Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
ICone: a novel device to scale up robotic rehabilitation and unlock the potential of motor recovery for stroke survivors. (ICone)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Italy
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-11-01
End date: 2020-02-29
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

ICone - The best therapy, everywhere. THE NEED FOR REHABILITATION IS INCREASING. Increasing the effectiveness of rehabilitation and lowering its cost is a global challenge, according to WHO. Due to the ageing population and higher survival rate after brain injuries (strokes), the number of stroke patients is increasing. Even years after the cerebrovascular accident, chronic patients hold potential for motor recovery; yet, intensive, interactive, challenging and personalized therapy is needed – this requires huge cost, long time, and resources. ROBOTIC REHABILITATION STILL FACES TECHNICAL LIMITS. Robots for rehabilitation, science confirms, could represent an adequate solution to deliver cost-effective therapy that is intensive, interactive, challenging and personalized. The main drawback is that robots for rehabilitation cannot be used outside of the hospital, and so they are precluded to chronic stroke patients. As a result, chronic patients hold potential for motor recovery, but they don’t have access to adequate treatment (robots). ICone: SCALE-UP OF ROBOTIC THERAPY. Heaxel produced ICone, the first portable robot for the neurorehabilitation of the upper limb, cleared for use outside of the hospital. All the ICone robots will be connected all together into a cloud network, so to facilitate the access of chronic patients to robotic therapy. FEASIBILITY STUDY. A Phase I project will allow to carefully organize customer development activities and go-to-market strategy. The business feasibility of different revenue models must be tested, to quickly and effectively start the commercialization of the robot, in order to deliver the best possible care to chronic patients. This Phase I study will be crucial, then, for an EIC acceleration project, where pilot clinical trials will be executed, as a validation of the market and of the proposed solution. Heaxel long-term goal is to bring robotic rehabilitation directly at the patient's home.

Keywords: tele rehabilitation,neuro rehabilitation,stroke,chronic stroke,neuroplasticity,physical therapy,robot therapy
Soft-bodied intelligence for Manipulation (SoMa)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Theme: Advanced interfaces and robots: Robotics and smart spaces
Action type: Research and Innovation actions
Partnership: Robotics SPARC (cPPP)
Countries involved: Austria,Italy,Germany,Italy,Germany,Switzerland,United Kingdom
Call: Robotics (H2020-ICT-2014-1, 2014)
Start date: 2015-05-01
End date: 2019-04-30
Duration (months): 48.0
Total project cost (EUR): 7096091.25
EU funding (EUR): 6321278.75
Participants: 7
Project status: CLOSED

The main obstacle to a wide-spread adoption of advanced manipulation systems in industry is their complexity, fragility, lack of strength, and difficulty of use. This project describes a path of disruptive innovation for the development of simple, compliant, yet strong, robust, and easy-to-program manipulation systems. The idea is: Soft Manipulation (SoMa). SoMa explores a new avenue of robotic manipulation with the environment, as opposed to manipulation of or in the environment. In our approach, the physical constraints imposed by objects in the environment and the manipulandum itself are not regarded as obstacles, but rather as opportunities to guide functional hand pre-shaping, adaptive grasping, and affordance-guided manipulation of objects. The exploitation of these opportunities, which we refer to as environmental constraints (EC), enables robust grasping and manipulation in dynamic, open, and highly variable environments. The key ingredient for the exploitation of EC is softness of hands, i.e. their embodied ability to comply and adapt to features of the environment. The traditional paradigm for robotic manipulation is in complete disarray in front of this shift of focus: state-of-the-art grasp planners are targeted towards rigid hands and objects, and attempt to find algorithmic solutions to inherently complex, often ill-posed problems. Further complicating matters, the requirement of planning for soft, uncertain interactions between hand and environment is entirely beyond the state of the art. However, this is how humans most often use their hands, and how we plan to change robotic manipulation.

