Senior Design Projects
ECS193 A/B Winter & Spring 2019
Deep learning for Alzheimer’s diseases using EEG visibility graph
| ********** | |
| Jiangyi Xia & John Olichney | |
| Center for Mind and Brain; Department of Neurology |
Project's details
| Deep learning for Alzheimer’s diseases using EEG visibility graph | |
| A major challenge of current research in Alzheimer’s disease ( AD ) is the development of sensitive and reliable ways to detect the disease in its earliest stages, when interventions and treatments are likely to be effective. In our lab, we study electrical brain activity during rest and tasks of attention, language, and memory using EEG. Our work shows that EEG measures are highly sensitive to early-stage AD and related cognitive impairments. Using the data we collected from patients and healthy elderly, we would like to build a deep learning framework for EEG-based classification of early stage AD. | |
| EEG time series will be converted into Visibility Graph ( VG ), such that discriminative graph features can be extracted for classification analyses. VG preserves the structure and dynamics of the original EEG time series and is efficient in extracting information from noisy, multivariate, and nonstationary data such as EEG. VG features will be selected based on their sensitivity to AD. Deep neural networks ( CNN ) will be created using selected VG features to classify between different AD stages and between AD patients and healthy elderly. Multiple methods will be attempted to improve signal-to-noise ratio in the EEG data. These include averaging EEG trials during which specific stimuli and cognitive processes occur, i.e., cognitive ERPs. | |
| Software implementing VG feature abstraction and a DNN that take in multi-channel EEG time series and produce: ( 1 ) classification statistics, and ( 2 ) visualizations of VG features and EEG channels that contribute to accurate classification. The students will be expected to deliver the source code and provide comprehensive documentation of the code. | |
| Python ( or MATLAB ), TensorFlow ( or other deep learning frameworks ) | |
| ********** | |
| 30-60 min weekly or more | |
| Open source project | |
| Attachment | Click here |
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| Team members | N/A |
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