Inspired by Star Trek: A Technology-Driven Approach to Personalized Medicine

The following article was part of a Star-Ledger and NJ.com op-ed series on engineering fields that will change the world by Rutgers School of Engineering faculty.

By Umer Hassan

Real world innovations–from submarines to self-driving cars–come straight from imaginary worlds of science fiction. Think Star Trek’s handheld tricorder, a medical diagnostic device that made its first appearance in the original TV series. This sci-fi precursor is now changing the face of personalized medicine by taking the tricorder concept to the next level.

Today, diabetics can anticipate a biosensor able to monitor their glucose levels through perspiration. An electrical graphene biosensor implant could detect genetic mutations as they happen, while UK researchers are developing a wearable biosensor that will collect data and assess the efficacy of rehab equipment and exercise.

Other biosensors will be able to quickly and inexpensively detect costly and potentially fatal medical conditions such as sepsis and AIDS. Together with Rutgers University colleagues, clinical and industry partners, my lab has been working to solve these global health challenges with new tools that focus on a highly personalized approach to medicine. Since the COVID-19 pandemic began, we are also hoping to apply this technology to fight against the coronavirus.

Sepsis–the body’s life-threatening response to infection–is not only deadly, it is the most expensive inpatient medical condition in the United States, with patients who develop sepsis often spending days in intensive care units at a cost of $10,000 a day–or more. Recognizing that sepsis is responsible for as many as six million largely preventable deaths a year, the World Health Organization has identified the prevention, diagnosis, and management of sepsis as a pressing global health priority.

By applying electrical and computer engineering skills to identify new biomarkers and devise machine-learning algorithms, or artificial intelligence systems, we hope to dramatically improve clinicians’ abilities to diagnose, predict–and ultimately manage–sepsis. Simply reacting to diseases is no longer enough–we need to predict them in order to treat patients in a much smarter way.

To this end, we are building an inexpensive medical device that even minimally trained health care providers can use to accurately diagnosis sepsis. This automated device would cost less than $10 a test and be simple to operate not only in resource-limited settings, but anywhere where a rapidly confirmed diagnosis of sepsis is needed.

In sub-Saharan Africa, where only one person in eight is even tested for HIV, many people infected with HIV go undetected until they develop severe complications from the disease. Those who are tested should be tested much earlier to receive access to therapeutics for their personalized care.

A related area of development includes cheap, disposable biosensors that will be as easy and convenient to use as a home pregnancy strip test to detect infections with people living with HIV/AIDS in underdeveloped sub-Saharan African nations. A secondary goal is to develop sensors able to monitor a patient’s response to the antiretroviral therapy they receive.

The positive health and economic impact of such sensors would be felt not only in underdeveloped nations, but also in the United States by reducing the cost of a single HIV test from hundreds of dollars to as little as $10.

My lab has also made the fight against COVID-19 an urgent research priority and a natural extension of our existing work. We are seeking to develop a sensor that could measure the ability of white blood cells to kill the virus in high-risk human patients. This could lead to new therapeutic interventions, and could help develop a rapid, easy-to-use widespread stratification test.

In terms of predicting health outcomes and personalizing therapeutic approaches economically, we are also collaborating with Robert Wood Johnson Medical Hospital to do just that by combining sensor data and electronic medical records data.

Advancing personalized medicine and health monitoring is also a key concern of my Rutgers School of Engineering colleague, electrical and computer engineering associate professor Mehdi Javanmard. His lab has been developing a “lab on a chip” with the potential to monitor everything from health to germs to pollutants.

His team’s innovative biosensor could be used in hand-held devices–akin to that old Star Trek tricorder–or wearable devices that measure biomarkers to track your health and exposure to harmful bacteria, viruses, and pollutants.

While a single biomarker is measured in home pregnancy tests, multiple biomarkers need to be tracked simultaneously to diagnose and manage complex health conditions such as heart disease, cancer, and inflammatory diseases. The lab on a chip is designed to meet that challenge. Additionally, within the next three to five years, a lab on a chip could quickly analyze a sample of what–if any–harmful bacteria are on a doorknob of a bathroom; test a salad for the presence of E. coli or Salmonella bacteria; or even quickly test for the flu.

In time, a future version of the smartphone will be the true tricorder of tomorrow. Smartphone based health sensors will ultimately transform the smartphone into an intelligent, all-in-one monitoring and diagnostic device.

Umer Hassan, an assistant professor of electrical and computer engineering at Rutgers University School of Engineering, holds a joint appointment at Rutgers Global Health Institute.

