Journal w/ review

1. 薄羽大樹, 山中祥太, 宮下芳明. Motor WidthとVisual Widthが異なる状況下でのポインティング性能. 情報処理学会論文誌, Vol. 60, No. 4, 1184--1199, 2019. [PDF]
2. Shota Yamanaka, and Hiroki Usuba. Rethinking the Dual Gaussian Distribution Model for Predicting Touch Accuracy in On-Screen-Start Pointing Tasks. Proc. ACM Hum.-Comput. Interact., Vol. 4, No. ISS, Article 205 (November 2020), 20 pages, 2020. https://doi.org/10.1145/3427333 [Acceptance rate 28%]
3. 薄羽大樹, 山中祥太, 宮下芳明. 直角に連結された幅の異なる経路をステアリングする操作のモデル化. 情報処理学会論文誌, Vol. 62, No. 2, 574--584, 2021.
4. 薄羽大樹, 山中祥太, 宮下芳明. Motor WidthとVisual Widthの差を考慮したポインティングのモデル化. 情報処理学会論文誌, Vol. 62, No. 2, 585--593, 2021.
5. Hiroki Usuba, Shota Yamanaka, and Homei Miyashita. Modeling Movement Times and Success Rates for Acquisition of One-Dimensional Targets with Uncertain Touchable Sizes. Proc. ACM Hum.-Comput. Interact., Vol. 5, No. ISS, Article 487 (November 2021), 15 pages, 2021. https://doi.org/10.1145/3486953 [Acceptance rate 29.9%]
6. Shota Yamanaka, and Hiroki Usuba. Computing Touch-Point Ambiguity on Mobile Touchscreens for Modeling Target Selection Times. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., Vol. 5, No. 4, Article 186 (Dec 2021), 21 pages, 2022. https://doi.org/10.1145/3494976
7. 島田雄輝, 薄羽大樹, 宮下芳明. 視線を用いた1次元ポインティングにおける1次サッカードエラー率のモデル化. 情報処理学会論文誌, Vol. 63, No. 2, 413--423, 2021.
8. Hiroki Usuba, Shota Yamanaka, Junichi Sato, and Homei Miyashita. Predicting Touch Accuracy for Rectangular Targets by Using One-Dimensional Task Results. Proc. ACM Hum.-Comput. Interact., Vol. 6, No. ISS, Article 579 (December 2022), 13 pages, 2022. https://doi.org/10.1145/3567732 [Acceptance rate 25.4%]
9. Shota Yamanaka, Hiroki Usuba, Wolfgang Stuerzlinger, and Homei Miyashita. The Effectiveness of Path-Segmentation for Modeling Lasso Times in Width-Varying Paths. Proc. ACM Hum.-Comput. Interact., Vol. 6, No. ISS, Article 584 (December 2022), 20 pages, 2022. https://doi.org/10.1145/3567737 [Acceptance rate 25.4%]
10. Shota Yamanaka, Hiroki Usuba, Haruki Takahashi, and Homei Miyashita. Predicting Success Rates in Steering Through Linear and Circular Paths by the Servo-Gaussian Model. International Journal of Human–Computer Interaction, Vol. 0, No. 0, 1--19, 2023. https://doi.org/10.1080/10447318.2023.2212221
11. Hiroki Usuba, Shota Yamanaka, and Junichi Sato. Clarifying the Effect of Edge Targets in Touch Pointing through Crowdsourced Experiments. , Vol. 7, No. ISS, Article 433 (December 2023), 19 pages, 2023. https://doi.org/10.1145/3626469

