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Human Activities

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Neural Network Ensembles for Sensor-Based Human Activity Recognition Within Smart Environments.

Sensors (Basel, Switzerland)
In this paper, we focus on data-driven approaches to human activity recognition (HAR). Data-driven approaches rely on good quality data during training, however, a shortage of high quality, large-scale, and accurately annotated HAR datasets exists fo...

Incremental Learning to Personalize Human Activity Recognition Models: The Importance of Human AI Collaboration.

Sensors (Basel, Switzerland)
This study presents incremental learning based methods to personalize human activity recognition models. Initially, a user-independent model is used in the recognition process. When a new user starts to use the human activity recognition application,...

Recognizing Human Daily Activity Using Social Media Sensors and Deep Learning.

International journal of environmental research and public health
The human daily activity category represents individual lifestyle and pattern, such as sports and shopping, which reflect personal habits, lifestyle, and preferences and are of great value for human health and many other application fields. Currently...

BIA: ehavior dentification lgorithm Using Unsupervised Learning Based on Sensor Data for Home Elderly.

IEEE journal of biomedical and health informatics
Behavior identification plays an important role in supporting homecare for the elderly living alone. In literature, plenty of algorithms have been designed to identify behaviors of the elderly by learning features or extracting patterns from sensor d...

A Fast and Robust Deep Convolutional Neural Networks for Complex Human Activity Recognition Using Smartphone.

Sensors (Basel, Switzerland)
As a significant role in healthcare and sports applications, human activity recognition (HAR) techniques are capable of monitoring humans' daily behavior. It has spurred the demand for intelligent sensors and has been giving rise to the explosive gro...

Selective Ensemble Based on Extreme Learning Machine for Sensor-Based Human Activity Recognition.

Sensors (Basel, Switzerland)
Sensor-based human activity recognition (HAR) has attracted interest both in academic and applied fields, and can be utilized in health-related areas, fitness, sports training, etc. With a view to improving the performance of sensor-based HAR and opt...

On-Device Deep Learning Inference for Efficient Activity Data Collection.

Sensors (Basel, Switzerland)
Labeling activity data is a central part of the design and evaluation of human activity recognition systems. The performance of the systems greatly depends on the quantity and "quality" of annotations; therefore, it is inevitable to rely on users and...

A Semisupervised Recurrent Convolutional Attention Model for Human Activity Recognition.

IEEE transactions on neural networks and learning systems
Recent years have witnessed the success of deep learning methods in human activity recognition (HAR). The longstanding shortage of labeled activity data inherently calls for a plethora of semisupervised learning methods, and one of the most challengi...

Providing Aging Adults Social Robots' Companionship in Home-Based Elder Care.

Journal of healthcare engineering
Population aging is increasingly serious. The application of social robots for home-based elder care is an important way to solve this problem. Aging adults' demands for social robots' companionship affect robotic designs. This study aimed to investi...

Efficient Activity Recognition in Smart Homes Using Delayed Fuzzy Temporal Windows on Binary Sensors.

IEEE journal of biomedical and health informatics
Human activity recognition has become an active research field over the past few years due to its wide application in various fields such as health-care, smart home monitoring, and surveillance. Existing approaches for activity recognition in smart h...