Cybersecurity in neural interfaces: Survey and future trends
With the joint advancement in areas such as pervasive neural data sensing, neural
computing, neuromodulation and artificial intelligence, neural interface has become a …
computing, neuromodulation and artificial intelligence, neural interface has become a …
Transformers in biosignal analysis: A review
Transformer architectures have become increasingly popular in healthcare applications.
Through outstanding performance in natural language processing and superior capability to …
Through outstanding performance in natural language processing and superior capability to …
[HTML][HTML] Machine learning-based feature extraction and classification of emg signals for intuitive prosthetic control
Signals play a fundamental role in science, technology, and communication by conveying
information through varying patterns, amplitudes, and frequencies. This paper introduces …
information through varying patterns, amplitudes, and frequencies. This paper introduces …
Open access dataset, toolbox and benchmark processing results of high-density surface electromyogram recordings
We provide an open access dataset of High densitY Surface Electromyogram (HD-sEMG)
Recordings (named “Hyser”), a toolbox for neural interface research, and benchmark results …
Recordings (named “Hyser”), a toolbox for neural interface research, and benchmark results …
Toward robust, adaptiveand reliable upper-limb motion estimation using machine learning and deep learning–A survey in myoelectric control
To develop multi-functionalhuman-machine interfaces that can help disabled people
reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) …
reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) …
Novel wearable HD-EMG sensor with shift-robust gesture recognition using deep learning
In this work, we present a hardware-software solution to improve the robustness of hand
gesture recognition to confounding factors in myoelectric control. The solution includes a …
gesture recognition to confounding factors in myoelectric control. The solution includes a …
Decoding hd-emg signals for myoelectric control-how small can the analysis window size be?
RN Khushaba, K Nazarpour - IEEE Robotics and Automation …, 2021 - ieeexplore.ieee.org
Recently the use of high-density electromyogram (HD-EMG) signal acquisition setups has
been promoted for myoelectric control and several databases have been made open access …
been promoted for myoelectric control and several databases have been made open access …
User-tailored hand gesture recognition system for wearable prosthesis and armband based on surface electromyogram
Surface electromyogram (sEMG)-based hand gesture recognition for prosthesis or armband
is an important application of the human–machine interface (HMI). However, the …
is an important application of the human–machine interface (HMI). However, the …
Multi-day dataset of forearm and wrist electromyogram for hand gesture recognition and biometrics
Surface electromyography (sEMG) signals have been used for advanced prosthetics control,
hand-gesture recognition (HGR), and more recently as a novel biometric trait. For these …
hand-gesture recognition (HGR), and more recently as a novel biometric trait. For these …
Optimization of HD-sEMG-based cross-day hand gesture classification by optimal feature extraction and data augmentation
Human–machine interaction requires accurate recognition of human intentions (eg, via hand
gestures). Here, we assessed the cross-day robustness of widely used hand gesture …
gestures). Here, we assessed the cross-day robustness of widely used hand gesture …