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Human Activities

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Deep Learning Multi-Class Approach for Human Fall Detection Based on Doppler Signatures.

International journal of environmental research and public health
Falling events are a global health concern with short- and long-term physical and psychological implications, especially for the elderly population. This work aims to monitor human activity in an indoor environment and recognize falling events withou...

WMNN: Wearables-Based Multi-Column Neural Network for Human Activity Recognition.

IEEE journal of biomedical and health informatics
In recent years, human activity recognition (HAR) technologies in e-health have triggered broad interest. In literature, mainstream works focus on the body's spatial information (i.e. postures) which lacks the interpretation of key bioinformatics ass...

Human Activity Recognition for AI-Enabled Healthcare Using Low-Resolution Infrared Sensor Data.

Sensors (Basel, Switzerland)
This paper explores the feasibility of using low-resolution infrared (LRIR) image streams for human activity recognition (HAR) with potential application in e-healthcare. Two datasets based on synchronized multichannel LRIR sensors systems are consid...

STC-NLSTMNet: An Improved Human Activity Recognition Method Using Convolutional Neural Network with NLSTM from WiFi CSI.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) has emerged as a significant area of research due to its numerous possible applications, including ambient assisted living, healthcare, abnormal behaviour detection, etc. Recently, HAR using WiFi channel state informa...

A Multimodal Fusion Approach for Human Activity Recognition.

International journal of neural systems
The problem of human activity recognition (HAR) has been increasingly attracting the efforts of the research community, having several applications. It consists of recognizing human motion and/or behavior within a given image or a video sequence, usi...

An Unobtrusive Human Activity Recognition System Using Low Resolution Thermal Sensors, Machine and Deep Learning.

IEEE transactions on bio-medical engineering
Given the aging population, healthcare systems need to be established to deal with health issues such as injurious falls. Wearable devices can be used to detect falls. However, most wearable devices are obtrusive, and patients generally do not like o...

Data Valuation Algorithm for Inertial Measurement Unit-Based Human Activity Recognition.

Sensors (Basel, Switzerland)
This paper proposes a data valuation algorithm for inertial measurement unit-based human activity recognition (IMU-based HAR) data based on meta reinforcement learning. Unlike previous studies that received feature-level input, the algorithm in this ...

Improving Inertial Sensor-Based Activity Recognition in Neurological Populations.

Sensors (Basel, Switzerland)
Inertial sensor-based human activity recognition (HAR) has a range of healthcare applications as it can indicate the overall health status or functional capabilities of people with impaired mobility. Typically, artificial intelligence models achieve ...

Real-Time Human Activity Recognition with IMU and Encoder Sensors in Wearable Exoskeleton Robot via Deep Learning Networks.

Sensors (Basel, Switzerland)
Wearable exoskeleton robots have become a promising technology for supporting human motions in multiple tasks. Activity recognition in real-time provides useful information to enhance the robot's control assistance for daily tasks. This work implemen...

Fine-Grained Unsupervised Temporal Action Segmentation and Distributed Representation for Skeleton-Based Human Motion Analysis.

IEEE transactions on cybernetics
Understanding the fine-grained temporal structure of human actions and its semantic interpretation is beneficial to many real-world tasks, such as sports movements, rehabilitation exercises, and daily-life activities analysis. Current action segmenta...