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Human Activities

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A Human Activity Recognition System Using Skeleton Data from RGBD Sensors.

Computational intelligence and neuroscience
The aim of Active and Assisted Living is to develop tools to promote the ageing in place of elderly people, and human activity recognition algorithms can help to monitor aged people in home environments. Different types of sensors can be used to addr...

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sens...

Close Human Interaction Recognition Using Patch-Aware Models.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
This paper addresses the problem of recognizing human interactions with close physical contact from videos. Due to ambiguities in feature-to-person assignments and frequent occlusions in close interactions, it is difficult to accurately extract the i...

Automated Cognitive Health Assessment From Smart Home-Based Behavior Data.

IEEE journal of biomedical and health informatics
Smart home technologies offer potential benefits for assisting clinicians by automating health monitoring and well-being assessment. In this paper, we examine the actual benefits of smart home-based analysis by monitoring daily behavior in the home a...

Analyzing Activity Behavior and Movement in a Naturalistic Environment Using Smart Home Techniques.

IEEE journal of biomedical and health informatics
One of the many services that intelligent systems can provide is the ability to analyze the impact of different medical conditions on daily behavior. In this study, we use smart home and wearable sensors to collect data, while ( n = 84) older adults ...

Graph Embedded Extreme Learning Machine.

IEEE transactions on cybernetics
In this paper, we propose a novel extension of the extreme learning machine (ELM) algorithm for single-hidden layer feedforward neural network training that is able to incorporate subspace learning (SL) criteria on the optimization process followed f...

Pervasive Sound Sensing: A Weakly Supervised Training Approach.

IEEE transactions on cybernetics
Modern smartphones present an ideal device for pervasive sensing of human behavior. Microphones have the potential to reveal key information about a person's behavior. However, they have been utilized to a significantly lesser extent than other smart...

Multipe/single-view human action recognition via part-induced multitask structural learning.

IEEE transactions on cybernetics
This paper proposes a unified framework for multiple/single-view human action recognition. First, we propose the hierarchical partwise bag-of-words representation which encodes both local and global visual saliency based on the body structure cue. Th...

Revolutionizing health monitoring: Integrating transformer models with multi-head attention for precise human activity recognition using wearable devices.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: A daily activity routine is vital for overall health and well-being, supporting physical and mental fitness. Consistent physical activity is linked to a multitude of benefits for the body, mind, and emotions, playing a key role in raising...

Enhanced In-Home Human Activity Recognition Using Multimodal Sensing and Spatiotemporal Machine Learning Architecture.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this research, we present an enhanced human activity recognition (HAR) framework using advanced machine learning models incorporating temporal dynamics, leveraging multimodal sensor data. Data from wearable wristbands and real-time location system...