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  2. Yutaka Hata

Yutaka Hata

  (畑 豊)

Profile Information

Affiliation
Vice President, Professor, Graduate School of Information Science, University of Hyogo
Degree
Doctor of Engineering(*Himeji Institute of Technology*)
Master of Engineering(*Himeji Institute of Technology*)
J-GLOBAL ID
200901047349838723
researchmap Member ID
1000057709
External link

平成元年姫路工業大学大学院博士課程修了(工学博士)．同年姫路工業大学工学部助手, 平成12年同教授，平成16年兵庫県立大学大学院工学研究科教授，平成25年10月兵庫県立大学大学院シミュレーション学研究科教授,　令和3年4月副学長兼情報科学研究科教授、現在に至る．2008-2017年WPI大阪大学免疫学フロンティア研究センター招へい教授，平成22年IEEE（米国電気電子学会）Fellow．
現在，医療・健康システムの研究に従事．Biomedical Wellness Award from SPIE Defense, Security, and Sensing(April. 2010, Orlando, USA), Franklin V. Taylor Best Paper Award from IEEE SMC (Oct. 2009, USA), Life Time Achievement Award from Intelligent Automation and Soft Computing- An international Journal (Sept. 2008, USA) 等の15の国際賞、井植文化賞、兵庫県科学賞等の国内賞を受賞．

Research Interests

 6

Research Areas

 5

Research History

 8
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Education

 3

Committee Memberships

 6
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Awards

 21
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Papers

 214
  • Naomi Yagi, Kazuki Otsuka, Yuki Yamanaka, Kentaro Mori, Yutaka Hata, Yasumitsu Fujii, Yoshitada Sakai
    Diagnostics, 16(8) 1164-1164, Apr 14, 2026  
    Background: In rehabilitation medicine, efficient gait analysis is crucial for evaluating postoperative recovery and frailty, especially given the increasing burden on clinicians due to an aging population. Objectives: This study aims to conduct preliminary validation of an automated linear walking evaluation system using 2D AI posture tracking. By evaluating the basic accuracy of the system on healthy individuals, we aim to establish a technical foundation for future introduction into clinical rehabilitation settings. Methods: In this observational study, we utilized a standard visible light camera for practical use. To evaluate accuracy, we compared 2D AI tracking against a gold-standard three-dimensional (3D) motion capture system during normal walking trials with 10 healthy participants. Specifically, we employed Dynamic Time Warping (DTW) to temporally align the asynchronous data streams from the 2D and 3D systems, ensuring precise comparison of joint angles. Results: Following the DTW-based alignment, the similarity with the 3D system was 0.806 ± 0.094 overall (Left: 0.797 ± 0.101, Right: 0.814 ± 0.086). Conclusions: In this preliminary validation, the proposed 2D AI posture tracking showed good agreement with the gold standard 3D motion capture for gait in healthy individuals. While the average systematic bias was within clinically acceptable limits, the observed limits of agreement suggest that this system is currently optimal as a foundational tool for gait screening. These results establish a technical foundation for the clinical application of this system.
  • Naomi Yagi, Shinsuke Nagami, Hitoshi Maezawa, Yutaka Hata
    Studies in Systems, Decision and Control, 41-60, Jan 2, 2026  
  • Naomi Yagi, Shinsuke Nagami, Hitoshi Maezawa, Yutaka Hata
    Studies in Systems, Decision and Control, 41-60, Jan 2, 2026  
  • A. Yoshida, N. Yagi, Y. Fujii, H. Shibutani, Y. Kobayashi, Y. Saji, Y. Sakai, Y. Hata
    ICMLC&ICWAPR2024, Sep, 2024  Last author
  • Y. Adachi, N. Yagi, Y. Ohara, K. Doi, Y. Takaya, K. Yamaguchi, S. Mizuta, M. Doshida, T. Takeuchi, H. Matsubayashi, T. Ishikawa, Y. Hata
    ICMLC&ICWAPR2024, Sep, 2024  Last author
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Misc.

