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Paperback. Condizione: Brand New. 250 pages. 7.49x0.88x9.22 inches. In Stock.

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Paperback. Condizione: new. Paperback. AI-Driven Human-Machine Interaction for Biomedical Engineering Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.

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Condizione: New. In English.

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Condizione: New. 2026. paperback. . . . . .

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Condizione: New. Offers practical insights into AI-driven methodologies for enhanced human-machine collaboration in healthcare and beyondProvides foundational knowledge of machine learning principles applicable across diverse industriesEquips reade.

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Paperback. Condizione: New. 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.…

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: Brand New. 250 pages. 7.49x0.88x9.22 inches. In Stock.

Paperback. Condizione: new. Paperback. AI-Driven Human-Machine Interaction for Biomedical Engineering Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Kartoniert / Broschiert. Condizione: New. 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 Int.

Condizione: New. 2026. paperback. . . . . . Books ship from the US and Ireland.

Condizione: New. Bridges deep learning techniques with practical cardiac robotic surgery applications for improved clinical outcomes and safetyOffers clear explanations and case studies to simplify complex AI concepts for multidisciplinary audiences.

Paperback. Condizione: New. 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.…

Paperback. Condizione: new. Paperback. AI-Driven Human-Machine Interaction for Biomedical Engineering Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condizione: Neu. Neuware - 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. …

Taschenbuch. Condizione: Neu. Neuware - Deep Learning for Cardiac Signal Analysis in Robotic Applications delves into the transformative role of artificial intelligence in enhancing robotic-assisted cardiovascular procedures. The book starts with the fundamentals of cardiac signals and deep learning, introducing key heart modalities, including the physiological underpinnings and challenges of signals like ECG and BCG and an overview of deep learning architectures relevant to signal processing. Pre-processing and feature extraction techniques are detailed to prepare readers for advanced analysis. Other sections focus on AI-enhanced cardiac signal analysis, covering arrhythmia detection, myocardial ischemia diagnostics, hypertension monitoring via BCG, and explainable AI approaches for fetal arrhythmia monitoring.The final section integrates AI with robotic cardiac surgery, addressing real-time signal integration, AI-guided intervention precision, intraoperative decision support, postoperative monitoring, and future trends in cardiac AI and robotic-assisted surgery. Addressing the complexities of heart signal interpretation amidst the dynamic environment of cardiac surgery, this book meets the critical need for a comprehensive resource that bridges deep learning advances with practical surgical applications. It responds to the challenge of understanding intricate bio-signals, such as ECG, VCG, and BCG, by providing clear explanations, case studies, and methodological insights tailored to improve surgical precision, safety, and patient outcomes.…

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