The Bridge - Issue 3, 2021 - 35

Graduate Research SP
Luz-Maria Sanchez Reyes
Mu Psi, Autonomous University of Queretaro, Ph.D. Student in Engineering
RESEARCH TOPIC
Non-invasive Biomedical Tools for the Detection of Brain Diseases
Dementia diseases, such as Alzheimer's, are the main cause of disability and dependency in older adults. The number of cases of these
diseases is expected to double by 2030 and triple by 2050, which has become an alarming problem for the health sector. Cognitive
impairment (CI), a decline in cognitive functions, is one of the first symptoms in the appearance of dementia diseases. This is why with
the detection of CI, an early detection of the disease could be achieved. The information offered by the electroencephalogram (EEG), a
record of bioelectrical activity, is clinically relevant for the detection of brain diseases and their symptoms. EEG in combination with signal
processing, feature extraction, and Artificial Intelligence (AI) classifiers can
achieve biomarker identification for automatic detection with high levels of
efficiency and fast response.
Luz Maria's work, supported by the Universidad de Querétaro, the
Universidad de Baja California, and Concordia University, has developed
auxiliary tools for the timely and efficient detection of brain diseases using
EEG information, signal processing, and AI. She has also developed a noninvasive
device for melanoma detection using image processing, a tool for
the automatic process in the synthesis of liposomes, and applications in the
area of robotics and renewable energy. She has collaborations with more
than 4 universities in Mexico and Canada.
Steps of the process for automatic detection of brain diseases using EEG
LEARN MORE
https://www.researchgate.net/profile/Luz-Maria-Reyes
CONTACT
https://www.linkedin.com/in/luz-mar%C3%ADa-s-814b4011b/
James Hunter
Gamma Theta, Missouri University of Science and Technology, Ph.D. Student in Electrical Engineering
RESEARCH TOPIC
Characterization of Electromagnetic Coupling to Electronic Devices
The electromagnetic susceptibility of electronic devices varies substantially from one device to another. James's work aims to characterize
coupling to printed circuit boards (PCBs) and their attached cables, with a goal of understanding when and why a device is most
susceptible, as well as how to handle that susceptibility. The characteristic of the coupled voltage can be radically altered by the
typical variations seen in these devices, such as the length of the wiring harness, the size of connectors on the device, the size of the
PCB board, trace locations, etc. The coupled voltage also depends on the frequency, angle of arrival, and polarization of the incident
electromagnetic wave. James has developed an approach to rapidly estimate the electromagnetic coupling to wiring harnesses and PCB
traces. By separating a complete device into separate components, e.g. the PCB, connectors, harnesses, etc., and characterizing each
" block " individually, a much more flexible model can be constructed. By cascading these blocks together, in much the way that Legos
are assembled to build bigger structures,
a much wider variety of devices can be
studied than by modeling each structure
individually. Simulations of the far-field
radiation patterns of the models are used
to find the statistical characteristics of the
coupled voltage while considering the
variations in the incident wave and the
device itself.
From left to right: 1. Farfield radiation pattern of a simple 2. A simple complete device created by cascading a trace,
two pin connector, and parallel wire harness. 3. Segment 1: PCB with trace. 4. Segment 2: Connector and parallel
wire combination.
LEARN MORE
https://emclab.mst.edu/
CONTACT
jdhzg8@umsystem.edu
TLIGHT
HKN.ORG
35

https://www.researchgate.net/profile/Luz-Maria-Reyes https://www.linkedin.com/in/luz-mar%C3%ADa-s-814b4011b/ https://emclab.mst.edu/ http://www.HKN.ORG

The Bridge - Issue 3, 2021

Table of Contents for the Digital Edition of The Bridge - Issue 3, 2021