AI-Driven Human-Machine Interaction for Biomedical Engineering: Concepts, Applications, and Methodologies
Editat de Kapil Gupta, Varun Bajaj, Deepak Kumar Jain, Raul Villamarin Rodriguez, Hemachandran Kannanen Limba Engleză Paperback – 22 apr 2026
Readers will delve into cutting-edge techniques, from deep learning to non-invasive computer vision, while also examining the implications of these technologies across industries. Each chapter equips readers with actionable insights and highlights emerging trends, ethical considerations, and the future of AI in HMI, ensuring a well-rounded perspective on this dynamic field. This is an invaluable resource for researchers, academics, and students in the fields of Biomedical Engineering, Computer Science, Data Science, Artificial Intelligence, and Healthcare Technology.
- Offers practical insights into AI-driven methodologies for enhanced human-machine collaboration in healthcare and beyond
- Provides foundational knowledge of machine learning principles applicable across diverse industries
- Equips readers with cutting-edge techniques for biomedical data classification and analysis
- Addresses ethical considerations and emerging trends in AI applications for informed decision-making
- Facilitates innovation by bridging theoretical concepts with real-world applications in human-machine interaction
Preț: 820.48 lei
Preț vechi: 1375.17 lei
-40% Nou
Puncte Express: 1231
Carte tipărită la comandă
Livrare economică 02-16 iulie
Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit pentru acest produs Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
Specificații
ISBN-13: 9780443446382
ISBN-10: 0443446385
Pagini: 382
Dimensiuni: 191 x 235 mm
Greutate: 0.45 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0443446385
Pagini: 382
Dimensiuni: 191 x 235 mm
Greutate: 0.45 kg
Editura: ELSEVIER SCIENCE
Cuprins
1. Basics, Constraints, and Future Potential of Machine Learning in HMI
2. Human-Computer Interaction for Cardiac Feedback: A Physics-Guided Deep Learning Approach
3. Classification of Steady State Visual Evoked Potentials in Brain-Computer Interface systems using Python
4. Contactless Vital Sign Monitoring Through Intelligent Human-Machine Interaction (HMI): A Systematic Review of Image- and Video-Based Techniques
5. AI-driven Scalable Software Architecture for Enhancing Human-Machine Interaction in Biomedical Data Ecosystems
6. AI-Driven Depression Detection Using EEG Signal Determinants and MTO
7. EEG-Driven Machine Learning for Recognition of Emergency Numbers for Crisis Readiness: A Translational Study
8. Suppression of Artifacts from EEG Signals using Quadratic Relative Error based LMS (QRE-LMS) Algorithm
9. Two-Stage Verification for Multi-Instance Feature Selection in Dental Anomaly Detection: A CNN-GRU Approach with Explainable AI and Optimization Techniques
10. Performance Evaluation of Vision Transformers for AI-driven Diagnosis of Bleeding Detection in Wireless Endoscopy Bleeding
11. Human Machine Interface In Healthcare Imaging And Medical Treatments
12. State-of-the-art methods for diagnosis of acute leukemia: A survey
13. Optimized Feature Subsets for Characterizing Fetal QRS Complexes in Non-Invasive Abdominal ECG Recordings
14. Multimodal AI in Human-Computer Interaction: Transforming Medical Feedback Delivery
15. Computer Vision for AI-Driven Human-Machine Interaction and Enhanced Diagnosis
16. Human-Machine Interaction in AI-Assisted Medical Diagnosis: Challenges and Future Directions
2. Human-Computer Interaction for Cardiac Feedback: A Physics-Guided Deep Learning Approach
3. Classification of Steady State Visual Evoked Potentials in Brain-Computer Interface systems using Python
4. Contactless Vital Sign Monitoring Through Intelligent Human-Machine Interaction (HMI): A Systematic Review of Image- and Video-Based Techniques
5. AI-driven Scalable Software Architecture for Enhancing Human-Machine Interaction in Biomedical Data Ecosystems
6. AI-Driven Depression Detection Using EEG Signal Determinants and MTO
7. EEG-Driven Machine Learning for Recognition of Emergency Numbers for Crisis Readiness: A Translational Study
8. Suppression of Artifacts from EEG Signals using Quadratic Relative Error based LMS (QRE-LMS) Algorithm
9. Two-Stage Verification for Multi-Instance Feature Selection in Dental Anomaly Detection: A CNN-GRU Approach with Explainable AI and Optimization Techniques
10. Performance Evaluation of Vision Transformers for AI-driven Diagnosis of Bleeding Detection in Wireless Endoscopy Bleeding
11. Human Machine Interface In Healthcare Imaging And Medical Treatments
12. State-of-the-art methods for diagnosis of acute leukemia: A survey
13. Optimized Feature Subsets for Characterizing Fetal QRS Complexes in Non-Invasive Abdominal ECG Recordings
14. Multimodal AI in Human-Computer Interaction: Transforming Medical Feedback Delivery
15. Computer Vision for AI-Driven Human-Machine Interaction and Enhanced Diagnosis
16. Human-Machine Interaction in AI-Assisted Medical Diagnosis: Challenges and Future Directions