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 …
Human activity recognition based on multienvironment sensor data
With the development of artificial intelligence and the broad application of sensors, human
activity recognition (HAR) technologies based on noninvasive environmental sensors have …
activity recognition (HAR) technologies based on noninvasive environmental sensors have …
Artificial intelligence in healthcare: review, ethics, trust challenges & future research directions
The use of artificial intelligence (AI) in medicine is beginning to alter current procedures in
prevention, diagnosis, treatment, amelioration, cure of disease and other physical and …
prevention, diagnosis, treatment, amelioration, cure of disease and other physical and …
Multi-input CNN-GRU based human activity recognition using wearable sensors
Abstract Human Activity Recognition (HAR) has attracted much attention from researchers in
the recent past. The intensification of research into HAR lies in the motive to understand …
the recent past. The intensification of research into HAR lies in the motive to understand …
Human activity recognition with smartphone and wearable sensors using deep learning techniques: A review
E Ramanujam, T Perumal… - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
Human Activity Recognition (HAR) is a field that infers human activities from raw time-series
signals acquired through embedded sensors of smartphones and wearable devices. It has …
signals acquired through embedded sensors of smartphones and wearable devices. It has …
A multibranch CNN-BiLSTM model for human activity recognition using wearable sensor data
Human activity recognition (HAR) has become a significant area of research in human
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …
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 …
Deep CNN-LSTM with self-attention model for human activity recognition using wearable sensor
Human Activity Recognition (HAR) systems are devised for continuously observing human
behavior-primarily in the fields of environmental compatibility, sports injury detection, senior …
behavior-primarily in the fields of environmental compatibility, sports injury detection, senior …