Work In Progress:  “Flash-Labs” as a Tool for Promoting Engagement and Learning in Signals and Systems for Biomedical Engineering Course

Uri Feldman; George D. Ricco

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Conference: 2023 ASEE Annual Conference & Exposition
Location: Baltimore , Maryland
Publication Date: June 25, 2023
Start Date: June 25, 2023
End Date: June 28, 2023
Conference Session: Biomedical Engineering Division (BED): Best of Works in Progress
Tagged Division: Biomedical Engineering Division (BED)
Tagged Topic: Diversity
Page Count: 5
DOI: 10.18260/1-2--44114
Permanent URL: https://peer.asee.org/44114
Download Count: 99

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Paper Authors

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Uri Feldman Wentworth Institute orcid.org/0000-0002-2986-748X

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Uri Feldman is an Assistant Professor of Biomedical Engineering in the School of Engineering at Wentworth Institute of Technology in Boston. He received a Ph.D. from the Massachusetts Institute of Technology’s Media Lab, a B.S. in Electrical Engineering from Case Western Reserve University in Cleveland, and an M.S. in Electrical Engineering from University of Illinois at Urbana Champaign. As a Postdoctoral Fellow at Harvard Medical School at Brigham and Women’s Hospital in Boston, Dr. Feldman developed informatics metrics to quantify performance of clinicians when using digital diagnostic tools. He has published in Radiology, Academic Radiology, IS&T, SPIE, and RESNA. As a Latino and native Spanish speaker, born in Peru, Dr. Feldman has created markets and commercialized innovative telemedicine products in Latin America for medical device companies, including Orex Computed Radiography, Kodak Health Group, and ICRco. Dr. Feldman also served as Chief Information Officer (CIO) of Boston Healthcare for the Homeless Program where he led the strategic planning and migration to EPIC Electronic Health Records system and novel meaningful use implementations through the Massachusetts Health Information Exchange. At Wentworth, Dr. Feldman is focused on project-based instruction, hands-on simulations, experiential learning approaches, and first year curriculum. Dr. Feldman is one of the lead instructors for Introduction to Engineering courses, with enrollments in the hundreds each fall. His research and teaching interests, in addition to first year engineering, include telemedicine, health informatics, rehabilitation engineering, and medical robotics. Dr. Feldman has collaborated with researchers and engineers from organizations including Tufts School of Veterinary Medicine, Boston Children’s Hospital, Vecnacares, and Restoreskills.

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George D. Ricco University of Indianapolis

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George D. Ricco is an engineering education educator who focuses on advanced analytical models applied to student progression, and teaching first-year engineering, engineering design principles, and project management.

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Abstract

Signals and Systems for Biomedical Engineering (BME) is a required course for seniors in a biomedical engineering program at a medium-sized engineering university on the East Coast. Signals and systems is an important course for engineers to take because it lays the foundation for digital signal processing, which is at the core of most technologies nowadays. The approach of the course is to engage students with a variety of active learning interventions to illustrate the fundamental concepts and methods of signals and systems. This paper illustrates how lab activities, integrated into the lecture periods, were utilized to enhance the teaching and learning of the complex concepts covered in the course. Inclusion of the active learning interventions described in this paper was motivated by the instructor’s experience and observations from delivering the course to eleven cohorts of students over the past five years. Signals and systems tends to be a challenging course for most engineering students, and more-so for BME students, because intuitive knowledge of calculus, differential equations, circuit analysis, and applications to human physiology are required. To absorb the material requires fluidity in shifting between mathematical and graphical representations of signals as well as switching between domains (e.g., time and frequency/ Laplace domains). Adding to the complexity, digital signal processing requires facility with modeling and simulation tools such as Matlab.

Signals and systems is usually taught from the perspective of mathematical modeling of systems, where the signals analyzed are mostly periodic and predictable. Signals and systems courses taught solely from the perspective of math lose the vital connections that students should make between theory and application . For BME students, an added challenge is that signals and systems focuses on modeling and analysis of physiological signals, which are typically not periodic and are less predictable. This presents a unique educational opportunity for BME students by learning the material by working with their own physiological signals. Students can relate the concepts and models to how their own bodies operate, such as analyzing their own vital signs including heart rate, blood pressure, and breathing rate.

