Papers EMG Gesture Recognition
“EMG Gesture Recognition” 태그가 달린 논문 8편 · 필터 해제
Low Power Neuromorphic EMG Gesture Classification
EMG (Electromyograph) signal based gesture recognition can prove vital for applications such as smart wearables and bio-medical neuro-prosthetic control. Spiking Neural Networks (SNNs) are promising for low-power, real-t…
ClassificationEMG Gesture RecognitionGesture RecognitionGPUSignals to Spikes for Neuromorphic Regulated Reservoir Computing and EMG Hand Gesture Recognition
Surface electromyogram (sEMG) signals result from muscle movement and hence they are an ideal candidate for benchmarking event-driven sensing and computing. We propose a simple yet novel approach for optimizing the spike…
BenchmarkingEMG Gesture RecognitionGesture RecognitionHand Gesture Recognition+2A 5 μW Standard Cell Memory-based Configurable Hyperdimensional Computing Accelerator for Always-on Smart Sensing
Hyperdimensional computing (HDC) is a brain-inspired computing paradigm based on high-dimensional holistic representations of vectors. It recently gained attention for embedded smart sensing due to its inherent error-res…
EMG Gesture RecognitionFault DetectionGesture RecognitionsEMG Gesture Recognition with a Simple Model of Attention
Myoelectric control is one of the leading areas of research in the field of robotic prosthetics. We present our research in surface electromyography (sEMG) signal classification, where our simple and novel attention-base…
Electromyography (EMG)EMG Gesture RecognitionGesture RecognitionMulti-class ClassificationA Transferable Adaptive Domain Adversarial Neural Network for Virtual Reality Augmented EMG-Based Gesture Recognition
Within the field of electromyography-based (EMG) gesture recognition, disparities exist between the offline accuracy reported in the literature and the real-time usability of a classifier. This gap mainly stems from two …
EMG Gesture RecognitionGesture RecognitionTransfer LearningDomain Adaptation for sEMG-based Gesture Recognition with Recurrent Neural Networks
Surface Electromyography (sEMG/EMG) is to record muscles' electrical activity from a restricted area of the skin by using electrodes. The sEMG-based gesture recognition is extremely sensitive of inter-session and inter-s…
Domain AdaptationEMG Gesture RecognitionGesture RecognitionAn EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional Classifier
EMG-based gesture recognition shows promise for human-machine interaction. Systems are often afflicted by signal and electrode variability which degrades performance over time. We present an end-to-end system combating t…
EMG Gesture RecognitionGeneral ClassificationGesture RecognitionOne-Shot Learning+2Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning
In recent years, deep learning algorithms have become increasingly more prominent for their unparalleled ability to automatically learn discriminant features from large amounts of data. However, within the field of elect…
Deep LearningEMG Gesture RecognitionGeneral ClassificationGesture Recognition+1