A FEASIBLE TEACHING TOOL FOR PHYSIOLOGICAL MEASUREMENT R. Stojanovic 1 , D. Karadaglic 2 , B. Asanin 3 , O. Chizhova 4 1 University of Montenegro, Professor, Podgorica, Montenegro 2 University of Manchester, Senior researcher, Manchester, UK 3 University of Montenegro, Professor, Podgorica, Montenegro 4 The MHU, Docent, Moscow, Russia Abstract— This paper describes the development of a vari- ety of classical biomedical experimental exercises by using interdisciplinary approach. A number of them have been developed integrating the knowledge of sensors, electronics, microprocessors and MATLAB software. The exercises de- picted here are intended to introduce students to fundamental concepts of biomedical instrumentation, from the sensing requirements to subsequent data analyze. This not only en- hances the fundamental knowledge, but also trains students in the application of complex concepts in real-world of practice and laboratory research. The emphasis is put on the measure- ment of physiological vital parameters. Similar concept can be applied to some other signals and systems, as well. Using pro- posed approach sophisticated and expensive equipment can be replaced successfully by a functional low cost hardware and/or versatile virtual instruments. Keywords— BME education, physiological measurements, teaching tool, ECG, PPG, MATLAB, virtual instrument. I. INTRODUCTION The fusion of practical knowledge from different disci- plines in the context of biomedical engineering education is important for the contemporary students and researchers. The approach with the application of a modular educational layout can result in a very effective learning environment that emulates real-world practice. Through several years of experiences in teaching a number of courses such as elec- tronics, measurements, microprocessors, we proved that the knowledge from these areas can be effectively applied in the design of flexible teaching exercises for purpose of bio- medical engineering education. The approach exposed in this paper differs from existing in the following points: instead of classical, relatively ex- pensive acquisition units/boards it uses general-purpose low cost microcontroller (MC), while standard stand alone monitoring units (special purpose computers and monitors) are replaced with MATLAB-based Virtual Instrument (VI), which can be powered by any PC compatible machine [1],[2],[3]. The sensing, amplifying and filtering of measur- ing data has been achieved by using electronic circuits based on standard components (transistors, operation ampli- fiers and digital gates) designed by students. The acquired analog signals are digitalized and processed by low-cost, low-power microcontroller (MC). Using parallel, serial or USB protocol the microcontroller sends the packed data in real-time to server (PC compatible machine). VI designed in MATLAB accepts the data, analyze them and display the desired biomedical signals and effects. Students also design microcontroller circuit, its firmware as well as associated functions for biomedical signal processing like plotting, filtering, transformation in frequency and time-frequency domain, QRS detection, heart rate variability (HRV) etc. Thus, these laboratory exercises permit the students to learn the concepts of the physiological phenomena and measurements at first, and secondly, to understand principle of system integration and signal processing of real-time data. They become familiar with the problems that cause real signals and try to solve them by knowledge from litera- ture or by own ideas. This paper offers an overview of our work in this area. The emphasis is placed on the representative experiments related to Electrocardiography (ECG) and Photoplethys- mography (PPG). Section 2 briefly introduces applied meth- odology, while Section 3 illustrates some of classical exer- cises performed by proposed tool. Sections 4 and 5 give the Conclusions and References. II. METHODOLOGY The laboratory toolset we propose is quit modular and consists of both, hardware and software units, Fig. 1. Its final appearance, in the process of exploitation, is given in Fig 2. A. Software architecture Overall software consists of firmware and MATLAB code. As mentioned, the firmware mainly supports acquisi- tion process and emulation of communication protocols. It is developed in widespread compilers like IAR or CodeVi- sion AVR and then uploaded to the MC’s program memory.