Cross-domain MLP and CNN Transfer Learning for Biological Signal Processing: EEG and EMG
- Submitting institution
-
Aston University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 45059751
- Type
- D - Journal article
- DOI
-
10.1109/ACCESS.2020.2979074
- Title of journal
- IEEE Access
- Article number
- 9027853
- First page
- 54789
- Volume
- 8
- Issue
- -
- ISSN
- 2169-3536
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
A - Aston Institute of Urban Technology and the Environment (ASTUTE)
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is an international collaboration (Federal University of Parana, Brazil). The outcomes of this work enabled us to be awarded 3 mobility grants (Newton Fund / CONFAP Brazil and IEEE RAS SIGHT) to extend this work and apply to real-world applications towards societal impact: (i) prosthetics and (ii) concentration levels of children with intellectual disabilities. This work will serve as basis for new grant proposals related to Brain-Computer Interfaces. It also helped us to establish contact with State University of Londrina Brazil for pilots with children with learning difficulties (novel findings related to children's brain waves will be published soon).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
