Artificial intelligence-based brain-computer interface:
Artificial Intelligence-Based Brain Computer Interface provides concepts of AI for the modeling of non-invasive modalities of medical signals such as EEG, MRI and FMRI. These modalities and their AI-based analysis are employed in BCI and related applications. The book emphasizes the real challenges...
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| Weitere beteiligte Personen: | , |
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| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
London ; San Diego, CA
Academic Press
[2022]
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9780323914123/?ar |
| Zusammenfassung: | Artificial Intelligence-Based Brain Computer Interface provides concepts of AI for the modeling of non-invasive modalities of medical signals such as EEG, MRI and FMRI. These modalities and their AI-based analysis are employed in BCI and related applications. The book emphasizes the real challenges in non-invasive input due to the complex nature of the human brain and for a variety of applications for analysis, classification and identification of different mental states. Each chapter starts with a description of a non-invasive input example and the need and motivation of the associated AI methods, along with discussions to connect the technology through BCI. Major topics include different AI methods/techniques such as Deep Neural Networks and Machine Learning algorithms for different non-invasive modalities such as EEG, MRI, FMRI for improving the diagnosis and prognosis of numerous disorders of the nervous system, cardiovascular system, musculoskeletal system, respiratory system and various organs of the body. The book also covers applications of AI in the management of chronic conditions, databases, and in the delivery of health services. Provides readers with an understanding of key applications of Artificial Intelligence to Brain-Computer Interface for acquisition and modelling of non-invasive biomedical signal and image modalities for various conditions and disorders Integrates recent advancements of Artificial Intelligence to the evaluation of large amounts of clinical data for the early detection of disorders such as Epilepsy, Alcoholism, Sleep Apnea, motor-imagery tasks classification, and others Includes illustrative examples on how Artificial Intelligence can be applied to the Brain-Computer Interface, including a wide range of case studies in predicting and classification of neurological disorders. |
| Beschreibung: | Includes bibliographical references and index. - Description based on print version record |
| Umfang: | 1 Online-Ressource (xv, 376 Seiten) illustrations |
| ISBN: | 9780323914123 0323914128 |
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| 520 | |a Artificial Intelligence-Based Brain Computer Interface provides concepts of AI for the modeling of non-invasive modalities of medical signals such as EEG, MRI and FMRI. These modalities and their AI-based analysis are employed in BCI and related applications. The book emphasizes the real challenges in non-invasive input due to the complex nature of the human brain and for a variety of applications for analysis, classification and identification of different mental states. Each chapter starts with a description of a non-invasive input example and the need and motivation of the associated AI methods, along with discussions to connect the technology through BCI. Major topics include different AI methods/techniques such as Deep Neural Networks and Machine Learning algorithms for different non-invasive modalities such as EEG, MRI, FMRI for improving the diagnosis and prognosis of numerous disorders of the nervous system, cardiovascular system, musculoskeletal system, respiratory system and various organs of the body. The book also covers applications of AI in the management of chronic conditions, databases, and in the delivery of health services. Provides readers with an understanding of key applications of Artificial Intelligence to Brain-Computer Interface for acquisition and modelling of non-invasive biomedical signal and image modalities for various conditions and disorders Integrates recent advancements of Artificial Intelligence to the evaluation of large amounts of clinical data for the early detection of disorders such as Epilepsy, Alcoholism, Sleep Apnea, motor-imagery tasks classification, and others Includes illustrative examples on how Artificial Intelligence can be applied to the Brain-Computer Interface, including a wide range of case studies in predicting and classification of neurological disorders. | ||
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| isbn | 9780323914123 0323914128 |
| language | English |
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| physical | 1 Online-Ressource (xv, 376 Seiten) illustrations |
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| spelling | Artificial intelligence-based brain-computer interface edited by Varun Bajaj and G.R. Sinha London ; San Diego, CA Academic Press [2022] 1 Online-Ressource (xv, 376 Seiten) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index. - Description based on print version record Artificial Intelligence-Based Brain Computer Interface provides concepts of AI for the modeling of non-invasive modalities of medical signals such as EEG, MRI and FMRI. These modalities and their AI-based analysis are employed in BCI and related applications. The book emphasizes the real challenges in non-invasive input due to the complex nature of the human brain and for a variety of applications for analysis, classification and identification of different mental states. Each chapter starts with a description of a non-invasive input example and the need and motivation of the associated AI methods, along with discussions to connect the technology through BCI. Major topics include different AI methods/techniques such as Deep Neural Networks and Machine Learning algorithms for different non-invasive modalities such as EEG, MRI, FMRI for improving the diagnosis and prognosis of numerous disorders of the nervous system, cardiovascular system, musculoskeletal system, respiratory system and various organs of the body. The book also covers applications of AI in the management of chronic conditions, databases, and in the delivery of health services. Provides readers with an understanding of key applications of Artificial Intelligence to Brain-Computer Interface for acquisition and modelling of non-invasive biomedical signal and image modalities for various conditions and disorders Integrates recent advancements of Artificial Intelligence to the evaluation of large amounts of clinical data for the early detection of disorders such as Epilepsy, Alcoholism, Sleep Apnea, motor-imagery tasks classification, and others Includes illustrative examples on how Artificial Intelligence can be applied to the Brain-Computer Interface, including a wide range of case studies in predicting and classification of neurological disorders. Artificial intelligence Medical applications Brain-computer interfaces Intelligence artificielle en médecine Interfaces cerveau-ordinateur Artificial intelligence ; Medical applications Bajaj, Varun HerausgeberIn edt Sinha, G. R. 1975- HerausgeberIn edt 9780323914123 Erscheint auch als Druck-Ausgabe 9780323914123 |
| spellingShingle | Artificial intelligence-based brain-computer interface Artificial intelligence Medical applications Brain-computer interfaces Intelligence artificielle en médecine Interfaces cerveau-ordinateur Artificial intelligence ; Medical applications |
| title | Artificial intelligence-based brain-computer interface |
| title_auth | Artificial intelligence-based brain-computer interface |
| title_exact_search | Artificial intelligence-based brain-computer interface |
| title_full | Artificial intelligence-based brain-computer interface edited by Varun Bajaj and G.R. Sinha |
| title_fullStr | Artificial intelligence-based brain-computer interface edited by Varun Bajaj and G.R. Sinha |
| title_full_unstemmed | Artificial intelligence-based brain-computer interface edited by Varun Bajaj and G.R. Sinha |
| title_short | Artificial intelligence-based brain-computer interface |
| title_sort | artificial intelligence based brain computer interface |
| topic | Artificial intelligence Medical applications Brain-computer interfaces Intelligence artificielle en médecine Interfaces cerveau-ordinateur Artificial intelligence ; Medical applications |
| topic_facet | Artificial intelligence Medical applications Brain-computer interfaces Intelligence artificielle en médecine Interfaces cerveau-ordinateur Artificial intelligence ; Medical applications |
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