9 citations · 35 across the 17 of their papers we have counts for
17 papers
X-BCD: Explainable Sensor-Based Behavioral Change Detection in Smart Home Environments
Gabriele Civitarese, Claudio Bettini
Behavioral changes in daily life activities at home can be digital markers of cognitive decline. However, such changes are difficult to assess through sporadic clinical visits and…
DomusFM: A Foundation Model for Event-Based Behavioral Monitoring in Smart-Homes
Michele Fiori, Gabriele Civitarese, Flora D. Salim +1
Smart-home sensor-based behavioral monitoring holds significant potential for healthcare, independent living, and early detection of functional or cognitive changes. In this settin…
Improving Zero-shot ADL Recognition with Large Language Models through Event-based Context and Confidence
Michele Fiori, Gabriele Civitarese, Marco Colussi +1
Unobtrusive sensor-based recognition of Activities of Daily Living (ADLs) in smart homes by processing data collected from IoT sensing devices supports applications such as healthc…
The SERENADE project: Sensor-Based Explainable Detection of Cognitive Decline
Gabriele Civitarese, Michele Fiori, Andrea Arighi +3
Mild Cognitive Impairment (MCI) affects 12-18% of individuals over 60. MCI patients exhibit cognitive dysfunctions without significant daily functional loss. While MCI may progress…
Personal Data Protection in Smart Home Activity Monitoring for Digital Health: A Case Study
Claudio Bettini, Azin Moradbeikie, Gabriele Civitarese
Researchers in pervasive computing have worked for decades on sensor-based human activity recognition (HAR). Among the digital health applications, the recognition of activities of…
Leveraging Large Language Models for Explainable Activity Recognition in Smart Homes: A Critical Evaluation
Michele Fiori, Gabriele Civitarese, Priyankar Choudhary +1
Explainable Artificial Intelligence (XAI) aims to uncover the inner reasoning of machine learning models. In IoT systems, XAI improves the transparency of models processing sensor…
GNN-XAR: A Graph Neural Network for Explainable Activity Recognition in Smart Homes
Michele Fiori, Davide Mor, Gabriele Civitarese +1
Sensor-based Human Activity Recognition (HAR) in smart home environments is crucial for several applications, especially in the healthcare domain. The majority of the existing appr…
Using Large Language Models to Compare Explainable Models for Smart Home Human Activity Recognition
Michele Fiori, Gabriele Civitarese, Claudio Bettini
Recognizing daily activities with unobtrusive sensors in smart environments enables various healthcare applications. Monitoring how subjects perform activities at home and their ch…
Large Language Models are Zero-Shot Recognizers for Activities of Daily Living
Gabriele Civitarese, Michele Fiori, Priyankar Choudhary +1
The sensor-based recognition of Activities of Daily Living (ADLs) in smart home environments enables several applications in the areas of energy management, safety, well-being, and…
Comparing Self-Supervised Learning Techniques for Wearable Human Activity Recognition
Sannara Ek, Riccardo Presotto, Gabriele Civitarese +3
Human Activity Recognition (HAR) based on the sensors of mobile/wearable devices aims to detect the physical activities performed by humans in their daily lives. Although supervise…
ContextGPT: Infusing LLMs Knowledge into Neuro-Symbolic Activity Recognition Models
Luca Arrotta, Claudio Bettini, Gabriele Civitarese +1
Context-aware Human Activity Recognition (HAR) is a hot research area in mobile computing, and the most effective solutions in the literature are based on supervised deep learning…
Combining Public Human Activity Recognition Datasets to Mitigate Labeled Data Scarcity
Riccardo Presotto, Sannara Ek, Gabriele Civitarese +3
The use of supervised learning for Human Activity Recognition (HAR) on mobile devices leads to strong classification performances. Such an approach, however, requires large amounts…
Neuro-Symbolic Approaches for Context-Aware Human Activity Recognition
Luca Arrotta, Gabriele Civitarese, Claudio Bettini
Deep Learning models are a standard solution for sensor-based Human Activity Recognition (HAR), but their deployment is often limited by labeled data scarcity and models' opacity.…
SelfAct: Personalized Activity Recognition based on Self-Supervised and Active Learning
Luca Arrotta, Gabriele Civitarese, Samuele Valente +1
Supervised Deep Learning (DL) models are currently the leading approach for sensor-based Human Activity Recognition (HAR) on wearable and mobile devices. However, training them req…
Ultrasound Detection of Subquadricipital Recess Distension
Marco Colussi, Gabriele Civitarese, Dragan Ahmetovic +4
Joint bleeding is a common condition for people with hemophilia and, if untreated, can result in hemophilic arthropathy. Ultrasound imaging has recently emerged as an effective too…
Context-driven Active and Incremental Activity Recognition
Gabriele Civitarese, Riccardo Presotto, Claudio Bettini
Human activity recognition based on mobile device sensor data has been an active research area in mobile and pervasive computing for several years. While the majority of the propos…
Extended Report: Fine-grained Recognition of Abnormal Behaviors for Early Detection of Mild Cognitive Impairment
Daniele Riboni, Claudio Bettini, Gabriele Civitarese +2
According to the World Health Organization, the rate of people aged 60 or more is growing faster than any other age group in almost every country, and this trend is not going to ch…