This course (BSE 4004) uses MATLAB to connect the computer to various measurement systems using different communication protocols (USB, RS232C and GPIB). The drivers for the instruments were all within standard capabilities of MathWorks products. MathWorks provided some guidance with the specific instruments used in this course.
The Department of Biological Systems Engineering (BSE) received an NSF grant to develop a curriculum based on the spiral-learning concept: repeatedly visiting authentic problems in the domain with increasing complexity. This concept may be applied not only to the achievement of domain-specific learning outcomes, such as the ability to control a biological system, but also to the development of competence with the "modern engineering tools necessary for engineering practice," such as MATLAB. Specifically, students entering the engineering program learn to use MATLAB for graphing and simple calculations during their freshmen year. In the following year, students in BSE complete instrumentation exercises in their sophomore design course (for example, switching a light on/off to achieve and maintain a desired temperature in a confined space) and also undertake a course on numerical methods using MATLAB. Students in the junior year take this course (Instrumentation), and in the senior year they complete the spiral-learning process by applying the skills developed to their capstone design project.
Even within this Instrumentation course, the spiral theme is apparent as students are expected to apply MATLAB to data acquisition and analysis problems with increasing complexity. For example, the students are initially given the MATLAB files for connecting to a multimeter. Later they are asked to develop MATLAB files to interface with a datalogger. Finally, they are required to apply digital signal processing and statistical analysis to the data collected from the instruments.
Upon completion of the course you should be able to:
• Select sensors for monitoring and/or controlling biological systems (includes consideration of precision and accuracy, appropriate sensing range, type of instrument)
• Simulate biological process control using different software (e.g. MATLAB)
• Perform computer based data acquisition
• Perform data analysis such as estimating uncertainty and obtaining relevant statistical parameters
• Perform data collection using instruments like chromatography, electrophoresis and spectroscopy.