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Decision SupporT and self-mAnagement system for stRoke survivoRs

Fact Sheet

Reporting

Results

Project information

STARR

Grant agreement ID: 689947

Project website

Status

Closed project

Start date

1 February 2016
End date

31 October 2019

Funded under:

H2020-EU.3.1.4.

Overall budget:

€ 4 354 568,25
EU contribution

€ 4 354 568,25

Coordinated by:

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES

France

Objective

Stroke a leading cause of death and disability, with an estimated total cost of €65 billion per year in Europe. Even though preventive measures are in place to reduce the incidence of stroke, the number of persons having a stroke in Europe is likely to increase from 1.1 million/year in 2000 to more than 1.5 million/year in 2025 because of the increasing ageing population. Secondary stroke carries with it a greater risk than first-ever stroke for death and disability. Also, as mortality from first strokes has decreased recently, the number of people at risk for a secondary stroke has increased, with an associated increase in healthcare costs. In order to reduce these stroke statistics and the associated cost, the self-management of stroke risk factors is particularly suitable and necessary for the following reasons: 1) risk factors for stroke are well-known, and 2) 90% of strokes or secondary stroke events are preventable if the risk factors are managed appropriately. The Decision SupporT and self-mAnagement system for stRoke survivoRs (STARR) project and the system developed in it are targeting the self-management of stroke risk factors. Based on existing computational predictive models of stroke risk, we will develop a modular, affordable, and easy-to-use system, which will inform stroke survivors about the relation between their daily activities (e.g., medication intake, physical and cognitive exercises, diet, social contacts) and the risk of having a secondary stroke. This will lead to better prevention and a reduction of the number of secondary stroke events, as well as to a more efficient participation of patients in medical decision-making. A multidisciplinary consortium has been built for achieving the objectives of this ambitious project, involving stroke survivors’ associations, healthcare actors, sensing and human-machine interfaces experts. The consortium also comprises 3 European companies which will exploit the results of the project after its end.

Field of Science

/medical and health sciences/basic medicine/pharmacology and pharmacy/pharmaceutical drug

/medical and health sciences/basic medicine/neurology/stroke

/social sciences/sociology/demography/mortality

Programme(s)

H2020-EU.3.1.4. - Active ageing and self-management of health

Topic(s)

PHC-28-2015 - Self management of health and disease and decision support systems based on predictive computer modelling used by the patient him or herself

Call for proposal

H2020-PHC-2015-single-stage

See other projects for this call

Funding Scheme

RIA - Research and Innovation action

Leaflet | Map data © OpenStreetMap contributors, Credit: EC-GISCO, © EuroGeographics for the administrative boundaries

Coordinator

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES

Address

Rue Leblanc 25
75015 Paris 15

France

Activity type

Research Organisations

EU Contribution

€ 817 166,25

Website

Contact the organisation

Participants (11)

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BLUELINEA

France

EU Contribution

€ 198 750

FONDATION HOPALE

France

EU Contribution

€ 502 075

THE STROKE ASSOCATION

United Kingdom

EU Contribution

€ 149 000

ISTRAZIVACKO-RAZVOJNI INSTITUT RT-RK DOO ZA SISTEME ZASNOVANE NA RACUNARIMA NOVI SAD

Serbia

EU Contribution

€ 468 125

TELEFONICA INVESTIGACION Y DESARROLLO SA

Spain

EU Contribution

€ 78 125

LUNDS UNIVERSITET

Sweden

EU Contribution

€ 492 107,50

UNIVERSITE DU LUXEMBOURG

Luxembourg

EU Contribution

€ 532 375

Servicio Vasco de Salud Osakidetza

Spain

EU Contribution

€ 357 102,50

FIZ KARLSRUHE - LEIBNIZ-INSTITUT FUR INFORMATIONSINFRASTRUKTUR GMBH

Germany

EU Contribution

€ 331 750

INIT SERVICES FOR SOCIAL INNOVATION SL

Spain

EU Contribution

€ 307 737

MAGILLEM DESIGN SERVICES SAS

France

EU Contribution

€ 120 255

Project information

STARR

Grant agreement ID: 689947

Project website

Status

Closed project

Start date

1 February 2016
End date

31 October 2019

Funded under:

H2020-EU.3.1.4.

