Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
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 …
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
Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …
tracking, wellness monitoring, and human–computer interaction, that measure and improve …
A survey on deep learning for human activity recognition
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 …
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
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 …
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 …
momentum in recent years, both in research and industrial applications. From the abstract …
Privacy‐preserving federated learning based on multi‐key homomorphic encryption
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 …
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
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 …
people because of its ability to learn extensive high-level information about human activity …
Zero-effort cross-domain gesture recognition with Wi-Fi
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 …
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
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 …
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
Deep learning for sensor-based activity recognition: A survey
Sensor-based activity recognition seeks the profound high-level knowledge about human
activities from multitudes of low-level sensor readings. Conventional pattern recognition …
activities from multitudes of low-level sensor readings. Conventional pattern recognition …