Presentation-Aid Armband with IMU, EMG Sensor and Bluetooth for Free-Hand Writing and Hand Gesture Recognition

Joselito Eduard E. Goh (), Marie Luvett I. Goh (), Jobelle S. Estrada (), Nikki C. Lindog (), Jan Carlo M. Tabulog () and Neil Earvin C. Talavera ()
Additional contact information
Joselito Eduard E. Goh: Adamson University
Marie Luvett I. Goh: Adamson University
Jobelle S. Estrada: Adamson University
Nikki C. Lindog: Adamson University
Jan Carlo M. Tabulog: Adamson University
Neil Earvin C. Talavera: Adamson University

International Journal of Computing Sciences Research, 2018, vol. 1, issue 3, 1-13

Abstract: Purpose: The study aimed to improve the presenters capability to give a presentation in a hands-free manner. It covered the design of a wearable armband that uses electromyography (EMG), Inertial Measurement Unit (IMU), and Bluetooth wireless technology. Also, it covered the development of presentation software for Windows operating system. Method: The study employed the common elements of engineering design process which includes problem identification, requirement analysis, design solution, implementation, and testing. Prototyping approach was used to design the armband to ensure that it can properly gather raw EMG and IMU signals. Object-Oriented Programming (OOP) was used to develop the presentation software so it could interpret the received signals into common hand gestures and facilitate free handwriting on air. Results: Raw EMG and IMU signals could be transmitted from the armband to the attached computer via Bluetooth successfully. The developed software was able to interpret the received signals from the armband and perform the corresponding computer navigation commands. It is able to recognize and translate dynamic gestures into an equivalent handwriting. Furthermore, it is able to read different file types such as Portable Document File (PDF), PowerPoint, Word document and audio-video media files. Conclusion: The angular velocity and linear acceleration data from arm movement along with the electromyographic data from forearm muscle contraction could be successfully used to implement hands-free navigation and free-hand writing on air. Thus, the integration of IMU with the EMG signals for dynamic hand gestures and free-handwriting work accordingly. Recommendations: To increase the number of recognizable gestures, additional EMG sensors must be placed in more strategic positions. Handwriting functionality could be improved with the use of additional handwriting recognition algorithm. Research Implications: Modern presentation tools like interactive whiteboard offers a lot of promising functionality but it comes with a price. The use of an add-on wearable device for lecture and presentation purposes will benefit various organizations and academic institutions since it will give them the advantage of modern presentation tools without having to abandon the currently usable laptop and LCD projectors.

Keywords: armband; electromyography sensor; hand gesture; hands-free writing; IMU sensor; presentation-aid; wearable technology (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.stepacademic.net/ijcsr/article/view/53/34 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jcs:journl:v:1:y:2018:i:3:p:1-13

DOI: 10.25147/ijcsr.2017.001.1.16

Access Statistics for this article

More articles in International Journal of Computing Sciences Research from Step Academic
Bibliographic data for series maintained by Liam Demafelix ().