Convolutional neural network-based human activity recognition for edge fitness and context-aware health monitoring devices
The vital signs can vary significantly depending on the daily physical activities, which may
not be due to defects of the organs. Under remote human health-monitoring applications, for …
not be due to defects of the organs. Under remote human health-monitoring applications, for …
Deep transfer learning with graph neural network for sensor-based human activity recognition
T Liao, J Zhao, Y Liu, K Ivanov… - … on Bioinformatics and …, 2022 - ieeexplore.ieee.org
The sensor-based human activity recognition (HAR) in mobile application scenarios is often
confronted with variation in sensing modalities and deficiencies in annotated samples. To …
confronted with variation in sensing modalities and deficiencies in annotated samples. To …
State-of-the-art survey on activity recognition and classification using smartphones and wearable sensors
SK Chaurasia, SRN Reddy - Multimedia Tools and Applications, 2022 - Springer
Abstract Activity Recognition and Classification (ARC) have enabled growth of many
automated applications like recommender services, old age assistance, health monitoring …
automated applications like recommender services, old age assistance, health monitoring …
Context-Aware Human Activity Recognition (CA-HAR) Using Smartphone Built-In Sensors
Context-awareness has the potential to enhance human activity recognition (HAR) by
identifying daily activities such as driving, studying, cooking, or showering. Most existing …
identifying daily activities such as driving, studying, cooking, or showering. Most existing …
Cross-location activity recognition using adversarial learning
Human activity recognition (HAR) is an emerging field of study to recognize human
movement and actions from recorded data. It plays a significant role in human-computer …
movement and actions from recorded data. It plays a significant role in human-computer …
Overcoming Data Scarcity in IMU-based Human Motion Analysis
Y Hao - 2022 - macsphere.mcmaster.ca
Deep learning techniques enable the automatic analysis and interpretation of human motion
from wearable sensor. However, despite extensive research efforts, the absence of vast …
from wearable sensor. However, despite extensive research efforts, the absence of vast …
Performance Comparison of Motion-Related Sensor Technology and Acoustic Sensor Technology in the Field of Human Health Monitoring
S Staab, L Bröning, J Luderschmidt… - Proceedings of the 2022 …, 2022 - dl.acm.org
Smartwatches are reaching more people every year and have long since found their way
into research. When monitoring the health of people with neurological conditions, it is crucial …
into research. When monitoring the health of people with neurological conditions, it is crucial …
Inertial sensor-based movement classification with dimension reduction based on feature aggregation
In this paper, a novel feature aggregation method is proposed for dimension reduction in
inertial sensor-based pattern recognition applications. The method is utilized in a movement …
inertial sensor-based pattern recognition applications. The method is utilized in a movement …
What augmentations are sensitive to hyper-parameters and why?
We apply augmentations to our dataset to enhance the quality of our predictions and make
our final models more resilient to noisy data and domain drifts. Yet the question remains …
our final models more resilient to noisy data and domain drifts. Yet the question remains …
Use the Direction of the Combined Vector of Accelerometers to Classify Daily Activities
Z Wang, L Mo - … Conference on Sensing, Measurement & Data …, 2022 - ieeexplore.ieee.org
Human Activity Recognition (HAR) is important for human physical fitness. Wearable sensor-
based HAR uses accelerometers (A), gyroscopes (G), and other sensors to collect human …
based HAR uses accelerometers (A), gyroscopes (G), and other sensors to collect human …