Enabling Clinical Research + Practice
The 2021 SENSE.nano symposium will focus on human subjects research, exploring how sensors and sensing systems can enable current medical studies and future clinical practice. Broken into two half-day webinars, SENSE.nano 2021 will investigate human health through various technologies including motion capture, physiological monitoring, and sensing tools for the study of bodily fluids.
Discussions and presentations around MIT research, clinical needs, societal changes, and implications will serve to help celebrate the reopening of the expanded Clinical Research Center (CRC) at MIT.
Day 1: October 25 (Monday): 1:00 PM – 4:30 PM EDT
Day 2: October 26 (Tuesday): 12:00 PM – 4:30 PM EDT
Please visit SENSE.nano 2021 for full agenda.
Welcome and Keynote
Dr. Anthony is Associate Director of MIT.nano, Faculty Lead for the Industry Immersion Program in Mechanical Engineering, and Co-Director of the MIT Clinical Research Center. With over 25 years’ experience in product realization—Dr. Anthony won an Emmy (from the Academy of Television Arts and Sciences) in broadcast technical innovation—Dr. Anthony designs instruments and techniques to monitor and control physical systems. His work involves systems analysis and design and calling upon mechanical, electrical, and optical engineering, along with computer science and optimization, to create solutions.
The focus of Dr. Anthony’s research is computational instrumentation—the design of instruments and techniques to measure and control complex physical systems. His research includes the development of instrumentation and measurement solutions for manufacturing systems and medical diagnostics and imaging systems. In addition to his academic work, he has extensive experience in market-driven technology innovation, product realization, and business entrepreneurship and commercialization at the intersection between information technology and advanced manufacturing. His teaching interests include the modelling of large-scale systems in a wide variety of decision-making domains and the development of optimization algorithms and software for analyzing and designing such systems. He has extensive experience in market-driven technology innovation as well as business entrepreneurship.
Vladimir Bulović is a Professor of Electrical Engineering at the Massachusetts Institute of Technology, holding the Fariborz Maseeh Chair in Emerging Technology. He directs the Organic and Nanostructured Electronics Laboratory, co-leads the MIT-Eni Solar Frontiers Center, leads the Tata GridEdge program, and is the Founding Director of MIT.nano, MIT's new 200,000 sqft nano-fabrication, nano-characterization, and prototyping facility. He is an author of over 250 research articles (cited over 50,000 times and recognized as the top 1% of the most highly cited in the Web of Science). He is an inventor of over 100 U.S. patents in areas of light emitting diodes, lasers, photovoltaics, photodetectors, chemical sensors, programmable memories, and micro-electro machines, majority of which have been licensed and utilized by both start-up and multinational companies. The three start-up companies Bulović co-founded jointly employ over 350 people, and include Ubiquitous Energy, Inc., developing nanostructured solar technologies, Kateeva, Inc., focused on development of printed electronics, and QD Vision, Inc. (acquired in 2016) that produced quantum dot optoelectronic components. Products of these companies have been used by millions. Bulović was the first Associate Dean for Innovation of the School of Engineering and the Inaugural co-Director of MIT’s Innovation Initiative, which he co-led from 2013 to 2018. For his passion for teaching Bulović has been recognized with the MacVicar Fellowship, MIT’s highest teaching honor. He completed his Electrical Engineering B.S.E. and Ph.D. degrees at Princeton University.
Professor Elazer Edelman is the Director of MIT’s Institute for Medical Engineering and Science (IMES) and holds tenured faculty appointments in the Department of Medicine at Harvard Medical School, and in the Division of Health Sciences and Technology at the Massachusetts Institute of Technology. He is the Director of the Harvard-MIT Biomedical Engineering Center and of MIT’s Clinical Research Center, and the current occupant of the Edward J. Poitras Chair at MIT.
Elazer Edelman received Bachelor’s and Master’s Degrees in Electrical Engineering from the Massachusetts Institute of Technology, an M.D. degree with distinction from Harvard Medical School, and then his Ph.D. in Medical Engineering and Medical Physics from the Massachusetts Institute of Technology. He is board certified in Internal Medicine, and in Cardiovascular Medicine, and currently serves as one of the Core Attending Physicians in the acute coronary care unit at the Brigham and Women’s Hospital of the Harvard Medical School.
