Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Machine learning has approached magnetic resonance image (MRI) analysis using multiple techniques, including deep supervised learning methodologies, where lesions such as tumors or features associated with defined pathologies have been identified sat...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Aphasia, a language disorder primarily caused by a stroke, is traditionally diagnosed using behavioral language tests. However, these tests are time-consuming, require manual interpretation by trained clinicians, suffer from low ecological validity, ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Decoding EEG-based, Motor Imagery Brain-Computer Interfaces (MI-BCI) in a subject-independent manner is very challenging due to high dimensionality of the EEG signal, and high inter-subject variability. In recent years, Convolutional neural networks ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Nouns and verbs constitute the fundamental elements of human language systems. Abundant studies have demonstrated that nouns and verbs exhibit different representations in both biological brains and various advanced deep neural networks (DNNs). Here,...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Neuroimaging data have become widely studied in the context of identifying brain-based markers of mental illness. however, this work is hampered by the use of symptom and self-report assessments of diagnosis, as well as lack of clarity in the nosolog...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
This study uses computer vision techniques to combine EfficientNet-3D and 3D Residual neural network(3DResnet) deep learning architecture to detect brain tumours in magnetic resonance imaging (MRI). The dataset includes a collection of 586 sets of br...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
When controlling a robot's velocity, it is necessary to provide force feedback to the user, which shows the amount of input from the neutral position. In this paper, we introduce three distinct force feedback models, each with one or two parameters, ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
As the worldwide incidence of stroke increases, supernumerary robotic limbs (SRLs), more specifically supernumerary robotic fingers (SRFs), present a potentially effective solution for enhancing the task related functionality of the upper-limbs of st...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Brain decoding is an emerging area in the fields of neuroscience and machine learning. The goal of decoding is to utilize measured brain activity to understand the thoughts or sensations of individuals. In the fields of computer vision and machine le...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
EEG classification is a challenging task due to the nonstationary nature of EEG data and the covariance shift induced by cross-subject variance. Recently, various machine learning and deep learning models have been developed to learn robust features ...