Approximately 15 minute walk to Hawaii Convention Center

On Tuesday, May 29, Jose C. Principe, Distinguished Professor of Electrical Engineering, University of Florida, gave a lecture about "Time based computation with pulse trains", at the Conference Hall of the School of Electrical and Computer Engineering, National Technical University of Athens.

Numeric computation is at the core of man-made computation models and its mathematical foundations are very well understood. However, we humans very likely do not use the same principles. This talk described efforts to think out of the digital computation box and searched for alternate computational methodologies with pulse trains. After a brief introduction, the integrate-and-fire converter was described to convert analog signals into pulse trains and two approaches for processing information in pulse trains were discussed that can be implemented in ultra-low power digital hardware, preserving the asynchronous nature of the pulse domain representations. The first approach learns using machine learning the structure of the data in a training set and implements an approximation directly in finite state machines. The other approach, less developed, shows that it is possible to perform addition, multiplication and convolution with pulse trains without using binary representations, with an accuracy compatible with IoT applications..

The deadline date of June 4 is approaching for the submission of two and four-page papers as well as tutorial and special session proposals.

The IEEE International Symposium on Biomedical Imaging (ISBI) is a scientific conference dedicated to mathematical, algorithmic, and computational aspects of biological and biomedical imaging, across all scales of observation. It fosters knowledge transfer among different imaging communities and contributes to an integrative approach to biomedical imaging. ISBI is a joint initiative from the IEEE Signal Processing Society (SPS) and the IEEE Engineering in Medicine and Biology Society (EMBS). The 2019 meeting will be held in Venice, Italy and will include tutorials, challenges and a scientific program composed of plenary talks, invited special sessions, as well as oral and poster presentations of peer-reviewed papers.

Soft robots continue to make headlines with their ability to squeeze, octopus-like, through narrow crevices; change shape; and survive impacts that would crush a traditional rigid robot. They distinguish themselves from their hard counterparts with their damage resilience, complex movements, and suitability for use with the human body. But as with many bipolar categories like soft and hard, it's in the in-between gradient areas that interesting hybrids and category-bucking solutions are found. Some now integrate skeletal components, while some use variable-stiffness materials; yet others seek to move from hard to soft more seamlessly through the design of actuators and sensors. In addition, soft robots are also now taking bioinspiration from other, less totally soft organisms (including humans).

Today, on one hand, software frameworks for deep-learning are becoming increasingly apable of training advanced neural-network models, while on the other hand, heterogeneous hardware components such as GPUs, FPGAs and ASICs dedicated to deep learning are beginning to challenge the computational limits of Moore's law. Together, these trends have influenced connected health systems, which comprise various processes for sensing, data transfer, storage and analysis in an effort to improve overall health and wellbeing. Increasingly, each of these processes are being infused with artificial intelligence (AI), leading to unprecedented advances in how automated care is being delivered.

To this end the Editorial Office of the Journal of Biomedical and Health Informatics (J-BHI) in collaboration with the Organizing Committees of the Organizing Committees of the IEEE International Conference on Biomedical and Health Informatics (BHI 2018) and the IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN 2018) organized a special issue on Special Issue on AI-Enabled Connected Health Informatics. This Special Issue addresses advances in all aspects of a connected health and informatic systems where AI has been evident, including sensing, transfer, storage and analytics of biomedical data. This is a trending area with new innovations produced virtually daily. Furthermore, the proposed topic should be viewed as being applicable to BSN and BHI audiences, which complement each other through advances in informatics and systems, respectively. This Special Issue also provides an opportunity for submissions that capture the end-to-end view of solutions that use automated informatics to address key healthcare scenarios.

We would like to cordially thank the Guest Editors, Prof. Chris Nugent, Prof. Georgia Tourassi and Dr. Shuayb Zarar for their significant contribution to the organization of this Special Issue and their continuous effort to attract 59 innovative papers of high quality to J-BHI from leading research groups worldwide.

A Locomotion Control Platform with Dynamic Electromagnetic Field for Active Capsule Endoscopy Fahad N. Alsunaydih, Jean-Michel Redoute, Mehmet R. Yuce Early Access Conventional radiological and endoscopic techniques utilizing long tubes were ineffective in visualizing the small bowel mucosa until the development of Wireless Capsule Endoscopy (WCE).



A Novel System to Measure Infants' Nutritive Sucking During Breastfeeding: the Breastfeeding Diagnostic Device (BDD) Longtu Chen, Ruth Lucas, Bin Feng Early Access Breastfeeding is optimal for infant health, but more than 66% of mothers cease exclusive breastfeeding within 3 months after giving birth. Evaluating infants' sucking effort provides valuable diagnosis to mothers encountering barriers with breastfeeding.