Medical Engineering

The course will prepare the student to identify surgical instruments, distinguish their category, know their use, and name them. This course will give emphasis on the knowledge and recognition of medical instruments, as well as instrumentation and how they will help physicians. The course will cover topics, such as the identification of medical instruments, their categories, use, and inspection. There will be emphasizes on testing their quality, how they are set up, sealed, other instruments like the robotic and laser instruments, endoscopes, other complex instruments, how they are regulated.

Learning outcomes

1.      To identify basic surgical instruments by category, name, and use;

2.      To demonstrate the different methods used to test and inspect various types of surgical instrumentation.

3.      To describe the use of surgical instrumentation.

4.      To understand how instrument quality assurance testing are done.

5.      To demonstrate the proper procedures for assembling instruments/procedure trays.

6.      To differentiate between various categories of special instrumentation utilized in operating rooms.

7.      To demonstrate inspection and testing of endoscopic and robotic instrumentation and how to select the appropriate packaging material for instrumentation sets and medical equipment.

8.      To demonstrate how to check packaging materials for defects, cleanliness, and function.

9.      To demonstrate how to sets in peel pouches, sterile wraps, and rigid pans are packed.

The course has an overview of discrete time signals and systems. Sampling/Reconstruction principles both in time and frequency domains. The Z-Transform and its properties. Structure of discrete time systems; tapped delay or lattice etc. Digital filter designs. Realization of digital filters (FIR and IIR). The discrete Fourier and inverse Fourier transforms. The fast Fourier transform (FFT) and its analysis. Image acquisition, sampling and quantization. Image enhancement: Spatial and frequency domain techniques. Image restoration: Inverse, Wiener and mean filtering. Image compression: Compression models.

This course gives you an introduction to modeling methods and simulation tools for a wide range for wide application in the medical industry. The different methodologies that will be taught in the course are applied to wide range of topics.  This course does not intend to go deeply into any numerical method or process and does not provide any recipe for the resolution of a particular problem, rather we will discuss physical models and all that is required for making a model and simulating the model. The assignments of this course will be made as practical as possible in order to allow the students actually create from scratch small models that will solve simple problems. Although programming will be used extensively in this course we do not require any advanced programming experience in order to complete it.