Keywords: grasping and manipulation,embodied intelligence,soft robotics,hand design,actuation,control,exploiting environmental constraints,human grasping,transfer human skills to robot
Sleep homeostasis in Caenorhabditis elegans (WORM_SLEEP)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Austria
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-06-01
End date: 2020-05-31
Duration (months): 24.0
Total project cost (EUR): 166156.8
EU funding (EUR): 166156.8
Participants: 2
Project status: CLOSED

The aim of my research is to unravel one of the biggest unresolved problems in neuroscience: the function of sleep. Sleep is an essential aspect of our lives, the importance of which appears clear in pathological conditions where its normal patterns are disrupted. Moreover, it is an evolutionary conserved phenomenon. It has been described and characterized at levels, ranging from behavioural to neural and molecular, in different animal species. Despite its conservation, pointing to a fundamental function in animal survival, the reason for sleep is still debated. Different hypotheses have been raised, such as the energy hypothesis, the synaptic homeostasis hypothesis, and the clearance hypothesis; there is evidence to support each. However, no conclusive agreement on the main reason why sleep evolved has been reached. This is mainly due to the difficulty in integrating the above-mentioned levels of characterization in a single model organism. I will overcome this limitation by studying sleep homeostasis in the nematode Caenorhabditis elegans. Since sleep is a global process spanning the entire brain, full understanding of its regulations requires investigation at levels ranging from molecular mechanisms in single cells to brain-wide network activity. This is currently achievable only in C. elegans, providing a small anatomically mapped nervous system, advanced genetic tools, and a novel whole-brain imaging approach with single-cell resolution that was developed in my host lab. I will leverage on this approach, as well as a new quantitative behavioural paradigm for sleep homeostasis in adult worms, to study the brain-wide effects of sleep deprivation. To unravel the essential function of sleep, I aim to: I: Characterize adult C. elegans sleep by quantitative behavioural analysis and whole brain imaging. II: Identify the neural signature of sleep deprivation. III: Isolate the final signal communicating sleep propensity to sleep-promoting centres.

Keywords: invertebrate neuroscience,calcium imaging,brain wide imaging,caenorhabditis elegans,sleep homeostasis,sleep deprivation,sleep dynamics,synapse homeostasis,brain energetics
Autonomous & Intelligent UAV-based Wind Turbine Inspection System for Cost-effective, Reliable, Safe and Actionable Blade Fault Detection and Prediction (Windrone Zenith)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Portugal
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2019)
Start date: 2019-09-01
End date: 2021-08-31
Duration (months): 24.0
Total project cost (EUR): 1956416.25
EU funding (EUR): 1339396.8
Participants: 1
Project status: CLOSED

Over the lifetime of a wind turbine, operation and maintenance costs represent 25% of total levelised cost per kWh produced. The majority of these costs are attributed to the wind turbine’s blades, yet current methods of inspecting these blades are outdated and inefficient. Blade inspection procedures still largely relies on qualified inspectors roping down each blade to manually inspect for any flaws or defects present on the blade. This is clearly a very hazardous, time-consuming (5 hours), and expensive method (€1500). Other less used methods of blade inspection include capturing blade images from ground cameras and manual review by experts. However, poor image quality and strong backlight leaves many blade flaws undetected. Unmanned Aerial Vehicles (UAVs) are now being used to take pictures of the blades from much closer up. Current UAV's however require dedicated experts for both flight control as well as image processing, analysis, and fault detection. Pro-Drone's integrated WindDrone Zenith’s solution is a breakthrough solution providing enabling 3-blade inspection in a single flight. Our technology solution is fully equipped with highly accurate inspection equipment hardware coupled with smart software. The software allows the UAV to be fly autonomously, avoid collisions, automatically detect any faults, and generate reports for the customer on each wind turbine inspected. Machine learning algorithms are used to continuously improve automated fault detection based on a growing database of captured images and their analysis. Our "BladeInsight" cloud reporting platform makes actionable reports available to our customers as part of this solution. Pro-Drone Zenith provides for a 50% direct cost saving, and decreases turbine inspection downtime by 6X, as compared to existing methods.

Keywords: wind energy,turbine inspection,artificial intelligence,autonomous uav,decision support,system
Integrated, Low-Cost and Stand-Alone Micro-Optical System for Grape Maturation and Vine Hydric Stress Monitoring (i-GRAPE)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Germany,Italy,Portugal,Portugal,Portugal
Call: Electronic Smart Systems (ESS) (H2020-ICT-2018-2, 2018)
Start date: 2018-12-01
End date: 2022-08-31
Duration (months): 45.0
Total project cost (EUR): 2686966.25
EU funding (EUR): 2686965.0
Participants: 6
Project status: CLOSED

