UNDER CONSTRUCTION

Listed below are some common and uncommon uses of signals and systems in biomedical engineering:

• ECG signals
• EMG signals
• EEG signals

DTFT example problem:

Uses for Signals and Systems in Biomedical Industry

• Wireless monitoring - Athena GTX
• Modeling biological systems - Bloomberg (not financial)
• Filtering noise from biological systems
• Cyberonics

http://www.embs.org/docs/careerguide.pdf

"What are some of the key areas of biomedical engineering?
Bioinformatics involves developing and using computer tools to collect
and analyze data related to medicine and biology. Work in bioinformatics
could involve using sophisticated techniques to manage and search
databases of gene sequences that contain many millions of entries.
BioMEMS Microelectromechanical systems (MEMS) are the integration
of mechanical elements, sensors, actuators, and electronics on a silicon
chip. BioMEMS are the development and application of MEMS in medicine
and biology. Examples of BioMEMS work include the development
of microrobots that may one day perform surgery inside the body, and the
manufacture of tiny devices that could be implanted inside the body to
deliver drugs on the body’s demand.
Biosignal Processing involves extracting useful information from biological
signals for diagnostics and therapeutics purposes. This could
mean studying cardiac signals to determine whether or not a patient will
be susceptible to sudden cardiac death, developing speech recognition
systems that can cope with background noise, or detecting features of
brain signals that can be used to control a computer.
Imaging and Image Processing X-rays, ultrasound, magnetic resonance
imaging (MRI), and computerized tomography (CT) are among the imaging
methods that are used to let us “see” inside the human body. Work in
this area includes developing low-cost image acquisition systems, image
processing algorithms, image/video compression algorithms and standards,
and applying advances in multimedia computing systems in a biomedical
context.
Information Technology
in biomedicine
covers a diverse range
of applications and
technologies, including
the use of virtual reality
in medical applications
(e.g. diagnostic
procedures), the application
of wireless and
mobile technologies in
health care settings,
artificial intelligence to
aid diagnostics, and
addressing security
issues associated with
making health care
information available
on the world wide web.
Instrumentation, Sensors, and Measurement involves the hardware
and software design of devices and systems used to measure biological
signals. This ranges from developing sensors that can capture a biological
signal of interest, to applying methods of amplifying and filtering the
signal so that it can be further studied, to dealing with sources of interference
that can corrupt a signal, to building a complete instrumentation
system such as an x-ray machine or a heart monitoring system.
Neural Systems and Engineering This emerging interdisciplinary field
involves study of the brain and nervous system and encompasses areas
such as the replacement or restoration of lost sensory and motor abilities
(for example, retinal implants to partially restore sight or electrical stimulation
of paralyzed muscles to assist a person in standing), the study of
the complexities of neural systems in nature, the development of neurorobots
(robot arms that are controlled by signals from the motor cortex in
the brain) and neuro-electronics (e.g. developing brain-implantable
micro-electronics with high computing power).
Physiological Systems Modeling Many recently improved medical
diagnostic techniques and therapeutic innovations have been a result of
physiological systems modeling. In this field, models of physiological
processes (e.g. the control of limb movements, the biochemistry of
metabolism) are developed to gain a better understanding of the function
of living organisms.
Proteomics A proteome
is the set of all
proteins produced by
a species, in the same
way the genome is the
entire set of genes.
Proteomics is the
study of proteomes –
the location, interactions,
structure, and
function of proteins.
Advances in proteomics
have included
the discovery of a new cellular process that explains how infections occur
in humans – an advance that is leading to new treatments for infectious
diseases. Additionally, these advances have led to discovery of a method
to detect protein patterns in the blood for early diagnosis of ovarian cancer.
Work in proteomics can also involve the development of hardware
devices that provide accurate and rapid measurements of protein levels.
Radiology refers to the use of radioactive substances such as x-ray, magnetic
fields as in magnetic resonance imaging, and ultrasound to create
images of the body, its organs and structures. These images can be used
in the diagnosis and treatment of disease, as well as to guide doctors in
image-guided surgery.
Robotics in Surgery includes the use of robotic and image processing
systems to interactively assist a medical team both in planning and executing
a surgery. These new techniques can minimize the side effects of
surgery by providing smaller incisions, less trauma, and more precision,
while also decreasing costs.
Telemedicine, sometimes called “telehealth” or “e-health,” involves the
transfer of electronic medical data from one location to another for the
evaluation, diagnosis, and treatment of patients in remote locations. This
usually involves the use of “connected” medical devices, advanced
telecommunications technology, video-conferencing systems, and networked
computing. Telemedicine can also refer to the use of these technologies
in health-related distance learning."

