Human body IoT systems based on the triboelectrification effect: energy harvesting, sensing, interfacing and communication

Q Zhang, C Xin, F Shen, Y Gong, YL Zi… - Energy & …, 2022 - pubs.rsc.org
In recent years, the internet of things (IoT) has been progressing rapidly with the integration
of technologies in various fields. At this stage, triboelectric nanogenerator (TENG) …

Learning for a robot: Deep reinforcement learning, imitation learning, transfer learning

J Hua, L Zeng, G Li, Z Ju - Sensors, 2021 - mdpi.com
Dexterous manipulation of the robot is an important part of realizing intelligence, but
manipulators can only perform simple tasks such as sorting and packing in a structured …

Participatory sensing and digital twin city: Updating virtual city models for enhanced risk-informed decision-making

Y Ham, J Kim - Journal of Management in Engineering, 2020 - ascelibrary.org
The benefits of a digital twin city have been assessed based on real-time data collected from
preinstalled Internet of Things (IoT) sensors (eg, traffic, energy use, air pollution, water …

Soft Sensors and Actuators for Wearable Human–Machine Interfaces

J Park, Y Lee, S Cho, A Choe, J Yeom, YG Ro… - Chemical …, 2024 - ACS Publications
Haptic human–machine interfaces (HHMIs) combine tactile sensation and haptic feedback
to allow humans to interact closely with machines and robots, providing immersive …

A two-stream neural network for pose-based hand gesture recognition

C Li, S Li, Y Gao, X Zhang, W Li - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Pose-based hand gesture recognition has been widely studied in the recent years.
Compared with full body action recognition, hand gesture involves joints that are more …

Exoskeletal devices for hand assistance and rehabilitation: A comprehensive analysis of state-of-the-art technologies

B Noronha, D Accoto - IEEE Transactions on Medical Robotics …, 2021 - ieeexplore.ieee.org
Robots are effective tools for aiding in the restoration of hand function through rehabilitation
programs or by providing in-task assistance. To date, a multitude of exoskeletal devices …

Adaptive spatiotemporal representation learning for skeleton-based human action recognition

J Yu, H Gao, Y Chen, D Zhou, J Liu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
How do humans recognize an action or an interaction in the real world? Due to the diversity
of viewing perspectives, it is a challenge for humans to identify a regular activity when they …

Soft human–machine interfaces: design, sensing and stimulation

W Dong, Y Wang, Y Zhou, Y Bai, Z Ju, J Guo… - International Journal of …, 2018 - Springer
Human–machine interfaces (HMIs) are widely studied to understand the human
biomechanics and/or physiology and the interaction between humans and machines/robots …

A hybrid multimodal fusion framework for sEMG-ACC-Based hand gesture recognition

S Duan, L Wu, B Xue, A Liu, R Qian… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Hand gesture recognition (HGR) based on surface electromyogram (sEMG) and
accelerometer (ACC) signals has attracted increasing attention. The design of an effective …

Deep human motion detection and multi-features analysis for smart healthcare learning tools

F Hajjej, M Javeed, A Ksibi, M Alarfaj… - Ieee …, 2022 - ieeexplore.ieee.org
Unhealthy lifestyle causes several chronic diseases in humans. Many products are
introduced to avoid such illnesses and provide e-learning-based healthcare services …