Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
BCI illiterate subject is defined as the subject who cannot achieve accuracy higher than 70%. BCI illiterate subject cannot produce stronger contralateral ERD/ERS activity, thus most of the frequency band-based algorithms cannot obtain higher accurac...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
In recent decades, motor imagery (MI) based brain-computer interface (BCI) is served as a control system or rehabilitation tool for motor disabled people. But it has limited applications because of its lower classification performance (classification...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
A Brain Computer Interface (BCI) character speller allows human-beings to directly spell characters using eye-gazes, thereby building communication between the human brain and a computer. Current popular BCI character speller systems employ a large n...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Recent advances in the unsupervised and generative models of deep learning have shown promise for application in biomedical signal processing. In this work, we present a portable resource-constrained ultrasound (US) system trained using Variational A...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
In the absence of duplicate high-dose CT data, it is challenging to restore high-quality images based on deep learning with only low-dose CT (LDCT) data. When different reconstruction algorithms and settings are adopted to prepare high-quality images...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Although myoelectric pattern recognition (MPR) has been considered as a milestone technique to enable dexterous control of multiple degrees of freedom, outlier data interference (i.e., novelty) is a big issue affecting stability of conventional MPR c...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Biometric technologies offer much convenience over the conventional approaches to identity recognition, but security and privacy concerns also accompany their applications. In this paper, an electrocardiogram (ECG)-based identification scheme is prop...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Automatic myocardial infarction (MI) detection using an electrocardiogram (ECG) is of great significance for improving the survival rate of patients. In this study, we propose a multi-lead ensemble neural network (MENN) to distinguish anterior myocar...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Despite the severe consequences of dysfunctional swallowing, there is no simple method of monitoring swallowing outside of clinical settings. People who cannot swallow cannot eat safely, resulting in profound changes in quality of life and risk of de...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
The automatic diagnosis of epilepsy using Electroencephalogram (EEG) signals had always been an important research direction. A novel automatic epilepsy detection method based on multi-weight transition network was proposed in this paper. The epilept...