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 …
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 …
[HTML][HTML] Physical human activity recognition using wearable sensors
This paper presents a review of different classification techniques used to recognize human
activities from wearable inertial sensor data. Three inertial sensor units were used in this …
activities from wearable inertial sensor data. Three inertial sensor units were used in this …
A tutorial on human activity recognition using body-worn inertial sensors
The last 20 years have seen ever-increasing research activity in the field of human activity
recognition. With activity recognition having considerably matured, so has the number of …
recognition. With activity recognition having considerably matured, so has the number of …
A survey on unsupervised learning for wearable sensor-based activity recognition
Abstract Human Activity Recognition (HAR) is an essential task in various applications such
as pervasive healthcare, smart environment, and security and surveillance. The need to …
as pervasive healthcare, smart environment, and security and surveillance. The need to …
Enabling technologies for operator 4.0: A survey
The fast development of smart sensors and wearable devices has provided the opportunity
to develop intelligent operator workspaces. The resultant Human-Cyber-Physical Systems …
to develop intelligent operator workspaces. The resultant Human-Cyber-Physical Systems …
From action to activity: sensor-based activity recognition
As compared to actions, activities are much more complex, but semantically they are more
representative of a human׳ s real life. Techniques for action recognition from sensor …
representative of a human׳ s real life. Techniques for action recognition from sensor …
Deep learning-based gait recognition using smartphones in the wild
Compared to other biometrics, gait is difficult to conceal and has the advantage of being
unobtrusive. Inertial sensors, such as accelerometers and gyroscopes, are often used to …
unobtrusive. Inertial sensors, such as accelerometers and gyroscopes, are often used to …
Robust human activity recognition from depth video using spatiotemporal multi-fused features
The recently developed depth imaging technologies have provided new directions for
human activity recognition (HAR) without attaching optical markers or any other motion …
human activity recognition (HAR) without attaching optical markers or any other motion …
Window size impact in human activity recognition
Signal segmentation is a crucial stage in the activity recognition process; however, this has
been rarely and vaguely characterized so far. Windowing approaches are normally used for …
been rarely and vaguely characterized so far. Windowing approaches are normally used for …