Written by Beata Lewandowska
CSV file: AOI overall stats
The "AOI overall stats" CSV contains the same metrics that are included in AOI on the heatmap dashboard. There are the following fields:
- string study_id - UUID,
- string item_id - UUID,
- string item_filename - the name of your file, as it was named while adding to the study,
- string item_cdn_url - URL to the tested item saved on our servers,
- int participant_count - for how many participants the eye-tracking data was collected for this item,
- string aoi_id - UUID,
- string aoi_name - the name that you give to an AOI while saving it,
- string aoi_item_parts - exact AOI parameters (area and time range), especially important for multi AOI,
- float aoi_size_overall_percents - expressed as the percentage value relative to the size of the entire image,
- int aoi_time_range_from_ms - the start time from which the values of the AOI were calculated (you can set this time with the orange slider under the heatmap),
- int aoi_time_range_to_ms - the end time to which the values of the AOI were calculated (you can set this time with the orange slider under the heatmap),
- int aoi_fixation_total_count - number of fixations within this area,
- int aoi_fixation_average_ttff_ms - the amount of time that it takes participants (on average) to make the first fixation at this area (in milliseconds),
- int aoi_fixation_average_total_time_spent_ms - the average amount of time that all the participant's fixations lasted in total (in milliseconds),
- int aoi_fixation_average_fixation_duration_ms - the time that the average fixation lasted for (in milliseconds),
- int aoi_fixation_average_first_fixation_duration_ms - the time that the average first fixation lasted for (in milliseconds),
- int aoi_fixation_participant_ratio_percents - how many of all the participants looked at the given area (based on fixations),
- int aoi_gaze_total_count - number of gazes within this area,
- int aoi_gaze_average_time_to_first_gaze_at_ms - the amount of time that it takes participants (on average) to look at this area (in milliseconds),
- int aoi_gaze_average_total_time_spent_ms - the average amount of time that a participant looked at the area based on gazes (in milliseconds),
- int aoi_gaze_total_time_spent_ms - the total amount of time that all participants looked at the area based on gazes (in milliseconds),
- float aoi_gaze_participant_ratio_percents - how many of all the participants looked at the given area (based on gazes),
- int aoi_visit_total_count - AOI visit is detected if there's a fixation within the AOI (or many fixations "one after another"),
- int aoi_revisit_total_count - how many times participants looked back at the AOI (in total),
- float aoi_revisit_average_count - how many times participants looked back at the AOI (on average),
NOTE:
If the participant didn't looked at the AOI, then visits = 0, revisits = 0.
If the participant looked once at the AOI, then visits = 1, revisits = 0.
If the participant looked N-times at the AOI, then visits = N, revisits = N-1.
The " average revisits count takes into the account those who have not looked at the AOI (it includes those with 0 visits and revisits).
We count separate visit if there's a long data gap between fixations.
- int aoi_click_total_count - how many clicks all participants made within this AOI,
- int aoi_click_average_time_to_first_click_ms - the amount of time that it takes participants (on average) to click at this area for the first time,
- int aoi_word_total_count - how many words were registered within the area.
- notes - this column contains:
- RealEye version,
- fixation filter settings:
- gazepoint interpolation (Hz) - to improve calculations we interpolate the data to 60 Hz;
- gazepoint interpolation max gap (ms) - we interpolate data if the timestamp gap between two input values is not bigger than this value (50 ms);
- gaze velocity threshold;
- min. fixation duration (Ms);
- max. fixation duration (Ms);
- moving median range (Ms);
- saccade max duration (Ms);
- TestCriteria - data was downloaded for participants:
- age=min:max,
- isGenderMale={true/false},
- isGenderFemale={true/false},
- isGenderOther={true/false},
- isGenderNotSpecified={true/false},
- qualityMin={from1 to 6},
- qualityMax={from 1 to 6},
- tags={tag1},{tag2},...,
- keys=KEY{anykey},
- isParticipantTypeRealEye={true/false},
- isParticipantTypeNonRealEye={true/false},
- timestamp of when the file was downloaded.
See the CSV file for the sample study: