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Found 6 papers, 1 papers with code
Advancing Brain-Computer Interface System Performance in Hand Trajectory Estimation with NeuroKinect
Our model demonstrates strong correlations between predicted and actual hand movements, with mean Pearson correlation coefficients of 0. 92 ($\pm$0. 015), 0. 93 ($\pm$0. 019), and 0. 83 ($\pm$0. 018) for the X, Y, and Z dimensions.
A Visual Domain Transfer Learning Approach for Heartbeat Sound Classification
Some of the previous studies found that the spectrogram of various types of heart sounds is visually distinguishable to human eyes, which motivated this study to experiment on visual domain classification approaches for automated heart sound classification.
Classification of Upper Arm Movements from EEG signals using Machine Learning with ICA Analysis
Classification of Cognitive-Motor Imagery activities from EEG signals is a critical task.
A Robust and Accurate Deep Learning based Pattern Recognition Framework for Upper Limb Prosthesis using sEMG
Moreover, the performance of traditional machine learning-based methods show limitation to categorize over a certain number of classes and degrades over a period of time.
T-BERT -- Model for Sentiment Analysis of Micro-blogs Integrating Topic Model and BERT
The empirical results show that the model improves in performance while adding topics to BERT and an accuracy rate of 90. 81% on sentiment classification using BERT with the proposed approach.
Source Aware Deep Learning Framework for Hand Kinematic Reconstruction using EEG Signal
The ability to reconstruct the kinematic parameters of hand movement using non-invasive electroencephalography (EEG) is essential for strength and endurance augmentation using exosuit/exoskeleton.
