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ViSionRF SIGNED

ViSionRF: Vital Signal Monitoring using Radio-Frequency Technologies – Standard IF-RI

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 ViSionRF project word cloud

Explore the words cloud of the ViSionRF project. It provides you a very rough idea of what is the project "ViSionRF" about.

people    rate    healthcare    disease    health    forget    maximizes    wi    trained    merges    detector    patients    physiological    million    breathing    fold    tremendously    body    home    monitoring    irregular    total    2050    decline    transparent    contributes    pressure    patient    remotely    algorithms    cognitive    citizens    shape    posture    suite    occurs    hybrid    learning    powerful    suffering    sufferers    alzheimer    power    stethoscope    wearing    worldwide    heart    signals    unlike    unobtrusive    time    wear    machine    projected    imperative    overwhelming    mobility    fi    alert    solution    envision    152    added    vital    doctor    tremendous    signal    completely    families    70    emergency    electronic    pulse    remote    carers    position    sensor    acts    device    beat    visionrf    equally    function    technologies    capture    radar    efficient    syndrome    monitor    single    society    wearable    memory    care    nearly    watch    dementia    82    impaired    full    deterioration    consists    2030    puts    repeatedly    sensors    rfid    breath   

Project "ViSionRF" data sheet

The following table provides information about the project.

Coordinator
HERIOT-WATT UNIVERSITY 

Organization address
address: Riccarton
city: EDINBURGH
postcode: EH14 4AS
website: www.hw.ac.uk

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 United Kingdom [UK]
 Total cost 224˙933 €
 EC max contribution 224˙933 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-EF-RI
 Starting year 2019
 Duration (year-month-day) from 2019-09-01   to  2021-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    HERIOT-WATT UNIVERSITY UK (EDINBURGH) coordinator 224˙933.00

Map

 Project objective

Dementia is a syndrome in which there is cognitive function deterioration and memory loss. Alzheimer's disease consists or contributes to 60–70% of dementia cases. At present, worldwide around 50 million people have dementia, but nearly 10 million new cases are added every year. The total number of people suffering from dementia is projected to reach 82 million in 2030 and 152 million by 2050 – a 3-fold increase. This puts tremendous pressure on the healthcare system and society as a whole. Equally important, dementia is overwhelming for patients' families and their carers, as they require full-time care and watch. For all these reasons it timely and imperative to develop a low-cost and efficient full-time health monitoring solution.

The goal of this research is to develop an unobtrusive system Suite (ViSionRF) that will be able to capture the vital physiological signals of users (breathing, heart rate, heart beat shape, body position), remotely by using low-power radar, Wi-Fi and RFID signal technologies. Envision a home with a single remote and unobtrusive device that acts as a stethoscope, heart monitor, irregular breath detector, and posture sensor. Such a home would have the ability to monitor your breathing, your heart (rate and pulse shape), and your position and alert your doctor when an emergency occurs. Such a home would help tremendously impaired citizens (e.g. dementia patients) and their carers.

Unlike traditional patient monitoring systems that require users to ‘wear’ devices and sensors, the proposed system does not require wearing any wearable electronic or on-body sensor. This maximizes mobility and makes the system completely transparent to the user. This is important as dementia sufferers repeatedly forget or decline to ‘wear’ their sensors. The goal will be achieved by developing a hybrid technology that merges Wi-Fi, radar and RFID responses with advanced signal processing algorithms that are further trained using powerful machine learning.

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

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