Biopotential signal monitoring systems in rehabilitation: A review
Monitoring physical activity in medical and clinical rehabilitation, in sports environments or
as a wellness indicator is helpful to measure, analyze and evaluate physiological …
as a wellness indicator is helpful to measure, analyze and evaluate physiological …
[HTML][HTML] A survey on modularity and distributivity in series-parallel hybrid robots
Parallel mechanisms are used increasingly often as modular subsystem units in various
robots and man-machine interfaces for their superior stiffness, payload-to-weight ratio and …
robots and man-machine interfaces for their superior stiffness, payload-to-weight ratio and …
[HTML][HTML] Intrinsic interactive reinforcement learning–Using error-related potentials for real world human-robot interaction
Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in
dynamic environments based on feedback. Explicit human feedback during robot RL is …
dynamic environments based on feedback. Explicit human feedback during robot RL is …
Real-time intended knee joint motion prediction by deep-recurrent neural networks
Y Huang, Z He, Y Liu, R Yang, X Zhang… - IEEE Sensors …, 2019 - ieeexplore.ieee.org
Human-assisting intelligent systems demand certain methods to precisely predict motorized
limb joint angles. This paper presents the application of deep-recurrent neural networks …
limb joint angles. This paper presents the application of deep-recurrent neural networks …
An embedded implementation based on adaptive filter bank for brain–computer interface systems
Background Brain–computer interface (BCI) is a new communication pathway for users with
neurological deficiencies. The implementation of a BCI system requires complex …
neurological deficiencies. The implementation of a BCI system requires complex …
[HTML][HTML] Modular Design and Decentralized Control of the Recupera Exoskeleton for Stroke Rehabilitation
Robot-assisted therapy has become increasingly popular and useful in post-stroke
neurorehabilitation. This paper presents an overview of the design and control of the dual …
neurorehabilitation. This paper presents an overview of the design and control of the dual …
Embedded brain computer interface: state-of-the-art in research
There is a wide area of application that uses cerebral activity to restore capabilities for
people with severe motor disabilities, and actually the number of such systems keeps …
people with severe motor disabilities, and actually the number of such systems keeps …
A data-driven machine learning approach for brain-computer interfaces targeting lower limb neuroprosthetics
Prosthetic devices that replace a lost limb have become increasingly performant in recent
years. Recent advances in both software and hardware allow for the decoding of …
years. Recent advances in both software and hardware allow for the decoding of …
A brain–robot interaction system by fusing human and machine intelligence
This paper presents a new brain–robot interaction system by fusing human and machine
intelligence to improve the real-time control performance. This system consists of a hybrid …
intelligence to improve the real-time control performance. This system consists of a hybrid …
Evaluating convolutional neural networks as a method of EEG–EMG fusion
Wearable robotic exoskeletons have emerged as an exciting new treatment tool for
disorders affecting mobility; however, the human–machine interface, used by the patient for …
disorders affecting mobility; however, the human–machine interface, used by the patient for …