Deep learning based multimodal biomedical data fusion: An overview and comparative review
J Duan, J ** advanced data analysis and machine learning …
A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition
Wearable devices that monitor muscle activity based on surface electromyography could be
of use in the development of hand gesture recognition applications. Such devices typically …
of use in the development of hand gesture recognition applications. Such devices typically …
Self-recalibrating surface EMG pattern recognition for neuroprosthesis control based on convolutional neural network
Hand movement classification based on surface electromyography (sEMG) pattern
recognition is a promising approach for upper limb neuroprosthetic control. However …
recognition is a promising approach for upper limb neuroprosthetic control. However …
Surface-electromyography-based gesture recognition by multi-view deep learning
Gesture recognition using sparse multichannel surface electromyography (sEMG) is a
challenging problem, and the solutions are far from optimal from the point of view of muscle …
challenging problem, and the solutions are far from optimal from the point of view of muscle …
Multiday EMG-based classification of hand motions with deep learning techniques
Pattern recognition of electromyography (EMG) signals can potentially improve the
performance of myoelectric control for upper limb prostheses with respect to current clinical …
performance of myoelectric control for upper limb prostheses with respect to current clinical …
EMG-centered multisensory based technologies for pattern recognition in rehabilitation: state of the art and challenges
In the field of rehabilitation, the electromyography (EMG) signal plays an important role in
interpreting patients' intentions and physical conditions. Nevertheless, utilizing merely the …
interpreting patients' intentions and physical conditions. Nevertheless, utilizing merely the …
Improved multi-stream convolutional block attention module for sEMG-based gesture recognition
S Wang, L Huang, D Jiang, Y Sun, G Jiang… - … in Bioengineering and …, 2022 - frontiersin.org
As a key technology for the non-invasive human-machine interface that has received much
attention in the industry and academia, surface EMG (sEMG) signals display great potential …
attention in the industry and academia, surface EMG (sEMG) signals display great potential …
A fully embedded adaptive real-time hand gesture classifier leveraging HD-sEMG and deep learning
This paper presents a real-time fine gesture recognition system for multi-articulating hand
prosthesis control, using an embedded convolutional neural network (CNN) to classify hand …
prosthesis control, using an embedded convolutional neural network (CNN) to classify hand …
Characterization of a benchmark database for myoelectric movement classification
In this paper, we characterize the Ninapro database and its use as a benchmark for hand
prosthesis evaluation. The database is a publicly available resource that aims to support …
prosthesis evaluation. The database is a publicly available resource that aims to support …