Remote patient monitoring using artificial intelligence: Current state, applications, and challenges
The adoption of artificial intelligence (AI) in healthcare is growing rapidly. Remote patient
monitoring (RPM) is one of the common healthcare applications that assist doctors to …
monitoring (RPM) is one of the common healthcare applications that assist doctors to …
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 …
Integrated sensing and communications: Toward dual-functional wireless networks for 6G and beyond
As the standardization of 5G solidifies, researchers are speculating what 6G will be. The
integration of sensing functionality is emerging as a key feature of the 6G Radio Access …
integration of sensing functionality is emerging as a key feature of the 6G Radio Access …
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 using tools of convolutional neural networks: A state of the art review, data sets, challenges, and future prospects
Abstract Human Activity Recognition (HAR) plays a significant role in the everyday life of
people because of its ability to learn extensive high-level information about human activity …
people because of its ability to learn extensive high-level information about human activity …
Deep gait recognition: A survey
Gait recognition is an appealing biometric modality which aims to identify individuals based
on the way they walk. Deep learning has reshaped the research landscape in this area …
on the way they walk. Deep learning has reshaped the research landscape in this area …
[HTML][HTML] Deep learning based human activity recognition (HAR) using wearable sensor data
S Gupta - International Journal of Information Management Data …, 2021 - Elsevier
Motion or inertial sensors such as gyroscope and accelerometer commonly found in
smartwatches and smartphones can measure characteristics such as acceleration and …
smartwatches and smartphones can measure characteristics such as acceleration and …
Deep learning for time series classification and extrinsic regression: A current survey
Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …
learning tasks. Deep learning has revolutionized natural language processing and computer …
A survey of human activity recognition in smart homes based on IoT sensors algorithms: Taxonomies, challenges, and opportunities with deep learning
Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of
sensors have encouraged the development of smart environments, such as smart homes …
sensors have encouraged the development of smart environments, such as smart homes …
Human activity recognition: Review, taxonomy and open challenges
Nowadays, Human Activity Recognition (HAR) is being widely used in a variety of domains,
and vision and sensor-based data enable cutting-edge technologies to detect, recognize …
and vision and sensor-based data enable cutting-edge technologies to detect, recognize …