| Paper Abstract and Keywords |
| Presentation |
2022-02-27 14:15
A time-series learning model for estimating the microsaccade segments from fixation eye movement data
Tomoaki Morimoto, Kousuke Nakagaki, Masahito Sakaguchi, Ryoma Kobata, Hisashi Yoshida, Takeshi Kohama (Kindai Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In this study, we constructed a time-series learning model with the structure of Bi-LSTM for fixation eye movement data to establish a highly accurate estimation method of the section consisting of the start and endpoints of microsaccades (MS). We evaluated the accuracy of MS prediction by training the original signal of the fixation eye movement, its higher-order derivative signal, and their sum-of-squares signal of each. As a result, the average MS detection rate was about 98.8$pm 2.3$%, and the recall rate and precision for the predicted MS section were about 89.2$pm 7.2$% and 84.8$pm 7.2$%, respectively. In order to examine the interaction of the features, we trained the system using only the features with high contribution derived by Permutation Importance. The result indicates that the higher-order differential signal and its sum-of-squares signal may interact with each other in the MS detection accuracy. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Eye movements / Fixation eye movement / Microsaccades / Neural networks / Time series learning / / / |
| Reference Info. |
ITE Tech. Rep., vol. 46, no. 7, HI2022-4, pp. 33-38, Feb. 2022. |
| Paper # |
HI2022-4 |
| Date of Issue |
2022-02-20 (HI) |
| ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
| Download PDF |
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| Conference Information |
| Committee |
HI IEICE-HIP ASJ-H VRPSY |
| Conference Date |
2022-02-27 - 2022-02-28 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
on line |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
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| Paper Information |
| Registration To |
HI |
| Conference Code |
2022-02-HI-HIP-H-VRPSY |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
A time-series learning model for estimating the microsaccade segments from fixation eye movement data |
| Sub Title (in English) |
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| Keyword(1) |
Eye movements |
| Keyword(2) |
Fixation eye movement |
| Keyword(3) |
Microsaccades |
| Keyword(4) |
Neural networks |
| Keyword(5) |
Time series learning |
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| 1st Author's Name |
Tomoaki Morimoto |
| 1st Author's Affiliation |
Kindai University (Kindai Univ.) |
| 2nd Author's Name |
Kousuke Nakagaki |
| 2nd Author's Affiliation |
Kindai University (Kindai Univ.) |
| 3rd Author's Name |
Masahito Sakaguchi |
| 3rd Author's Affiliation |
Kindai University (Kindai Univ.) |
| 4th Author's Name |
Ryoma Kobata |
| 4th Author's Affiliation |
Kindai University (Kindai Univ.) |
| 5th Author's Name |
Hisashi Yoshida |
| 5th Author's Affiliation |
Kindai University (Kindai Univ.) |
| 6th Author's Name |
Takeshi Kohama |
| 6th Author's Affiliation |
Kindai University (Kindai Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2022-02-27 14:15:00 |
| Presentation Time |
25 minutes |
| Registration for |
HI |
| Paper # |
HI2022-4 |
| Volume (vol) |
vol.46 |
| Number (no) |
no.7 |
| Page |
pp.33-38 |
| #Pages |
6 |
| Date of Issue |
2022-02-20 (HI) |
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