Transformers in healthcare: A survey

S Nerella, S Bandyopadhyay, J Zhang… - arXiv preprint arXiv …, 2023 - arxiv.org
With Artificial Intelligence (AI) increasingly permeating various aspects of society, including
healthcare, the adoption of the Transformers neural network architecture is rapidly changing …

A narrative review on wearable inertial sensors for human motion tracking in industrial scenarios

E Digo, S Pastorelli, L Gastaldi - Robotics, 2022 - mdpi.com
Industry 4.0 has promoted the concept of automation, supporting workers with robots while
maintaining their central role in the factory. To guarantee the safety of operators and improve …

Temporal-channel convolution with self-attention network for human activity recognition using wearable sensors

E Essa, IR Abdelmaksoud - Knowledge-Based Systems, 2023 - Elsevier
Human activity recognition (HAR) is an essential task in many applications such as health
monitoring, rehabilitation, and sports training. Sensor-based HAR has received increasing …

Hamlet: A hierarchical multimodal attention-based human activity recognition algorithm

MM Islam, T Iqbal - 2020 IEEE/RSJ International Conference on …, 2020 - ieeexplore.ieee.org
To fluently collaborate with people, robots need the ability to recognize human activities
accurately. Although modern robots are equipped with various sensors, robust human …

Multi-gat: A graphical attention-based hierarchical multimodal representation learning approach for human activity recognition

MM Islam, T Iqbal - IEEE Robotics and Automation Letters, 2021 - ieeexplore.ieee.org
Recognizing human activities is one of the crucial capabilities that a robot needs to have to
be useful around people. Although modern robots are equipped with various types of …

Human movement and ergonomics: An industry-oriented dataset for collaborative robotics

P Maurice, A Malaisé, C Amiot, N Paris… - … Journal of Robotics …, 2019 - journals.sagepub.com
Improving work conditions in industry is a major challenge that can be addressed with new
emerging technologies such as collaborative robots. Machine learning techniques can …

Mumu: Cooperative multitask learning-based guided multimodal fusion

MM Islam, T Iqbal - Proceedings of the AAAI conference on artificial …, 2022 - ojs.aaai.org
Multimodal sensors (visual, non-visual, and wearable) can provide complementary
information to develop robust perception systems for recognizing activities accurately …

Stmt: A spatial-temporal mesh transformer for mocap-based action recognition

X Zhu, PY Huang, J Liang… - Proceedings of the …, 2023 - openaccess.thecvf.com
We study the problem of human action recognition using motion capture (MoCap)
sequences. Unlike existing techniques that take multiple manual steps to derive …

A survey of immersive technologies and applications for industrial product development

R Liu, C Peng, Y Zhang, H Husarek, Q Yu - Computers & Graphics, 2021 - Elsevier
With the expanded digitalization of manufacturing and product development process,
research into the use of immersive technology in smart manufacturing has increased. The …

Data quality and reliability assessment of wearable EMG and IMU sensor for construction activity recognition

SS Bangaru, C Wang, F Aghazadeh - Sensors, 2020 - mdpi.com
The workforce shortage is one of the significant problems in the construction industry. To
overcome the challenges due to workforce shortage, various researchers have proposed …