His research interests combine his scientific and medical training. His laboratory has earned international recognition in investigation, diagnosis, and treatment of various cardiovascular diseases. He and his laboratory have pioneered basic findings in vascular biology and the development and assessment of biotechnology, especially at the interface of tissues, devices, and materials and, in particular, imaging in cardiovascular disease and fusion imaging. Most recently, he and his students have focused on machine learning and artificial intelligence in the diagnosis and prognostication of critical diseases like aortic stenosis.
Dr. Edelman also directs the Harvard-MIT Biomedical Engineering Center, dedicated to applying the rigors of the physical sciences to elucidate fundamental biologic processes and mechanisms of disease. Many of his findings are now in clinical trial validation. Almost 350 students and postdoctoral fellows have passed through Dr. Edelman's laboratory, enabling publications of numerous papers and patents. He is a fellow of the American College of Cardiology, American Heart Association, Association of University Cardiologists, American Society of Clinical Investigation, American Institute of Medical and Biological Engineering, American Academy of Arts and Sciences, National Academy of Medicine and National Academy of Engineering, and National Academy of Inventors. As Chief Scientific Advisor of Science: Translational Medicine, he has set the tone for the national debate on translational research and innovation.
In her role as Medical Director, Cecilia Stuopis provides strategic and clinical leadership for all MIT Medical services including primary and specialty care, ancillary services, community wellness, student mental health and counseling, and campus public health.
Prior to coming to MIT, Stuopis served as the Vice President and ACO Executive Medical Director of Dartmouth-Hitchcock in New Hampshire, and served as Chair of the Department of Obstetrics and Gynecology, Nashua Division for 11 years. She holds a Master of Science in Healthcare Delivery Science from Dartmouth College, and holds a Medical Doctorate from the University of Nevada, School of Medicine. She recently became a Certified Physician Executive through the American Association of Physician Leadership. Stuopis is also an MIT alumna, having earned her Bachelor of Science in Aeronautics and Astronautics.
Session 1: Movement and Motion
Ellen Roche is currently an Associate Professor (W.M Keck Foundation Career Development Professor) at the Institute for Medical Engineering and Science and the Department of Mechanical Engineering at the Massachusetts Institute of Technology. She directs the Therapeutic Technology Design and Development Lab.
Roche completed her PhD at Harvard University School of Engineering and Applied Sciences. Her research focuses on applying innovative technologies to the development of cardiac devices. Her research includes development of novel devices to repair or augment cardiac function using disruptive approaches such as soft robotics, combination of mechanical actuation with delivery of cell therapy, and use of light activated biodegradable adhesives.
Dr. Roche was employed in the medical device industry for over five years as a research and development engineer and employs her understanding of the medical device industry and the regulatory pathways to medical device commercialization in her academic research. She is the recipient of multiple awards including the Fulbright International Science and Technology Award, the Wellcome Trust Seed Award in Science, an American Heart Association Pre-Doctoral Award, a National Science Foundation CAREER Award, an NIH Trailblazer Award and a Charles H. Hood Award for Excellence in Child Health Research.
The prevalence of single ventricle physiology is estimated to be ~1 in 3000 live births. Currently, the preferred treatment is a series of surgeries resulting in a palliative Fontan physiology. The Fontan circulation connects systemic and pulmonic circuits in series, rather than in parallel, via a surgical connection called the Fontan shunt located in the inferior vena cava (IVC). While this treatment allows patients to survive with a single ventricle, there are a myriad of deleterious effects associated with the Fontan circulation that are precipitated from the abnormal hemodynamics.
Recently, respiratory mechanics have been identified as the governing contributor to changes in Fontan flow patterns and resulting retrograde flow. Development in therapies for Fontan patients, and Fontan survival rates has stagnated over the past 20 years. While there is great interest in identifying and developing interventions for these patients, both invasive and non-invasive, the ability to explore and test potential therapies remains limited. There is no working animal model, nor are there any sophisticated in vitro or in silico models that can recreate the complex Fontan physiology. This gap in the field limits the development of therapeutic solutions.