Paper at international conference w/ review

1. Hiroki Usuba, Shota Yamanaka, and Homei Miyashita. User Performance by the Difference Between Motor and Visual Widths for Small Target Pointing. In Proceedings of the 10th Nordic Conference on Human-Computer Interaction (NordiCHI '18), 161--169, 2018. http://doi.acm.org/10.1145/3240167.3240171 [Full paper; acceptance rate 24.5%] [PDF]
2. Hiroki Usuba, Shota Yamanaka, and Homei Miyashita. Pointing to Targets with Difference Between Motor and Visual Widths. In Proceedings of the 30th Australian Conference on Computer-Human Interaction (OzCHI '18), 374--383, 2018. http://doi.acm.org/10.1145/3292147.3292150 [Long paper; acceptance rate 40%] [PDF]
3. Kaito Yamada, Hiroki Usuba, and Homei Miyashita. Modeling Drone Crossing Movement with Fitts' Law. In HCI International 2019 -- Late Breaking Papers, 422--432, 2019. https://doi.org/10.1007/978-3-030-30033-3_33 [PDF]
4. Hiroki Usuba, Shota Yamanaka, and Homei Miyashita. Touch Pointing Performance for Uncertain Touchable Sizes of 1D Targets. In Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '19), 20:1--20:8, 2019. http://doi.acm.org/10.1145/3338286.3340131 [Acceptance rate 26.4%] [PDF]
5. Hiroki Usuba, Shota Yamanaka, and Homei Miyashita. Comparing Lassoing Criteria and Modeling Straight-Line and One-Loop Lassoing Motions Considering Criteria. In Proceedings of the 2019 ACM International Conference on Interactive Surfaces and Spaces (ISS '19), 181--191, 2019. https://doi.org/10.1145/3343055.3359707 [Academic Paper; acceptance rate 30.6%] [PDF]
6. Mayumi Nakanishi, Hiroki Usuba, and Homei Miyashita. Effects of Delboeuf Illusion on Pointing Performance. In Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OZCHI'19), 476--479, 2019. https://doi.org/10.1145/3369457.3369520 [Short paper; acceptance rate 48.2%] [PDF]
7. Shota Yamanaka, Hiroki Usuba, Haruki Takahashi, and Homei Miyashita. Peephole Steering: Speed Limitation Models for Steering Performance in Restricted View Sizes. In Proceedings of Graphics Interface 2020 (GI 2020), 461 -- 469, 2020. [Acceptance rate 51.7%]
8. Shota Yamanaka, Hiroki Usuba, Haruki Takahashi, and Homei Miyashita. Servo-Gaussian Model to Predict Success Rates in Manual Tracking: Path Steering and Pursuit of 1D Moving Target. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology (UIST '20), 844--857, 2020. https://doi.org/10.1145/3379337.3415896 [Acceptance rate 21.6%]
9. Hiroki Usuba, Shota Yamanaka, and Homei Miyashita. A Model for Pointing at Targets with Different Clickable and Visual Widths and with Distractors. In 32nd Australian Conference on Human-Computer Interaction (OzCHI '20), 1--10, 2020. https://doi.org/10.1145/3441000.3441019 [Acceptance rate 46%]
10. Shota Yamanaka, Hiroki Usuba, and Homei Miyashita. Bivariate Effective Width Method to Improve the Normalization Capability for Subjective Speed-Accuracy Biases in Rectangular-Target Pointing. In CHI Conference on Human Factors in Computing Systems (CHI '22), 13 pages, 2022. https://doi.org/10.1145/3491102.3517466 [Acceptance rate 24.6%]
11. Shota Yamanaka, and Hiroki Usuba. Tuning Endpoint-Variability Parameters by Observed Error Rates to Obtain Better Prediction Accuracy of Pointing Misses. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23), 18 pages, 2023. https://doi.org/10.1145/3544548.3580746

Poster and demo at international conference w/ review

1. Kaito Yamada, Hiroki Usuba, and Homei Miyahita. Modeling Drone Pointing Movement with Fitts' Law. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (CHI EA '19), LBW2519:1--LBW2519:6, 2019. http://doi.acm.org/10.1145/3290607.3312835 [Acceptance rate 42.2%] [PDF]

Paper at domestic conference w/ review

1. 薄羽大樹, 宮下芳明. コメントイン：コメントを先に書くことによる新形態のAPIリファレンス. 第23回インタラクティブシステムとソフトウェアに関するワークショップ論文集（WISS2015）, 2015. [Acceptance rate 44%] [PDF] [Video]
2. 薄羽大樹, 山中祥太, 宮下芳明. Motor WidthとVisual Widthの差を考慮したポインティングのモデル化. インタラクション2019論文集, 122--130, 2019. [Acceptance rate 53%] [PDF]
3. 薄羽大樹, 山中祥太, 宮下芳明. 幅の異なる経路が連結されたコーナリングタスクのモデル化. インタラクション2020論文集, 78--86, 2020. [Acceptance rate 50%] [PDF]
4. 島田雄輝, 薄羽大樹, 宮下芳明. 視線を用いた1次元ポインティングにおける1次サッカードエラー率のモデル化. インタラクション2021論文集, 1--10, 2021.