SmartNurse | Bringing persuasive computing training assistance for healthcare personnel from lab experiments to educational practice

Summary
The aim of this proposal is to develop a strategy for transforming the results of a series of experiments in using persuasive computing technologies in emergency nurse training into a system that can be used in real life educational settings. The experiments were conducted as part of the SmartSociety FET Open project, which aims to develop new ways of human-machine collaboration. They were jointly done by the partners of this proposal with DFKI being in charge of the technology and Southampton providing the experimental setting within their nursing school that puts hundreds of professional nurses and nurse candidates through elaborate training simulations each year. The experiments have shown that sensor-based activity recognition combined with novel interaction techniques can, in principle provide significant benefit to both the students and the trainers. They also generate significant interest within the health care community, which included both enthusiasms for the potential and sepsis on potential problems. In this project, we want to understand which parts of the experiments are suitable for short to mid-term transition into real life education practice, how to overcome the corresponding technical, regulatory and social hurdles and how the introduction of such systems could be financed.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/754554
Start date: 01-05-2017
End date: 31-10-2018
Total budget - Public funding: 100 000,00 Euro - 100 000,00 Euro
Cordis data

Original description

The aim of this proposal is to develop a strategy for transforming the results of a series of experiments in using persuasive computing technologies in emergency nurse training into a system that can be used in real life educational settings. The experiments were conducted as part of the SmartSociety FET Open project, which aims to develop new ways of human-machine collaboration. They were jointly done by the partners of this proposal with DFKI being in charge of the technology and Southampton providing the experimental setting within their nursing school that puts hundreds of professional nurses and nurse candidates through elaborate training simulations each year. The experiments have shown that sensor-based activity recognition combined with novel interaction techniques can, in principle provide significant benefit to both the students and the trainers. They also generate significant interest within the health care community, which included both enthusiasms for the potential and sepsis on potential problems. In this project, we want to understand which parts of the experiments are suitable for short to mid-term transition into real life education practice, how to overcome the corresponding technical, regulatory and social hurdles and how the introduction of such systems could be financed.

Status

CLOSED

Call topic

FETOPEN-04-2016-2017

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.2. EXCELLENT SCIENCE - Future and Emerging Technologies (FET)
H2020-EU.1.2.1. FET Open
H2020-FETOPEN-2016-2017
FETOPEN-04-2016-2017 FET Innovation Launchpad