Frágil-IA: Artificial Intelligence for Personalised Care for Frailty

General description of the project

Frailty is a clinical state of vulnerability characterised by a decrease in functional reserve and responsiveness stressors, which can manifest itself in various ways. It is considered one of the main risk factors for adverse events in older people, as it is associated with an increased incidence of falls, disability, hospitalisation and mortality. Its prevalence is high, affecting a significant proportion of the population older than 65 years.

Multicomponent Training (MCT), which integrates strength, endurance, balance and flexibility, has proved to be an effective intervention for improving frailty and reducing the risk of falls. However, its implementation in daily clinical practice faces significant challenges, including low adherence to exercise programmes and limited availability of human and material resources to ensure the correct execution of the prescribed exercises.

In this context, the project aims to improve the care and quality of life of elderly people with frailty syndrome by developing an assistive device for performing therapeutic exercises, both during hospitalisation and at home. The device incorporates a camera-based vision system that measures relevant exercise parameters, such as range of motion and number of repetitions performed, among others functional indicators. Simultaneously, the system provides visual feedback via a screen, showing the correct execution of each exercise and the expected range of motion, with the aim of promoting safe and correct practice in line with therapeutic guidelines.

Objectives

This project aims at providing elderly people with frailty syndrome with a set of physical and digital tools designed to facilitate the implementation of exercise programmes and enhance rehabilitation processes. These tools are designed to assist the user during the execution of the exercises, favouring a safe and correct practice, adjusted to individual functional capacities.

In the first phase, the devices will be installed in the health centres participating in the project, where they will be used by healthcare personnel to guide and supervise the start of the rehabilitation process. The devices will have a touchscreen interface that will allow direct interaction with the system and the visualisation of the prescribed exercises, as well as sensors and cameras capable of objectively recording the patient’s movements.

The aim is to implement a programme on these devices that can assign exercises to be performed according to each patient's needs, based on both their pre-existing conditions and their ability to complete the exercises from the previous cycle.

In addition, the project includes the implementation of an outpatient rehabilitation module that will allow patients to continue their exercise programme at home once they have been discharged from hospital. This module will also be equipped with sensors and tracking systems that will enable remote, real-time monitoring by the healthcare team. This approach ensures continuity of treatment outside the hospital environment and also contributes to a more efficient use of healthcare resources by freeing up hospital capacity.

Contribution of NAIR Center

NAIR Center plays a strategic role in the project as it leads the development of the components that require the use of artificial intelligence of the application.

Working closely with consortium partners, the centre will be responsible for conducting advanced clinical data analysis to identify existing patterns. As data from individuals at all stages of rehabilitation will be used, it will also be possible to extract relevant trends in patient progress.

NAIR Center will also be responsible for designing and developing an artificial intelligence engine capable of automating data analysis and generating personalised diagnoses and recommendations, increasing its accuracy as new records are added. At the same time, it will build predictive models aimed at optimising exercise routines and individualised rehabilitation programmes, based on the experience of health professionals. The objective of this model will be to promote patient autonomy and increase the effectiveness of therapies.

Partners

Funding

Project funded by the Francisco Soria Melguizo Foundation's 2023 Call for Biomedical Research Grants.

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