Overall budget:

€ 4 354 568,25
EU contribution

€ 4 354 568,25

Coordinated by:

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES

France

Project information

STARR

Grant agreement ID: 689947

Project website

Status

Closed project

Start date

1 February 2016
End date

31 October 2019

Funded under:

H2020-EU.3.1.4.

Overall budget:

€ 4 354 568,25
EU contribution

€ 4 354 568,25

Coordinated by:

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES

France

Periodic Reporting for period 2 - STARR (Decision SupporT and self-mAnagement system for stRoke survivoRs)

Reporting period: 2017-08-01 to 2018-07-31

Summary of the context and overall objectives of the project

Stroke is a leading cause of death and disability, with an estimated total cost of approximately €64 billion per year in Europe.
Recurrent stroke carries with it a greater risk than first-ever stroke for death and disability. In the same time, secondary stroke prevention has proved not very successful in the general population. One of the main reasons for these poor results is the fact that quality healthcare outcomes depend upon patients' adherence to recommended treatments. This adherence remains a challenge, since people do not always understand or remember well enough what they are supposed to do to follow the treatment or to improve their general health status. Furthermore, they do not feel actively involved in a collaborative decision-making process with their physician(s). On the other end of the patient-healthcare professionals relationship, healthcare professionals need to have an understanding of why, how, and when patients do not engage in optimal self-management behaviours in order to engage in a fruitful collaboration with their patients and co-manage more efficiently a person’s health condition.
Thus, better results in the prevention of stroke could be achieved if we improved patients’ adherence to treatments, the management and self-management of stroke risk factors (e.g. high blood pressure, unhealthy diet, alcohol consumption, physical inactivity) and the collaboration between patients and healthcare professionals. This is the main objective of the STARR project. We developed a modular, affordable, and easy-to-use system, which informs stroke survivors about the relation between their daily activities (e.g. medication intake, physical and cognitive exercise, diet, social contacts) and the risk of having a secondary stroke. The STARR system is based on an existing computational predictive model of stroke risk factors; a number of connected objects integrating off-the-shelf sensors for real-time sensing of proprioceptive functions and simple movements; a vision-based sensing platform for measuring the execution of more complex rehabilitation tasks, as well as for evaluating the stroke survivor’s emotional state; a Decision-Support System (DSS) integrating and processing all this information, evaluating progress towards the achievement of given rehabilitation and lifestyle change goals, and providing the basis for personalised diagnosis and prognosis of the stoke survivor’s health status and of a secondary stroke; a number of cloud services assuring the relations with informal and formal carers, peers and medical staff; a processing unit collecting and distributing the information from the sensors to the different modules; self-management services for stroke survivors giving recommendations and support for improving the adherence to prescribed treatments and adopting a healthier lifestyle.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

We collected future users' and stakeholders' needs, wishes and fears at 4 locations in Europe (France, Spain, Sweden and the UK). In total, 141 stroke suvivors and more than 40 representatives of other stakeholders were involved in the studies. We produced substantial information to design the STARR platform. The system is currently being intergrated and iterative usability tests are done. It will be evaluated in a pilot starting in February 2018.

