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Full Description
Artificial Intelligence Applications for Brain-Computer Interfaces focuses on the advancements, challenges, and prospects of future technologies involving noninvasive brain-computer interfaces (BCIs). It includes the processing and analysis of multimodal signals, integrated computation-acquisition devices, and implantable neuro techniques.
This book not only provides cross-disciplinary research in BCI but also presents divergent applications on telerehabilitation, emotion recognition, neuro-rehabilitation, cognitive workload assessments, and ambient assisted living solutions.
In 15 chapters, this book describes how BCIs connect the brain with external devices like computers and electronic gadgets. It analyzes the neural signals from the brain to obtain insights from the brain patterns using multiple noninvasive wearable sensors. It gives insight into how sensor outcomes are processed through machine-intelligent models to draw inferences. Each chapter starts with the importance, problem statement, and motivation. A description of the proposed methodology is provided, and related works are also presented.
Each chapter can be read independently, and therefore, the book is a valuable resource for researchers, health professionals, postgraduate students, postdoc researchers, and academicians in the fields of BCI, prosthesis, computer vision, and mental state estimation, and all those who wish to broaden their knowledge in the allied field.
Contents
1. Introduction to brain-computer interface: research trends and applications
SAEED MIAN QAISAR AND ABDULHAMIT SUBASI
2. Preprocessing and feature extraction techniques for brain-computer interface
ABDULHAMIT SUBASI AND SAEED MIAN QAISAR
3. Emotional state monitoring and applications with brain-computer interfaces
EVIN SAHIN SADIK
4. Hand kinematics and decoding hindlimb kinematics using local field potentials using a deep neural network decoding framework
JIGAR SARDA, MILIND SHAH, ROHAN VAGHELA, DARSH VAISHNANI AND HIRVA PATEL
5. Closed-loop brain_computer interfaces for musculoskeletal impulse prediction
K. RANJINI, POOJA GOUD, AMBESHWAR KUMAR AND R. MANIKANDAN
6. Classification of motor imagery tasks in brain-computer interface using ensemble learning
ABDULHAMIT SUBASI AND SAEED MIAN QAISAR
7. The application of brain_computer interface in Alzheimer's disease studies based on machine learning algorithms
HELIA GIVIAN
8. Brain_computer interfaces and deep learning methods for cognitive impairments
SEDA SASMAZ KARACAN
9. Prospects and challenges in decoding consumer behavior using neurotechnology
TARA CHAND, VASUNDHARAA S. NAIR, PARVATHANENI NAGA SRINIVASU AND VINOD JANGIR KUMAR
10. Electroencephalography-based emotion recognition with empirical mode decomposition and ensemble machine learning methods
ABDULHAMIT SUBASI, MUHAMMED ENES SUBASI AND SAEED MIAN QAISAR
11. Brain-computer interfaces for security and authentication
MOUMITA CHANDA, OLIVE MAZUMDER, SOUVIK PAUL AND TAWFIKUR RAHMAN
12. A case study on artifical intelligence based data processing in passive brain-computer interface
PARVEEN KUMAR SEKHARAMANTRY, USAMA A. SYED, UMER FAROOQ AND DINH DUNG VAN
13. Analyzing eyewitness recognition accuracy using event-related potential and eye-tracking analysis: an experimental investigation
SAMIKSHA DAS, DERICK H. LINDQUIST, TARA CHAND AND MOHITA JUNNARKAR
14. Ambient assisted living through passive brain-computer interface technology for assisting paralyzed people
SANCHITA GOSWAMI, PRITHU BANIK, ANIKET KUMAR MEENA AND ANJANEYULU BENDI
15. Challenges and future directions in brain-computer interface research for exoskeletons usage
HEMANTH P.K. SUDHANI, PRABHAKAR VATTIKUTI AND DASARI REKHA
