Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges

S Qiu, H Zhao, N Jiang, Z Wang, L Liu, Y An, H Zhao… - Information …, 2022 - Elsevier
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …

Deep learning in human activity recognition with wearable sensors: A review on advances

S Zhang, Y Li, S Zhang, F Shahabi, S Xia, Y Deng… - Sensors, 2022 - mdpi.com
Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …

A survey on deep learning for human activity recognition

F Gu, MH Chung, M Chignell, S Valaee… - ACM Computing …, 2021 - dl.acm.org
Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

Deep learning for sensor-based human activity recognition: Overview, challenges, and opportunities

K Chen, D Zhang, L Yao, B Guo, Z Yu… - ACM Computing Surveys …, 2021 - dl.acm.org
The vast proliferation of sensor devices and Internet of Things enables the applications of
sensor-based activity recognition. However, there exist substantial challenges that could …

Lstm networks using smartphone data for sensor-based human activity recognition in smart homes

S Mekruksavanich, A Jitpattanakul - Sensors, 2021 - mdpi.com
Human Activity Recognition (HAR) employing inertial motion data has gained considerable
momentum in recent years, both in research and industrial applications. From the abstract …

Privacy‐preserving federated learning based on multi‐key homomorphic encryption

J Ma, SA Naas, S Sigg, X Lyu - International Journal of …, 2022 - Wiley Online Library
With the advance of machine learning and the Internet of Things (IoT), security and privacy
have become critical concerns in mobile services and networks. Transferring data to a …

Human activity recognition using tools of convolutional neural networks: A state of the art review, data sets, challenges, and future prospects

MM Islam, S Nooruddin, F Karray… - Computers in biology and …, 2022 - Elsevier
Abstract Human Activity Recognition (HAR) plays a significant role in the everyday life of
people because of its ability to learn extensive high-level information about human activity …

Zero-effort cross-domain gesture recognition with Wi-Fi

Y Zheng, Y Zhang, K Qian, G Zhang, Y Liu… - Proceedings of the 17th …, 2019 - dl.acm.org
Wi-Fi based sensing systems, although sound as being deployed almost everywhere there
is Wi-Fi, are still practically difficult to be used without explicit adaptation efforts to new data …

Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges

HF Nweke, YW Teh, MA Al-Garadi, UR Alo - Expert Systems with …, 2018 - Elsevier
Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …

Deep learning for sensor-based activity recognition: A survey

J Wang, Y Chen, S Hao, X Peng, L Hu - Pattern recognition letters, 2019 - Elsevier
Sensor-based activity recognition seeks the profound high-level knowledge about human
activities from multitudes of low-level sensor readings. Conventional pattern recognition …