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Engaging Community College Students in Emerging Human-Machine Interfaces Research through Design and Implementation of a Mobile Application for Gesture Recognition

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Conference

2018 ASEE Zone IV Conference

Location

Boulder, Colorado

Publication Date

March 25, 2018

Start Date

March 25, 2018

End Date

March 27, 2018

Tagged Topic

Diversity

Page Count

12

Permanent URL

https://peer.asee.org/29610

Download Count

53

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Paper Authors

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Kattia Chang Cañada College

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Kattia Chang is a sophomore student at Cañada College in Redwood cIty, majoring in Computer Engineering. Her interests include embedded systems, robotics, and machine learning.

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Karina Abad Cañada College

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Karina Abad is currently a junior at Canada College in Redwood City, CA, majoring in Computer Science. She hopes to pursue a career in business and technology.

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Ricardo Jesus Colin Canada College

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Ricardo Colin is currently a junior at Canada College in Redwood City, Ca, majoring in Computer Engineering. His research interest includes embedded systems and wireless technology, and hopes to pursue a position which will enable him to use his skills.

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Charles Tolentino University of California, Merced

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Charles Tolentino is currently attending the University of California, Merced as a transfer student who is pursuing a degree in Computer Science and Engineering.

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Cameron Malloy University of California, Berkeley

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Cameron Malloy is currently a junior at the University of California, Berkeley, majoring in Applied Mathematics and Computer Science. He's interested in data analytics, blockchain technology, and machine learning, and aspires to be a data scientist.

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Alex David San Francisco State University

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Currently a student at SFSU in the Embedded Electrical and Computer Systems program. Focusing on real time embedded machine learning and cloud/edge computing.

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Amelito G Enriquez Canada College Orcid 16x16 orcid.org/0000-0002-1259-0680

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Amelito Enriquez is a professor of Engineering and Mathematics at Cañada College in Redwood City, CA. He received a BS in Geodetic Engineering from the University of the Philippines, his MS in Geodetic Science from the Ohio State University, and his PhD in Mechanical Engineering from the University of California, Irvine. His research interests include technology-enhanced instruction and increasing the representation of female, minority and other underrepresented groups in mathematics, science and engineering.

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Wenshen Pong P.E. San Francisco State University

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Wenshen Pong received his Ph.D. in Structural Engineering from the State University of New York at Buffalo. He joined the School of Engineering at San Francisco State University in 1998. He teaches courses in Civil/Structural Engineering.

Dr. Pong is a registered Professional Engineer in California. He is a member of the American Society of Civil Engineers and the Structural Engineers Association of California. He has published over fifty technical papers in the areas of Structural Control and Earthquake Engineering. Dr. Pong has been the Director of the School of Engineering at SFSU with 20 full-time faculty and over 25 part-time faculty since 2009.

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Zhaoshuo Jiang P.E. San Francisco State University

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Zhaoshuo Jiang graduated from the University of Connecticut with a Ph.D. degree in Civil Engineering. Before joining San Francisco State University as an assistant professor, he worked as a structural engineering professional at Skidmore, Owings & Merrill (SOM) LLP. As a licensed professional engineer in the states of Connecticut and California, Dr. Jiang has been involved in the design of a variety of low-rise and high-rise projects. His current research interests mainly focus on Smart Structures Technology, Structural Control and Health Monitoring and Innovative Engineering Education.

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Cheng Chen San Francisco State University

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Dr. Cheng Chen is currently an associate professor in the school of engineering at San Francisco State University. His research interests include earthquake engineering, structural reliability and fire structural engineering.

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Kwok Siong Teh San Francisco State University

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Kwok Siong Teh received his B.S., M.S., Ph.D. degrees in Mechanical Engineering from the University of Illinois Urbana-Champaign, University of Michigan at Ann Arbor, and University of California at Berkeley in 1997, 2001, and 2004, respectively. He is currently an associate professor of mechanical engineering at San Francisco State University. His primary research interests are in: (i) the synthesis, characterization, and applications of metal oxides, conductive polymer, and low dimensional carbon nanostructures for energy generation and storage; (ii) engineering design pedagogy that incorporates makerspace, case studies, and scenario-based learning.