This project aims at the development of fully integrated, small, low-cost, standalone smart system used for grape maturation monitoring. It will consist of an optical detection head ( flexible strip or transparent canopy) connected to the grape bunch, including power, signal pre-processing, and wireless communications. The detection head will be optically based (UV-VIS-NIR) using an integration of LED sources and photodiode/interference filter arrays at wafer level or wafer package level. This project aims at the development of a fully integrated, small, low-cost, standalone device used for grape maturation and vine hydric stress monitoring. It will consist of an optical detection head connected to the top of the grape bunch, including power, signal preprocessing, and communications. Reflectance and fluorescence measurements will be used at various wavelengths to probe spectral signatures for phenols (for instance anthocyanins reflectance have a maximum absorption band at around 500-540nm, and flavonols-reflectance at 300-400 at about 370nm), for clorophile chlorophylls (fluorescence at 680-750nm) and other indexes. pH and Brix will be correlated with the optical reflectance and fluorescence measurements. The project concept originated from conversations between Sogrape (a major wine producing company with estates in Portugal, Spain, Chile and Australia and the realization of the pressing need for the development of a standalone device for grape maturation and vine hydric stress control. Partners with the required know how were then contacted to bring in and incorporate the various components required at wafer level, wafer package level, component level and system level necessary for the devclopment of an electronic smart system. Furthemore, the consortium as a whole can carry developed systems into volume production.

Keywords: integrated microspectrometers,precision farming,grape monitoring
Globalisation- and Technology-Driven Labour Market Change and Fertility (LABFER)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Social World and Its Diversity
Panel description: Sociology, social psychology, social anthropology, education sciences, communication studies
Countries involved: Poland
Call: ERC Consolidator Grant (ERC-2019-COG, 2019)
Start date: 2020-10-01
End date: 2025-09-30
Duration (months): 60.0
Total project cost (EUR): 1998100.0
EU funding (EUR): 1998100.0
Participants: 1
Project status: SIGNED

LABFER is the first project that will LABFER is the first project that will comprehensively describe and evaluate fertility consequences of the unprecedented changes in the labour market, caused by digitalisation and globalisation. These changes have been taking place during the last three decades and intensified after the Great Recession. They are reflected in: rising demand for skills, massive worker displacement, spread of new work arrangements, increasing work demands and growing inequalities in labour market prospects between the low-and-medium and the highly skilled. They are likely driving the post-crisis fertility decline in the most advanced nations, which is to date not understood. LABFER is thus highly relevant and timely. It has four main objectives: 1) to study the impact of the ongoing labour market change on fertility (macro-level); 2) to examine the individual-level mechanisms behind the observed macro-level fertility effects of the ongoing labour market change; 3) to investigate the role of the growing inequalities between the low-and-medium and the highly skilled for the relative fertility patterns of the two groups; 4) to study the role of family and employment policies in moderating the fertility effects of the labour market change. Our methodological approach is innovative. We will link data at several layers of observation (country, region, industry, firm, couple and individual) to account for the policy, work and family context of childbearing. We will also use novel labour market measures to capture the ongoing labour market change. Mixture cure models will be employed to separate the effects of covariates on birth timing and probability that the birth occurs. LABFER will break the ground by providing understanding of how the dynamic labour market changes are associated with and potentially affect the current and future fertility dynamics and its socio-economic gradients. It will also have implications for family and employment policies.

Keywords: fertility,labour market,employment,globalisation,digitalisation,family and employment policies,oecd countries
A 24/7 platform providing access to services for isolated communities and reduced mobility residents (TownHall24)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: SME instrument
Countries involved: Finland
Call: Small business innovation research for Transport and Smart Cities Mobility (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2017-02-01
End date: 2017-04-30
Duration (months): 3.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Over the past decades, new residential areas have emerged further and further away from urban centers. This trend can be observed in all urban areas around Europe. Although this has some advantages (larger, greener and cheaper living areas) there are also carry important inconveniencies. The lack of efficient and easy transportation and logistics implies that consumers cannot access or afford their preferred services without using the car. The total annual value of car usage by consumers to access stores and services in Finland alone is estimated at €3.5 Billion. Extrapolated to the EU, this amounts over €300 Billion. Moreover, 25% of the population does not have proper access to these commercial areas because of reduced mobility (elderly, young people, families without a second car). To solve these problems, while taking advantage of a newly to be developed market segment, we have funded Community Constructor to develop TownHall24. Community Constructor is a spin-off of Coreorient, the company behind the sustainable crowdsourced delivery service PiggyBaggy. TownHall24 is a physical shared space within walking distance, self-powered, sustainable, easy-to-be-installed and internet-connected. Members of the local community can use it for services such as deliveries, rentals, second hand sales, recycling, public services or access to locally relevant information. After some pilot trials in Finland 50-80% of the participants wanted to keep using TownHall24 and 85% wanted the piloted services to continue operating. The successful implementation of TownHall24 will create flourishing local markets in which more people can participate, while simultaneously reducing car using. TownHall24 will greatly improve access to services in local communities in a sustainable way, while allowing Community Constructor grow to achieve €46 Million of profits.