 541
  • 八木直美, 中村朱里, 川村直子, 前澤仁志, 酒井良忠, 柏岡秀紀, 平田雅之, 柳田敏雄, 畑豊, 畑豊
    人工知能学会第二種研究会資料(Web), 2024(AIMED-014), 2024  
  • T Maekawa, T Morimoto, S Mizuta, H Matsubayashi, T Takeuchi, Y Hata, T Ishikawa
    39th Hybrid Annual Meeting of the ESHRE, Jun, 2023  
  • 畑 豊
    知能と情報, 30(2) 64-66, 2018  
  • 116(393) 83-88, Jan 18, 2017  
  • Hata Yutaka
    SYSTEMS, CONTROL AND INFORMATION, 61(8) 311-315, 2017  
  • 岸田 俊文, 米倉 功治, 畑 豊
    システム制御情報学会研究発表講演会講演論文集, 61st, 2017  
  • 森 健太郎, 徳永 義光, 佐久本 哲郎, 中島 章, 米須 勇, 畑 豊
    システム制御情報学会研究発表講演会講演論文集, 61st, 2017  
  • Yutaka Hata, Syoji Kobashi, Hiroshi Nakajima
    Systems of Systems Engineering: Principles and Applications, 233-250, Jan 1, 2017  Peer-reviewed
  • 森勇樹, 森勇樹, DE LA MORA Daniela Martinez, DE LA MORA Daniela Martinez, 田下徳起, 小橋昌司, 黄田育宏, 畑豊, 吉岡芳親, 吉岡芳親
    日本磁気共鳴医学会雑誌, 37(1), 2017  
  • 岸田俊文, 石川智基, 今脇節朗, 畑豊
    バイオメディカル・ファジィ・システム学会年次大会講演論文集(CD-ROM), 30th, 2017  
  • 畑豊
    バイオメディカル・ファジィ・システム学会年次大会講演論文集(CD-ROM), 30th, 2017  
  • 森健太郎, 湯河惇, 河野淳, 畑豊
    バイオメディカル・ファジィ・システム学会年次大会講演論文集(CD-ROM), 30th 235-236, 2017  
  • KOYA Yoshiharu, ISHIKAWA Tomomoto, MATSUBAYASHI Hidehiko, HATA Yutaka
    Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications (CD-ROM), 48th 93‐97-97, 2017  
    <p>In recent years, the trend of people marrying later in life has been significantly increasing. In the US, 60% of married women in their 40s reportedly have infertility. In half of these cases, a female factor is the cause. As a consequence, infertility treatments are widely performed. One such treatment is in-vitro fertilization. This technique directly removes a follicle from the ovary and ovum is fertilized it with sperm under a microscope by embryologist. Ovulation inducers can stimulate the growth of 10 to 15 follicles. However, 20% to 30% usually contain vacuoles and do not support ovary growth. In some cases, ova that are as much as 90% vacuolated do support ovary growth[1]. It thus cannot be determined whether a follicle has an ovum or is vacuolated unless the follicle is examined under a microscope. Consequently, it is useful to determine in advance whether a follicle has an ovum because follicle collection is painful for the woman. However, to date, a non-invasive method of identifying vacuolated ova does not exist. Therefore, we herein propose a method using ultrasound to determine whether a follicle has an ovum.</p>
  • 湯河 惇, 河野 淳, 西井 達矢, 畑 豊
    システム制御情報学会研究発表講演会講演論文集, 60, May 25, 2016  
  • 60 4p, May 25, 2016  
  • Hiroaki Komori, Shoji Kobashi, Naotake Kamiura, Yutaka Hata, Ken Ichi Sorachi
    2015 4th International Conference on Informatics, Electronics and Vision, ICIEV 2015, Nov 20, 2015  Peer-reviewed
  • 樋口 瑞樹, 空地 顕一, 畑 豊
    システム制御情報学会研究発表講演会講演論文集, 59 4p, May 20, 2015  
  • 樋口 翔士, 畑 豊
    システム制御情報学会研究発表講演会講演論文集, 59 6p, May 20, 2015  
  • 西川 祥平, 酒井 良忠, 畑 豊
    システム制御情報学会研究発表講演会講演論文集, 59 5p, May 20, 2015  
  • HATA Yutaka
    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, 27(5) 144-148, 2015  
  • NAKANO Ryosuke, KOBASHI Syoji, KURAMOTO Kei, WAKATA Yuki, ANDO Kumiko, ISHIKURA Reiichi, ISHIKAWA Tomomoto, HIROTA Shozo, HATA Yutaka
    Medical Imaging Technology, 33(2) 49-57, 2015  
    In order to develop a computer-aided diagnosis system for neonatal cerebral disorders, some methods of brain segmentation from MR images using atlas model have been studied. As neonatal cerebrum deforms quickly by natural growth, single model cannot represent growth model properly. Due to the variation of newborn brain growth even at same age, age based model will not give appropriate result. In this paper, we propose a method for estimating growth index using manifold learning and generating fuzzy object growth model (FOGM). Brain anatomical landmarks are used for manifold learning. In addition, we propose a fuzzy connectedness segmentation method using FOGM to segment the brain region. In comparison with the previous single model based method, the proposed method improved the segmentation accuracy by using FOGM.
  • 湯河惇, 河野淳, 西井達矢, 上浦尚武, 小橋昌司, 畑豊
    システム制御情報学会研究発表講演会講演論文集(CD-ROM), 59th, 2015  
  • Yutaka Hata, Hiroshi Nakajima
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, E97D(9) 2218-2225, Sep, 2014  
  • 林 治尚, 井内 善臣, 畑 豊
    大学情報システム環境研究 = Academic information processing environment research, 17 67-76, Jul, 2014  
