Opendata, web and dolomites

SET - Chronic Pain

SET – The defibrillator for Chronic Pain

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

Project "SET - Chronic Pain" data sheet

The following table provides information about the project.

Coordinator
KLEINKLEIN GMBH 

Organization address
address: LEHMGRUBENWEG 17
city: Lindau
postcode: 88131
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]
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3.1.4. (Active ageing and self-management of health)
2. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
3. H2020-EU.2.3.1. (Mainstreaming SME support, especially through a dedicated instrument)
4. H2020-EU.3.1.6. (Health care provision and integrated care)
 Code Call H2020-SMEINST-1-2016-2017
 Funding Scheme SME-1
 Starting year 2016
 Duration (year-month-day) from 2016-07-01   to  2016-10-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    KLEINKLEIN GMBH DE (Lindau) coordinator 50˙000.00

Map

 Project objective

SET solution for chronic pain.

100 million EU sufferers, €300 billion, Age related.

Current solutions do not look at data, biomarkers, or take into consideration the individual differences between patients. With real data from large groups of patients, for the first time we can characterize the autonomic nervous system, which is depreciated in chronic pain patients, and use it to fight chronic pain. With the therapy, we attack the underlying psychological cause for the pain. The SET device allows us to do this efficiently. Using ICT data, we will be able to a real progress on this large social problem. By iterating, continuing to add data, measuring results, and adjusting approaches, we can attack chronic pain and make people pain free.

SET was tested at the University of Marburg with 120 patients that included 2 sham protocols. Of the non-control participants, 100% of fibromyalgia patients became pain free for six months, and 82% at the 12-month follow-up.

The data, which includes all the EKG and blood pressure data from each patient session as well as the patients' initial interview and progress data from the E-learning system, will be uploaded to a MySQL database hosted on a medical grade cloud server. Data mining and analytics software will only have read access and only anonymized access will be available, so that it will not be possible to identify any individual patient.

Patent protection, a highly experienced team, a clear strongly motivated market will make the company successful. In the process many therapy based SMEs will be formed and enhanced.

A real solution for a debilitating social problem which invloves ICT, big data, and job creation.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "SET - CHRONIC PAIN" 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 (fabio@fabiodisconzi.com) 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 "SET - CHRONIC PAIN" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.3.1.4.;H2020-EU.2.1.1.;H2020-EU.2.3.1.;H2020-EU.3.1.6.)

CLINICOVERY (2018)

CLINICOVERY, a versatile, high quality, environmental-friendly, easy to use e-Clinical solution for clinical research

Read More  

ImmuneHunter (2017)

Bioinformatics platform for profiling of health: allowing early and accurate detection of multiple diseases simultaneously

Read More  

SensUS (2018)

SensUS: A non-invasive and quantitative ultrasound (QUS) device for an objective monitoring of the childbirth labour process.

Read More