Name
Abstract | ||
|---|---|---|
Disorders of the vestibular system possibly decrease vision, causing abnormal nystagmus and dizziness. To diagnose abnormal nystagmus, various studies have been reported including the use of rotating chair tests and videonystagmography. However, these tests are unsuitable for home use due to their high costs. Thus, a low-cost video-oculography system is necessary to obtain clinical features at home. In this paper, we present a goggle-type low-cost video-oculography system using an infrared camera and Raspberry Pi board for tracking the pupils and evaluating a vestibular system. Horizontal eye movement is derived from video data obtained from an infrared camera and infrared light-emitting diodes, and the velocity of head rotation is obtained from a gyroscope sensor. Each pupil was extracted using a morphology operation and a contour detection method. Rotatory chair tests were conducted with our developed device. To evaluate our system, gain, symmetry, and phase were measured and compared System 2000. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s13640-018-0266-x | EURASIP Journal on Image and Video Processing |
Keywords | Field | DocType |
Infrared camera,Video-oculography,VOG,Videonystagmography,VNG | Computer vision,Gyroscope,Videonystagmography,Vestibular system,Computer science,Pupil,Video-oculography,Nystagmus,Eye movement,Artificial intelligence,Vog | Journal |
Volume | Issue | ISSN |
2018 | 1 | 1687-5281 |
Citations | PageRank | References |
1 | 0.43 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Youngsun Kong | 1 | 11 | 4.68 |
| Suhwan Lee | 2 | 1 | 0.43 |
| Jinseok Lee | 3 | 14 | 4.19 |
| Yunyoung Nam | 4 | 266 | 39.60 |