Purdue Biomedical Research with Signals and Systems

Electrical Engineering

https://engineering.purdue.edu/ECE/Research/Areas/BiomedIS.whtml

Biophotonics and Medical Imaging

https://engineering.purdue.edu/BME/Research/BIO

Neuroengineering

https://engineering.purdue.edu/BME/Research/NE

Pedro Irazoqui

Systems Science and Engineering

https://engineering.purdue.edu/BME/Research/HCS

Rundell

Lawley

Other Purdue courses that use Signals and Systems (for Biomedical Engineering)

• BME 495/420 - Control for Biomedical and Healthcare Engineering (Fall)
• BME 495/430 - Biomedical Imaging Modalities (Spring)
• BME 595/510 - Analog Integrated-Circuit Design (Fall)
• BME 595/511 - BIOSIGNAL PROCESSING (Fall)
• BME 521/ ABE 560 - Biosensors: Fundamentals and Applications (Fall)

An introduction to the field of biosensors and an in-depth and quantitative view of device design and performance analysis. An overview of the current state of the art to enable continuation into advanced biosensor work and design. Topics emphasize biomedical, bioprocessing, environmental, food safety, and biosecurity applications.

• BME 528/ ECE 528 - Measurement and Stimulation of the Nervous System (Spring)

Engineering principles addressing questions of clinical significance in the nervous system: neuroanatomy, fundamental properties of excitable tissues, hearing, vision, motor function, electrical and magnetic stimulation, functional neuroimaging, disorders of the nervous system, development and refinement of sensory prostheses.

• BME 560 - Modeling and Analysis of Physiological and Healthcare Systems
• ECE 368 - Data Structures
• ECE 438 - Digital Signal Processing with Applications

The course is presented in five units. Foundations: the review of continuous-time and discrete-time signals and spectral analysis; design of finite impulse response and infinite impulse response digital filters; processing of random signals. Speech processing; vocal tract models and characteristics of the speech waveform; short-time spectral analysis and synthesis; linear predictive coding. Image processing: two-dimensional signals, systems and spectral analysis; image enhancement; image coding; and image reconstruction. The laboratory experiments are closely coordinated with each unit. Throughout the course, the integration of digital signal processing concepts in a design environment is emphasized.

• ECE 441 - Distributed Parameter Systems
• ECE 473 - Intro to Artificial Intelligence (Spring)

The course introduces fundamental areas of artificial intelligence: knowledge representation and reasoning; machine learning; planning; game playing; natural language processing; and vision.

• ECE 510 at IUPUI - Introduction to Biometrics
• ECE 511/ PSY 511 - Psychophysics (Fall)

An examination of the relationship between physical stimuli and perception (visual, auditory, haptics, etc.). Includes a review of various methods for studying this relationship and of the mathematical and computational tools used in modeling perceptual mechanisms.

• ME 375 - System Modeling and Analysis

Introduction to modeling electrical, mechanical, fluid, and thermal systems containing elements such as sensors and actuators used in feedback control systems. Dynamic response and stability characteristics. Closed loop system analysis including proportional, integral, and derivative elements to control system response.

• ME 413 - Noise Control: Fundamentals of Acoustic Waves

Fundamentals of acoustic waves. Psychoacoustics and theories of hearing. Environmental and building acoustics. Measurement methods and common instrumentation. Noise control methods. Machinery noise. Community reaction. Legal aspects. Design-oriented semester project. Course work in differential equations.

