Joint Spatial-Spectral Feature Space Clustering for Speech Activity Detection from ECoG Signals
- Submitting institution
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University of Hertfordshire
- Unit of assessment
- 12 - Engineering
- Output identifier
- 19721255
- Type
- D - Journal article
- DOI
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10.1109/TBME.2014.2298897
- Title of journal
- IEEE Transactions on Biomedical Engineering
- Article number
- -
- First page
- 1241
- Volume
- 61
- Issue
- 4
- ISSN
- 0018-9294
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2014
- URL
-
-
- Supplementary information
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-
- 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
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2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The research leading to the outputs presented in this paper was initiated using funding by the European Commissions’ FP7 research programme (EU FP7 ARMOR). The University of Patras, Greece, Johns Hopkins (USA) and Sinapse (Singapore) subsequently collaborated to publish original work on Brain-Computer Interfaces using ECoG signals, as proposed in this paper, instead of EEG. The research focused directly to applications on patients with communication disabilities. Since, this paper has produced a new line of research at UH targeting the development of sensors technology in human computer interaction.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -