Brain-computer interfaces : lab experiments to real-world applications /
Saved in:
Imprint: | Amsterdam, Netherlands : Academic Press, 2016. ©2016 |
---|---|
Description: | 1 online resource (436 pages) |
Language: | English |
Series: | Progress in Brain Research, 0079-6123 ; Volume 228 Progress in brain research ; Volume 228. |
Subject: | |
Format: | E-Resource Book |
URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/12379608 |
MARC
LEADER | 00000cam a2200000Mi 4500 | ||
---|---|---|---|
001 | 12379608 | ||
005 | 20200828230743.7 | ||
006 | m o d | ||
007 | cr |n|---||||| | ||
008 | 160912t20162016ne o 001 0 eng | ||
020 | |a 0128092629 | ||
020 | |a 9780128092620 | ||
020 | |a 0128042168 | ||
020 | |a 9780128042168 | ||
035 | |a (OCoLC)1099565118 | ||
035 | 9 | |a (OCLCCM-CC)1099565118 | |
040 | |a AU@ |b eng |e rda |c AU@ |d OCLCO |d OCLCF |d OCLCQ | ||
049 | |a MAIN | ||
050 | 4 | |a QP360.7 |b .B735 2016 | |
245 | 0 | 0 | |a Brain-computer interfaces : |b lab experiments to real-world applications / |c edited by Damien Coyle. |
264 | 1 | |a Amsterdam, Netherlands : |b Academic Press, |c 2016. | |
264 | 4 | |c ©2016 | |
300 | |a 1 online resource (436 pages) | ||
336 | |a text |b txt |2 rdacontent |0 http://id.loc.gov/vocabulary/contentTypes/txt | ||
337 | |a computer |b c |2 rdamedia |0 http://id.loc.gov/vocabulary/mediaTypes/c | ||
338 | |a online resource |b cr |2 rdacarrier |0 http://id.loc.gov/vocabulary/carriers/cr | ||
490 | 1 | |a Progress in Brain Research, |x 0079-6123 ; |v Volume 228 | |
500 | |a Includes index. | ||
505 | 0 | |a Front Cover; Brain-Computer Interfaces: Lab Experiments to Real-World Applications; Copyright; Contributors; Contents; Preface; Part I: User Training; Chapter 1: Advances in user-training for mental-imagery-based BCI control: Psychological and cognitive factors and their ne ... ; 1. Introduction; 2. Psychological and Cognitive Factors Related to MI-BCI Performance; 2.1. Emotional and Cognitive States That Impact MI-BCI Performance; 2.2. Personality and Cognitive Traits That Influence MI-BCI Performance. | |
505 | 8 | |a 2.3. Other Factors Impacting MI-BCI Performance: Demographic Characteristics, Experience, and Environment2.4. To Summarize: MI-BCI Performance Is Affected by the Users (1) Relationship with Technology, (2) Attention, and (3) S ... ; 3. The User-Technology Relationship: Introducing the Concepts of Computer Anxiety and Sense of Agency-Definition and Neur ... ; 3.1. Apprehension of Technology: The Concept of CA-Definition; 3.2. ``I did That!:́́ The Concept of Sense of Agency-Definition; 3.3. ``I did That!:́́ The Concept of Sense of Agency-Neural Correlates. | |
505 | 8 | |a 4. Attention-Definition and Neural Correlates4.1. Attention-Definition; 4.2. Attention-Neural Correlates; 5. Spatial Abilities-Definition and Neural Correlates; 5.1. Spatial Abilities-Definition; 5.2. Spatial Abilities-Neural Correlates; 6. Perspectives: The User-Technology Relationship, Attention, and Spatial Abilities as Three Levers to Improve MI-BCI Use ... ; 6.1. Demonstrating the Impact of the Protocol on CA and Sense of Agency; 6.2. Raising and Improving Attention; 6.3. Increasing Spatial Abilities; 7. Conclusion; References; Part II: Non-Invasive Decoding of 3D Hand and Arm Movements. | |
505 | 8 | |a Chapter 2: From classic motor imagery to complex movement intention decoding: The noninvasive Graz-BCI approach1. Overview; 2. Methods; 2.1. Classic Motor Imagination; 2.1.1. SMR-based BCIs for control; 2.1.2. SMR-based BCIs for communication; 2.1.3. SMR-based BCI training (classic vs adaptive); 2.2. Decoding Motor Execution; 2.3. Decoding Motor Imagination; 2.4. Decoding Movement Targets; 2.5. Decoding Movement Goals; 3. Conclusion; Acknowledgment; References; Chapter 3: 3D hand motion trajectory prediction from EEG mu and beta bandpower; 1. Introduction; 2. Methods. | |
505 | 8 | |a 2.1. Experimental Paradigm2.2. Data Acquisition; 2.3. Data Preprocessing; 2.3.1. EEG data preprocessing; 2.3.1.1. Re-referencing and bandpass filtering; 2.3.1.2. Independent component analysis; 2.3.1.3. The potential time-series model; 2.3.1.4. The bandpower time-series model; 2.3.2. Kinematic data preprocessing; 2.3.3. Data synchronization, data validation, and task interval separation; 2.4. Kinematic Data Reconstruction; 2.4.1. Multiple linear regression; 2.5. Architecture Optimization, Training, Test, and Cross-Validation; 2.5.1. Data separation for inner-outer cross-validation. | |
500 | |a 2.5.2. Optimization 1: Time lag and embedding dimension. | ||
588 | 0 | |a Online resource; title from PDF title page (ebrary, viewed September 12, 2016) | |
650 | 0 | |a Brain-computer interfaces. |0 http://id.loc.gov/authorities/subjects/sh2007000197 | |
650 | 0 | |a Electroencephalography. |0 http://id.loc.gov/authorities/subjects/sh85042138 | |
650 | 7 | |a Brain-computer interfaces. |2 fast |0 (OCoLC)fst01742078 | |
650 | 7 | |a Electroencephalography. |2 fast |0 (OCoLC)fst00906445 | |
655 | 4 | |a Electronic books | |
700 | 1 | |a Coyle, Damien, |e editor. |0 http://id.loc.gov/authorities/names/nb2016019654 |1 http://viaf.org/viaf/3625148122897195200007 | |
830 | 0 | |a Progress in brain research ; |v Volume 228. |0 http://id.loc.gov/authorities/names/n42019859 | |
903 | |a HeVa | ||
929 | |a oclccm | ||
999 | f | f | |i ba560902-88e1-515e-8ab6-08d95fbdd0ed |s 5491ec1a-dec1-52d1-83b2-51c5c4d3a99c |
928 | |t Library of Congress classification |a QP360.7 .B735 2016 |l Online |c UC-FullText |u https://www.sciencedirect.com/science/bookseries/00796123/228 |z Elsevier |g ebooks |i 11979694 |