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<p><strong>Transforming Imagined Thoughts into Speech Using a Covariance-Based Subset Selection Method</strong></p>

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Title Statement <p><strong>Transforming Imagined Thoughts into Speech Using a Covariance-Based Subset Selection Method</strong></p>
 
Added Entry - Uncontrolled Name Agarwal, Prabhakar ; Department of Electronics & Communication Engineering, National Institute of Technology, Delhi-110 040, India
Kumar, Sandeep
 
Uncontrolled Index Term Brain-computer interfacing, Covariance, Electroencephalogram
 
Summary, etc. <p class="Abstract">With the advancement of engineering solutions in the medical domain, the patient’s life can become comfortable. This work recognizes the silent speech of three words. The decoding of silent speech can be useful for patients who are in a locked-in syndrome state. Moreover, it is also applicable to entertainment, cognitive biometrics, and brain-computer interfacing. Brain waves of these imagined words in the delta, theta, alpha, beta, gamma, and high gamma frequency bands are analysed. Covariance based connectivity features are extracted in each frequency band. The principal features which represent more than 95% of the variance are selected as a subset of the covariance connectivity matrix. This sub-set is tested on five classifiers. The maximum accuracy achieved is 76.4% in the theta band. Also, theta and high gamma band contain maximum information about imagined speech with average accuracies of 68.32% and 62.09% respectively.</p>
 
Publication, Distribution, Etc. Indian Journal of Pure & Applied Physics (IJPAP)
2022-10-21 11:23:26
 
Electronic Location and Access application/pdf
http://op.niscair.res.in/index.php/IJPAP/article/view/67746
 
Data Source Entry Indian Journal of Pure & Applied Physics (IJPAP); ##issue.vol## 59, ##issue.no## 3 (2021): Indian Journal of Pure & Applied Physics
 
Language Note en
 
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