Development of a wireless wearable electrooculogram recorder for IoT based applications

Chakraborty, Suvodip; Dasgupta, Anirban; Dash, Punyashlok; Routray, Aurobinda

doi:10.1109/isie.2017.8001559

Cited by 6 publications

(2 citation statements)

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“…[10], [14] According to this study, the device's ease of use, portability, and convenience of wearing make it superior to current EOG recorders. The recording software is an Android app, making it ideal for both everyday users and Internet of Things (IoT) applications that rely on eye tracking.…”

Section: Literature Reviewmentioning

confidence: 99%

EOG Based Eye Blink Detection using VB GUI for Eye Writing Applications

Kamalnath,

Ponselvan,

Basha

et al. 2023

IJCSMC

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Usage of bio-signals from Electro-Oculo-Gram (EOG) in Human Computer Interaction (HCI) systems is one of the burgeoning study areas as of now. In order to provide support for physically challenged persons (or keypad Contactless HCI) in operating basic computer functions without making any physical touch with the computer keypad or mouse, we propose a framework utilization concept that changes movement of cursor on the computer screen using virtual keypad based on Visual Basic Graphical User Interface (VB GUI) with the eye movement detection through webcam of the system for different computer functions. In this work, VB GUI platform is used for a web browsing application and corresponding platform operation steps have been included. With the VB GUI, the basic cursor movements in the directions of left, right, up, and down to access the web links on the web page which is treated as eye writing in the concept of human computer interaction. Similarly, we can access different computer Apps such as MS-Doc, XL sheets, Audio and video files etc. Further, this paper focus is on prototype development of different home automation system applications.

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Section: Literature Reviewmentioning

confidence: 99%

EOG Based Eye Blink Detection using VB GUI for Eye Writing Applications

Kamalnath,

Ponselvan,

Basha

et al. 2023

IJCSMC

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“…Utilization of EOG signals is one method that has been widely developed in establishing communication between humans and machines [12], [14]. The development of EOG research has been carried out with various implementations, such as virtual keyboards as communication aids [8], [14]- [17], robot manipulator control [4], wheelchair control [18], [19], robot control [1], [20], mouse control [5], game development [2], IoT Application development [21], internet browsing application development [22], alarm system [23] and other developments.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Interface Efficiency: Adaptive Virtual Keyboard Minimizing Keystrokes in Electrooculography-Based Control

Anandika,

Laksono,

Suhaimi

et al. 2023

JNTE

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Rapid technological developments, one of which is technology to build communication relationships between humans and machines using Biosignals. One of them is Electrooculography (EOG). EOG is a type of biosignals obtained from eye movement. Research related to EOG has also developed a lot, especially for virtual keyboard control. Research on virtual keyboard control based on eye gaze motion using electrooculography technology has been widely developed. Previous research mostly drew conclusions based on time consumption in typing paragraphs. However, it has not been seen based on the number of eye gaze motions made by the user. In this research, an adaptive virtual keyboard system is built, controlled using EOG signals. The adaptive virtual keyboard is designed with 7x7 dimensions and has 49 buttons, including main buttons, letters, numbers, symbols, and unused buttons. The layout of the adaptive virtual keyboard has six zones. Each zone has a different number of steps. Characters located in the same zone have the same number of steps. The adaptive feature is to rearrange the position of the character's button based on the previously used characters. In the experiments, 30 respondents controlled static and adaptive virtual keyboards with 7 paragraphs typed. Adaptive mode rearranges the position of buttons based on k-selection activities from respondents. the k numbers are 10, 30, 50, 70 and 100. Two virtual keyboard modes are evaluated based on the number of steps required to type the paragraphs. Test results show that the performance of the adaptive virtual keyboard can shorten the number of user steps compared to static mode. There are tests of the optimal system that can be reduced up to 283 number of steps and from respondents, that can reduced up to 258 number of steps or about 40% of steps. This research underscores the promise of EOG-driven adaptive virtual keyboards, signaling a notable stride in augmenting user interaction efficiency in typing experiences, heralding a promising direction for future human-machine interface advancements.

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