BioMedical Engineering OnLine

http://pulse.embs.org/july-2016/chinas-13th-five-year-plan-offers-opportunities-biomedical-engineering/

"Biomedical engineering (BME) and the medical device industry show a remarkable rise in China, perhaps as a result of previous five-year plans which have emphasized these areas. According to the data of 2015 China Blue Book of Development of Medical Device Industry, during the 12th five-year plan, China focused intently on nurturing medical companies and developing medical equipment, regarding it as an emerging industry. The number of medical equipment manufacturers climbed to 17,211 in 2015, up from 14,603 in 2011..."

Medical robotics in the last few decades has achieved rapid development and has been widely applied in surgical field. The types of medical robotics include neurosurgery robotics, orthopedics robotics, laparoscopic robotics, vascular interventional robotics, prosthetics and exoskeleton robotics, assistive and rehabilitation robotics and capsule robotics. The robotics are important for surgery. Key technological research in medical robotics and automation is now very essential.

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This Special Issue will present a multifaceted, multidisciplinary view of how current research and developments in technology in the area of e-Health and m-Health can support improved health and lead to increased benefits for the patients. Contributions about novel technologies, sensors, software or apps, strategies for effective eHealth implementation, as well as studies on benefits and challenges of eHealth are welcome.

If you are interested in contributing to the Special Issue, please contact the Editor, Alessia Paglialonga (alessia.paglialonga@ieiit.cnr.it).

Submissions are invited to a new Special Issue on Artificial Intelligence in biomedical imaging. Artificial intelligence is increasingly used in various fields of life. One such area is medicine. Modern medical imaging provides an increasing number of features derived from different types of analysis,  including artificial intelligence. These features are most often used for a variety of analyses including fuzzy logic, evolutionary calculations, neural networks, or artificial life. Proper image processing, appropriate selection of features and artificial intelligence method can support medical diagnostics. This area has been in recent years the subject of many research papers and research grants. Consequently, this Special Issue is devoted to the subject of artificial intelligence, in its broadest sense, in biomedical engineering with particular emphasis on medical imaging. Therefore, I invite  authors who deal with new and modified machine learning methods, evolutionary calculations and their new applications in biomedical imaging. I hope that this Special Issue will be for readers a valuable supplement to the knowledge of new artificial intelligence methods and its applications in new areas of medical imaging.

If you are interested in contributing to the Special Issue, please contact the Editor, Robert Koprowski (robert.koprowski@us.edu.pl).

Signal processing and modeling techniques have been consistently playing a significant role in the field of neuroengineering research. This special issue will focus on the use and elaboration of latest signal processing and modeling techniques, e.g., deep machine learning, nonlinear dynamical approaches, etc., to analyze biomedical data relevant for neuroengineering research.

More specifically, these advanced techniques are applied to EMG, EEG, brain-computer and brain-machine interfaces, neural computation and modeling, neural prostheses, neuro-robotics, neuromodulation, etc. The special issue will be an international forum for researchers working in the fields of neuroengineering, computational neuroscience, and integrative physiology to report the most recent developments and ideas, especially in their clinical applications. This Special Issue emphasizes (but not limited to) the following research topics:

• Noise suppression and removal in analyzing neurophysiological signals
• Nonlinear dynamical approaches and multivariate and multiscale techniques for analyzing neurophysiological signals
• Application of machine learning and deep neural networks for detection and classification of and neurological diseases
• Advanced signal processing in brain-computer interface and neuro-prosthetic devices
• Acquisition and analysis of  neurophysiological signals from mobile and wearable devices and body sensor network techniques
• Clinical applications of advanced signal processing in neuroengineering

The Special Issue is Guest Edited by Fei Chen, Shi-xiong Chen and Dong-mei Hao. If you are interested in submitting to the Special Issue, please contact Fei Chen (fchen@sustc.edu.cn).

Submission deadline 28th February 2018.

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