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 …
HGRBOL2: human gait recognition for biometric application using Bayesian optimization and extreme learning machine
The goal of gait recognition is to identify a person from a distance based on their walking
style using a visual camera. However, the covariates such as a walk with carrying a bag and …
style using a visual camera. However, the covariates such as a walk with carrying a bag and …
A machine-learning approach for stress detection using wearable sensors in free-living environments
Stress is a psychological condition resulting from the body's response to challenging
situations, which can negatively impact physical and mental health if experienced over …
situations, which can negatively impact physical and mental health if experienced over …
A deep learning network with aggregation residual transformation for human activity recognition using inertial and stretch sensors
With the rise of artificial intelligence, sensor-based human activity recognition (S-HAR) is
increasingly being employed in healthcare monitoring for the elderly, fitness tracking, and …
increasingly being employed in healthcare monitoring for the elderly, fitness tracking, and …
A social media event detection framework based on transformers and swarm optimization for public notification of crises and emergency management
Social media allows the spread of vital information regarding crises and emergencies. Thus,
emergency management systems can benefit from social media because they can be used …
emergency management systems can benefit from social media because they can be used …
An optimized deep learning model for human activity recognition using inertial measurement units
Human activity recognition (HAR) has recently gained popularity due to its applications in
healthcare, surveillance, human‐robot interaction, and various other fields. Deep learning …
healthcare, surveillance, human‐robot interaction, and various other fields. Deep learning …
[HTML][HTML] Real-time machine learning for human activities recognition based on wrist-worn wearable devices
Wearable technologies have slowly invaded our lives and can easily help with our day-to-
day tasks. One area where wearable devices can shine is in human activity recognition, as …
day tasks. One area where wearable devices can shine is in human activity recognition, as …
Internet‐of‐Things‐Based Suspicious Activity Recognition Using Multimodalities of Computer Vision for Smart City Security
Automatic human activity recognition is one of the milestones of smart city surveillance
projects. Human activity detection and recognition aim to identify the activities based on the …
projects. Human activity detection and recognition aim to identify the activities based on the …
Deep human motion detection and multi-features analysis for smart healthcare learning tools
Unhealthy lifestyle causes several chronic diseases in humans. Many products are
introduced to avoid such illnesses and provide e-learning-based healthcare services …
introduced to avoid such illnesses and provide e-learning-based healthcare services …
Accelerometer-based human fall detection using sparrow search algorithm and back propagation neural network
T Wang, B Wang, Y Shen, Y Zhao, W Li, K Yao, X Liu… - Measurement, 2022 - Elsevier
To reduce the injury caused by the fall and solve the problems of low efficiency and low
accuracy of traditional fall prediction methods, an optimized BP neural network fall prediction …
accuracy of traditional fall prediction methods, an optimized BP neural network fall prediction …