Skip to content

MOTIVA lies in the intersection of biomedical engineering, computer science, psychology, and clinical research, making the coordination of two subprojects essential. The team is formed by researchers from “Universidad Politécnica de Madrid” (UPM) and “Fundación de Investigación Biomédica del Hospital Universitario de Getafe” (FIBHUG), including biomedical engineers, computer science engineers, a geriatrician, a psychologist, user experience researchers, a physiotherapist, an epidemiologist, a statistician, and a clinical pharmacologist. Researchers from UPM belong to the Ageing Lab1 , part of the Centre for Biomedical Technology (CTB), and the Human Computer Interaction and Advanced Interactive Systems research group of the Computer Science School. FIBHUG and UPM maintains a close collaboration in many projects and researchers from FIBHUG are also part of the Ageing Lab since its foundation as a joint laboratory in 2014. It is worth highlighting the relevance of both entities in terms of research and knowledge transfer. According to the last report of research and knowledge transfer of the Spanish Universities from CRUE, UPM is among the top five Spanish Universities in practically all the indicators related to the Competitive funding and Knowledge transfer, being the technical university that has obtained the most funding from research projects, both national and European. Moreover, CTB is a leading research centre in biomedical technology. On the other hand, Hospital Universitario de Getafe and its FIBHUG2 are a leading research centre in geriatrics and frailty. Together, both institutions cover all areas needed to fulfill the objectives of MOTIVA.

BACKGROUND AND STATE OF THE ART

The ageing of population in Western societies is the result of the continuous decline of fertility rate and the increase of life expectancy. As the number of older adults increases both in absolute and relative terms, it is of paramount importance to provide this population with the means and tools to experience healthy ageing. A meta-analysis has shown that physical exercise performed by community-dwelling older adults improves body composition and health-related variables. To our knowledge, the effectiveness of the VIVIFRAIL programme in relatively healthy community-dwelling individuals have not been assessed nor its adherence without supervision. Unsupervised approaches are better than supervised ones because of resource constraints in healthcare systems and the steady increase in the number of older people living alone, which make it difficult to implement these supervised lifestyle intervention programmes on a routine and comprehensive basis. Therefore, there is an unmet need for unsupervised physical exercise programmes. 

THE CHALLENGE

VIVIFRAIL has developed a mobile application that allows users to  follow it on their own, but which suffers from fundamental limitations:

1) Exercises are recommended based on the score obtained by the user in the Short Physical Performance Battery (SPPB) (Guralnik et al, 1994), a test that can be quickly administered by an external evaluator (professional or caregiver), and that is sensitive to change and able to predict adverse events in older population. Nevertheless, to date, it is not possible for older adults to perform this test without external supervision, obtaining feedback on whether the test is being evaluated correctly or not. We have developed in previous projects devices to measure gait speed and sit-to-stand test at home, which are two of the three SPPB domains, but there is not a suitable unsupervised measure of the third domain, balance assessment, for older persons.

2) The VIVIFRAIL app does not provide individuals with any feedback on how intensely they are performing the exercises to see if they are making progress. This information could increase adherence to the programme and, consequently, its effectiveness. What is more, there is a lack of information on what frequency and intensity of the exercises provide the best results in terms of increased functionality, something which could be known linking the performance in the exercises with the health outcomes.

3) The VIVIFRAIL app does not include any motivational support or strategies to prevent lack of adherence, nor it offers the possibility to contact with other peers to follow the exercise programme.

OUR PROJECT

MOTIVA aims to overcome these limitations by developing innovative ICT solutions for the autonomous measurement of the SPPB test and the intensity of the exercises. Assessing older adult’s functional status via the SPPB and assessing their performance during their VIVIFRAIL exercising sessions requires movement analysis techniques.

There are various approaches to movement analysis depending on the technology they use to capture the input data. In our previous ActiveUP project, we already developed a low-cost, wearable and IoT compatible inertial device which has already gone into industrial design and manufacturing by the Spanish electronics company Televes. Within the ActiveUP project as well, we developed a UbiHome system which is an edge computing system for the Internet of Things (IoT) that operates as a wireless network that comprises sensors, an edge node, and a gateway with an Internet connection. Data processing modules transform raw data into clinically relevant information, thus reducing the amount of information that must be transmitted over the Internet. Thus, MOTIVA already has an infrastructure for the data capturing stage, and the focus will be on the algorithms to process that data for functional and performance assessment. 

