Simple to Complex, Single to Concurrent Sensor based Human Activity Recognition: Perception and Open Challenges
S Ankalaki - IEEE Access, 2024 - ieeexplore.ieee.org
Human activity recognition (HAR) has attracted considerable research attention due to its
essential role in various domains, ranging from healthcare to security, safety, and …
essential role in various domains, ranging from healthcare to security, safety, and …
MarNASNets: Towards CNN model architectures specific to sensor-based human activity recognition
S Kobayashi, T Hasegawa, T Miyoshi… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Deep learning (DL) models for sensor-based human activity recognition (HAR) are still in
their nascent stages compared with image recognition. HAR's inference is generally …
their nascent stages compared with image recognition. HAR's inference is generally …
Image expression of time series data of wearable IMU sensor and fusion classification of gymnastics action
Y Zhao, F Dong, T Sun, Z Ju, L Yang, P Shan… - Expert Systems with …, 2024 - Elsevier
Human activity recognition (HAR) based on multimodal wearable motion sensors is a
valuable technology, and gymnastics action recognition is one of its important application …
valuable technology, and gymnastics action recognition is one of its important application …
Pelican Optimization Algorithm with Deep Learning for Aspect based Sentiment Analysis on Asian Low Resource Languages
Recently, sentiment analysis (SA) has become more popular as it is crucial to moderate and
examine the data from the internet. It contains several applications, such as social media …
examine the data from the internet. It contains several applications, such as social media …
[HTML][HTML] Deep Wavelet Convolutional Neural Networks for Multimodal Human Activity Recognition Using Wearable Inertial Sensors
Recent advances in wearable systems have made inertial sensors, such as accelerometers
and gyroscopes, compact, lightweight, multimodal, low-cost, and highly accurate. Wearable …
and gyroscopes, compact, lightweight, multimodal, low-cost, and highly accurate. Wearable …
Optimizing Edge Computing for Activity Recognition: A Bidirectional LSTM Approach on the PAMAP2 Dataset
A Bollampally, J Kavitha, P Sumanya, D Rajesh… - … , Technology & Applied …, 2024 - etasr.com
This study investigates the application of a Bidirectional Long Short-Term Memory (BiLSTM)
model for Human Activity Recognition (HAR) using the PAMAP2 dataset. The aim was to …
model for Human Activity Recognition (HAR) using the PAMAP2 dataset. The aim was to …
Integrating AI and ChatGPT in Wearable Devices for Enhanced Abnormal Activity Reporting: A Mixture of Experts Approach
K Brutzman, Q Burns, V Cammisa… - 2024 IEEE 4th …, 2024 - ieeexplore.ieee.org
The rapid advancement of Artificial Intelligence (AI) and Generative AI (GAI) has greatly
enhanced the capabilities of wearable devices, extending their use beyond just senior …
enhanced the capabilities of wearable devices, extending their use beyond just senior …
Revolutionizing health monitoring: Integrating transformer models with multi-head attention for precise human activity recognition using wearable devices
A Muniasamy - Technology and Health Care - content.iospress.com
BACKGROUND: A daily activity routine is vital for overall health and well-being, supporting
physical and mental fitness. Consistent physical activity is linked to a multitude of benefits for …
physical and mental fitness. Consistent physical activity is linked to a multitude of benefits for …
Temporal Convolutional Recurrent Neural Network for Elderly Activity Recognition: Manuscript Received: 18 April 2024, Accepted: 10 June 2024, Published: 15 …
JH Ng, YH Pang, SR Sekaran… - … and Applied Physics, 2024 - journals.mmupress.com
Research on smartphone-based human activity recognition (HAR) is prevalent in the field of
healthcare, especially for elderly activity monitoring. Researchers usually propose to use of …
healthcare, especially for elderly activity monitoring. Researchers usually propose to use of …