Development of a Computer Writing System Based on EOG

Brain-computer interface (BCI) technology shows potential for application to motor rehabilitation therapies that use neural plasticity to restore motor function and improve quality of life of stroke survivors. However, it is often difficult for BCI systems to provide the variety of control commands necessary for multi-task real-time control of soft robot naturally. In this study, a novel multimodal human-machine interface system (mHMI) is developed using combinations of electrooculography (EOG), electroencephalography (EEG), and electromyogram (EMG) to generate numerous control instructions. Moreover, we also explore subject acceptance of an affordable wearable soft robot to move basic hand actions during robot-assisted movement. Six healthy subjects separately perform left and right hand motor imagery, looking-left and looking-right eye movements, and different hand gestures in different modes to control a soft robot in a variety of actions. The results indicate that the number of mHMI control instructions is significantly greater than achievable with any individual mode. Furthermore, the mHMI can achieve an average classification accuracy of 93.83% with the average information transfer rate of 47.41 bits/min, which is entirely equivalent to a control speed of 17 actions per minute. The study is expected to construct a more user-friendly mHMI for real-time control of soft robot to help healthy or disabled persons perform basic hand movements in friendly and convenient way.

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“…Average time presents mean time of whole task in 1 min. These parameters have been calculated previously as follows (López et al, 2017).…”

Section: Methodsmentioning

confidence: 99%

An EEG/EMG/EOG-Based Multimodal Human-Machine Interface to Real-Time Control of a Soft Robot Hand

et al. 2019

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“…Diagram blok sistem penggerak kursor menggunakan sinyal EOG Fokus dari penelitian ini ialah bagaimana penderita dapat berinteraksi dengan komputer menggunakan gerakan mata. Teknik pendeteksi gerakan mata yang sudah ada saat ini adalah teknik pendeteksi gerakan mata berbasis video-okulografi (VOG) dan berbasis elektrookulografi (EOG) [2]. Pada VOG, kamera digunakan untuk merekam satu atau kedua mata kemudian dengan algoritma pendeteksi gerakan mata, mata dapat terekam.…”

Section: Pendahuluanunclassified

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1] [fysuratman, achmadrizal]@telkomuniversity.ac.id [2] [3] KEYWORDS:ABSTRACT Electrooculogram, Thresholding, Cursor, Motor Disability

Amyotrophic Lateral Sclerosis (ALS) is an illness due to lack of nourishment in human motoric nerves. This illness causes the sufferer a loss in motoric movement.

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confidence: 99%

Pengembangan Sistem Pengendali Kursor Menggunakan Sinyal Elektrookulogram (EOG)

Perdana

Suratman

Rizal

2019

jtim

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Amyotrophic Lateral Sclerosis (ALS) is an illness due to lack of nourishment in human motoric nerves. This illness causes the sufferer a loss in motoric movement. Thankfully there is still an organ that move well regardless the illness, and that is eye movement. Eye tracking method have been applied to controlling computer. Majority of eye tracking methods are divided into two methods, video-oculography (VOG), and electrooculography (EOG). VOG used camera as video recorder and processed using image processing to track eye movement. EOG used skin electrode that were usually used in electrocardiography, which could detect electrical activity on the back of eye. The principle in this research is to design a cursor controlling system using EOG sensor and classified the signal using simple thresholding method. The result would be cursor movement based on eye movement. Purpose of this final assignment is to design a cursor controlling system based EOG sensor. The experimental results yield an accuracy of 98% for the cursor movement controlling. The system can control the direction of the cursor's movement but cannot control other activities of the cursor.

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“…Some of the studies have focused on moving the cursor towards the desired letter of a virtual keyboard by moving the eye in four directions (right, left, up, and down) and the desired letter is selected by the blink of an eye [7,[26][27][28]. The achieved writing speeds are higher than the BCI systems but it is still insufficient when compared with optical tracking based methods.…”

Section: Introductionmentioning

confidence: 99%

“…The achieved writing speeds are higher than the BCI systems but it is still insufficient when compared with optical tracking based methods. In another EOG-based approach, it has been tried to draw letters using eye movements [21,[28][29][30][31]. This method has been able to improve the writing speed by about 8 wpm, but the recognition rate of written characters is low.…”

Section: Introductionmentioning

confidence: 99%

A New PC-Based Text Entry System Based on EOG Coding

Yildiz¹,

Ülkütaş

2018

Advances in Human-Computer Interaction

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Some disadvantages of optical eye tracking systems have increased the interest to EOG (Electrooculography) based Human Computer Interaction (HCI). However, text entry attempts using EOG have been slower than expected because the eyes should move several times for entering a character. In order to improve the writing speed and accuracy of EOG based text entry, a new method based on the coding of eye movements has been suggested in this study. In addition, a real time EOG based HCI system has developed to implement the method. In our method all characters have been encoded by single saccades in 8 directions and different dwell time. In order to standardize dwell times and facilitate the coding process, computer assisted voice guidance was used. A number of experiments have been conducted to examine the effectiveness of the proposed method and system. At the end of the fifth trials, an experienced user was able to write at average 13.2 wpm (5 letters = 1 word) with 100% accuracy using the developed system. The results of our experiments have shown that text entry with the eye can be done quickly and efficiently with the proposed method and system.

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Development of a Computer Writing System Based on EOG

Cited by 33 publications

References 49 publications

An EEG/EMG/EOG-Based Multimodal Human-Machine Interface to Real-Time Control of a Soft Robot Hand

An EEG/EMG/EOG-Based Multimodal Human-Machine Interface to Real-Time Control of a Soft Robot Hand

Pengembangan Sistem Pengendali Kursor Menggunakan Sinyal Elektrookulogram (EOG)

A New PC-Based Text Entry System Based on EOG Coding

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