Abstract
Wearable EEG enables non-invasive recording of brain signals when individuals engage in day-to-day activities. They are widely used in conditions such as epilepsy. RELIEVE https://project-relieve.eu/project-profile/ is an EU-funded project creating a wearable EEG unit, machine-learning models, and an ultrasound vagus nerve stimulator, which could ultimately be employed for applications in epilepsy management. Although many AI models exist for EEG artifact removal, to date they have not been deployed on edge hardware for real-time processing. In the EEG sensor device itself. Here, we report our progress in implementing a deep autoencoder network for artifact removal on edge hardware.
Original language | English |
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Publication status | Accepted/In press - 26 Sept 2024 |
Event | IEEE Sensors 2024 - Kobe Portopia Hotel, Kobe, Japan Duration: 20 Oct 2024 → 23 Oct 2024 https://2024.ieee-sensorsconference.org/ |
Conference
Conference | IEEE Sensors 2024 |
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Country/Territory | Japan |
City | Kobe |
Period | 20/10/24 → 23/10/24 |
Internet address |
Keywords
- Electroencephalography
- Artifacts
- Artificial Intelligence
- Machine Learning
- Deep Learning
- Edge Computing