We conduct extensive experiments with eight existing domain adaptation algorithms on sensor-based cross domain human activity recognition (HAR) tasks, including ...

Abstract—Domain adaptation can apply knowledge learned from the source domain to the target domain by reducing data distribution discrepancy inter domains.

Sensor-based Human Activity Recognition (HAR) plays an important role in health care. However, great individual differences limit its application scenarios and ...

This process entails aggregating information from neighboring nodes, resembling the traditional convolution applied in convolutional neural networks (CNNs). The ...

An up-to-date & curated list of Awesome IMU-based Human Activity Recognition(Ubiquitous Computing) papers, methods & resources. Please note that most of the ...

Sensor-based human activity recognition is to recognise human daily activities through a collection of ambient and wearable sensors.

A multi-sensor deep learning approach for complex daily living activity recognition · A survey on wearable sensor modality centred human activity recognition in ...

Mar 12, 2024 · Deep Domain Adaptation model for. Time Series data [14] focuses on sensor-based HAR domain ... for sensor-based human activity recognition: ...

Nov 6, 2023 · We empirically validate our proposed approach. Based on results from human activity recognition, electromyography, and synthetic datasets, we ...

Feb 20, 2024 · The experimental results demonstrate the efficacy of our approach in sensor-based HAR tasks, achieving impressive average accuracies of 98.88%, ...