Roche will discuss how her group builds quantitative tools that can serve as test platforms for interventions for the single ventricle physiology. Her group builds physical testbeds that allow them to quantify the effect of breathing mechanics on hemodynamics in silico, in vitro and validate them with a clinical imaging study in patients at Boston Children’s Hospital. By monitoring critical hemodynamic indicators like IVC retrograde flow, hepatic venous pressure, and cardiac return, they aim to predict potentially beneficial interventions on the benchtop that can allow them to predict the impact of invasive and non-invasive interventions on this patient group.
Prof. Jeehwan Kim's group at MIT focuses on innovations in nanotechnology for next generation computing and electronics. Prof. Kim joined MIT in September 2015. Before joining MIT, he was a Research Staff Member at IBM T.J. Watson Research Center in Yorktown Heights, NY since 2008 right after his Ph.D. He worked on next generation CMOS and energy materials/devices at IBM. Prof. Kim is a recipient of 20 IBM high value invention achievement awards. In 2012, he was appointed a “Master Inventor” of IBM in recognition of his active intellectual property generation and commercialization of his research. After joining MIT, he continuously worked nanotechnology for advanced electronics/photonics. As its recognition, he received LAM Research foundation Award, IBM Faculty Award, DARPA Young Faculty Award, and DARPA Director’s Fellowship. He is an inventor of > 200 issued/pending US patents and an author of > 50 articles in peer-reviewed journals. He currently serves as Associate Editor of Science Advances, AAAS. He received his B.S. from Hongik University, his M.S. from Seoul National University, and his Ph.D. from UCLA, all of them in Materials Science.
Electronic skins (e-skins)—electronic sensors mechanically compliant to human skin—have long been developed as an ideal electronic platform for noninvasive human health monitoring. For reliable physical health monitoring, the interface between the e-skin and human skin must be conformal and intact consistently. However, conventional e-skins cannot perfectly permeate sweat in normal day-to-day activities, resulting in degradation of the intimate interface over time and impeding stable physical sensing.
In this talk, Kim will present a sweat pore–inspired perforated e-skin that can effectively suppress sweat accumulation and allow inorganic sensors to obtain physical health information without malfunctioning. The auxetic dumbbell through-hole patterns in perforated e-skins lead to synergistic effects on physical properties including mechanical reliability, conformability, areal mass density, and adhesion to the skin. The perforated e-skin allows one to laminate onto the skin with consistent homeostasis, enabling multiple inorganic sensors on the skin to reliably monitor the wearer’s health over a period of weeks.
Humans are supremely adaptive. That makes measurement difficult because the act of measuring may change the behavior to be measured. With a view to improving devices to treat balance disorders, we try to quantify the neuro-mechanical dynamics of upright human balance. The usual approach to dynamic system identification applies perturbations and observes their consequences, but perturbing upright balance induces humans to change how they balance (e.g. they crouch).
A solution Hogan pursued takes advantage of the noisiness (stochasticity) of the neuromotor system. Humans cannot stand perfectly still. However, the temporal fluctuations of their ground reaction force vectors are not entirely random—they exhibit surprising patterns when mapped to the frequency domain. By modeling this phenomenon Hogan successfully estimated the net multi-variable neuro-mechanical impedance (stiffness and damping) about the hip and ankle—without perturbing the subjects.
Session 2: Physiological Monitoring
Paul Blainey is a core member of the Broad Institute of MIT and Harvard and an associate professor in the Department of Biological Engineering at MIT. An expert in microanalysis systems for studies of individual molecules and cells, Blainey is applying such technologies to advance understanding of functional properties of molecules and cells and the mechanisms underlying these properties. Broadly, research in the Blainey group integrates molecular, optical, microfluidic, and computational tools to understand and engineer cellular activities related to a wide range of health challenges.
Genetic screens are important life science research tools that can teach us how genetic elements in our bodies’ cells relate to normal health, disease, and the way drug therapies work by checking the effects of engineered genetic changes in laboratory samples. Recently, CRISPR and other technologies have enabled screening of many genetic elements at once in ‘pooled’ formats.
Here, Blainey will present optical pooled screening — a new method of pooled genetic screening – which enables researchers to link pooled genetic ‘perturbations’ with visually observable phenotypes in human cells. This works by sequencing a tag inside each cell that identifies the genetic perturbations present. Microscopy-based readout enables genetic screens for new types of biological functions and at scales needed for comprehensive ‘genome-wide’ screens of tens or hundreds of millions of cells.
