SCAGOT: Semi-Supervised Disentangling Context and Activity Features Without Target Data for Sensor-Based HAR

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成果类型：

期刊论文

作者：

Duan, Furong;Zhu, Tao*;Chen, Liming;Ning, Huansheng;Liu, Chao;...

通讯作者：

Zhu, Tao;Wan, YP

作者机构：

[Duan, Furong; Wan, YP; Zhu, Tao; Wan, Yaping; Zhu, T] Univ South China, Dept Comp Sci, Hengyang 421001, Peoples R China.

[Duan, Furong] Ulster Univ, Dept Comp Engn & Built Environm, Belfast BT15 1ED, North Ireland.

[Chen, Liming] Dalian Univ Technol, Sch Comp Sci & Technol, Dalian 116024, Peoples R China.

[Ning, Huansheng] Univ Sci & Technol Beijing, Dept Comp & Commun Engn, Beijing 100083, Peoples R China.

[Liu, Chao] Hunan Wanxiang Technol Co, Shaoyang 410125, Peoples R China.

通讯机构：

[Wan, YP ; Zhu, T] U

Univ South China, Dept Comp Sci, Hengyang 421001, Peoples R China.

语种：

英文

关键词：

Data models;Human activity recognition;Sensors;Training;Feature extraction;Context modeling;Computational modeling;Transfer learning;Deep learning;Adaptation models;Context agnostic;deep learning;human activity recognition (HAR);semi-supervised;sensors

期刊：

IEEE Sensors Journal

ISSN：

1530-437X

年：

2025

卷：

期：

页码：

14220-14234

DOI：

10.1109/JSEN.2025.3543928

基金类别：

10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62006110) 10.13039/501100004735-Natural Science Foundation of Hunan Province (Grant Number: 2024JJ7428 and 2023JJ30518)

机构署名：

本校为第一且通讯机构

院系归属：

计算机科学与技术学院

摘要：

Classic deep learning methods for human activity recognition (HAR) from wearable sensors struggle with cross-person and cross-position challenges due to nonidentical data distributions caused by context variations (e.g., user, sensor placement). Existing solutions show promise but usually require extensive labeled data from source and target contexts, which is often unavailable in real-world scenarios. To address these limitations, we introduce semi-supervised context agnostic representation learning without target (SCAGOT), a novel semi-supervised approach that learns context-agnostic activit...

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SCAGOT: Semi-Supervised Disentangling Context and Activity Features Without Target Data for Sensor-Based HAR

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