Safeguarding Tomorrow: Winning the Cybersecurity Arms Race

The following article was part of a Star-Ledger and NJ.com op-ed series on engineering fields that will change the world by Rutgers School of Engineering faculty.

By Saman Zonouz

Chances are, when you think of warfare, you think of soldiers in physical battles intended to kill people and destroy property. But today, we are threatened by a new kind of war. Cyber–or computer–warfare, which involves remote attacks and reconnaissance through nation-funded channels, is emerging–and being increasingly deployed–in place of more costly, conventional attacks.

At the same time, industry, government and university researchers have recognized the need for innovative approaches to thwart potentially devastating cyberattacks on everything from hospitals and voting machines to power grids and military systems. Headway has been made, for instance, by the U.S. Naval Academy’s renewed insistence on teaching celestial navigation to limit undue reliance on GPS. While steps are being taken to overcome inherent cloud data and vulnerabilities in the Internet of Things (which encompasses everything connected to the Internet), there is increased pressure to establish cyberwarfare rules to mitigate future state-on-state cyber conflicts.

Attackers know that few things are more harmful to a society’s economy, public health and safety than the disruption of essential services provided by cyber-physical infrastructures such as power grids. And few things are more attractive targets for nation/state hackers and attackers than these infrastructures. The cost of a major power outage is astronomical: the massive 2003 Northeast electrical blackout affected 50 million people and cost an estimated $6 billion. Beginning in 2015, we have seen the impact of repeated Russian cyberattacks on Ukraine’s power grid, which disrupted the flow of electricity to consumers.

As the cybersecurity arms race between defenders and attackers escalates, researchers are asking: How can we protect vulnerable infrastructures from the disruption of cyberattacks?

While a number of purely cybersecurity protections have been developed in the past few decades for computing systems, these solutions are not directly applicable to cyber-physical systems such as power grids that seamlessly integrate computation and physical components to provide essential services.

Recognizing the vulnerability of our infrastructures to hackers and attackers, the U.S. government created programs such as the National Science Foundation’s to cyber-physical systems program to fuel research in this field. The program has funded my ongoing research at the Rutgers School of Engineering in this area, which focuses on systems that have both cyber and physical components that interact to ensure that everything operates smoothly.

Many current cyber defense solutions are reactive; when an attack occurs, they react and adapt. We are, instead, developing proactive cyber defense solutions able to anticipate and respond effectively to cyberattacks. We also are designing secure mechanisms for cyber-physical critical infrastructures.

The first step in determining how best to protect electricity grids from cyberattacks is to pinpoint the weaknesses likely to be attacked. Manual tolerance procedures and cyber-security solutions alone offer inadequate protection. By identifying such weaknesses, effective safeguards can be designed, so that if an attack happens, built-in defenses will exist.

While our solutions are inherently complicated due to the complex dynamics and interactions of cyber-physical systems, they are truly resilient. These systems’ resilience does not guarantee absolute protection against any attack, yet it enables them to analyze, predict, tolerate, respond to – and recover from – highly debilitating cybersecurity attacks in near real time.

To date, we have successfully developed automated intrusion detection systems and automated response systems that we are transitioning to some industry partners to help them safeguard their own products.

This means that cyber-physical systems administrators and power grid operators will be able to both monitor incident response capabilities as well as to provide proactive response measures that will enable them to avoid future incidents–and ultimately protect some of our most vulnerable, yet essential, cyber-physical infrastructures.

Lasting solutions to pressing societal problems often result from productive research collaborations, which is why Rutgers researchers are also working together with Texas A&M University, the University of Illinois at Urbana-Champaign, Pacific Northwest National Labs and Sandia National Labs on a recently funded U.S. Department of Energy project to enhance the reliability and resilience of our energy infrastructure.

The project will revolutionize the way energy management systems are designed, deployed and operated by building a secure, next-generation, end-to-end energy management system that is both cyber-physical and secure. By being able to detect malicious and abnormal events by fusing cyber and physical data–and facilitating online and automated control actions – these energy management systems will further safeguard cyber-physical critical infrastructures.

Saman Zonouz is an associate professor in the Department of Electrical and Computer Engineering at Rutgers University School of Engineering.