We have also done a critical analysis of the existing clinical literature on models of stroke risk. We chose 2 models as applicable for the design of STARR (Zuum and the Stroke Riskometer) on the basis of the objectives of the project. Zuum was implemented in the DSS. Also, one model for motion analysis and guidance using a 3D skeleton representation was implemented. It is used for guiding a patient in correctly performing an action or movement by presenting him/her with feedback that is easy to interpret. This model for motion analysis, together with another one on emotion analysis, is currently integrated with the STARR system. We also started developing physoclogical models for behavioural change to halep sustaining patients' motivation to adopt a healthier lifestyle.
As for sensing, we chose easy-to-install, reliable, low-cost and energy- and performance-efficient sensors (e.g. Kinect Version 2 for vision-based tasks; compact inertial sensors cheaper than 2€ with a battery lasting one week). The inertial and pressure sensors were integrated inan insole for unobtrusive motion analysis.
Finally, an analysis of the data flows from a data protection perspective was done. The purpose was to ensure that the data flows, which underlie the STARR architecture, comply with the EU data protection legal provisions. Attention was paid that the stroke survivor retains control over the processing of his data and is thus able to see, control and decide what it is they want to share with anyone else.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

STARR is scoping the extent to which existing risk factor management, modelling and technology could be applied to secondary stroke prevention. The originality of the approach lies in the work on the extension of existing models to support independent decision-making by the stroke survivor. Also, all these different models are enriched with real-time data on stroke survivors’ daily activities. Another original aspect of the project is the feedback given to the user when sensing their motions. This feedback and the associated algorithms for vision sensing have been described in a number of peer-reviewed publications.

A highly scalable DSS has been developped. The original features of the DSS implementation and validation are related to two key areas: (1) PaaS layer for the predictive model execution, which provides easy adaptation and upgrade of predictive models; (2) scalability, allowing the support for growing number of users by means of straightforward (re)configuration. The PaaS layer, which provides the execution environment for the predictive models, is a novel solution, facilitating the split between the predictive model design and validation, and its technical implementation.

A number of self-management services (i.e. mobile applications and games, serious games) are currently being developped. They allow stroke survivors to adopt a healthier lifetyle and practice their rehabilitation alone or with a therapist. Their originality lies in the fact that they are supported by psychological models for health behaviour change.

The general impact of the STARR system on stroke consequences will mainly be evaluated during this pilot. Currently, our impact actions are mainly focused on dissemination of the current project resutls to relevant stakeholders.

Project information

STARR

Grant agreement ID: 689947

Project website

Status

Closed project

Start date

1 February 2016
End date

31 October 2019

Funded under:

H2020-EU.3.1.4.

Overall budget:

€ 4 354 568,25
EU contribution

€ 4 354 568,25

Coordinated by:

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES

Project information

STARR

Grant agreement ID: 689947

Project website

Status

Closed project

Start date

1 February 2016
End date

31 October 2019

Funded under:

H2020-EU.3.1.4.

Overall budget:

€ 4 354 568,25
EU contribution

€ 4 354 568,25

Coordinated by:

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES

France

Deliverables

Documents, reports (13)

Self-management in stroke

Will describe the risk factors for stroke; the current practice in the stroke pathway with regards to discharge decisions and what happens in the first 6 months; the current use of tele-rehabilitation and other technology in stroke. The report will also suggest functional and non-functional requirements to enable self-management.

Predictive modelling and stroke

Will cover the major types of model found in clinical decision making in stroke; why and when they are used, and by who and in which setting (acute, prevention, rehabilitation progression). We will describe the usefulness of these models and which ones we will use and why.

Guidelines for compliance with privacy rules - data collection combination and storage

Data collection combination and storage -UMünster- (R, PU) : will provide a legal guideline to ensure the systems compatibility with data protection and privacy law. Solutions to reduce legal risks in the monitoring process are developed and explained to ensure a privacy-friendly approach to collecting the patients’ health data.

Guidelines for compliance with privacy rules - data transmission

Will define legal requirements especially for the planned transmission of the health data collected by the sensing technologies. An essential topic will be the confidentiality and protection of the patient data communication as a violation of these aspects is able to cause a massive breach of data protection and privacy law.

