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 …
Sensor-based and vision-based human activity recognition: A comprehensive survey
Human activity recognition (HAR) technology that analyzes data acquired from various types
of sensing devices, including vision sensors and embedded sensors, has motivated the …
of sensing devices, including vision sensors and embedded sensors, has motivated the …
Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges
Abstract Body Sensor Networks (BSNs) have emerged as a revolutionary technology in
many application domains in health-care, fitness, smart cities, and many other compelling …
many application domains in health-care, fitness, smart cities, and many other compelling …
Deep-learning-enhanced human activity recognition for Internet of healthcare things
Along with the advancement of several emerging computing paradigms and technologies,
such as cloud computing, mobile computing, artificial intelligence, and big data, Internet of …
such as cloud computing, mobile computing, artificial intelligence, and big data, Internet of …
Enhanced skeleton visualization for view invariant human action recognition
Human action recognition based on skeletons has wide applications in human–computer
interaction and intelligent surveillance. However, view variations and noisy data bring …
interaction and intelligent surveillance. However, view variations and noisy data bring …
Gesture recognition using a bioinspired learning architecture that integrates visual data with somatosensory data from stretchable sensors
Gesture recognition using machine-learning methods is valuable in the development of
advanced cybernetics, robotics and healthcare systems, and typically relies on images or …
advanced cybernetics, robotics and healthcare systems, and typically relies on images or …
A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions
Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …
the computer vision. It has critical application in wide variety of tasks including gaming …
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 …
Elderly fall detection systems: A literature survey
Falling is among the most damaging event elderly people may experience. With the ever-
growing aging population, there is an urgent need for the development of fall detection …
growing aging population, there is an urgent need for the development of fall detection …
Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Activity detection and classification using different sensor modalities have emerged as
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …