AIMC Topic: Signal Processing, Computer-Assisted

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Diagnosing Suicidal Ideation from Resting State EEG Data Using a Machine Learning Algorithm.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Suicide poses a global health crisis with significant social and economic impact. Prevention may be possible if objective quantitative methods are developed to supplement the often inaccurate interview-based risk assessments. Our research goal is to ...

EEG-GMACN: Interpretable EEG Graph Mutual Attention Convolutional Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electroencephalogram (EEG) is a valuable technique to record brain electrical activity through electrodes placed on the scalp. Analyzing EEG signals contributes to the understanding of neurological conditions and developing brain-computer interface. ...

ECG Beat-By-Beat Classification Using Hybrid Transformer Neural Network Model in Smart Health.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Wearable cardiac monitors can be used to detect potential heart attack by syncing with smartphone apps for instant data analysis and alerts. Our goal is to build an efficient smart health application to help patients prevent and early diagnose the ri...

Cough-DL: A Deep Learning Model for Ear-Worn Cough Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Cough serves as a crucial bio-marker for evaluation and monitoring of pulmonary conditions. With growing interest towards automatic cough detection systems, it's important to acknowledge the existing hurdles on the way for a robust cough counter. The...

Deep Residual Neural Networks for Spatial EEG Source Imaging.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
EEG source imaging is an indispensable tool for non-invasive study of brain function. Existing methods mainly directly deal with the EEG inverse problem by imposing prior constraints. However, different brain activation patterns may produce similar p...

Resource-Efficient Continual Learning for Personalized Online Seizure Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Epilepsy, a major neurological disease, requires careful diagnosis and treatment. However, the detection of epileptic seizures remains a significant challenge. Current clinical practice relies on expert analysis of EEG signals, a process that is time...

Identifying Reproducibly Important EEG Markers of Schizophrenia with an Explainable Multi-Model Deep Learning Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The diagnosis of schizophrenia (SZ) can be challenging due to its diverse symptom presentation. As such, many studies have sought to identify diagnostic biomarkers of SZ using explainable machine learning methods. However, the generalizability of ide...

The Impact of Cross-Validation Schemes for EEG-Based Auditory Attention Detection with Deep Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This study assesses the performance of different cross-validation splits for brain-signal-based Auditory Attention Decoding (AAD) using deep neural networks on three publicly available Electroencephalography datasets. We investigate the effect of tri...

Enhancing Wearable based Real-Time Glucose Monitoring via Phasic Image Representation Learning based Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In the U.S., over a third of adults are pre-diabetic, with 80% unaware of their status. This underlines the need for better glucose monitoring to prevent type 2 diabetes and related heart diseases. Existing wearable glucose monitors are limited by th...

Enhancing sleep stage classification with 2-class stratification and permutation-based channel selection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We present a method that uses a convolutional neural network (CNN) called EEGNeX to extract and classify the characteristics of sleep-related waveforms from electroencephalographic (EEG) signals in different stages of sleep. Our results showed that t...