A computer‐aided educational device and toolbox for biomedical signal processing at the undergraduate level

Abstract

Engineering education requires both a theoretical and practical basis; some aspects are better understood through practical examples. Providing practical experience in biomedical engineering is of great importance in terms of understanding concepts and assisting the retention of learning. Hands‐on experience can be particularly beneficial in supporting the theoretical explanation of the acquisition, processing, and displaying of biomedical signals. This study has developed an expansion board that can be plugged into Raspberry Pi boards to capture electroencephalography (EEG), electrooculography (EOG), electrocardiography (ECG), and electromyography (EMG) biomedical signals with a single‐channel amplifier circuit. A toolbox has been written in the Python programming language to; capture, process, filter, apply fast fourier transform, and display these signals. The device and laboratory applications were introduced in the curriculum of a final year module, “Introduction to Biomedical Engineering” in the Department of Electrical and Electronics Engineering at Gazi University. The pedagogical value of the application was assessed by administering a questionnaire to the students. Results show the use of measurement and display of biomedical signals increased the curiosity and motivation of the students in Biomedical Engineering.

Software-oriented Collaborative Project-based Learning of Biomedical Signal Processing in Simulated Industry-like Conditions

“…Others expected to extend their knowledge of biomedicine data acquisition systems (DAQs), including analog-to-digital converters and programming of integrated circuit systems. These DAQs are an essential part of BSP systems [16], [17], however, they are not strictly associated with the syllabus of the proposal. Despite many preferences and expectations from the participants, the BSP course emphasises the algorithmic and software-oriented points of view rather than the acquisitions or medical interpretations of the results.…”

“…The related works might be classified into three categories, namely generalpurpose or medical signals-oriented, medicine or engineering students-dedicated, and menu-driven or programming skillsdependent. We analyzed several implementations of biomedical signal processing (BSP) courses and classified them into three groups: 1) virtual laboratories, allowing for distant access, but with a closed list of selectable options limiting the creativity and not resembling future workplaces [12]- [15], 2) acquisition laboratories simulating a diagnostic room focused on the recording of various signals but limiting the processing to a set of predefined procedures [16], [17], 3) hands-on computer laboratories with typical DSP procedures demonstrated using examples from electrophysiology [18], [19].…”

An educational tool for understanding MPEG‐2 video compression and coding techniques

“…In Gerson et al [7], new multimedia software and a workbook for the improvement of 3-D spatial visualization skills for engineering students is described. In Tepe and Savaştaer [16], an expansion board for Raspberry Pi is presented as a tool for the acquisition, processing, and displaying of biomedical signals. A new educational simulation tool designed for the generic study of wireless networks is presented in Sanguino et al [14].…”