Cargando…
EEG-based diagnosis of Alzheimer disease : a review and novel approaches for feature extraction and classification techniques /
EEG-Based Diagnosis of Alzheimer Disease: A Review and Novel Approaches for Feature Extraction and Classification Techniques provides a practical and easy-to-use guide for researchers in EEG signal processing techniques, Alzheimer's disease, and dementia diagnostics. The book examines different...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Academic Press,
[2018]
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | SCIDIR_on1031373552 | ||
| 003 | OCoLC | ||
| 005 | 20231120010251.0 | ||
| 006 | m o d | ||
| 007 | cr cnu|||unuuu | ||
| 008 | 180416s2018 enka ob 001 0 eng d | ||
| 040 | |a N$T |b eng |e rda |e pn |c N$T |d N$T |d EBLCP |d OPELS |d OCLCF |d D6H |d MERER |d OCLCQ |d INT |d NLE |d OCLCQ |d U3W |d LVT |d ITD |d OCLCQ |d UKAHL |d OCLCQ |d S2H |d OCLCO |d UX1 |d VT2 |d OCLCA |d OCLCQ |d OCLCO |d K6U |d OCLCQ |d SFB |d OCLCQ |d OCLCO | ||
| 019 | |a 1235837878 | ||
| 020 | |a 9780128153932 |q (electronic bk.) | ||
| 020 | |a 0128153938 |q (electronic bk.) | ||
| 020 | |a 9780128153925 |q (electronic bk.) | ||
| 020 | |a 012815392X |q (electronic bk.) | ||
| 035 | |a (OCoLC)1031373552 |z (OCoLC)1235837878 | ||
| 050 | 4 | |a RC523 | |
| 060 | 4 | |a 2018 G-221 | |
| 060 | 4 | |a WT 156 | |
| 072 | 7 | |a HEA |x 039000 |2 bisacsh | |
| 072 | 7 | |a MED |x 014000 |2 bisacsh | |
| 072 | 7 | |a MED |x 022000 |2 bisacsh | |
| 072 | 7 | |a MED |x 112000 |2 bisacsh | |
| 072 | 7 | |a MED |x 045000 |2 bisacsh | |
| 082 | 0 | 4 | |a 616.831075 |2 23 |
| 100 | 1 | |a Kulkarni, Nilesh, |e author. | |
| 245 | 1 | 0 | |a EEG-based diagnosis of Alzheimer disease : |b a review and novel approaches for feature extraction and classification techniques / |c Nilesh Kulkarni and Vinayak Bairagi. |
| 264 | 1 | |a London : |b Academic Press, |c [2018] | |
| 300 | |a 1 online resource : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Online resource; title from PDF title page (EBSCO, viewed April 17, 2018). | |
| 505 | 0 | |a Intro; Title page; Table of Contents; Copyright; Dedication; Acknowledgments; Chapter One: Introduction; Abstract; 1.1. Alzheimer disease; 1.2. Causes and symptoms of the disease; 1.3. Stages and clinical diagnosis of Alzheimer's disease; 1.4. Importance of diagnosis of Alzheimer's disease and its impact on society; 1.5. A brief review on different methods used for diagnosis of Alzheimer disease; Summary; Chapter Two: Electroencephalogram and Its Use in Clinical Neuroscience; Abstract; 2.1. EEG recording and measurement; 2.2. EEG rhythms. | |
| 505 | 8 | |a 2.3. Early diagnosis of Alzheimer's disease by means of EEG signalsSummary; Chapter Three: Role of Different Features in Diagnosis of Alzheimer Disease; Abstract; 3.1. Introduction; 3.2. What is feature extraction?; 3.3. Need of feature extraction; 3.4. Linear features; 3.5. Conclusions; Chapter Four: Use of Complexity Features for Diagnosis of Alzheimer Disease; Abstract; 4.1. Introduction; 4.2. Use of new complexity features in Alzheimer's disease diagnosis; 4.3. Discussion and conclusion; Summary; Chapter Five: Classification Algorithms in Diagnosis of Alzheimer's Disease; Abstract. | |
| 505 | 8 | |a 5.1. IntroductionSummary; Chapter Six: Results, Discussions, and Research Challenges; Abstract; 6.1. Results; 6.2. Conclusions; 6.3. Contribution; 6.4. Limitations of the study; 6.5. Future scope; Index. | |
| 520 | |a EEG-Based Diagnosis of Alzheimer Disease: A Review and Novel Approaches for Feature Extraction and Classification Techniques provides a practical and easy-to-use guide for researchers in EEG signal processing techniques, Alzheimer's disease, and dementia diagnostics. The book examines different features of EEG signals used to properly diagnose Alzheimer's Disease early, presenting new and innovative results in the extraction and classification of Alzheimer's Disease using EEG signals. This book brings together the use of different EEG features, such as linear and nonlinear features, which play a significant role in diagnosing Alzheimer's Disease. | ||
| 650 | 0 | |a Alzheimer's disease |x Diagnosis. | |
| 650 | 0 | |a Electroencephalography. | |
| 650 | 1 | 2 | |a Alzheimer Disease |x diagnosis |0 (DNLM)D000544Q000175 |
| 650 | 2 | 2 | |a Electroencephalography |x methods |0 (DNLM)D004569Q000379 |
| 650 | 2 | |a Electroencephalography |0 (DNLM)D004569 | |
| 650 | 6 | |a �Electroenc�ephalographie. |0 (CaQQLa)201-0021971 | |
| 650 | 7 | |a HEALTH & FITNESS |x Diseases |x General. |2 bisacsh | |
| 650 | 7 | |a MEDICAL |x Clinical Medicine. |2 bisacsh | |
| 650 | 7 | |a MEDICAL |x Diseases. |2 bisacsh | |
| 650 | 7 | |a MEDICAL |x Evidence-Based Medicine. |2 bisacsh | |
| 650 | 7 | |a MEDICAL |x Internal Medicine. |2 bisacsh | |
| 650 | 7 | |a Alzheimer's disease |x Diagnosis |2 fast |0 (OCoLC)fst00806537 | |
| 650 | 7 | |a Electroencephalography |2 fast |0 (OCoLC)fst00906445 | |
| 700 | 1 | |a Bairagi, Vinayak, |e author. | |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9780128153925 |z Texto completo |