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Progress Report
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Technological Advancements in Biomedicine for Healthcare Applications
Technology continues to play a major role in all aspects of society, particularly healthcare. Advancements such as biomedical image processing, technology in rehabilitation, and biomedical robotics for healthcare have aided in significant strides in the biomedical engineering research field. Technological Advancements in Biomedicine for Healthcare Applications presents an overview of biomedical technologies and its relationship with healthcare applications. This reference source is essential for researchers and practitioners aiming to learn more about biomedical engineering and its related fields.
Augmentation of Brain Function: Facts, Fiction and Controversy
Volume I, entitled “Augmentation of Brain Functions: Brain-Machine Interfaces”, is a collection of articles on neuroprosthetic technologies that utilize brain-machine interfaces (BMIs). BMIs strive to augment the brain by linking neural activity, recorded invasively or noninvasively, to external devices, such as arm prostheses, exoskeletons that enable bipedal walking, means of communication and technologies that augment attention. In addition to many practical applications, BMIs provide useful research tools for basic science. Several articles cover challenges and controversies in this rapidly developing field, such as ways to improve information transfer rate. BMIs can be applied to th...
Neural Information Processing
The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.