In MOTIVA, we will take advantage of the fact that most of the activities in both the SPPB and the VIVIFRAIL programme involve some kind of repetitive movement, which according to our previous experience, provides enough constraints to fight the effects of noise. However, we still need to design and validate a sensor to autonomously measure the balance, to complete the SPPB test; and adapt the IMU position and algorithms to detect movements to assess performance during the exercises, overcoming the first and second limitations. 

With regards to the third limitation, the lack of adherence can hinder the effectiveness of the proposed exercise programme. One way to maintain adherence in the absence of supervision is for the individuals to receive automated reinforcement messages and motivational support in line with their motivational profile. Taking as a reference an existing questionnaire for the assessment of motivational traits, the Motivational Trait Questionnaire (MTQ), we designed an objective behavioural test in the form of a game, where the player is faced to specific situations in which the behavioural decision made is interpreted as evidence of certain motivational traits. In MOTIVA, we aim to evaluate the validity of the game as a psychometric instrument in the target population and expand the coverage of the users’ motivational traits.

OBJECTIVES AND STATUS

Design, develop and validate an ICT solution for functional assessment through the autonomous realization of the Short Physical Performance Battery (SPPB) test at home

Design, develop and validate an ICT solution for assessing the user’s performance when exercising, without external supervision. 

Desining, developing and validating a computational tool for identifying the motivational trait profile of the user autonomously:

Design, implement and validate the MOTIVA ecosystem, a set of personalized exercise plans adapted to the user functional status, the specific performance, and the motivational trait profile:

Co-design, implement and validate the MOTIVA ecosystem, a set of personalized exercise plans adapted to the user functional status, the specific performance, and the motivational trait profile:

To carry out a randomized controlled trial to compare the adherence of motivational strategies and supervised performance of VIVIFRAIL: 

Carrying out a before-after trial for demonstrating the effectiveness of the personalised exercise programme in improving functional capacity, cognitive function, emotional status, quality of life and autonomy to perform instrumental activities of daily living, and reducing disability, healthcare utilisation and loneliness. 

RELATED PUBLICATIONS

Regina Maritzol Tenemaza Vera (2023, to be defended in February). “Propuesta de un Sistema de Recomendación Contextual para Rutas Turísticas basado en un Algoritmo Genético”. Supervised by: Angélica de Antonio Jiménez, Jaime Ramírez Rodriguez. doi: link
Ji Yeon Yu (2022). “Smarthome technology for the elderly: adaptation to the user needs and acceptance framework”. Supervised by: Angélica de Antonio Jiménez, Elena Villalba Mora. doi: link
Daniel Fernández-Avilés Pedraza (2021). “Modelado y Gestión de la Motivación en sistemas computacionales”. Supervised by: Angélica de Antonio Jiménez, Elena Villalba Mora. doi: link
José Nevardo Paladines Morán (2021). “Integración de un Sistema de Diálogo con un Sistema Inteligente de Tutoría dirigido al entrenamiento procedimental”. Supervised by: Jaime Ramírez Rodriguez. doi: link
Mauro Danilo Martínez Espinoza (2020). “Marco Integrado de Desarrollo de Aplicaciones Móviles: Un Enfoque Ágil”. Supervised by: Xavier Ferré Grau. doi: link
Luis Fernando González Alvarán (2020). “Programadores con Dislexia: Programación Visual frente a la Programación Textual”. Supervised by: Loïc Martínez Normand. doi: link
Doris Cruz Cáliz Ramos (2020). “Usability Testing Guide for Mobile Applications Focused on People with Down Syndrome (USATESTDOWN)”. Supervised by: Loïc Martínez Normand. doi: link
Diego Riofrío Luzcando (2017). “Propuesta de un Modelo de Comportamiento Colectivo de Estudiantes para un Sistema Inteligente de Tutoría dirigido al Entrenamiento Procedimental”. Supervised by: Jaime Ramírez Rodriguez. doi: link
Cristian Moral Martos (2016). “Modelling the visualization and exploration of document collections with user and purpose-based adaptation”. Supervised by: Angélica de Antonio Jiménez, Xavier Ferré Grau. doi: link
Graciela Lara López (2016). “Computational model for the generation of directions for object location in virtual environments: spatial and perceptual aspects”. Supervised by: Angélica de Antonio Jiménez. doi: link