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ScientIST: Biomedical Engineering Experiments Supported by Mobile Devices, Cloud and IoT

1
IT—Instituto de Telecomunicações, 1049-001 Lisboa, Portugal
2
Instituto Superior Técnico, Universidade de Lisboa, 1050-049 Lisboa, Portugal
*
Authors to whom correspondence should be addressed.
Signals 2020, 1(2), 110-120; https://doi.org/10.3390/signals1020006
Received: 3 August 2020 / Revised: 25 August 2020 / Accepted: 2 September 2020 / Published: 7 September 2020
Currently, mobile devices such as smartphones or tablets are widespread within the student community. However, their potential to be used in classrooms is yet to be fully explored. Our work proposes an approach that benefits from the ease of access to mobile devices, and combines it with state-of-the-art software and hardware. This approach builds upon previous developments from our team on biosignal acquisition and analysis, and is designed towards the enrichment of the teaching experience for students, namely in what concerns laboratory activities in the field of biomedical engineering. The implementation of such methodology aims at involving students more actively in the learning process, using case studies and emerging educational approaches such as project-based, active and research-based learning. It also provides an effective option for remote teaching, as recently required by the COVID-19 outbreak. In our approach (ScientIST) we explore the use of the Arduino MKR WIFI 1010, a variant of the popular electronic platform, recently launched for prototyping Internet of Things (IoT) applications, and the Google Science Journal (GSJ), a digital notebook created by Google, to support laboratory activities using mobile devices. This approach has shown promising results in two case studies, namely, documenting a Histology laboratory class and a Photoplethysmography (PPG) data acquisition and processing experiment. The System Usability Scale (SUS) was used in the evaluation of the students’ experience, revealing an overall score of 78.68%. View Full-Text
Keywords: m-Learning; Internet of Things; digital notebooks; project-based learning; biomedical engineering m-Learning; Internet of Things; digital notebooks; project-based learning; biomedical engineering
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MDPI and ACS Style

Pinto, J.F.; Silva, H.P.d.; Melo, F.; Fred, A. ScientIST: Biomedical Engineering Experiments Supported by Mobile Devices, Cloud and IoT. Signals 2020, 1, 110-120. https://doi.org/10.3390/signals1020006

AMA Style

Pinto JF, Silva HPd, Melo F, Fred A. ScientIST: Biomedical Engineering Experiments Supported by Mobile Devices, Cloud and IoT. Signals. 2020; 1(2):110-120. https://doi.org/10.3390/signals1020006

Chicago/Turabian Style

Pinto, Joana F., Hugo P.d. Silva, Francisco Melo, and Ana Fred. 2020. "ScientIST: Biomedical Engineering Experiments Supported by Mobile Devices, Cloud and IoT" Signals 1, no. 2: 110-120. https://doi.org/10.3390/signals1020006

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