Description of use case scenarios and their technical requirements

Will present a number of use case scenarios and the associated technical requirements for the sensing platform

Data management plan: second update

Presents the data management strategy of the consortium after the project

Privacy implications

Will describe the applicable European law and its key data protection principles that are relevant for the planned technical framework. Potential legal risks in performing the monitoring system will be identified. The result is an overview of legally critical aspects in the sensing technologies and its use on the participating patients.

Final user requirements and recommendations, living document

The report will describe the final version of evolving user requirements

Data management plan: first update

First update of the data management strategy of the consortium

Initial user requirements

The report will describe a first-version of the user requirements

Quality Assurance Plan

Describes the quality standards to be applied throughout the project.

Generic guidelines for the user-centred design of DSS for stroke survivors

Will include a number of generic guidelines for user-centred design of similar applications and to users with similar needs

Data management plan

Describes the data management strategy of the consortium.

Other (1)

Websites, patent fillings, videos etc. (1)

Publications

Conference proceedings (17)

Conjuring up new technology – using magic objects in co-ideation with stroke survivors

Author(s): Rassmus-Gröhn, K., Magnusson, C., Rydeman, B., Randall, G., Belson, S.

Published in: Accepted for publication at the 14th AAATE conference (Association for the Advancement of Assistive Technology in Europe) to be held in Sheffield, UK, 13-14th of September 2017, 2017

Emotion surveillance for security purposes and the risk of manipulative uses of emotion insights

Author(s): Francesca Pichierri

Published in: 2017

Facial Expression Recognition via Joint Deep Learning of RGB-Depth Map Latent Representations

Author(s): O. Oyedotun, G. Demisse, A. Shabayek, D. Aouada, B. Ottersten

Published in: International Conference on Computer Vision Workshops, 2017

Self-Management System For Stroke Survivors Project First Steps: What Do The Patients, Caregivers And Medical Staff Need? The Usability Of Technology For Stroke Rehabilitation

Author(s): L. Ortiz, A. Gutierrez Ruiz, M. Anastassova, S. Bouilland, C. Magnusson, A. Alava

Published in: 2017

Design for me?

Author(s): Charlotte Magnusson, Per-Olof Hedvall, Björn Breidegard

Published in: 2018, Page(s) 93-99

DOI: 10.1007/978-3-319-94277-3_17

Visual and Human-Interpretable Feedback for Assisting Physical Activity

Author(s): Michel Antunes, Renato Baptista, Girum Demisse, Djamila Aouada, Björn Ottersten

Published in: Lecture Notes in Computer Science book series (LNCS, volume 9914), 2016, Page(s) 115-129

DOI: 10.1007/978-3-319-48881-3_9

Technologies For Stroke Rehabilitation: Needs And Opportunities

Author(s): L. Ortiz, A. Gutierrez Ruiz, M. Anastassova, S. Bouilland, C. Magnusson, M.P. Abaitua

Published in: 2017

Preliminary Data of Self-management System for Stroke Survivors Project: Unmet Needs of Patients, Caregivers and Medical Staff

Author(s): L. Ortiz, A. Gutierrez Ruiz, M. Anastassova, S. Bouilland, C. Magnusson

Published in: 2017

Enhanced Trajectory-based Action Recognition using Human Pose

Author(s): K. Papadopoulos, M. Antunes, D. Aouada, B. Ottersten

Published in: 2017 IEEE International Conference on Image Processing, 2017

Universal balance?

Author(s): Charlotte Magnusson, Héctor Caltenco, Kirsten Rassmus-Gröhn and Bitte Rydeman

Published in: UDHEIT 2018 proceedings, 2018

Oportunidades Y Necesidades Tecnológicas Actuales En LaRehabilitación Del Ictus

Author(s): Agustín Gutiérrez Ruíz, Leire Ortiz Fernandez, Margarita Anastassova, Stephane Bouilland, Charlotte Magnusson, Maria Paz Abaitua Ezquerra

Published in: 2017

¿Qué Necesitan Los Supervivientes De Un Ictus, Sus Cuidadores Y El Personal Sanitario? Usabilidad De La Tecnología En El Automanejo.

