We focus on head-worn devices (e.g., earbuds and smart glasses), a relatively unexplored domain compared to traditional smartwatch- or smartphone-based HAR.

These earbuds consist of two Bluetooth-enabled units, each equipped with one microphone, while the left unit further houses one 6-axis. Inertial Measurement ...

Multi-Frequency Federated Learning for Human Activity Recognition Using Head-Worn Sensors. Dario Fenoglio, Mohan Li, Davide Casnici, Matías Laporte, ...

This paper proposes a federated learning framework integrating spiking neural networks (SNNs) with long short-term memory (LSTM) networks for energy-efficient ...

Sep 19, 2024 · Human activity recognition (HAR) has been applied in a variety of domains such as security and surveillance, human-robot interaction, and entertainment.

Oct 22, 2024 · A Federated learning based system called HARFLS was developed for wearable sensor-based human activity recognition to achieve high recognition ...

Nov 15, 2021 · In this paper, we propose FedDL, a novel federated learning system for HAR that can capture the underlying user relationships and apply them to learn ...

This paper systematically categorizes and summarizes existing work that introduces deep learning methods for wearables-based HAR and provides a comprehensive ...

This paper addresses the topic of Privacy-aware Human Activity Recognition with Smart Glasses and explores a federated learning approach to achieve accurate ...

In this article, we propose a multi-level feature fusion technique for multimodal human activity recognition using multi-head Convolutional Neural Network (CNN)