Alessia Paglialonga

Adjunct Professor

Politecnico di Milano

Italy

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About

Alessia Paglialonga is an Adjunct Professor at Politecnico di Milano, Italy. Her research interests include emotion recognition using virtual reality, physiological responses in speech-in-noise testing, and advancements in IoT and AI in pneumology. She has contributed to the field through various publications that explore machine learning applications in health records and the characterization of physiological reactions to emotional stimuli.

Articles (17)

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2025

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2025

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2025

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2024

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2024

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2022

Collaborators (4)

Pedro A. Moreno-Sanchez

University of Tampere

FINLAND

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Riccardo Barbieri

Professor

Politecnico di Milano - Milano Leonardo

ITALY

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Luca Mainardi

Associate Professor

Politecnico di Milano

ITALY

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Karim Keshavjee

Assistant Professor, Teaching Stream

University of Toronto

CANADA

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Alessia Paglialonga

Research Interests

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About

Articles (17)

Advancing emotion recognition with Virtual Reality: A multimodal approach using physiological signals and machine learning

An adaptive protocol to assess physiological responses as a function of task demand in speech-in-noise testing

Long-Term Diabetes Prevention via Physical Activity: An Output-Feedback MPC Approach

Comparative Assessment of Physiological Responses to Emotional Elicitation by Auditory and Visual Stimuli

Advancements on IoT and AI applied to Pneumology

Multiclass Counterfactual Explanations Using Support Vector Data Description

Identifying prognostic factors for survival in intensive care unit patients with SIRS or sepsis by machine learning analysis on electronic health records

Characterization of the Intelligibility of Vowel–Consonant–Vowel (VCV) Recordings in Five Languages for Application in Speech-in-Noise Screening in Multilingual Settings

Characterization of Inclination Analysis for Predicting Onset of Heart Failure from Primary Care Electronic Medical Records

The Long-Term Effects of Physical Activity on Blood Glucose Regulation: A Model to Unravel Diabetes Progression

Applying Patient Segmentation Using Primary Care Electronic Medical Records to Develop a Virtual Peer-to-Peer Intervention for Patients with Type 2 Diabetes

Dual-View Single-Shot Multibox Detector at Urban Intersections: Settings and Performance Evaluation

Characterization of Synthetic Health Data Using Rule-Based Artificial Intelligence Models

A Novel Approach for Segment-Length Selection Based on Stationarity to Perform Effective Connectivity Analysis Applied to Resting-State EEG Signals

A novel method to derive personalized minimum viable recommendations for type 2 diabetes prevention based on counterfactual explanations

Evaluation of Machine Learning Algorithms and Explainability Techniques to Detect Hearing Loss From a Speech-in-Noise Screening Test

Counterfactual Building and Evaluation via eXplainable Support Vector Data Description

Collaborators (4)

Pedro A. Moreno-Sanchez

Riccardo Barbieri

Luca Mainardi

Karim Keshavjee

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