is partly done via the cell phone, and partly via a personal website. Simple reminders and motivational messages are best suited for communication via the cell phone, while a website is more appropriate for detailed progress feedback, such as diagrams of the changes in mood in the past period, or overviews of number of goals that have been met, etc. The feedback about the effect of his actions that is provided to a patient will stimulate him to maintain effective behaviour, or motivate him to change behaviour that is ineffective with respect to his therapy. The consequences of such changes will again be monitored and communicated to the patient.

The developed system will be evaluated in practice in an open study. This will by done by applying the system to in total 100 of depressed patients in primary care in two EU countries. The feedback from the patients and the general practitioners about the system will be used to improve and optimize the system.

Seven workpackages have been distinguished and can be viewed by using the drop down menu under project.