Abstract
We are researching and developing dynamic interpersonal distance models and real-time recognition systems for the social development training therapy of children with autism spectrum disorders (ASD). In particular, we modeled the quantitative measurements of chasing behaviors observed during therapy. Chasing behaviors are a highly social activity because children need to predict the movement of a partner (therapist). In order to measure these behaviors, the video coding using observational method by experts is needed but it is very time consuming. We consider that establishing models for real-time automated recognition of chasing behavior supports social skills development programs for children with ASD. This study focuses on chasing behavior and presents experimental results for recognition of chasing behavior during actual therapy. The proposed system reveals that it is possible to extract tracking behaviors which closely agree with therapist observations.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 115-120 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538607701 |
| DOIs | |
| Publication status | Published - 2017 Nov 14 |
| Event | 16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017 - Oxford, United Kingdom Duration: 2017 Jul 26 → 2017 Jul 28 |
Other
| Other | 16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017 |
|---|---|
| Country | United Kingdom |
| City | Oxford |
| Period | 17/7/26 → 17/7/28 |
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ASJC Scopus subject areas
- Cognitive Neuroscience
- Information Systems
- Computer Science (miscellaneous)
Cite this
Modeling of the chasing behaviors for developmental program of children with autism spectrum disorders. / Tsuji, Airi; Sekine, Satoru; Enomoto, Takuya; Matsuda, Soichiro; Yamamoto, Jyun'ichi; Suzuki, Kenji.
Proceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 115-120 8109739.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Modeling of the chasing behaviors for developmental program of children with autism spectrum disorders
AU - Tsuji, Airi
AU - Sekine, Satoru
AU - Enomoto, Takuya
AU - Matsuda, Soichiro
AU - Yamamoto, Jyun'ichi
AU - Suzuki, Kenji
PY - 2017/11/14
Y1 - 2017/11/14
N2 - We are researching and developing dynamic interpersonal distance models and real-time recognition systems for the social development training therapy of children with autism spectrum disorders (ASD). In particular, we modeled the quantitative measurements of chasing behaviors observed during therapy. Chasing behaviors are a highly social activity because children need to predict the movement of a partner (therapist). In order to measure these behaviors, the video coding using observational method by experts is needed but it is very time consuming. We consider that establishing models for real-time automated recognition of chasing behavior supports social skills development programs for children with ASD. This study focuses on chasing behavior and presents experimental results for recognition of chasing behavior during actual therapy. The proposed system reveals that it is possible to extract tracking behaviors which closely agree with therapist observations.
AB - We are researching and developing dynamic interpersonal distance models and real-time recognition systems for the social development training therapy of children with autism spectrum disorders (ASD). In particular, we modeled the quantitative measurements of chasing behaviors observed during therapy. Chasing behaviors are a highly social activity because children need to predict the movement of a partner (therapist). In order to measure these behaviors, the video coding using observational method by experts is needed but it is very time consuming. We consider that establishing models for real-time automated recognition of chasing behavior supports social skills development programs for children with ASD. This study focuses on chasing behavior and presents experimental results for recognition of chasing behavior during actual therapy. The proposed system reveals that it is possible to extract tracking behaviors which closely agree with therapist observations.
UR - http://www.scopus.com/inward/record.url?scp=85040568695&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040568695&partnerID=8YFLogxK
U2 - 10.1109/ICCI-CC.2017.8109739
DO - 10.1109/ICCI-CC.2017.8109739
M3 - Conference contribution
SP - 115
EP - 120
BT - Proceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
ER -