Sensors and functionalities of non-invasive wrist-wearable devices: A review
Wearable devices have recently received considerable interest due to their great promise for
a plethora of applications. Increased research efforts are oriented towards a non-invasive …
a plethora of applications. Increased research efforts are oriented towards a non-invasive …
3D Human Action Recognition: Through the eyes of researchers
Abstract Human Action Recognition (HAR) has remained one of the most challenging tasks
in computer vision. With the surge in data-driven methodologies, the depth modality has …
in computer vision. With the surge in data-driven methodologies, the depth modality has …
A survey on human-aware robot navigation
Intelligent systems are increasingly part of our everyday lives and have been integrated
seamlessly to the point where it is difficult to imagine a world without them. Physical …
seamlessly to the point where it is difficult to imagine a world without them. Physical …
Fuzzy integral-based CNN classifier fusion for 3D skeleton action recognition
Action recognition based on skeleton key joints has gained popularity due to its cost
effectiveness and low complexity. Existing Convolutional Neural Network (CNN) based …
effectiveness and low complexity. Existing Convolutional Neural Network (CNN) based …
A study of accelerometer and gyroscope measurements in physical life-log activities detection systems
Nowadays, wearable technology can enhance physical human life-log routines by shifting
goals from merely counting steps to tackling significant healthcare challenges. Such …
goals from merely counting steps to tackling significant healthcare challenges. Such …
SensCapsNet: deep neural network for non-obtrusive sensing based human activity recognition
C Pham, S Nguyen-Thai, H Tran-Quang, S Tran… - IEEE …, 2020 - ieeexplore.ieee.org
Recently, the recent advancement of deep learning with the capacity to perform automatic
high-level feature extraction has achieved promising performance for sensor-based human …
high-level feature extraction has achieved promising performance for sensor-based human …
Physical workload tracking using human activity recognition with wearable devices
J Manjarres, P Narvaez, K Gasser, W Percybrooks… - Sensors, 2019 - mdpi.com
In this work, authors address workload computation combining human activity recognition
and heart rate measurements to establish a scalable framework for health at work and …
and heart rate measurements to establish a scalable framework for health at work and …
Personalizing activity recognition models through quantifying different types of uncertainty using wearable sensors
Recognizing activities of daily living (ADL) provides vital contextual information that
enhances the effectiveness of various mobile health and wellness applications …
enhances the effectiveness of various mobile health and wellness applications …
Stochastic recognition of human physical activities via augmented feature descriptors and random forest model
Human physical activity recognition from inertial sensors is shown to be a successful
approach for monitoring elderly individuals and children in indoor and outdoor …
approach for monitoring elderly individuals and children in indoor and outdoor …
Hybrid Deep Learning Approaches for sEMG Signal‐Based Lower Limb Activity Recognition
Lower limb activity recognition utilizing body sensor data has attracted researchers due to its
practical applications, such as neuromuscular disease detection and kinesiological …
practical applications, such as neuromuscular disease detection and kinesiological …