ISBI 2018
April 4-7, 2018 in Washington DC
Registration in NOW open! 

DEADLINE to submit 1 page abstracts is Monday, 15, January 2018
Housing now OPEN for ISBI 2018
Sponsorship Opportunities Now Available
   Are you interested in a sponsorship opportunity at ISBI 2018? Find out more HERE
EMBC 2018
EMBC 2018 will be on July 17-21, 2018 in Honolulu, Hawaii 
Registration is NOW open! 
Take this time to use any funding you have 
available by
completing early registration!
Call for Contributed Papers and 1 Page Papers
Author Instructions for Contributed and 1 Page Papers

C ontributed Papers-Full are presented either as an oral presentation or a poster presentation. The type of presentation will be determined by the Conference Editorial Board based on factors such as the reviewer's suggestions and topic of the paper. All presented and contributed papers will be published in IEEE Xplore and indexed by PubMed and Medline.

At least one author of the paper must be registered at the appropriate full conference rate (Member, Non-member, Student member, Student non-member) in order to upload the final paper. If complete payment of a registration fee is not received, authors will not be able to proceed with uploading their final manuscript. While any author of the paper may be registered, only the designated "corresponding author" may upload the final paper. Once a manuscript has been uploaded, the registration fees cannot be refunded. Please be sure that the attending author completes payment and uploads the final paper. This means that they must be the "corresponding author".

Housing now OPEN for EMBC 2018
Hilton Hawaiian Village Waikiki 
Beach Resort

Approximately 15 minute walk to Hawaii Convention Center

2005 Kalia Road Honolulu, Hawaii 96815
Tel:  +1-808-949-4321 

Click here to book at EMBC discounted rates, before June 13, 2018.

Sponsorship Opportunities Now Available
Are you interested in a sponsorship opportunity at EMBC 2018? Find out more HERE
Will you be adding your name to this years EMBC WALL OF FAME????
BHI - BSN 2018
4-7, March 2018 in Las Vegas, Nevada
IEEE International Conference on Wearable & 
Implantable Body Sensor Networks
DEADLINE for FINAL Upload of Papers & Abstracts is January 15, 2018
The IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN) 2018 is the 15th in a series of annual conferences sponsored by IEEE EMBS dedicated to address the challenges in the areas of sensor-exploiting medical/healthcare systems and networking. IEEE BSN18 will be co-located with the HIMSS2018 (Health Information Management Systems Society Annual Conference) and the IEEE BHI2018 (IEEE International Conference on Biomedical and Health Informatics) in Las Vegas, March 4-7, 2018. The joint program will have world-renowned speakers from research institutes, government agencies, and industry. More than a thousand attendees are expected in this leading event for healthcare and medical technologies.

Call for Papers
The 2nd IEEE Life Sciences Conference (LSC) will be held in Montreal, Canada 28-30 October 2018. The IEEE Life Sciences Technical Community (LSTC), which is supported by multiple IEEE member societies, is the sponsor of the conference. As such, the conference will cover diverse topics within the theme.

LSC 2018 will include tutorials and a scientific program composed of plenary talks, invited sessions, Lecture and poster presentations of peer-reviewed papers. In addition, there will be a host of special events, including a Standards Track, an IEEE Women in Engineering event, a High School Competition, a graduate students' competition, and other Initiatives to be announced shortly.
Nominations are now being accepted for 2018 EMBS Awards
EMBS sponsors Awards of member recognition for technical and professional excellence, service to the society, local activities, publications and student papers. Nominations for these awards are accepted annually in January, Award Recipients are announced in April and the awards are presented at the Society's Annual International Conference.
We would like to extend the chance to nominate a EMB Chapter for an award this year. Please click on the button below to submit a nomination.

Accepting Nominations for:

Society Awards:
  • Academic Career Achievement Award
  • Professional Career Achievement Award
  • Early Career Achievement Award
  • Distinguished Service Award
  • Technical Achievement Awards

Chapter Awards: 

  • Outstanding Chapter Award 
  • Best New Chapter Award
  • Outstanding Performance Award for a Student Chapter or Club
  • Best New Student Chapter or Club Award

Save the Date
Technical Activities Spotlight
BIIP Committee Updates
The BIIP committee members have been performing scientific reviews for the 2018 IEEE International Symposium for Biomedical Imaging (IEEE-ISBI) over the past few months. IEEE-ISBI is a leading scientific conference dedicated to mathematical, algorithmic, and computational aspects of biological and biomedical imaging, and EMBS has been a technical co-sponsor of ISBI since 2002. 

