Name
Abstract | ||
|---|---|---|
Objective: Accurate quantification of neurodegenerative disease progression is an ongoing challenge that complicates efforts to understand and treat these conditions. Clinical studies have shown that eye movement features may serve as objective biomarkers to support diagnosis and tracking of disease progression. Here, we demonstrate that saccade latency-an eye movement measure of reaction time-can... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/JBHI.2019.2913846 | IEEE Journal of Biomedical and Health Informatics |
Keywords | Field | DocType |
Diseases,Cameras,Task analysis,Visualization,Portable computers,Biomedical measurement,Face | Population,Computer vision,Gaze,Convolutional neural network,Latency (engineering),Computer science,Eye movement,Artificial intelligence,Saccade,Patient state,Intraclass correlation | Journal |
Volume | Issue | ISSN |
24 | 3 | 2168-2194 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hsin-Yu Lai | 1 | 2 | 2.39 |
| Gladynel Saavedra-Pena | 2 | 0 | 0.34 |
| Charles G. Sodini | 3 | 827 | 180.94 |
| V. Sze | 4 | 1007 | 58.98 |
| Thomas Heldt | 5 | 2 | 9.54 |