ScientIST – Scientific Experiments in the Field of Biomedical Engineering Supported by Mobile Devices and IoT

The project aims at exploring mobile devices and the Internet of Things (IoT) as pedagogical tools to be used in classrooms, laboratories, or at home. Our work combines the ease of access to this type of devices with state-ofthe-art software and hardware, as a way of enriching the learning experience for students, namely in what concerns practical and laboratory activities in the field of biomedical engineering. This approach can be particularly relevant to support distance learning. What was done The project builds upon previous developments from the team in the field of biosignal acquisition and instrumentation, to allow students to experience different physiological phenomena individually or in a group, without having the typical limitations associated with access to laboratory facilities or specialized equipment. In our approach (ScientIST) we explore the use of: 1) Arduino MKR WIFI 1010, a variant of the popular electronic platform recently launched for prototyping Internet of Things (IoT) applications; 2) Google Science Journal (GSJ), a digital notebook created by Google to support laboratory activities using mobile devices both in terms of execution and in the documentation of the results achieved; and 3) Jupyter Notebooks, a web-based interactive computational environment used to organize content, including code, text, mathematics, plots, and rich media. The implemented tools formed the basis for the development of projects and laboratories (in the classroom or at students’ premises) in the context of 4 curricular units of the Integrated

The project

Master Program in Bioengineering (MEBiom). Other relevant information

Our work aims at involving students more actively in the learning process using case studies, project-based learning, active learning and research-based learning. It also proved to be an effective approach to quickly respond to some of the needs raised by the migration to distance learning during the COVID-19 outbreak. Survey results from a pilot study performed in one of the courses where ScientIST has been deployed, indicated an overall 78.68% System Usability Scale (SUS) score reported by the students. Moreover, the approach has shown promising results in multiple case studies, including reporting of the main findings during Histology classes, and Photoplethysmography (PPG) data acquisition and processing. ScientIST can be immediately transposed to other courses at Instituto Superior Técnico (IST), and even scaled to other universities both at a national and international level.

Ana Fred (afred@lx.it.pt) Hugo Plácido da Silva (hsilva@lx.it.pt) Department of Bioengineering

UC: Machine Learning in Bioengineering, Introduction to Biomedical Engineering, Project in Biomedical Engineering, Signal Acquisition and Instrumentation in Bioengineering