The course is scheduled as three fifty-minute lectures per week. Since there is not enough time for a full-length lab, “Flash-labs” were introduced to be covered within the lecture sessions. Labs help students to learn the concepts in depth and to gain practical skills. Flash-labs are “pre-canned” for students, so they just need to execute them and report and discuss their findings with their classmates in small groups and through reflective postings in their e-portfolios, and with peer review. Flash-labs focus on biomedical applications including ECG, EEG, EMG, filtering in hearing-aids, heart-rate-variability to monitor stress levels, as well as clinical application such as blood pressure monitoring and closed-loop drug infusion control.

In this paper, results of analysis of the effectiveness and impact of flash-labs in signals and systems course are presented. Thematic analysis of student reports and reflections is currently being performed following established methods, with themes identified solely based on collected data without pre-existing code sets. Future plans include photovoice analysis of student reflections about their flash-lab experience. Preliminary observations indicate that, while some of the labs were more effective than others, overall, they served to deepen the understanding and application of the material learned in the course. One of the authors of this paper, is delivering the course in the Spring 2023 semester. Data from this offering may be incorporated if time to publication allows.

Citation
Format

Feldman, U., & Ricco, G. D. (2023, June), Work In Progress: “Flash-Labs” as a Tool for Promoting Engagement and Learning in Signals and Systems for Biomedical Engineering Course Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--44114

TY - CPAPER
AB - Signals and Systems for Biomedical Engineering (BME) is a required course for seniors in a biomedical engineering program at a medium-sized engineering university on the East Coast. Signals and systems is an important course for engineers to take because it lays the foundation for digital signal processing, which is at the core of most technologies nowadays. The approach of the course is to engage students with a variety of active learning interventions to illustrate the fundamental concepts and methods of signals and systems. This paper illustrates how lab activities, integrated into the lecture periods, were utilized to enhance the teaching and learning of the complex concepts covered in the course.
Inclusion of the active learning interventions described in this paper was motivated by the instructor’s experience and observations from delivering the course to eleven cohorts of students over the past five years. Signals and systems tends to be a challenging course for most engineering students, and more-so for BME students, because intuitive knowledge of calculus, differential equations, circuit analysis, and applications to human physiology are required. To absorb the material requires fluidity in shifting between mathematical and graphical representations of signals as well as switching between domains (e.g., time and frequency/ Laplace domains). Adding to the complexity, digital signal processing requires facility with modeling and simulation tools such as Matlab.

Signals and systems is usually taught from the perspective of mathematical modeling of systems, where the signals analyzed are mostly periodic and predictable. Signals and systems courses taught solely from the perspective of math lose the vital connections that students should make between theory and application . For BME students, an added challenge is that signals and systems focuses on modeling and analysis of physiological signals, which are typically not periodic and are less predictable. This presents a unique educational opportunity for BME students by learning the material by working with their own physiological signals. Students can relate the concepts and models to how their own bodies operate, such as analyzing their own vital signs including heart rate, blood pressure, and breathing rate.

The course is scheduled as three fifty-minute lectures per week. Since there is not enough time for a full-length lab, “Flash-labs” were introduced to be covered within the lecture sessions. Labs help students to learn the concepts in depth and to gain practical skills. Flash-labs are “pre-canned” for students, so they just need to execute them and report and discuss their findings with their classmates in small groups and through reflective postings in their e-portfolios, and with peer review. Flash-labs focus on biomedical applications including ECG, EEG, EMG, filtering in hearing-aids, heart-rate-variability to monitor stress levels, as well as clinical application such as blood pressure monitoring and closed-loop drug infusion control.

In this paper, results of analysis of the effectiveness and impact of flash-labs in signals and systems course are presented. Thematic analysis of student reports and reflections is currently being performed following established methods, with themes identified solely based on collected data without pre-existing code sets. Future plans include photovoice analysis of student reflections about their flash-lab experience. Preliminary observations indicate that, while some of the labs were more effective than others, overall, they served to deepen the understanding and application of the material learned in the course. One of the authors of this paper, is delivering the course in the Spring 2023 semester. Data from this offering may be incorporated if time to publication allows.

AU - Uri Feldman
AU - George D. Ricco
CY - Baltimore , Maryland
DA - 2023/06/25
PB - ASEE Conferences
TI - Work In Progress: “Flash-Labs” as a Tool for Promoting Engagement and Learning in Signals and Systems for Biomedical Engineering Course
UR - https://peer.asee.org/44114
DO - 10.18260/1-2--44114
ER -