Liao earned his computer science PhD at MIT in Aug 2021, advised by Prof Polina Golland. He studies machine learning and develop computational tools driven by clinical problems. Liao is excited about ubiquitous computing and its potential to advance health care. His PhD research has been supported by Merrill Lynch Fellowship and Siebel Fellowship.
Liao proposes and demonstrates a representation learning approach by maximizing the mutual information between local features of images and text. The goal of this approach is to learn useful image representations by taking advantage of the rich information contained in the free text that describes the findings in the image. Liao's method trains image and text encoders by encouraging the resulting representations to exhibit high local mutual information. He makes use of recent advances in mutual information estimation with neural network discriminators. Liao argues that the sum of local mutual information is typically a lower bound on the global mutual information. His experimental results in the downstream image classification tasks demonstrate the advantages of using local features for image-text representation learning.
Dr. Jongyoon Han is currently a professor in the Department of Electrical Engineering and Computer Science and the Department of Biological Engineering, Massachusetts Institute of Technology. He received B.S.(1992) and M.S.(1994) degree in physics from Seoul National University, Seoul, Korea, and Ph.D. degree in applied physics from Cornell University in 2001. He was a research scientist in Sandia National Laboratories (Livermore, CA), until he joined the MIT faculty in 2002. He received NSF CAREER award (2003) and Analytical Chemistry Young Innovator Award (ACS, 2009). His research is mainly focused on applying micro/nanofabrication techniques to a very diverse set of fields and industries, including biosensing, desalination / water purification, biomanufacturing, dentistry, and neuroscience. He is currently the lead PI for MIT’s participation for NIIMBL (The National Institute for Innovation in Manufacturing Biopharmaceuticals).
In the diagnostics and surveillance of COVID-19 and many other pathogens, it is necessary to be able to detect the lowest abundance virus or bacterial cells, often contained in a large volume of original sample. Current sample preparation workflow is not adequate to handle this challenge, therefore limiting the lower limit of detection around ~10 copies/uL, regardless of the downstream sensing methodologies used.
In this presentation, Han will demonstrate that we can address this sample preparation challenge directly by introducing an efficient electrokinetic concentration system, which can concentrate dilute detection targets (viruses, cells, biomolecules) from a large sample volumes (~100mL) into a small volume (as small as ~10pL), achieving extremely high level of effective signal enhancement for downstream detection. This may allow direct, non-amplifying detection of the target biomolecules, which could enable rapid, real-time monitoring of various targets.
Using the system, Han has demonstrated that low abundance viral and bacterial targets below ~1CFU/ml can be concentrated and detected reliably, by collecting low abundance targets from a large volume of original sample (1~100mL). This system could impact not only the disease diagnostics and monitoring, but also the detection of adventitious agents in standard bioprocessing, which is an ongoing challenge in pharmaceutical industry.
Catherine Ricciardi | DNP, ANP-BC, MIT Institute for Medical Engineering and Science
Tatiana Urman | Clinical Research Nurse Coordinator, MIT Institute for Medical Engineering and Science
Xiang (Shawn) Zhang | Postdoctoral Associate
Dexter Ang is the Chairman and Cofounder of Pison. Ang’s responsibilities include OEM partnerships, investor relations, and business development with consumer electronics and military clients. Ang is a SME for Human Factors for the Augmented Reality Enterprise Alliance (AREA). Drawing on his expertise in HCI and mechanical engineering, Ang led Pison’s development of its patented nerve-sensing ENG technology and integration for disruptive capabilities. Prior to founding Pison, Ang worked as a senior trader specializing in signal processing and low latency communication at Jump Trading—a market leader in high frequency trading.
