EOG-based eye tracking protocol using baseline drift removal algorithm for long-term eye movement detection.

• This paper proposes a new DOSbFC algorithm to remove baseline drift of EOG Signals. • This paper presents a new electrode positioning scheme based on eyeglasses. • This paper provides a long-term eye movement detection function with high accuracy. This paper presents a new method to remove baseline drift and noise by using a differential electrooculography (EOG) signal based on a fixation curve (DOSbFC) and a new electrode positioning scheme based on eyeglasses for user convenience. In addition, a desktop application and mobile applications to control the human–computer interface were implemented. Finally, we created experimental EOG eyeglasses and a new detection protocol using the proposed method for long-term step-by-step detection of eye movements and user comfort. The proposed DOSbFC calculates the difference values of accumulated EOG signals between the initial eye movement and fixation time. It allows long-term detection of eye movements with high accuracy and only requires a single calibration. The vertical and ground electrodes of the standard electrode positioning scheme caused discomfort of subjects; the proposed electrode positioning scheme solves these problems and enables the use of existing eyeglasses without design modification. The experimental results demonstrated that the average accuracy of the long-term eye movement detection was 94%, whereas those of the band pass filter and wavelet transform were 61% and 64%, respectively. This was because baseline drift and noise were removed by averaging the signal variations. Further experimental results demonstrated that the average information transfer rate of the proposed method was 6.0, whereas those of the band pass filter and wavelet transform were 1.1 and 0.9, respectively. [ABSTRACT FROM AUTHOR]