DHU Radar

TOLIFE: Combining artificial intelligence and smart sensing toward better management and improved quality of life in chronic obstructive pulmonary disease

Keywords: Artificial Intelligence (AI), Chronic Obstructive Pulmonary Disease (COPD), Digital Health Innovation, Sensors
Owner
TOLIFE EU project consortium
Type
Digital solution and service (e.g. application/digital health portal/platform/AI based system/etc.)
Short description
Chronic obstructive pulmonary disease (COPD) refers to a group of diseases associated with breathing-related problems that affect millions of people worldwide. COPD is very heterogeneous, necessitating personalised treatment and management approaches. However, due to extrapulmonary effects and comorbidities, patients often do not respond to pharmacological and non-pharmacological treatments. To address this problem, the EU-funded TOLIFE project proposes to develop an AI solution that processes daily life patient data captured by unobtrusive sensors. The AI-based platform will predict COPD exacerbations and assess health outcomes. Using a patient management tool, clinicians can then offer early and personalised treatment, improving quality of life of patients.
Maturity
The idea has been formulated and/or research and experiments are underway to test a “proof of concept”
Countries
Germany
Italy
Spain
Geographical scope
International
Language(s)
English
Comment
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Submitted in other database or repository of digital health resources that is publicly available
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Additional information

Relations
to clinicians / care practitioners
Clinical decision support
Health data analytics (Artificial Intelligence/algorithm development and calibration/machine learning/risk stratification tools/etc.)
Clinical team care planning and collaboration tools (e.g. digital shared care plan)
to patients / citizens
Remote monitoring apps/health outcomes tracking
Sensors/wearable devices
Telehealth and telemedicine
Personalised prevention apps
Health promotion and wellness apps and wearables/virtual coaches
Health data analytics (Artificial Intelligence/algorithm development and calibration/machine learning/risk stratification tools/etc.)
Digital tools to support health education (health literacy)/digital health literacy
Digital tools to support patient feedback and reporting of outcomes and experiences
Primary target patient group (age)
Adults (25-64), Older adults (65+)
Use case and care pathway positioning
Treatment, Disease monitoring, treatment compliance, self-management, Early detection and early diagnosis, precision diagnosis