This innovative practice work-in-progress paper presents the outline of a bachelor level medical engineering lab that comprises electronical sensor signal processing. It explains how to teach and educate medical technology students the entire signal processing chain up to medical interpretation based on the practically relevant, widespread example of pulse oximetry. The various analog circuit blocks and the required post-processing with a microcontroller are discussed, as well as the interaction of all blocks to form the pulse oximeter system. For this purpose, the students are divided into small teams of three and receive a printed circuit board developed specifically for the experiment. With this board it is possible to extract certain parts of the signal processing measurement chain and analyze them with different tools, e.g. wave generator and oscilloscope. The accompanying handout guides and challenges students through the complex analysis of pulse oximetry, with subtasks to assist them. Tutors are available to support students with questions or if they get stuck. The aim of this practical exercise is for the students themselves to understand which individual steps are required and how they interact in order to obtain a valid measured value at the end. They learn the practical relevance and application of various electronic components and filter circuits, as well as the subsequent digitization and post-processing with the help of a microcontroller. In addition, the participants will familiarize themselves with the use of various measuring devices. The associated handout and its tasks do not provide step-by-step instructions. The students are encouraged to think creatively in their groups and to engage in group discussions so they understand the problem and find a solution for each subtask. After solving each subtask, the group receives feedback from a tutor who explains whether the solution to the task is right or wrong and whether there could have been smarter ways. By the end of the exercise, the students will have understood the complete signal path in depths from the sensor to the interpretation of the measured value and all the difficulties involved, based on a modern medical technology application.