Keywords: logistics,walking distance,self powered,sustainable,internet connected
Genes, genealogies and the evolution of demographic change and social inequality (GENPOP)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Social World and Its Diversity
Panel description: Sociology, social psychology, social anthropology, education sciences, communication studies
Countries involved: Italy,United Kingdom
Call: ERC Consolidator Grant (ERC-2019-COG, 2019)
Start date: 2020-10-01
End date: 2025-09-30
Duration (months): 60.0
Total project cost (EUR): 1985705.98
EU funding (EUR): 1985705.98
Participants: 2
Project status: SIGNED

This is the first comprehensive study that combines historical and contemporaneous data to understand how population processes evolve via three interrelated channels: (1) multigenerational transmission, (2) assortative mating and (3) migration. Existing research focuses on recent factors to explain contemporaneous population trends, missing the long-view of demographic changes. As population processes (fertility and mortality) evolve slowly across generations, we urgently need to adopt a long-term perspective to comprehend demographic phenomena and design effective policies. I address this need by using newly available data on internet-based genealogies, micro-census data and genetics, to investigate long-term population processes in family networks. Building on my previous research on demography and genetics, I first develop a new theoretical model of transmission of differential fertility and mortality in family networks. Second, I examine diversity between and within families and its persistence across generations. Third, I use innovative Big Data from genealogy social networks and micro-census data to understand the long-term effect of migration on multiple generations. Fourth, I describe the long-term patterns of assortative mating combining data from genetics and genealogy. This project will infuse new data linkages and produce methodological development in the use of Big Data in demography and beyond. The project will focus on the historical period from approximately 1800 until now in Europe and United States, a period of dramatic demographic and epidemiological changes that radically transformed our societies. This transdisciplinary project will overturn established links and deliver major breakthroughs in our understanding of demographic change. This project is not only ground breaking by setting a new research agenda, but due to the inclusion of genealogy data and their linkage with micro-census data, will yield major innovations in social sciences.
Scalable Deep learning AI driver influence solutions - Road Lifeguard for global prevention of car accidents (Road Lifeguard)

Framework: Horizon 2020 — Societal Challenges
Action type: SME instrument
Countries involved: Belgium
Call: H2020-EIC Accelerator pilot –SME Instrument - Green Deal (H2020-EIC-SMEInst-2018-2020-4, 2020)
Start date: 2020-10-01
End date: 2022-09-30
Duration (months): 24.0
Total project cost (EUR): 2822375.0
EU funding (EUR): 1975662.5
Participants: 1
Project status: CLOSED

Greater Than is a high-tech company that has been working with connected cars since 2004, providing AI based risk insights and digital insurance solutions. Created by a team with extensive experience from the automotive industry and the telecom market, we wanted to see what happens when user-generated data was extracted from the driver to use in real-time. By starting to harness driving data at an early stage of the Big Data era, we have gained extensive experience in using driving data and Artificial Intelligence to create services that contribute to safer, smarter and more environmentally friendly driving. This is done by Machine Learning, and self-learning AI algorithms. Our flagship product, Enerfy, produces unparalleled results. Driving behavior improves by up to 50% in a matter of months, CO2 emissions reduce by up to 26% and car accidents by 40%. Users of the innovation connect an On-Board Diagnostics device (an OBD reader) to the car’s port. While driving, the device transmits driving data - such as curvature, acceleration and speed - to the cloud where our AI analyzes real-time data in comparison with its database of 500 million past driving situations. Our method – protected by 7 registered patents – achieves a risk assessment accuracy of 99.98%. The technology is geo-independent and applicable everywhere in the world. As a result of this, Enerfy was acknowledged as the global standard to measure safe driving by the world’s number one promoter of road safety: the FIA (Fédération Internationale de l'Automobile). The ability to profile users’ driving risk has found numerous applications. Insurers, OEMs, fleets and motor organizations benefit from diminished driving risk. End-users enjoy a gamified phone application which displays each trips’ risk in a score format, provides personalized tips for safer driving and enables insurance premium discounts.

Keywords: artificial intelligence,insurance,traffic,accident prevention,digitalization,new business models,connected car,insurtech,road safety,sustainability