Enabling humans to efficiently and naturally interact with robot and IoT systems will be critical to the future success and adoption of these emerging technologies. Neural interface wearables represent an advancing field of human-machine interface (HMI) technologies with the potential to overcome limitations that have previously been restrictive in these industries. For example, interacting with a smartphone while on the move, while gloves or PPE are donned, and when maintaining heads-up situational awareness causes user error and delays decision and action times. Pison's patented wearable neural interface gesture control technology allows users to quickly and accurately interact with electronic systems- e.g., indicating and sharing points of interest for robot waypoints by simply pointing and gesturing where the waypoint is desired. Gesture control expands the spectrum of when users can interact with robotic endpoints. As a result, these systems become accessible to 5x-10x more users throughout the course of a mission, allowing robots to realize their full potential as force multipliers.
Greg Ekchian, PhD, is an entrepreneur, engineer, and innovator. He has spent his career at the interface of academic research and life science start-ups. Greg is currently the co-founder and CEO of Stratagen Bio, where he is developing a suite of novel tissue oxygen sensors to personalize and customize treatments across a wide range of clinical indications. He was previously awarded the Blavatnik Fellowship in Life Science Entrepreneurship at Harvard Business School and the Kavanaugh Translational Innovation Fellowship at the Massachusetts Institute of Technology. Greg was also named to MIT Technology Review’s 35 Innovators Under 35 in 2020. He holds a BS in Biomedical Engineering from Boston University and an MEng and PhD in Materials Science and Engineering from the Massachusetts Institute of Technology.
A hardware and software engineer who started his career in measurement research at the UK’s National Physical Laboratory, developing new measurement techniques centered around audio, and industrial and medical ultrasonics. As a Research Engineer in the MIT M+Vision/LinQ biomedical innovation programme Ian co-created projects centered around unmet medical needs, leading hardware and software development of a rich variety of measurement device prototypes, leading to the spin-out of several companies, including Leuko. Now Chief Technology Officer and Co-founder of Leuko, Ian is driving the development of the PointCheck product through R&D, studies, and design for manufacturing.
Leuko is developing PointCheck, the first device to provide noninvasive neutropenia screening in the home, set to improve safety, efficacy and economics for chemotherapy. Started by Leuko's co-founders in the MIT M+Vision/LinQ programme, since spinning out, Leuko has been developing PointCheck with the support of developmental usability and performance studies at sites including the MIT CRC, to ensure a product that meets regulatory requirements around performance and usability, and is set to make impact.
Session 3: Imaging
Lester Wolfe Professor of Chemistry
MIT Department of Chemistry
Professor Moungi Bawendi received his A.B. in 1982 from Harvard University and his Ph.D. in chemistry in 1988 from The University of Chicago. This was followed by two years of postdoctoral research at Bell Laboratories, working with Dr. Louis Brus, where he began his studies on nanomaterials. Bawendi joined the faculty at MIT in 1990, becoming Associate Professor in 1995 and Professor in 1996.
Professor Bawendi has followed an interdisciplinary research program that aims at probing the science and developing the technology of chemically synthesized nanocrystals. Prof. Bawendi has been at the forefront of the science and technology of semiconductor nanocrystal quantum dots for over two decades. This work has included the development of novel methods for synthesizing, characterizing, and processing quantum dots and magnetic nanoparticles as novel materials building blocks, studying the fundamental optical properties of quantum dots using a variety of spectroscopic methods, including the development of optical tools to study single nanocrystals, and combining quantum dots with various optical and electronic device structures to study their device properties. His work has also included developing applications of quantum dots in biological and biomedical imaging and sensing, in light emitting devices, photodetection, and solar energy conversion.
Professor Bawendi has published over 250 papers on the science and technology of quantum dots and other materials systems, and has helped four start-up companies in commercializing quantum dot technology. A fifth company spun out from Bawendi’s laboratory uses knowledge gained from his work on quantum dots, applying it to a medical device.
Bawendi has won numerous awards for his work. Among these are the Raymond and Beverly Sackler Prize in the Physical Sciences, the EO Lawrence award in Materials Chemistry from the US Department of Energy, the Fred Kavli Distinguished Lecture in Nanoscience from the Materials Research Society, and the American Chemical Society Award in Colloid and Surface Chemistry.
Bawendi is a fellow of the American Association for the Advancement of Science, a fellow of the American Academy of Arts and Sciences, and a member of the National Academy of Sciences.
