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A robust multimodal detection system: physical exercise monitoring in long-term care environments
Introduction Falls are a major cause of accidents that can lead to serious injuries, especially
among geriatric populations worldwide. Ensuring constant supervision in hospitals or smart …
among geriatric populations worldwide. Ensuring constant supervision in hospitals or smart …
Depth sensors-based action recognition using a modified K-ary entropy classifier
Surveillance system is acquiring an ample interest in the field of computer vision. Existing
surveillance system usually relies on optical or wearable sensors for indoor and outdoor …
surveillance system usually relies on optical or wearable sensors for indoor and outdoor …
Machine learning and deep learning models for human activity recognition in security and surveillance: a review
Human activity recognition (HAR) has received the significant attention in the field of security
and surveillance due to its high potential for real-time monitoring, identifying the abnormal …
and surveillance due to its high potential for real-time monitoring, identifying the abnormal …
Context aware crowd tracking and anomaly detection via deep learning and social force model
The world's expanding populace, the variety of human social factors, and the densely
populated environment make humans feel uncertain. Individuals need a safety officer who …
populated environment make humans feel uncertain. Individuals need a safety officer who …
Multi-sensor-based action monitoring and recognition via hybrid descriptors and logistic regression
In the fields of body-worn sensors and computer vision, current research is being done to
track and detect falls and activities of daily living using the automatic recognition of human …
track and detect falls and activities of daily living using the automatic recognition of human …
Deep ontology-based human locomotor activity recognition system via multisensory devices
Recognition of human locomotor activities is crucial for monitoring the motion patterns.
Current studies for human locomotor activities recognition focused on detecting basic motion …
Current studies for human locomotor activities recognition focused on detecting basic motion …
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 …
Deep activity recognition based on patterns discovery for healthcare monitoring
Healthcare monitoring for humans is important due to several factors including life quality
and early detection of health-related problems. Human activity patterns recognition is the …
and early detection of health-related problems. Human activity patterns recognition is the …
A light-weight artificial neural network for recognition of activities of daily living
Human activity recognition (HAR) is essential for the development of robots to assist humans
in daily activities. HAR is required to be accurate, fast and suitable for low-cost wearable …
in daily activities. HAR is required to be accurate, fast and suitable for low-cost wearable …
Quantitative analysis of mother wavelet function selection for wearable sensors-based human activity recognition
Recent advancements in the Internet of Things (IoT) wearable devices such as wearable
inertial sensors have increased the demand for precise human activity recognition (HAR) …
inertial sensors have increased the demand for precise human activity recognition (HAR) …