Author(s): Agustín Gutiérrez Ruíz, Leire Ortiz Fernandez, Margarita Anastassova, Stephane Bouilland, Charlotte Magnusson, Juan Andres Alava Menica

Published in: 2017

Smart environments in the health context, self-management and data protection in the STARR Project

Author(s): Pracesca Pichierri, Diana Dimitrova

Published in: 2017

Stroke and Universal Design

Author(s): Charlotte Magnusson , Margarita Anastassova , Sabrina Paneels , Kirsten Rassmus-Gröhn , Bitte Rydeman , Gary Randall , Leire Ortiz Fernandez , Stephand Bouilland , Julien Pager , Per-Olof Hedvall

Published in: UDHEIT 2018 proceedings, 2018

Enhanced Trajectory-based Action Recognition Using Human Pose

Author(s): K. Papadopoulos M. Antunes D. Aouada B. Ottersten

Published in: IEEE International Conference on Image Processing, 2017

Designing activity games for stroke survivors

Author(s): Charlotte Magnusson, Héctor Caltenco, Steinunn Ólafsdóttir

Published in: International Workshop on Haptic and Audio Interaction Design - HAID2019, 2019

Stroke survivors’ user requirements for monitoring and self-management services: a preliminary evaluation

Author(s): Margarita Anastassova, Sabrina Panëels, Julien Pager, Mehdi Boukallel, Stéphane Bouilland, Leire Ortiz Fernandez

Published in: 2016

Peer reviewed articles (3)

Home self-training: Visual feedback for assisting physical activity for stroke survivors

Author(s): Renato Baptista, Enjie Ghorbel, Abd El Rahman Shabayek, Florent Moissenet, Djamila Aouada, Alice Douchet, Mathilde André, Julien Pager, Stéphane Bouilland

Published in: Computer Methods and Programs in Biomedicine, Issue 176, 2019, Page(s) 111-120, ISSN 0169-2607

DOI: 10.1016/j.cmpb.2019.04.019

Deformation-Based 3D Facial Expression Representation

Author(s): Girum G. Demisse, Djamila Aouada, Björn Ottersten

Published in: ACM Transactions on Multimedia Computing, Communications, and Applications, Issue 14/1s, 2018, Page(s) 1-22, ISSN 1551-6857

DOI: 10.1145/3176649

Localized Trajectories for 2D and 3D Action Recognition

Author(s): Konstantinos Papadopoulos, Girum Demisse, Enjie Ghorbel, Michel Antunes, Djamila Aouada, Björn Ottersten

Published in: Sensors, Issue 19/16, 2019, Page(s) 3503, ISSN 1424-8220

DOI: 10.3390/s19163503

Project information

STARR

Grant agreement ID: 689947

Project website

Status

Closed project

Start date

1 February 2016
End date

31 October 2019

Funded under:

H2020-EU.3.1.4.

Overall budget:

€ 4 354 568,25
EU contribution

€ 4 354 568,25

Coordinated by:

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES

Project information

STARR

Grant agreement ID: 689947

Project website

Status

Closed project

Start date

1 February 2016
End date

31 October 2019

Funded under:

H2020-EU.3.1.4.

Overall budget:

€ 4 354 568,25
EU contribution

€ 4 354 568,25

Coordinated by:

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES

France

Project information

STARR

Grant agreement ID: 689947

Project website

Status

Closed project

Start date

1 February 2016
End date

31 October 2019

Funded under:

H2020-EU.3.1.4.

Overall budget:

€ 4 354 568,25
EU contribution

€ 4 354 568,25

Coordinated by:

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES

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Last update: 13 September 2019

Record number: 199902

Permalink: https://cordis.europa.eu/project/rcn/199902/en

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Periodic Reporting for period 2 - STARR (Decision SupporT and self-mAnagement system for stRoke survivoRs)

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