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Human Activities

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Human Activity Prediction Based on Forecasted IMU Activity Signals by Sequence-to-Sequence Deep Neural Networks.

Sensors (Basel, Switzerland)
Human Activity Recognition (HAR) has gained significant attention due to its broad range of applications, such as healthcare, industrial work safety, activity assistance, and driver monitoring. Most prior HAR systems are based on recorded sensor data...

Human activity recognition in an end-of-life consumer electronics disassembly task.

Applied ergonomics
The production of electronic waste, also known as e-waste, has risen with the growing reliance on electronic products. To reduce negative environmental impact and achieve sustainable industrial processes, recovering and reusing products is crucial. A...

Video-Based Human Activity Recognition Using Deep Learning Approaches.

Sensors (Basel, Switzerland)
Due to its capacity to gather vast, high-level data about human activity from wearable or stationary sensors, human activity recognition substantially impacts people's day-to-day lives. Multiple people and things may be seen acting in the video, disp...

Identification and Classification of Human Body Exercises on Smart Textile Bands by Combining Decision Tree and Convolutional Neural Networks.

Sensors (Basel, Switzerland)
In recent years, human activity recognition (HAR) has gained significant interest from researchers in the sports and fitness industries. In this study, the authors have proposed a cascaded method including two classifying stages to classify fitness e...

A Light-Weight Artificial Neural Network for Recognition of Activities of Daily Living.

Sensors (Basel, Switzerland)
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 devices to ensure portable and safe assistance. Current computat...

Human Activity Recognition Using Attention-Mechanism-Based Deep Learning Feature Combination.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) performs a vital function in various fields, including healthcare, rehabilitation, elder care, and monitoring. Researchers are using mobile sensor data (i.e., accelerometer, gyroscope) by adapting various machine lear...

Towards Recognition of Human Actions in Collaborative Tasks with Robots: Extending Action Recognition with Tool Recognition Methods.

Sensors (Basel, Switzerland)
This paper presents a novel method for online tool recognition in manual assembly processes. The goal was to develop and implement a method that can be integrated with existing Human Action Recognition (HAR) methods in collaborative tasks. We examine...

Deep Learning for Human Activity Recognition on 3D Human Skeleton: Survey and Comparative Study.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) is an important research problem in computer vision. This problem is widely applied to building applications in human-machine interactions, monitoring, etc. Especially, HAR based on the human skeleton creates intuitiv...

Counting Activities Using Weakly Labeled Raw Acceleration Data: A Variable-Length Sequence Approach with Deep Learning to Maintain Event Duration Flexibility.

Sensors (Basel, Switzerland)
This paper presents a novel approach for counting hand-performed activities using deep learning and inertial measurement units (IMUs). The particular challenge in this task is finding the correct window size for capturing activities with different du...

Explaining and Visualizing Embeddings of One-Dimensional Convolutional Models in Human Activity Recognition Tasks.

Sensors (Basel, Switzerland)
Human Activity Recognition (HAR) is a complex problem in deep learning, and One-Dimensional Convolutional Neural Networks (1D CNNs) have emerged as a popular approach for addressing it. These networks efficiently learn features from data that can be ...