A systematic review of technological advancements in signal sensing, actuation, control and training methods in robotic exoskeletons for rehabilitation
Purpose The purpose of this review paper is to address the substantial challenges of the
outdated exoskeletons used for rehabilitation and further study the current advancements in …
outdated exoskeletons used for rehabilitation and further study the current advancements in …
Human lower limb motion intention recognition for exoskeletons: A review
Human motion intention (HMI) has increasingly gained concerns in lower limb exoskeletons
(LLEs). HMI recognition (HMIR) is the precondition for realizing active compliance control in …
(LLEs). HMI recognition (HMIR) is the precondition for realizing active compliance control in …
All-weather, natural silent speech recognition via machine-learning-assisted tattoo-like electronics
The internal availability of silent speech serves as a translator for people with aphasia and
keeps human–machine/human interactions working under various disturbances. This paper …
keeps human–machine/human interactions working under various disturbances. This paper …
Multimodal fusion approach based on EEG and EMG signals for lower limb movement recognition
In this study, the fusion of cortical and muscular activities based on discriminant correlation
analysis DCA) is developed to recognize bilateral lower limb movements. Electromyography …
analysis DCA) is developed to recognize bilateral lower limb movements. Electromyography …
A hand-modeled feature extraction-based learning network to detect grasps using sEMG signal
Recently, deep models have been very popular because they achieve excellent
performance with many classification problems. Deep networks have high computational …
performance with many classification problems. Deep networks have high computational …
A sequential learning model with GNN for EEG-EMG-based stroke rehabilitation BCI
H Li, H Ji, J Yu, J Li, L Jin, L Liu, Z Bai… - Frontiers in Neuroscience, 2023 - frontiersin.org
Introduction Brain-computer interfaces (BCIs) have the potential in providing neurofeedback
for stroke patients to improve motor rehabilitation. However, current BCIs often only detect …
for stroke patients to improve motor rehabilitation. However, current BCIs often only detect …
Hb vsEMG signal classification with time domain and Frequency domain features using LDA and ANN classifier
Y Narayan - Materials Today: Proceedings, 2021 - Elsevier
The surface electromyography (sEMG) signals have been widely employed for the
development of the human–machine interface and have enormous bio-engineering …
development of the human–machine interface and have enormous bio-engineering …
Bio-signal based motion control system using deep learning models: A deep learning approach for motion classification using EEG and EMG signal fusion
H Aly, SM Youssef - Journal of Ambient Intelligence and Humanized …, 2023 - Springer
Bioelectrical time signals are the signals that can be measured through the electrical
potential difference across an organ over the time. Electroencephalography (EEG) signals …
potential difference across an organ over the time. Electroencephalography (EEG) signals …
Electroencephalogram and surface electromyogram fusion-based precise detection of lower limb voluntary movement using convolution neural network-long short …
X Zhang, H Li, R Dong, Z Lu, C Li - Frontiers in Neuroscience, 2022 - frontiersin.org
The electroencephalogram (EEG) and surface electromyogram (sEMG) fusion has been
widely used in the detection of human movement intention for human–robot interaction, but …
widely used in the detection of human movement intention for human–robot interaction, but …
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 …