ICT4FPM 2026 Abstracts

Area 1 - Information and Communication Technologies for Frailty Prevention and Monitoring
Full Papers Short Papers

Area 1 - Information and Communication Technologies for Frailty Prevention and Monitoring

Full Papers
Paper Nr: 6
Title:

WiFi-ISAC in Ambient Assisted Living for Frailty Monitoring
Authors:

Maria Gardano
Abstract: Frailty is a multidimensional condition associated with ageing and increased vulnerability to adverse health outcomes. In Ambient Assisted Living (AAL), its monitoring requires continuous, unobtrusive, and reliable observation of behavioral and physiological indicators. In this context, WiFi-based Integrated Sensing and Communication (WiFi-ISAC) has emerged as a promising technology, since it combines sensing and communication while reusing already deployed indoor wireless infrastructures. This paper presents a structured narrative review of WiFi-ISAC for indoor human monitoring, with a focus on its relevance to frailty monitoring in AAL environments. The review first discusses the evolution from traditional WiFi sensing to WiFi-ISAC, highlighting recent advances in IEEE 802.11bf and more integrated sensing and communication architectures. It then analyzes the main human-centric use cases reported in the literature and maps them onto frailty-related indicators through the frailty phenotype and the deficit accumulation model. The analysis shows that WiFi-ISAC is particularly suitable for monitoring mobility-, posture-, activity-, and respiration-related dimensions of frailty, while other indicators remain only indirectly inferable or not measurable through RF sensing alone.
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Paper Nr: 7
Title:

Experimental Assessment of an Immersive Low-Latency Audio System Designed for Remote Therapeutic Intervention
Authors:

E. Bonifazi, G. Cucchieri, E. Felici, M. Osimani, L. Rossi, G. Bergamino, V. Bruschi, S. Cecchi, M. Fioretti, L. Gabrielli, I. Marcantoni, S. Spinsante, S. Squartini and A. Terenzi
Abstract: The global increase in the older adult population has heightened the need for accessible interventions supporting cognitive health. Early therapeutic approaches addressing Subjective Cognitive Decline (SCD), which is a widespread condition and early risk factor for Mild Cognitive Impairment and Alzheimer’s disease, represent a key stage for preventive action. Music therapy is one of the most effective non-pharmacological approaches for enhancing cognition and emotional well-being in individuals with SCD; however, remote delivery is of-ten limited by restricted interaction, high audio latency, and lack of realistic sound rendering. These barriers hinder synchronous musical engagement, reducing therapeutic efficacy. This study presents an experimental evaluation of an innovative low-latency immersive audio system designed to facilitate remote music-based interventions for older adults with SCD. By enabling more natural interaction and enhanced auditory immersion, the system aims to improve feasibility, engagement, and therapeutic potential. The research was carried out within the Vitality project, funded by the Italian Ministry of University and Research under the National Recovery and Resilience Plan.
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Short Papers
Paper Nr: 5
Title:

Extraction of Respiration Signal from Head and Chest Motion with a Stereo Depth Camera
Authors:

Antonio Nocera, Michela Raimondi and Ennio Gambi
Abstract: Cardio-respiratory issues are included in the general assessment of the frailty status of an elderly subject as they accumulate with aging. Given the low adherence of the wearable devices, a depth camera is considered to measure the respiration rate of a standing subject at different distances. The typical algorithm to extract the respiration signal comprises a first step of pose extraction using a deep learning architecture, followed by a second step of region-of-interest integration and tracking over time. Common regions of interest include the chest and abdomen. In this paper, the head is tested as a novel region of interest for extracting the respiration rate based on its mechanical coupling with chest motion. The approach is tested on five subjects at different distances and shows promising results with a mean absolute error below 1 breath per minute within a distance of 2 meters and a mean absolute error of 0.11 breaths per minute at a distance of 1 meter.
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Paper Nr: 8
Title:

Digital Health Platform Based on Data Analytics for Scenario Simulation in Mental Health and Social Coexistence: A Multiscale Approach to Healthy Aging in the Colombian Orinoquía Region
Authors:

Roberto Ferro Escobar and Danilo Alberto Vera Parra
Abstract: This study presents the design, implementation, and evaluation of a digital health platform aimed at monitoring, analyzing, and simulating scenarios related to mental health and social coexistence in the Colombian Orinoquía region. The proposed solution integrates information and communication technologies (ICT), advanced data analytics, and machine learning models to enable multiscale analysis at both territorial and individual levels. The platform incorporates real-world morbidity and mortality data, revealing significant territorial disparities across departments. Results show a high concentration of events in Casanare, a marked prevalence among the working-age population, and a predominance in males. Transport-related incidents-particularly those involving motorcycles-are identified as a critical influencing factor. A central contribution is the integration of predictive models within an interactive simulation environment through two complementary analytical components: a territorial model (City Model) and an individual-level model (Person Model). These enable dynamic exploration of "what-if" scenarios, real-time estimation of event occurrence probabilities, and evidence-based decision-making. The platform advances beyond descriptive observatories by incorporating predictive and prescriptive analytics, positioning it as an intelligent decision support system. The multiscale approach deepens understanding of complex phenomena while generating strategic inputs for targeted interventions and public policy, contributing to the promotion of healthy aging and improved quality of life.
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Paper Nr: 9
Title:

FrailTrack: An Ecological Momentary Assessment Application for Frailty Evaluation within an Internet of Things Ecosystem
Authors:

Juan Campello-Serrano, Carlo Huesca-Spairani, Pau Climent-Pérez and Francisco Florez-Revuelta
Abstract: Frailty is a dynamic and multidimensional condition that requires continuous and context-aware monitoring to enable early detection and intervention. However, traditional assessment methods rely on episodic, clinic-based evaluations that fail to capture real-life variability. Recent advances in Internet of Things (IoT) technologies and Ecological Momentary Assessment (EMA) offer new opportunities for unobtrusive, in-situ monitoring of both objective and subjective health indicators. This paper presents FrailTrack, a mobile application developed within the EMA-FRAILTY project, designed to support ecological and continuous frailty assessment within an IoT ecosystem. We describe the FrailTrack pipeline, detailing how it integrates EMA-based questionnaires with data from heterogeneous IoT devices to enable multimodal monitoring. The approach combines self-reported frailty indicators with sensor-derived behavioral data, supporting a more comprehensive and ecologically valid evaluation. We position FrailTrack as an integration layer bridging subjective and objective data, and argue that such systems represent a paradigm shift toward continuous, real-world, and person-centered frailty assessment.
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