[HTML][HTML] Deep learning in human activity recognition with wearable sensors: A review on advances
Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …
tracking, wellness monitoring, and human–computer interaction, that measure and improve …
[HTML][HTML] Wearable sensor-based human activity recognition with transformer model
Computing devices that can recognize various human activities or movements can be used
to assist people in healthcare, sports, or human–robot interaction. Readily available data for …
to assist people in healthcare, sports, or human–robot interaction. Readily available data for …
Surface electromyography and artificial intelligence for human activity recognition-A systematic review on methods, emerging trends applications, challenges, and …
Human activity recognition (HAR) has become increasingly popular in recent years due to its
potential to meet the growing needs of various industries. Electromyography (EMG) is …
potential to meet the growing needs of various industries. Electromyography (EMG) is …
Human activity recognition using wearable sensors by heterogeneous convolutional neural networks
Recent researches on sensor based human activity recognition (HAR) are mostly devoted to
designing various network architectures to enhance their feature representation capacity for …
designing various network architectures to enhance their feature representation capacity for …
Densely knowledge-aware network for multivariate time series classification
Multivariate time series classification (MTSC) based on deep learning (DL) has attracted
increasingly more research attention. The performance of a DL-based MTSC algorithm is …
increasingly more research attention. The performance of a DL-based MTSC algorithm is …
Human activity recognition using marine predators algorithm with deep learning
In the era of smart life, tracking human activities and motion can play a significant role in the
advanced modern applications, such as the Internet of things (IoT), Internet of healthcare …
advanced modern applications, such as the Internet of things (IoT), Internet of healthcare …
A human activity recognition method based on lightweight feature extraction combined with pruned and quantized CNN for wearable device
Human Activity Recognition (HAR) is becoming an essential part of human life care. Existing
HAR methods are usually developed using a two-level approach, wherein a first-level …
HAR methods are usually developed using a two-level approach, wherein a first-level …
Human activity recognition in cyber-physical systems using optimized machine learning techniques
Abstract Human Activity Recognition (HAR) is an active research topic as it finds use in
many real-world applications such as health monitoring and biometric user identification …
many real-world applications such as health monitoring and biometric user identification …
[PDF][PDF] Sport-Related Activity Recognition from Wearable Sensors Using Bidirectional GRU Network.
S Mekruksavanich, A Jitpattanakul - Intelligent Automation & Soft …, 2022 - cdn.techscience.cn
Numerous learning-based techniques for effective human activity recognition (HAR) have
recently been developed. Wearable inertial sensors are critical for HAR studies to …
recently been developed. Wearable inertial sensors are critical for HAR studies to …
Deformable convolutional networks for multimodal human activity recognition using wearable sensors
Recent years have witnessed significant success of convolutional neural networks (CNNs)
in human activity recognition (HAR) using wearable sensors. Nevertheless, prior works have …
in human activity recognition (HAR) using wearable sensors. Nevertheless, prior works have …