Fixation Computation

The fixation computation node can be used to compute fixation data from raw eye movement data. In many cases, fixation data already exists in the data, and in that case, there is normally no need to use this node. However, if your data does not contain fixation data, and you want to use a visualization that requires fixation data (e.g. a scan path), then using this node is required.

This node implements the dispersion threshold identification algorithm described by Salvucci and Goldberg1.

Outputs

The fixation computation node computes fixation data from the input node and adds the computed data as extra columns to input data. Thus the output consists of the same columns as the input, plus these additional three columns:

FixationNumber
The fixations are consecutively numbered in this column, starting with 1. If no fixation was detected at a specific moment in time, this column will be 0 at that time.
FixationX
The x coordinate of the fixation, as computed from the input coordinates.
FixationY
The y coordinate of the fixation, as computed from the input coordinates.

Aggregation

The fixation computation node is not able to aggregate, because it only adds columns to the input data and thus a computed aggregation cannot exist.

Settings

Eye X Column:
The X coordinate column.
Eye Y Column:
The Y coordinate column.
Fixation Index Column Name:
The name for the fixation index column.
Fixation X Coordinate Column Name:
The name for the fixation x coordinate column.
Fixation Y Coordinate Column Name:
The name for the fixation y coordinate column.
Ignore (0, 0):
Ignore (0, 0) coordinates. If selected, a (0, 0) coordinate will not break a fixation. This can be useful, if the data maps many undetected eye positions to (0, 0), but should be used carefully, as it may lead to incorrect fixation detection.
Maximum Dispersion:
The maximum dispersion.
Minimum Rows:
The minimal fixation length, in data rows.

Footnotes:

1

Dario D. Salvucci and Joseph H. Goldberg, Identifying Fixations and Saccades in Eye-Tracking, http://dx.doi.org/10.1145/355017.355028

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