Engaging Community College Students in Computer Engineering Research through Design and Implementation of a Versatile Gesture Control Interface

• Published in: Association for Engineering Education - Engineering Library Division Papers
• Main Authors: Yan, Jeffrey Thomas, Dalton, James LeRoy, Chang, Kattia, Bianca Corine Villanueva Doronila, Victor Josue Melara Alvarado, Thomas, Christopher, Donovan, Ian M, Bholla, Kartik, Enriquez, Amelito G, Pong, Wenshen, Jiang, Zhaoshuo, Chen, Cheng, Teh, Kwok Siong, Mahmoodi, Hamid, Jiang, Hao, Okada, Kazunori, Zhang, Xiaorong
• Format: Conference Proceeding
• Language: English
• Published: Atlanta American Society for Engineering Education-ASEE 20.04.2017
• Subjects: College students; Colleges & universities; Community colleges; Community participation; Computer engineering; Data analysis; Design of experiments; Electromyography; Engineering education; Engineering profession; Engineering research; Forearm; Gesture recognition; Government agencies; Interfaces; Internships; Man-machine interfaces; Muscles; Recognition; Rehabilitation; Signal processing; STEM education; Students; Technical education; Time management; Virtual reality

Given the important role of community colleges in undergraduate education, in order to increase the recruitment of STEM students and improve undergraduate STEM education, it is crucial to develop strategies to inspire community college students’ interest in STEM. 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 was developed to engage community college students in leading-edge engineering research. In summer 2016, 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 an intelligent electromyography (EMG)-based gesture control interface which deciphers EMG signals collected from forearm muscles to identify users’ intended hand and arm movements. The gesture control interface has great potential to provide natural human-machine interaction in a variety of applications, from assistive devices through rehabilitation therapy to virtual reality (VR). The developed interface provides easy connection with a commercial EMG-based armband Myo and a modular software engine for customizable gesture recognition as well as a special pipeline for converting recognition decisions into control commands for external applications. The students also conducted usability testing of the gesture control interface on human subjects by using it to control a first-person shooter (FPS) virtual reality game which was developed by another community college student intern. The project provided a great opportunity for the student interns to gain research experience and learn valuable knowledge in human-machine interfaces, EMG signal processing, and gesture recognition. It also helped them improve their skills in experimental design, data analysis, scientific writing and presentation, as well as teamwork and time management. The outcome of this project indicated that the internship program was an effective method for inspiring community college students’ interest in computer engineering research and strengthening their confidence and capability in pursuing an engineering profession.