The eye tracker is used in many fields such as education, marketing, psychology, medicine, among others. However, commercial devices are costly, spanning from a few hundred to several thousand dollars. Therefore, an inexpensive-monocular-remote (IMR) eye tracker is developed for education and research, which implements the Pupil-Center-Corneal-Reflection technique. The IMR device consists of a low-cost camera with a near-IR pass filter that captures subject’s eye images, a moderate-cost computer that processes these images, as well as two near-IR light sources that create glints and illuminate the eye. The pupil detection algorithm is developed by combining the advantages of two recent algorithms, named BORE and PDIF, and gaze points are estimated from pupil-glints vectors via a fourth-order polynomial. An experimental evaluation is conducted concurrently on the research eye tracker IMR at the operating frequency of 30 Hz and the commercial-high-end-head-free device VT3 Mini at 60 Hz, in a challenge condition: subjects sit down near a window, and some of them wear glasses. Also, their heads are placed on a fixed chin rest, and the data is acquired when both devices successfully estimate gaze points. The experimental results in 11 sample data, obtained from 7 subjects, show that the overall ratio of the number of filtered/raw samples and raw/idea samples are 88.92% and 98.63% in order. Whereas the overall precision of the IMR eye tracker is nearly equal to that of the VT3 Mini device (0.57 degrees and 0.54 degrees, respectively), the overall accuracy of the proposed eye tracker is better than that of the commercial device (1.04 degrees and 1.34 degrees, respectively). Regarding eye safety, the radiant power and the burn-hazard-weighted radiance of the proposed device are much smaller than their limitations, according to IEC 62471. With these results, the IMR eye tracker is appropriate for education and needs to be improved in terms of data validation to satisfy the research purpose.

No abstract

In dynamic threshold method to detect QRS complex from ECG signal, especially in real-time application, there are two main issues: baseline drift and noise. This paper introduces an improved QRS complex detecting method using dynamic threshold algorithm combined with a new method of electrodes placement to minimize baseline drift and different types of noise in real-time ECG acquisition with moving patients. Our method proved to be more effective in detecting QRS complex with less error due to minimized baseline drift and noise in original ECG signal.