Chronic liver diseases developing from fatty liver constitute an evolving public health problem. We strategically combine 808 nm excitation with near infrared (NIR) and shortwave infrared (SWIR) detection to reliably monitor liver injury in vivo in mice by label-free imaging of the endogenous biomarker, lipofuscin, which is surprisingly bright under these conditions. In the NIR/SWIR optical window, tissue is rendered translucent while interfering background signals are suppressed, allowing for noninvasive imaging. As a result, we show that NIR/SWIR imaging of lipofuscin can discern pathology from normal liver processes with high specificity and high sensitivity. We monitor the longitudinal progression and regression of liver necroinflammation and fibrosis in vivo in models of non-alcoholic fatty liver disease and advanced fibrosis. Furthermore, we show that human tissue can also be clearly distinguished as non-alcoholic steatohepatitis (NASH) or NASH-cirrhosis by lipofuscin autofluorescence in the NIR/SWIR. We develop computational methods to remove lipofuscin autofluorescence from pre-clinical and clinical tissue slices stained for immunofluorescence.
Juejun (JJ) Hu received the B.S. degree from Tsinghua University, China, in 2004, and the Ph.D. degree from Massachusetts Institute of Technology, Cambridge, MA, USA, in 2009, both in materials science and engineering. He is currently the Merton C. Flemings Career Development Associate Professor at MITs Department of Materials Science and Engineering. His primary research interest is enhanced photonmatter interactions in nanophotonic structures, with an emphasis on on-chip spectroscopy and chemical sensing applications using novel infrared glasses. Prior to joining MIT, he was an Assistant Professor at the University of Delaware from 2010 to 2014., Hu has authored and coauthored more than 60 refereed journal publications since 2006 and has been awarded six U.S. patents. He has been recognized with the National Science Foundation Faculty Early Career Development award, the Gerard J. Mangone Young Scholars Award, the University of Delaware College of Engineering Outstanding Junior Faculty Member, the University of Delaware Excellence in Teaching Award, among others.,Dr. Hu is currently the Deputy Editor of the OSA journal Optical Materials Express, and he is a Member on technical program committees for conferences including MRS, CLEO, OSA Congress, ACerS GOMD, ICG, and others. (Based on document published on 13 September 2016)
Wide field-of-view (FOV) optics are important for many biomedical imaging applications spanning microscopy, endoscopic imaging, and fundus photography. The traditional approach for widefield imaging entails complex optics with multiple cascaded lens elements, which significantly increases the size, weight, and cost of the system.
Here, Hu describes a lens design based on optical metasurfaces which transforms a flat piece of glass into a “fisheye” lens capable of high-quality imaging over near 180° FOV. The lens features a simple, compact architecture and can be manufactured at low cost leveraging standard Si microfabrication technologies. Hu will discuss the theory and experimental demonstration of the lens and highlight potential biomedical sensing applications of the technology.
Daniel Moyer is a posdoctoral associate at MIT CSAIL working with Polina Golland. He completed his doctorate in computer science at University of Southern California under Greg Ver Steeg and Paul Thompson. His research is focused on machine learning and its applications to medical imaging.
This talk will cover our recent MICCAI 2021 paper. We demonstrate an object tracking method for 3D volumetric images with fixed computational cost and state-of-the-art performance. Previous methods predicted transformation parameters from convolutional layers. We instead propose an architecture that neither flattens convolutional features nor uses fully connected layers, but instead relies on equivariant filters to preserve transformations between inputs and outputs (e.g., rotations/translations of inputs rotate/translate outputs). The transformation is then derived in closed form from the outputs of the filters. This method is useful for applications requiring low latency, such as real-time tracking. We demonstrate our model on synthetically augmented adult brain MRI, as well as fetal brain MRI, which is the intended use-case.
Session 4: Specimens and Biopsies
Praneeth Namburi is a Research Scientist at the Institute for Medical Engineering and Sciences at MIT working on movement research and education. He received a bachelor's degree in Electrical and Electronic Engineering from Nanyang Technological University in Singapore. He got his Ph.D. in experimental neuroscience from MIT studying neural circuit mechanisms for dissociating positive and negative associative memories.
Namburi's current research is focused on the biomechanics of efficient, stable and coordinated movement. He draws inspiration from artists and athletes in specialized movement disciplines such as dancing and fencing to investigate skilled movement.
