Deep learning for time series forecasting: a survey
Time series forecasting has become a very intensive field of research, which is even
increasing in recent years. Deep neural networks have proved to be powerful and are …
increasing in recent years. Deep neural networks have proved to be powerful and are …
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 …
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 …
Human activity recognition using inertial, physiological and environmental sensors: A comprehensive survey
In the last decade, Human Activity Recognition (HAR) has become a vibrant research area,
especially due to the spread of electronic devices such as smartphones, smartwatches and …
especially due to the spread of electronic devices such as smartphones, smartwatches and …
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 …
Human activity recognition using inertial sensors in a smartphone: An overview
The ubiquity of smartphones and the growth of computing resources, such as connectivity,
processing, portability, and power of sensing, have greatly changed people's lives. Today …
processing, portability, and power of sensing, have greatly changed people's lives. Today …
Machine and deep learning for sport-specific movement recognition: A systematic review of model development and performance
Objective assessment of an athlete's performance is of importance in elite sports to facilitate
detailed analysis. The implementation of automated detection and recognition of sport …
detailed analysis. The implementation of automated detection and recognition of sport …
Gait analysis in neurological populations: Progression in the use of wearables
Gait assessment is an essential tool for clinical applications not only to diagnose different
neurological conditions but also to monitor disease progression as it contributes to the …
neurological conditions but also to monitor disease progression as it contributes to the …
Deep learning for monitoring of human gait: A review
AS Alharthi, SU Yunas, KB Ozanyan - IEEE Sensors Journal, 2019 - ieeexplore.ieee.org
The essential human gait parameters are briefly reviewed, followed by a detailed review of
the state of the art in deep learning for the human gait analysis. The modalities for capturing …
the state of the art in deep learning for the human gait analysis. The modalities for capturing …
Deep convolutional neural network with rnns for complex activity recognition using wrist-worn wearable sensor data
S Mekruksavanich, A Jitpattanakul - Electronics, 2021 - mdpi.com
Sensor-based human activity recognition (S-HAR) has become an important and high-
impact topic of research within human-centered computing. In the last decade, successful …
impact topic of research within human-centered computing. In the last decade, successful …