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Human Activities

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Radar Signal Processing and Its Impact on Deep Learning-Driven Human Activity Recognition.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) using radar technology is becoming increasingly valuable for applications in areas such as smart security systems, healthcare monitoring, and interactive computing. This study investigates the integration of convoluti...

A comparative analysis of LSTM models aided with attention and squeeze and excitation blocks for activity recognition.

Scientific reports
Human Activity Recognition plays a vital role in various fields, such as healthcare and smart environments. Traditional HAR methods rely on sensor or video data, but sensor-based systems have gained popularity due to their non-intrusive nature. Curre...

In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models Against Variability.

Sensors (Basel, Switzerland)
Deep learning (DL)-based Human Activity Recognition (HAR) using wearable inertial measurement unit (IMU) sensors can revolutionize continuous health monitoring and early disease prediction. However, most DL HAR models are untested in their robustness...

Detection of human activities using multi-layer convolutional neural network.

Scientific reports
Human Activity Recognition (HAR) plays a critical role in fields such as healthcare, sports, and human-computer interaction. However, achieving high accuracy and robustness remains a challenge, particularly when dealing with noisy sensor data from ac...

Data Reconstruction Methods in Multi-Feature Fusion CNN Model for Enhanced Human Activity Recognition.

Sensors (Basel, Switzerland)
BACKGROUND: Human activity recognition (HAR) plays a pivotal role in digital healthcare, enabling applications such as exercise monitoring and elderly care. However, traditional HAR methods relying on accelerometer data often require complex preproce...

Decision Fusion-Based Deep Learning for Channel State Information Channel-Aware Human Action Recognition.

Sensors (Basel, Switzerland)
WiFi channel state information (CSI) has emerged as a promising modality for human action recognition due to its non-invasive nature and robustness in diverse environments. However, most existing methods process CSI channels collectively, potentially...

Explaining Human Activity Recognition with SHAP: Validating insights with perturbation and quantitative measures.

Computers in biology and medicine
In Human Activity Recognition (HAR), understanding the intricacy of body movements within high-risk applications is essential. This study uses SHapley Additive exPlanations (SHAP) to explain the decision-making process of Graph Convolution Networks (...

Federated Learning for IoMT-Enhanced Human Activity Recognition with Hybrid LSTM-GRU Networks.

Sensors (Basel, Switzerland)
The proliferation of wearable sensors and mobile devices has fueled advancements in human activity recognition (HAR), with growing importance placed on both accuracy and privacy preservation. In this paper, the author proposes a federated learning fr...

CLEAR: Multimodal Human Activity Recognition via Contrastive Learning Based Feature Extraction Refinement.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) has become a crucial research area for many applications, such as Healthcare, surveillance, etc. With the development of artificial intelligence (AI) and Internet of Things (IoT), sensor-based HAR has gained increasin...

Identifying the combined impact of human activities and natural factors on China's avian species richness using interpretable machine learning methods.

Journal of environmental management
With human activities-derived escalating climate change and rapid urbanization, avian species face significant survival challenges. Understanding the impact of human activities and environmental drivers on avian species richness is critical for effec...