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Hamid Mahmoodi San Francisco State University

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Hamid Mahmoodi received his Ph.D. degree in electrical and computer engineering from Purdue University, West Lafayette, IN, in 2005. He is currently a professor of electrical and computer engineering in the School of Engineering at San Francisco State University. His research interests include low-power, reliable, and high-performance circuit design in nano-electronic technologies. He has published more than one hundred technical papers in journals and conferences and holds five U.S. patents. He was a co-recipient of the 2008 SRC Inventor Recognition Award, the 2006 IEEE Circuits and Systems Society VLSI Transactions Best Paper Award, 2005 SRC Technical Excellence Award, and the Best Paper Award of the 2004 International Conference on Computer Design. He has served on technical program committees of Custom Integrated Circuits Conference, International Symposium on Low Power Electronics Design, and International Symposium on Quality Electronics Design.

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Hao Jiang San Francisco State University

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Hao Jiang received the B.S. degree in materials sciences from Tsinghua University, China, in 1994 and the Ph.D. degree in electrical engineering from the University of California, San Diego, in 2000.

Hao Jiang has been with San Francisco State University since August 2007 as an assistant professor in electrical engineering. Prior joining SFSU, he worked for Broadcom Corporation, Jazz Semiconductor and Conexant Systems Inc. His research interests are in the general area of analog integrated circuits, particularly in ultra-low-power circuits for biomedical applications.

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Xiaorong Zhang San Francisco State University

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Xiaorong Zhang received the B.S. degree in computer science from Huazhong University of Science and Technology, China, in 2006, the M.S. and the Ph.D. degrees in computer engineering from University of Rhode Island, Kingston, in 2009 and 2013 respectively. She is currently an Assistant Professor in the School of Engineering at San Francisco State University. Her research interests include embedded systems, wearable technologies, neural-machine interface, and cyber-physical systems.

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Abstract

Undergraduate research experience has been identified as an effective approach for engaging science, technology, engineering, and mathematics (STEM) students and increasing their retention rates. Community colleges enroll almost half of the nation’s undergraduate students and play a significant role in STEM education. Thus it is important to develop strategies to provide community college students with research opportunities and experiences. With support from the Department of Education Minority Science and Engineering Improvement Program (MSEIP), a cooperative internship program between a community college and a public comprehensive university has been developed to engage community college students in leading-edge engineering research. In summer 2017, five sophomore students from the community college participated in a ten-week computer engineering research internship project in a research lab at the four-year university. This internship project aimed to develop a low-cost, portable, and flexible human-machine interface for real-time gesture recognition. Electromyography (EMG) is a technique for measuring the electrical activity generated by skeletal muscles. EMG pattern recognition (PR) is an intelligent method for deciphering neuromuscular information from EMG signals to identify users’ intended movements. The human-machine interface developed by the interns provides real-time processing speed and sufficient storage capacity for computationally complex EMG PR algorithms by integrating mobile and cloud computing techniques. Specifically, a mobile Android application was developed which provides easy interface with a commercial EMG sensing armband Myo (Thalmic Labs) and a modular software engine seamlessly integrating a variety of signal processing modules, from data acquisition through pattern recognition, to real-time evaluation and control. In addition, an interface between the Android application and the Amazon Web Services Cloud Server was built which allows real-time cloud computing and storage. Real-time experiments were conducted on able-bodied subjects for hand gesture recognition to evaluate the accuracy, response time, and usability of the developed system. The project provided a great opportunity for the student interns to gain valuable research experience in human-machine interfaces and to improve their skills in teamwork, time management, as well as scientific writing and presentation. It also helped the students strengthening their confidence and interest in pursuing a STEM profession.

Chang, K., & Abad, K., & Colin, R. J., & Tolentino, C., & Malloy, C., & David, A., & Enriquez, A. G., & Pong, W., & Jiang, Z., & Chen, C., & Teh, K. S., & Mahmoodi, H., & Jiang, H., & Zhang, X. (2018, March), Engaging Community College Students in Emerging Human-Machine Interfaces Research through Design and Implementation of a Mobile Application for Gesture Recognition Paper presented at 2018 ASEE Zone IV Conference, Boulder, Colorado. https://peer.asee.org/29610

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