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Kempenhaeghe

8 Projects, page 1 of 2
  • Funder: European Commission Project Code: 324257
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  • Funder: European Commission Project Code: 120209
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  • Funder: European Commission Project Code: 101139769
    Overall Budget: 34,764,800 EURFunder Contribution: 11,274,500 EUR

    We are surrounded by a variety of more-or-less intelligent technical devices, designed to serve you us or others. Applications onin your mobile phones, wrist-worn health sensors on your wrists, autonomous vacuum cleaners, robots on the factory floor and increasingly autonomous cars – all pledge to ease your tasks and keep usyou safe and healthy. SThe seamless interplay with these devices gets gainsmore importane as these devices proliferate and grow in t with the increased autonomy and pervasive presence of the devices. We expect continuously available support fromin the services they provide − yet we want them to disappear unobtrusively in the background when not needed. In order to provide support in a collaborative environment with human, physical and digital players, the technology needs to be equipped with senses to grasp human presence, their mental and physical state, their activities and their intentions. This is required to ensure human safety, safeguard their health, and allow for natural interaction. This project intends to improve sensing of human presence, behaviour and health in a collaborative or common environment by means of multi-sensor systems.

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  • Funder: European Commission Project Code: 101099481
    Overall Budget: 2,809,260 EURFunder Contribution: 2,809,260 EUR

    The goal of Project RELIEVE is to build the very first non-invasive effective closed-loop monitoring and intervention system for brain-related disorders. The outcomes can be used to treat or manage various psychiatric and neurological disorders. We do this by pushing the technological boundaries in two separate domains. (1) AI domain: We develop a class of mathematical and algorithmic tools for brain data based on the recently developed mathematical theories that are potentially useful for the real-time monitoring of the brain data. Such advancements have shown promise in robotics and self-driving cars and have high potential to work efficiently in highly dynamic environments where personalization and low computation power is a must. This makes such algorithms runnable using brain data such as EEG (electric activity on the head surface) on ordinary wearable devices. (2) Neurostimulation domain: We combine two characteristics of the ultrasound waves in stimulation and imaging of the nervous system to build the first smart-navigated wearable ultrasound patch. We also choose the vagus nerve as the target for neurostimulation as one of the most promising sites to interact with the nervous system with proven implications for a large spectrum of neurological and psychiatric disorders (e.g. dementia, depression, epilepsy, etc.). We call this unit 'WU-VNS' standing for non-invasive wearable ultrasound vagus nerve stimulation. In the next three years, we will use epilepsy as the first use case of the developed technologies to train and test a closed-loop system. For this, the AI monitors the brain through a patch that records EEG in addition to other physiological measures such as heart rate and motion. Upon prediction of a forthcoming anomaly (seizure in this case) by the AI unit, the neurostimulation module activates and stimulates the vagus nerve non-invasively. During this process also a so-called 'active learning' happens in which the AI learns from the reactions of the nervous system to the stimulation protocol and can fine-tune the protocol for future interventions. To achieve this, we have designed a complex phase-based development and testing plan: The first two generations (Gen. 1 and 2) are the intermediate versions of the full system and act in open loops validating each of the AI and neurostimulation subsystems. These two generations already have high potentials to independently turn into medical device products with large market needs. Ultimately, in Gen. 3 we close the loop by integrating the AI and the WU-VNS and consequently validate the efficacy and the usability of the system.

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  • Funder: European Commission Project Code: 692470
    Overall Budget: 18,444,600 EURFunder Contribution: 5,895,050 EUR

    The ageing population and related increase in chronic diseases put considerable pressure on both the healthcare system and the society, resulting in an unsustainable rise of healthcare costs. As a result there is an urgent need to improve efficiency of care and reduce hospitalisation time in order to control cost and increase quality of life. Addressing this need, medical applications need to become less invasive and improve disease detection, diagnosis and treatment using advanced imaging and sensing techniques. ASTONISH will deliver breakthrough imaging and sensing technologies for monitoring, diagnosis and treatment applications by developing smart optical imaging technology that extends the use of minimally invasive diagnosis and treatment and allows for unobtrusive health monitoring. The project will integrate miniaturized optical components, data processing units and SW applications into smart imaging systems that are less obtrusive, cheaper, more reliable and easier to use than state of the art systems. This results into 6 demonstrators by which the technologies will be validated and which allow for pre-clinical testing in the scope of the project. The overall concept within ASTONISH builds on the development and application of common imaging/sensing technologies. Smart algorithms, multimodal fusion techniques and biomedical signal processing will process the acquired data and advanced user interfaces will simplify the complex clinical tasks. These technology components will be integrated to build application specific solutions for physiological signs monitoring, tumour detection, minimally invasive surgery, brain function monitoring and rehabilitation. The ASTONISH partners cover the full value chain, from semiconductor manufacturing to clinical centres testing the final application. The proposed innovations improve the global competitiveness of the European industry in the healthcare domain.

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