Efficient Implementation and Design of a New Single-Channel Electrooculography-Based Human–Machine Interface System

Wu, Jiaping; Ang, Andrew; Tsui, K.M.; Wu, Hsiang-En; Hung, Y. S.; Hu, Yong; Mak, Joseph N.; Chan, S. C.; Zhang, Z. G.

doi:10.1109/tcsii.2014.2368617

Cited by 30 publications

(10 citation statements)

References 13 publications

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“…They classified three types of eye movements (upward, downward, and blinking) with an 84% classification accuracy. In the study by Wu et al they classified four classes of commands which were combined with three types of eye movements (double blink, single blink, and looking up) [ 15 ]. They measured single-channel EOG using a MindWave Mobile Headset (NeoroSky, San Jose, CA, USA), and the classification accuracy was 92.3%.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, there are several studies that developed goggle-type wearable EOG measurement systems to improve the user’s comfort by reducing preparation time [ 11 , 12 , 13 ]. However, the electrodes around the eyes often cause discomfort to the user, and this discomfort has been the motivation for many studies [ 14 , 15 , 16 , 17 ]. To simplify and improve user convenience, many studies have proposed new electrode placement that can replace conventional EOG electrode placement [ 14 , 15 , 16 , 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Wearable Forehead EOG Measurement System for Human Computer Interfaces

Heo

Yoon

Park

2017

Sensors

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Amyotrophic lateral sclerosis (ALS) patients whose voluntary muscles are paralyzed commonly communicate with the outside world using eye movement. There have been many efforts to support this method of communication by tracking or detecting eye movement. An electrooculogram (EOG), an electro-physiological signal, is generated by eye movements and can be measured with electrodes placed around the eye. In this study, we proposed a new practical electrode position on the forehead to measure EOG signals, and we developed a wearable forehead EOG measurement system for use in Human Computer/Machine interfaces (HCIs/HMIs). Four electrodes, including the ground electrode, were placed on the forehead. The two channels were arranged vertically and horizontally, sharing a positive electrode. Additionally, a real-time eye movement classification algorithm was developed based on the characteristics of the forehead EOG. Three applications were employed to evaluate the proposed system: a virtual keyboard using a modified Bremen BCI speller and an automatic sequential row-column scanner, and a drivable power wheelchair. The mean typing speeds of the modified Bremen brain–computer interface (BCI) speller and automatic row-column scanner were 10.81 and 7.74 letters per minute, and the mean classification accuracies were 91.25% and 95.12%, respectively. In the power wheelchair demonstration, the user drove the wheelchair through an 8-shape course without collision with obstacles.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Wearable Forehead EOG Measurement System for Human Computer Interfaces

Heo

Yoon

Park

2017

Sensors

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“…As shown in our previous study, various kinds of EOG signals, such as looking towards different directions and blinking in different ways, can be used to indicate the user's intentions [8]. However, because the system proposed in this paper is primarily focused on practical aspects and is aimed at providing an alternative communication pathway for the disabled people, only both-eye double blinks (DB) will be used as control signals in this paper.…”

Section: B Eog Signalsmentioning

confidence: 99%

A user-friendly wearable single-channel EOG-based human-computer interface for cursor control

Ang

Zhang

Hung

et al. 2015

2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)

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This paper presents a novel wearable single-channel electrooculography (EOG) based human-computer interface (HCI) with a simple system design and robust performance. In the proposed system, EOG signals for control are generated from double eye blinks, collected by a commercial wearable device (the NeuroSky MindWave headset), and then converted into a sequence of commands that can control cursor navigations and actions. The EOG-based cursor control system was tested on 8 subjects in indoor or outdoor environment, and the average accuracy is 84.42% for indoor uses and 71.50% for outdoor uses. Compared with other existing EOG-based HCI systems, this system is highly user-friendly and does not require any training. Therefore, this system has the potential to provide an easy-to-use and cheap assistive technique for locked-in patients who have lost their main body muscular abilities but with proper eye-condition.

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“…For example, eye gestures were analyzed again for the interface and control of appliances [ 25 ] and the solution to the drift problem [ 26 ] was also revised. Other research can be found where a novel encoding paradigm to convey users’ intentions is presented as a preliminary step to develop an HCI [ 27 ]. The only EOG-based GUIs oriented to physically disabled persons that can be found in the last three years are [ 28 ] and [ 29 ].…”

Section: Related Workmentioning

confidence: 99%

Development of a Computer Writing System Based on EOG

López

Ferrero

Yangüela

et al. 2017

Sensors

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The development of a novel computer writing system based on eye movements is introduced herein. A system of these characteristics requires the consideration of three subsystems: (1) A hardware device for the acquisition and transmission of the signals generated by eye movement to the computer; (2) A software application that allows, among other functions, data processing in order to minimize noise and classify signals; and (3) A graphical interface that allows the user to write text easily on the computer screen using eye movements only. This work analyzes these three subsystems and proposes innovative and low cost solutions for each one of them. This computer writing system was tested with 20 users and its efficiency was compared to a traditional virtual keyboard. The results have shown an important reduction in the time spent on writing, which can be very useful, especially for people with severe motor disorders.

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Efficient Implementation and Design of a New Single-Channel Electrooculography-Based Human–Machine Interface System

Cited by 30 publications

References 13 publications

A Novel Wearable Forehead EOG Measurement System for Human Computer Interfaces

A Novel Wearable Forehead EOG Measurement System for Human Computer Interfaces

A user-friendly wearable single-channel EOG-based human-computer interface for cursor control

Development of a Computer Writing System Based on EOG

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