Topics of Interest

The topics of interest include but are not limited to the following areas:


    Biomedical signal processing involves the analysis of these measurements to provide useful information upon which clinicians can make decisions. Engineers are discovering new ways to process these signals using a variety of mathematical formulae and algorithms. Working with traditional bio-measurement tools, the signals can be computed by software to provide physicians with real-time data and greater insights to aid in clinical assessments.


    Biomedical imaging concentrates on the capture of images for both diagnostic and therapeutic purposes. Snapshots of in vivo physiology and physiological processes can be garnered through advanced sensors and computer technology. Biomedical image processing is similar in concept to biomedical signal processing in multiple dimensions. It includes the analysis, enhancement and display of images captured via x-ray, ultrasound, MRI, nuclear medicine and optical imaging technologies.


    A biosensor is any piece of hardware that interacts with a biological or physiological system to acquire a signal for either diagnostic or therapeutic purposes. Data gathered using biosensors are then processed using biomedical signal processing techniques as a first step toward facilitating human or automated interpretation. The body sends out very weak electrical signals, which must somehow be captured and converted into useful information.


    Both computational biology and bioinformatics draw upon many of the same disciplines to derive distinct, but related, information about biological processes. Understanding the functioning of living systems is the realm of the physiologist. Bioengineers working in computational biology might explore, for example, how blood flows through the body or how air flows through the lungs. This "plumbing"" can be mathematically modeled to help determine the health of an individual patient.


    The term "biomechanics" is used to describe the application of mechanics-the study of how motor systems create force and motion-to biological systems. Biomechanics often employs traditional engineering techniques. Biorobotic technologies are often utilized to provide assistance to accommodate a deficiency-either as fully-functioning robots or highly advanced prosthetics; the latter represents one area in which neural engineering and biorobotics intersect as both disciplines are required in order to first signal and then generate movement.


    Neural engineers are interested in understanding, interfacing with and manipulating the nervous system. Computational neuroscientists are creating computer models of neural systems down to the level of single neurons. Scientists are also exploring how neurons communicate with one another by taking recordings from actual neurons and having those recordings "interact" with recordings from other neurons. Using quantitative techniques, the nature of these communications are being measured and analyzed.


    Thousands of people die every year waiting for an organ transplant and far more are plagued by diseased organs. Those with spinal cord injuries suffer from many other health issues as a result of their inability to move and walk. And while we marvel at the prowess of surgeons able to transplant a face or hand, the results are far from perfect. Tissue engineering brings together several disciplines to create living tissue to replace or repair skin, a failing organ or a damaged or missing body part.


    With critical care doctors in short supply and located in regional medical centers, ICUs became the first specialty to turn to the power of telemedicine. Telemedicine allows attending physicians in rural hospitals to consult with specialists at renowned institutions. This means that patient data must be transmitted and received both reliably and timely. Biomedical engineers are involved in the development of communication technologies and applications.


    The engineers who focus specifically on diagnostic and therapeutic systems address the practical aspects of research. Rather than exploring the features of cardiac arrhythmias, for example, they consider what, specifically, could be developed to detect such arrhythmias. They look at what is needed in medicine and then help to figure out how to apply the findings of researchers into a functional product.