Using natural viewing behavior to screen for and reconstruct visual field defects
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'There is a need for simple and effective ways to screen for visual field defects (VFD). Watching a movie is a simple task most humans are familiar with. Therefore we assessed whether it is possible to detect and reconstruct visual field defects based on free viewing eye movements, recorded while watching movie clips. Participants watched 90 movie clips of one minute, with and without simulated visual field defects (sVFD), while their eye movements were tracked. We simulated homonymous hemianopia (HH) (left and right sided) and glaucoma (small nasal arc, large nasal arc, and tunnel vision). We generated fixation density maps of the visual field and trained a linear support vector machine to predict the viewing conditions of each trial of each participant based on these maps. To reconstruct the visual field defect, we computed 'viewing pr' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Free-viewing eye movements","Simulated visual field defects","Visual Field Defects"]} <|eot_id|>
 Here is the Description of a dataset. Description:'There is a need for simple and effective ways to screen for visual field defects (VFD). Watching a movie is a simple task most humans are familiar with. Therefore we assessed whether it is possible to detect and reconstruct visual field defects based on free viewing eye movements, recorded while watching movie clips. Participants watched 90 movie clips of one minute, with and without simulated visual field defects (sVFD), while their eye movements were tracked. We simulated homonymous hemianopia (HH) (left and right sided) and glaucoma (small nasal arc, large nasal arc, and tunnel vision). We generated fixation density maps of the visual field and trained a linear support vector machine to predict the viewing conditions of each trial of each participant based on these maps. To reconstruct the visual field defect, we computed 'viewing pr' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
There is a need for simple and effective ways to screen for visual field defects (VFD). Watching a movie is a simple task most humans are familiar with. Therefore we assessed whether it is possible to detect and reconstruct visual field defects based on free viewing eye movements, recorded while watching movie clips. Participants watched 90 movie clips of one minute, with and without simulated visual field defects (sVFD), while their eye movements were tracked. We simulated homonymous hemianopia (HH) (left and right sided) and glaucoma (small nasal arc, large nasal arc, and tunnel vision). We generated fixation density maps of the visual field and trained a linear support vector machine to predict the viewing conditions of each trial of each participant based on these maps. To reconstruct the visual field defect, we computed 'viewing pr
Free-viewing eye movements; Simulated visual field defects; Visual Field Defects