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Chronic Stress Biomarkers for Early Detection and Prevention of Burnout

Total Cost €


EC-Contrib. €






Project "SOMA Analytics" data sheet

The following table provides information about the project.


Organization address
postcode: 83052
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Project website
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3.1. (SOCIETAL CHALLENGES - Health, demographic change and well-being)
2. H2020-EU.2.3.1. (Mainstreaming SME support, especially through a dedicated instrument)
 Code Call H2020-SMEINST-1-2014
 Funding Scheme SME-1
 Starting year 2014
 Duration (year-month-day) from 2014-12-01   to  2015-05-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

In 2013, the costs of work-related depression in the EU-27 was estimated to be €617 billion annually , taking in account costs to employers resulting from absenteeism (€272 billion), loss of productivity (€242 billion), healthcare costs (€63 billion) and social welfare costs (€39 billion).

The project focuses on the early detection of work-related psychological stress resulting in negative health outcomes, such as burnout or depression.

• In phase 1, the project will validate the technical and commercial feasibility of a non-obtrusive smartphone-based solution able to detect stress based on the analysis of speech, sleep and typing behaviour. The project will establish the market interest (competitive analysis, willingness to pay) and recruit corporate organizations willing to participate to clinical trials in phase 2.

• In phase 2, the project will implement a clinical trial in order to demonstrate the validity of the existing solution prototype based on the stress biomarkers researched in phase 1. The solution will be tested with adult subjects against other known stress biomarker sensors.

One of the key innovations of the project is the use of speech analysis to evaluate chronic stress by using a dual approach: first, recognize stressed speech using two nonlinear feature models and second, recognize emotion profiles in order to assess mental resilience. The analysis follows a machine learning approach by identifying relevant features to build classifiers which are then trained on a suitable data set.

The platform built in this project will also be used to develop an ecosystem of partner companies (e.g. wearable suppliers, online coaching services) that can reuse SOMA Analytics algorithms inside their own product offerings, thus driving further European innovation in the area.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "SOMA ANALYTICS" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email ( and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "SOMA ANALYTICS" are provided by the European Opendata Portal: CORDIS opendata.

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