We would like to highlight a recent paper from our committee member Dr. Shuo Li, entitled "Full Left Ventricle Quantification via Deep Multitask Relationships Learning". This paper presents a novel machine learning approach for cardiac image analysis. Its early conference version won the 2017 MICCAI young scientist award. A synopsis of the paper is as follows:
"Full quantification of left ventricle (LV) indices is one of the most important clinical tasks required for cardiac disease diagnosis. There are significant technical challenges associated with this problem, such as high variability of cardiac structure across subjects, the complexity of temporal dynamics of cardiac sequences, etc. Dr. Shuo Li's group has been working closely with clinicians on this problem over the last few years. In their previous award-winning work (MICCAI young scientist award) and this paper published by the journal of Medical Image Analysis, they proposed a deep multitask relationship learning network to tackle this problem. The proposed approach features the use of a deep convolution neural network (CNN) for expressive cardiac representation and two parallel recurrent neural networks for modeling temporal dynamics of cardiac sequences. Further, the proposed approach estimates three types of LV indices with a Bayesian framework that automatically learns multitask relationships. The proposed approach is the first exploration of multitask relationship leaning in deep neural networks, and experimental results demonstrate its effectiveness for accurate prediction. This approach can potentially be used for comprehensive clinical assessment of global, regional and dynamic cardiac functions, which can dramatically reduce the current clinical diagnostic workflow and improve the overall cardiac care.".

Chapter Spotlight
We created the Opportunity to learn one of the popular and applicable  VHDL language for Medical applications and Network with fellow programmers and coding enthusiasts. The research on Internet of Things (IoT) is being promoted in the field of Medical Application. This workshop is to intend to impart knowledge in the basics of IoT in the field Medical application. The hands on training is provided in the different sensors with FPGA board. Advanced applications included in the workshop to provide knowledge on current industrial trends. 

Finally, the best project idea contest has been conducted and winners awarded with cash prizes.Totally 52 students (IEEE EMBS) attended the workshop. The resource person created knowledge to students, about the details associated with the research from this workshop.
Publications Spotlight
Imaging Depression
More than 15 million people in the United States suffer from depression. According to a 2015 U.S. Centers for Disease Control (CDC) study, half of the 120 Americans who take their lives every day have been diagnosed with the disease. Despite the urgency of these numbers, science has yet to provide an adequate solution: A third of all people have no response to antidepressants whatsoever, and for all existing treatments-antidepressants, ECT, TMS, and DBS-there's only a general understanding of how and why they work. 

This reflects a larger problem in the field of neuropsychology: what causes depression in the first place? Some researchers have argued that depression symptoms are a direct response to the interactions among neurotransmitters, neurocircuits, and the immune system. Recently, by using functional magnetic resonance imaging (fMRI) on patients diagnosed with depression to observe brain activity in real time, researchers were able to find some commonalities in the degree and location of abnormal circuitry. 

Tunable and Lightweight On-Chip Event Detection for Implantable Bladder Pressure Monitoring Devices
Robert Karam  ;  Steve J.A. Majerus ;  Dennis J. Bourbeau ; 
Margot S. Damaser ; and  Swarup Bhunia
Lower urinary tract dysfunctions, such as urinary incontinence and overactive bladder, are conditions that greatly affect the quality of life for millions of individuals worldwide. For those with more complex pathophysiologies, diagnosis of these conditions often requires a urodynamics study, providing physicians with a snapshot view of bladder mechanics. Recent advancements in implantable bladder pressure monitors and advanced data analysis techniques have made diagnosis through chronic monitoring a promising prospect. However, implants targeted at treatment must remain in the bladder for long periods of time, making minimizing power consumption a primary design objective. Currently, much of the typical implant's power draw is due to data transmission. Previous work has demonstrated an adaptive rate transmission technique to reduce power consumption. 

However, the ultimate reduction in power consumption can only be attained when the device does not transmit bladder pressure samples, but rather bladder events. In this paper, we present an algorithm and circuit level implementation for on-chip bladder pressure data compression and event detection. It is designed to be a complete, tunable, and lightweight diagnosis and treatment framework for bladder pressure monitoring implants, capable of selectively transmitting compressed bladder pressure data with tunable quality, "snapshots" of significant bladder events, or simply indicate events occurred for the highest energy efficiency. The design aims to minimize area through resource reuse, leading to a total area of 1.75 mm2, and employs advanced VLSI techniques for power reduction. With compression and event detection enabled, the design consumes roughly 2.6 nW in TSMC 0.18-μm technology. With only event detection, this reduces to 2.1 nW, making this approach ideal for long-life implantable bladder pressure monitoring devices. .

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Please send any chapter news, events or happenings, call for papers, distinguished lecturer visits, awards received by members, etc. to the EMBS Content Form for inclusion in next week's newsletter. We look forward to hearing from you.

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