ECE Graduate Bo Li (2017 PhD) to receive the 2020 IEEE Signal Processing Society Young Author Best Paper Award

ECE Graduate Bo Li (2017 PhD) has been selected to receive the 2020 IEEE Signal Processing Society Young Author Best Paper Award for the paper "Optimum Co-Design for Spectrum Sharing between Matrix Completion Based MIMO Radars and a MIMO Communication System", IEEE Transactions on Signal Processing, September 2016 that he co-authored with ECE Professors Athina Petropulu and Wade Trappe.

The paper addresses the ever-growing need for bandwidth that wireless devices face by allowing sharing of spectrum with radars. The authors show that spectrum that was previously reserved for radar can be used to share spectrum between radar and communication systems. To reap the advantages of the available spectrum, the interference between the two systems must be managed. While managing interference is a classic problem in the radar and communication community, prior to this paper there had been very little work that jointly examined interference between these two different types of technologies. This paper (along with some earlier conference versions of it by the authors) introduces a new line of research for cooperative design of the two systems that aims to control interference between radar and communication systems. Compared to non-cooperative approaches in the literature, the proposed approach can improve spectrum utilization because it introduces more degrees of freedom. In particular, the paper jointly optimizes the signaling schemes of a MIMO radar based on sparse sensing and matrix completion (MIMO-MC radar) and a communication system. The result is that interference is minimized while both systems meet their operational objectives.

This work was part of Bo Li’s PhD thesis, for which he also received the 2017 Robert T. Hill Memorial Best Dissertation Award, given by the Institute of Electrical and Electronics Engineers (IEEE) Aerospace and Electronics Systems Society (AESS). Bo is currently working on radar based perception for autonomous vehicles at Aurora. He and co his ca-authors will be recognized at the Awards Ceremony at the IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP) 2021 in Toronto, Canada.

Congratulations to Bo, Athina and Wade!

Star Trek-inspired personalized medicine is on the horizon

Rutgers ECE professor Umer Hassan researches personalized medicine.   An opinion article Dr. Hassan wrote for the Star Ledger was published online at NJ.com.   Umer Hassan, an assistant professor of electrical and computer engineering at the Rutgers University School of Engineering, holds a joint appointment at Rutgers Global Health Institute.

Real-world innovations – from submarines to self-driving cars – come straight from imaginary worlds of science fiction. Think Star Trek’s handheld tricorder, a medical diagnostic device that made its first appearance in the original TV series.  

This sci-fi precursor is now changing the face of personalized medicine by taking the tricorder concept to the next level. Today, diabetics can anticipate a biosensor able to monitor their glucose levels through perspiration. A biosensor implant could detect genetic mutations as they happen, while British researchers are developing a wearable biosensor that will collect data and assess the efficacy of rehabilitation equipment and exercise.

Link to the full article on NJ.com

IEEE Meet the ECE Faculty Panel

 

IEEE and Minority Engineering Educational Task (MEET) will be hosting a Meet the ECE Faculty Panel on Thursday, 12/3 at 12pm as a wrap-up /season finale to the Coffee Chats we've had this semester. This panel will be a discussion with Prof. Trappe, Godrich, Bajwa, and Sarwate on their research, professional experiences, and academic journeys. 

 

Dario Pompili elevated to IEEE Fellow

It is our great pleasure to inform you that the IEEE Board of Directors, at its November 2020 meeting, elevated Professor Dario Pompili to IEEE Fellow, effective 1 January 2021, with the following citation:

for contributions to underwater acoustic communication networks

Each year, following a rigorous evaluation procedure, the IEEE Fellow Committee recommends a select group of recipients for elevation to IEEE Fellow. Less than 0.1% of voting members are selected annually for this member grade elevation.

Congratulations on this outstanding recognition of professional achievement, Dario!

Sad news about Herbert Freeman

Herbert Freeman, former ECE colleague and State of New Jersey Professor of Computer Engineering, died Sunday morning November 15th.  Prof. Freeman died at his home in New Jersey, he was 94.  Joan, his wife of 65 years, and his daughters Nancy and Susan were with him. His son Robert predeceased him.

Herbert Freeman was recognized as a pioneer in Computer Science and Engineering.  He had a distinguished career and won many professional awards and honors.   He was the founder of MapText Inc. and he also served as Director of the CAIP center at Rutgers University.

More information about Dr. Freeman:

https://www.legacy.com/obituaries/nytimes/obituary.aspx?pid=197122184

https://en.m.wikipedia.org/wiki/Herbert_Freeman https://web.archive.org/web/20100913163224/

https://web.archive.org/web/20100913163224/http://www.ece.rutgers.edu/di...

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