activity
20192025
most citedA Methodology for Obtaining Objective Measurements of Population Obesogenic Behaviors in Relation to the Environment

13 citations · 28 across the 5 of their papers we have counts for

collaborators

9 papers

eess.SP2025

Estimation of Food Intake Quantity Using Inertial Signals from Smartwatches

Ioannis Levi, Konstantinos Kyritsis, Vasileios Papapanagiotou +2

Accurate monitoring of eating behavior is crucial for managing obesity and eating disorders such as bulimia nervosa. At the same time, existing methods rely on multiple and/or spec…

cs.CY2025

A system for objectively measuring behavior and the environment to support large-scale studies on childhood obesity

Vasileios Papapanagiotou, Ioannis Sarafis, Leonidas Alagialoglou +3

Advances in IoT technologies combined with new algorithms have enabled the collection and processing of high-rate multi-source data streams that quantify human behavior in a fine-g…

eess.SP2024

Prediabetes detection in unconstrained conditions using wearable sensors

Dimitra Tatli, Vasileios Papapanagiotou, Aris Liakos +2

Prediabetes is a common health condition that often goes undetected until it progresses to type 2 diabetes. Early identification of prediabetes is essential for timely intervention…

eess.SP20249 cited

Transportation mode recognition based on low-rate acceleration and location signals with an attention-based multiple-instance learning network

Christos Siargkas, Vasileios Papapanagiotou, Anastasios Delopoulos

Transportation mode recognition (TMR) is a critical component of human activity recognition (HAR) that focuses on understanding and identifying how people move within transportatio…

cs.LG2023

Which Augmentation Should I Use? An Empirical Investigation of Augmentations for Self-Supervised Phonocardiogram Representation Learning

Aristotelis Ballas, Vasileios Papapanagiotou, Christos Diou

Despite recent advancements in deep learning, its application in real-world medical settings, such as phonocardiogram (PCG) classification, remains limited. A significant barrier i…

eess.AS2021

Self-Supervised Feature Learning of 1D Convolutional Neural Networks with Contrastive Loss for Eating Detection Using an In-Ear Microphone

Vasileios Papapanagiotou, Christos Diou, Anastasios Delopoulos

The importance of automated and objective monitoring of dietary behavior is becoming increasingly accepted. The advancements in sensor technology along with recent achievements in…