H2020Индивидуална стипендия2021–2023

EarlyCare · Unobtrusive Health Monitoring System for the Early Detection of Heart- and Micturition-Related Diseases

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2021-04-01 → 2023-09-18
Финансиране от ЕС: 172 932 €
Участници: 1
Схема: MSCA-IF

Линиите свързват координатора с партньорите.

Накратко на български

Сензори за газове и радиочестоти следят за ранни признаци на диабет и сърдечна недостатъчност, като например необичайно често уриниране. Това помага за откриване на първи симптоми при хора, живеещи сами, без да нарушава техния комфорт и поверителност.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Unobtrusive Health Monitoring System for the Early Detection of Heart- and Micturition-Related Diseases

EarlyCare is a two-year project focusing on the development and validation of non-wearable, unobtrusive, and privacy-preserving health monitoring systems, namely gas and radiofrequency physiological sensors, to monitor early warning signs of Diabetes Mellitus (DM) and Congestive Heart Failure (CHF) by exploiting advanced time series analysis and explainable artificial intelligence. To achieve this overarching objective, significant advancements have been made in the following research areas: • The first area of the research for the EarlyCare project was the development of highly sensitive gas sensors to detect urine occurrence and derive the abnormal micturition such as nocturia and pollakiuria as warning signs of both DM and CHF. In this regard, the project proposed an innovative methodology including graphene and metal oxide hybrid nanostructures along with appropriate machine learning (ML) models for the detection of these warning signs. • The second area of the research focused on the development of deep learning (DL) and ML models to detect abnormal cardiac rhythm and abnormal respiration. The key idea was to investigate the capabilities of newly developed radiofrequency technologies together with DL/ML techniques and heart rate variability time series analysis in the recognition of arrhythmia and abnormal respiration. • The third area of research dealt with the development of trustworthy and explainable AI (XAI) approach to simulate the detection of DM and CHF via the Belief Rule-Based Expert System. EarlyCare is not intending to diagnose DM and CHF; it rather proposes unobtrusive solutions to detect the first apparent symptoms that are often overlooked without compromising the comfort and privacy of the users (e,g., older adults living alone).

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

EarlyCare project aims at developing and implementing cutting-edge sensing technologies and advanced Artificial Intelligence (AI) techniques to create a Health Monitoring System enabling early prediction of Diabetes Mellitus (DM) and Congestive Heart Failure (CHF), through the continuous monitoring of vital signs of older adults’ living alone related to micturition and cardiac activities as well as their warning signs. The innovative aspect of EarlyCare solution is the efficient deployment of completely nonwearable, unobtrusive, and privacy-friendly devices such as gas sensors and wireless physiological sensors which are coupled with explainable AI to detect and analyse the underestimated warning signs (i.e., nocturia and pollakiuria as abnormal micturition activity, arrhythmia and breathlessness). The AI-powered systems will be trained using publicly accessible sets and refined during the first phase of piloting. EarlyCare will be integrated into an interoperable IoT platform (enSenior) and validated on voluntary patients. The successful conclusion of this project will contribute to promote healthy ageing and reduce burden of formal and informal caregivers of older adults by advancing in development of eHealth tools and smart devices. The proposed multidisciplinary research activities, training, transferable skills and secondments will grant the improvement and acquisition of the most appropriate skills for his future career development.

Оригинален текст от CORDIS (на английски).

Участници

N-VISION SYSTEMS AND TECHNOLOGIES SL · IGUALADAКоординаторИспания