Human activity recognition in artificial intelligence framework: a narrative review
Human activity recognition (HAR) has multifaceted applications due to its worldly usage of
acquisition devices such as smartphones, video cameras, and its ability to capture human …
acquisition devices such as smartphones, video cameras, and its ability to capture human …
Human activity recognition with smartphone and wearable sensors using deep learning techniques: A review
Human Activity Recognition (HAR) is a field that infers human activities from raw time-series
signals acquired through embedded sensors of smartphones and wearable devices. It has …
signals acquired through embedded sensors of smartphones and wearable devices. It has …
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 …
[HTML][HTML] Deep learning based human activity recognition (HAR) using wearable sensor data
S Gupta - International Journal of Information Management Data …, 2021 - Elsevier
Motion or inertial sensors such as gyroscope and accelerometer commonly found in
smartwatches and smartphones can measure characteristics such as acceleration and …
smartwatches and smartphones can measure characteristics such as acceleration and …
A survey of human gait-based artificial intelligence applications
We performed an electronic database search of published works from 2012 to mid-2021 that
focus on human gait studies and apply machine learning techniques. We identified six key …
focus on human gait studies and apply machine learning techniques. We identified six key …
Resnet-se: Channel attention-based deep residual network for complex activity recognition using wrist-worn wearable sensors
Smart mobile devices are being widely used to identify and track human behaviors in simple
and complex daily activities. The evolution of wearable sensing technologies pertaining to …
and complex daily activities. The evolution of wearable sensing technologies pertaining to …
Deep learning approaches for continuous authentication based on activity patterns using mobile sensing
Smartphones as ubiquitous gadgets are rapidly becoming more intelligent and context-
aware as sensing, networking, and processing capabilities advance. These devices provide …
aware as sensing, networking, and processing capabilities advance. These devices provide …
The first step is the hardest: pitfalls of representing and tokenizing temporal data for large language models
Abstract Objectives Large language models (LLMs) have demonstrated remarkable
generalization and across diverse tasks, leading individuals to increasingly use them as …
generalization and across diverse tasks, leading individuals to increasingly use them as …
Deep ConvLSTM with self-attention for human activity decoding using wearable sensors
Decoding human activity accurately from wearable sensors can aid in applications related to
healthcare and context awareness. The present approaches in this domain use recurrent …
healthcare and context awareness. The present approaches in this domain use recurrent …
Deep convolutional neural network with rnns for complex activity recognition using wrist-worn wearable sensor data
Sensor-based human activity recognition (S-HAR) has become an important and high-
impact topic of research within human-centered computing. In the last decade, successful …
impact topic of research within human-centered computing. In the last decade, successful …