• ME 588 - Mechatronics: Integrated Design of Electro-Mechanical Systems (Fall)

Electronic and interfacing techniques for design and control of electro-mechanical systems. Basic digital and analog design with applications to electro-mechanical interfacing via hands-on laboratory experience. Commonly used actuators and sensors and corresponding interfacing techniques. Realistic and integrated product development experience provided through a comprehensive final project where working prototypes are built to defined specifications.

ECE 38200 - Feedback System Analysis And Design
In this course, classical concepts of feedback system analysis and associated compensation techniques are presented. In particular, the root locus, Bode diagram, and Nyquist criterion are used as determinants of stability. 

ECE 44500 - Modern Filter Design
Solution to the filtering approximation problem via Butterworth, Chebyshev, Elliptic, etc., approaches. Transfer function scaling and type transformations. Effects of A/D and D/A conversion. Digital filter design methods. Active filter design using operational amplifiers. Operation and design of switched capacitor filters. A laboratory for the construction of digital filters is provided.

ECE 48300 - Digital Control Systems Analysis And Design
The course introduces feedback computer controlled systems, the components of digital control systems, and system models on the z-domain (z-transfer functions) and on the time domain (state variable representations.) The objectives for system design and evaluation of system performance are considered. Various discrete-time controllers are designed including PID-controllers, state and output feedback controllers, and reconstruction of states using observers. The systems with the designated controllers are tested by simulations.

ECE 51300 - Diffraction, Fourier Optics, And Imaging
Modern theories of diffraction and Fourier optics for imaging, optical communications, and networking. Imaging techniques involving diffraction and/or Fourier analysis with application to tomography, magnetic resonance imaging, synthetic aperture radar, and confocal microscopy. Additional topics in optical communications and networking, including wave propagation in free space, fiber, integrated optics, and related design issues. Simulation studies, using Matlab and other software packages for analysis and design.

ECE 52100 - Acoustics In Engineering And Medicine
An introduction to the uses of acoustics in medical imaging, flaw detection, blood flow measurement, and signal processing. Topics include physical acoustics, bulk, surface and plate waves, transducer design, ultrasonic lenses and mirrors, pulse echo and ultrasonic doppler systems, bulk and surface wave signal processing devices, holographic imaging, clinical applications of ultrasonic imaging, and acoustic flaw detection.

ECE 52200 - Problems In The Measurement Of Physiological Events
(BIOL 563, VPH 522) Lectures devoted to the methods used to measure physiological events with demonstrations and laboratory exercises to emphasize the practical aspects of quantitative measurements on living subjects. The systems covered are cardiovascular, respiratory, central and peripheral nervous, gastrointestinal, and renal.

ECE 52600 - Fundamentals Of MEMS And Micro-Integrated Systems
(BME 58100) Key topics in micro-electro-mechanical systems (MEMS) and biological micro-integrated systems; properties of materials for MEMS; microelectronic process modules for design and fabrication. Students will prepare a project report on the design of a biomedical MEMS-based micro-integrated system.

ECE 52800 - Measurement And Stimulation Of The Nervous System
(BME 52800) Engineering principles addressing questions of clinical significance in the nervous system: neuroanatomy, fundamental properties of excitable tissues, hearing, vision, motor function, electrical and magnetic stimulation, functional neuroimaging, disorders of the nervous system, development and refinement of sensory prostheses.

ECE 53800 - Digital Signal Processing I
Theory and algorithms for processing of deterministic and stochastic signals. Topics include discrete signals, systems, and transforms, linear filtering, fast Fourier transform, nonlinear filtering, spectrum estimation, linear prediction, adaptive filtering, and array signal processing.

ECE 57000 - Artificial Intelligence
Introduction to the basic concepts and various approaches of artificial intelligence. The first part of the course deals with heuristic search and shows how problems involving search can be solved more efficiently by the use of heuristics and how, in some cases, it is possible to discover heuristics automatically. The next part of the course presents ways to represent knowledge about the world and how to reason logically with that knowledge. The third part of the course introduces the student to advanced topics of AI drawn from machine learning, natural language understanding, computer vision, and reasoning under uncertainty. The emphasis of this part is to illustrate that representation and search are fundamental issues in all aspects of artificial intelligence