Trained dancers move elegantly as a stable and coordinated whole. Even though most untrained individuals are unable to move like trained dancers, they produce coordinated movements during walking and running. Our goal is to understand which aspects of coordination generalize across locomotion and more specialized human pursuits such as dancing. Motivated by the idea that dancers represent rhythm in their body, we chose to focus on how muscles represent rhythm. In this talk, I will outline our approach to investigating how rhythm is represented in muscles, and how this can be used to better understand stability and coordination in the body.
Koomson is an Associate Professor in the Department of Electrical and Computer Engineering and the Tisch College of Civic Life at Tufts University. She completed the B.S. and M.Eng. degrees in electrical engineering and computer science at the Massachusetts Institute of Technology in 1998 and 1999, respectively. As a George C. Marshall Scholar, she studied at the University of Cambridge and received the M.Phil. and Ph.D. degrees in electrical engineering in 2000 and 2003, respectively. She is currently a 2021 Dr. Martin Luther King Jr. Visiting Professor at MIT.
Koomson’s research lies at the intersection of biology, medicine, and electrical engineering. Her interests are in micro/nanoelectronic circuits and systems, biomedical devices, health informatics, and advanced nano-/microfluidic systems to probe intercellular communication. She has co-authored several book chapters, publications, and holds a patent for a system and method for measuring phase delay and amplitude of an optical signal in animal tissue. In 2005, she held an Adjunct Professor appointment at Howard University. She has held visiting appointments at Rensselaer Polytechnic Institute and Boston University. Her research funding sponsors include NIH, NSF, DARPA, Catalyst Foundation, and W.M. Keck Foundation.
Koomson is a George C. Marshall Scholar, Intel Foundation Scholar, National Science Foundation Graduate Research Fellow, and 2010 recipient of the NSF Faculty Early Career Development (CAREER) Award. She served as the Technical Program Chair of the 60th IEEE Midwest Symposium on Circuits in Systems. She is a member of several professional societies, technical program committees, and editorial boards for high impact journals.
Near-infrared spectroscopy (NIRS) techniques are creating pathways toward new applications to study biological tissue, including functional brain imaging, cerebral oximetry, stroke assessment, and optical mammography. NIRS methods are used to compute the concentrations of biological chromophores, such as oxygenated and deoxygenated hemoglobin, that have specific absorption spectra and indicate tissue oxygen perfusion.
Koomson will present a non-invasive device implementing frequency-domain NIRS techniques for real-time monitoring of cerebral perfusion at the point of care. In the area of pediatric neurology, this tool enables assessment of hemorrhage. The HemoSensis tool implements advanced NIRS methods in a compact form factor by employing low-power solid-state optical devices and a patented system-on-chip (SoC) platform.
Koomson will present the core technology and present system validation results. This tool advances the field of diffuse optical imaging by developing special techniques for data collection and analysis of NIRS data and enables dual-task measurements on ambulating subjects.
Dr. Feigin-Almon is a research scientist at the Department of Mechanical Engineering and the Institute for Medical Engineering and Science (IMES) at MIT. The focus for Dr. Feigin-Almon’s research encompasses the area of assessing motion and function, and their relation to musculoskeletal and neurological health. Most of his work in this domain centers on using deep learning approaches to accelerate the application of seismic approaches to raw ultrasound signals and understanding the information that can be garnered from this marriage.
Assessing muscle health and muscle function is essential for diagnostics of a multitude of musculoskeletal and neurological afflictions. These encompass such conditions as degenerative muscle diseases, muscle atrophy due to bed rest or neurological conditions, return to play after muscle injuries, and neurological related conditions such as traumatic brain injuries, neurological afflictions, and spasticity.
Currently, there are no imaging solutions capable of assessing muscle health and function during dynamic motion. This means that we either try to extrapolate the required information from images at rest, and/or resort to alternate methods including clinical examination, electrophysiological methods (Electromyography - EMG), and biomechanical methods. Feigin-Almon will present a novel ultrasound-based imaging solution capable of assessing muscle function in motion. To this end, he utilizes a deep-learning approach applied to pre-imaging raw ultrasound signals to recover speed of sound maps in tissue. Feigin-Almon will show that these can provide interactive, real-time, functional full-slice EMG-like images.