The aim of this thesis is to introduce biomedical sensors based on different measurement principles and to test its basic functions, as well as, to rate the results of the measurements and comparing them. A pulseoximeter and an ECG device is introduced in this project, as well as, the signal processing functions that are used to get data from raw signals. In this configuration I use a Zynq SoC platform (named PYNQ – Z1) as a master, which is capable of collecting and processing data from the slave devices (the sensors). The most important feature of the previously mentioned SoC is that it is hybrid – both a microprocessor and an FPGA can be found on it. The reason of chosing this device was purely didactic and self-motivation played a huge role as well, because the complexity of the signal processing and the speed of the data doesn’t require an FPGA arhitecture – there is no need for hardware accelerated processing here. I use the FPGA system for only making the external connections to the sensors. The signal processing is done by the ARM mikroprocessor.
The above mentioned didactics viewpoints and self-motivations are based on the eager for getting to know the concepts of ’System-on-a-Chip’. In addition, to get to know the ’design flow’ of a Zynq platform, using its IDE. That’s because these skills are useful during real and serious projects which aren’t restricted to biomedical devices, but general signal processing issues with SoC-s. That is why the pulse detecting algorithms are done with a simple finite state machine (FSM) and do not provide consistent data for medical analysis.