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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.

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

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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