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 …
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 …
Human action recognition and prediction: A survey
Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …
have been moving from inferring the present state to predicting the future state. Vision-based …
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 …
A survey on wearable sensor modality centred human activity recognition in health care
Increased life expectancy coupled with declining birth rates is leading to an aging
population structure. Aging-caused changes, such as physical or cognitive decline, could …
population structure. Aging-caused changes, such as physical or cognitive decline, could …
Deep convolutional and lstm recurrent neural networks for multimodal wearable activity recognition
FJ Ordóñez, D Roggen - Sensors, 2016 - mdpi.com
Human activity recognition (HAR) tasks have traditionally been solved using engineered
features obtained by heuristic processes. Current research suggests that deep convolutional …
features obtained by heuristic processes. Current research suggests that deep convolutional …
Biometric user identification based on human activity recognition using wearable sensors: An experiment using deep learning models
S Mekruksavanich, A Jitpattanakul - Electronics, 2021 - mdpi.com
Currently, a significant amount of interest is focused on research in the field of Human
Activity Recognition (HAR) as a result of the wide variety of its practical uses in real-world …
Activity Recognition (HAR) as a result of the wide variety of its practical uses in real-world …