  • 樋口 翔士, 畑 豊
    システム制御情報学会研究発表講演会講演論文集, 58 6p, May 21, 2014  
  • Naomi Yagi, Tomomoto Ishikawa, Yutaka Hata
    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, E97A(4) 913-922, Apr, 2014  
  • NAKANO Ryosuke, KOBASHI Syoji, KURAMOTO Kei, WAKATA Yuki, ANDO Kumiko, ISHIKURA Reiichi, ISHIKAWA Tomomoto, HIROTA Shozo, HATA Yutaka
    IEICE technical report., 113(410) 47-52, Jan 26, 2014  
    To develop a computer-aided diagnosis system for neonatal cerebral disorders, some literatures have shown atlas-based methods for segmenting parenchymal region in MR images. Because neonatal cerebrum deforms quickly by natural growth, we desire an atlas growth model. This paper proposes two methods for generating fuzzy object growth model (FOGM), which is an extension of fuzzy object model (FOM). The first method generates a growth-index weighted FOM in which the index is calculated from age. Because the growth index will be different from person to person even though the same age, the second method estimates the growth-index from MR images using manifold learning. To evaluate the proposed methods, we segment the parenchymal region of 16 neonatal subjects (revised age; 0-2 years old). The results showed that FOGM was superior to FOM, and manifold learning based method gave the best accuracy. And, the growth index estimated with manifold learning was significantly correlated with both of age and cerebral volume (p&lt;0.001).
  • MORITA Kento, KOBASHI Syoji, KURAMOTO Kei, WAKATA Yuki, ANDO Kumiko, ISHIKURA Reiichi, ISHIKAWA Tomomoto, HIROTA Shozo, HATA Yutaka
    IEICE technical report., 113(410) 53-58, Jan 26, 2014  
    MR image registration (IR) has been used in brain function analysis, voxel-based-morphometry, etc. The conventional IR methods mainly use MR signal based likelihood. However, they cannot prevent miss registration of different gyri because they do not evaluate correspondence of sulci. Also, we cannot directly apply methods for adult brain to neonatal brain because there are large differences in MR signal and sulcal width. This paper introduces a new feature called sulcal-distribution index (SDI) which is calculated from MR signal around the cerebral surface. Next, we propose a non-rigid 3D IR method using flattening with SDI. The likelihood used is mutual information of SDI. The new method evaluates the correspondence of cerebral sulci in IR. And, the method will be effective for neonatal brain in which the accurate delineation of cerebral surface is difficult because the method evaluates the MR signal around the cerebral surface. Results in 3 neonates (modified age; 3-5 weeks) showed the decrease of the angle between vectors of feature point direction.
  • Higuchi Shoji, Hata Yutaka
    Proceedings of the Fuzzy System Symposium, 30th 524-529, 2014  
    This paper describes fuzzy evaluation method for criteria dependency in human health conditions by changing medical checkup reference. In our previous paper, we proposed an evaluation method based on fuzzy logic for health checkup data. This method converted health checkup data into fuzzy normal degree to evaluate multivariate data. We defined the fuzzy normal degree as an attribute value in closed interval [0, 1] by using fuzzy membership function which was defined by diagnostic criteria. Furthermore, total health indices which are defined by operation of the fuzzy normal degrees are treated as the same scale. These indices can express human health conditions in health checkup result using fuzzy set. In this paper, to investigate fuzzy normal degrees by changing to new reference interval, we employ new reference interval and form new diagnostic criteria, and visualized health changes by calculating the total health indices using our proposed method. As the result, we succeeded in visualizing health change by fuzzy normal degree and fuzzy health indices, and confirmed quantitatively that disease patients decrease by changing to new reference interval.
  • Taniguchi Yusuke, Nakajima Hiroshi, Tsuchiya Naoki, Tanaka Junichi, Aita Fumiji, Hata Yutaka
    Proceedings of the Japan Joint Automatic Control Conference, 57 1995-2001, 2014  
    本論文では2つのサーマルアレイセンサを使用し，人の姿勢推定を行うシステムを提案する．本システムではサーマルアレイセンサを天井と壁に設置し，16×16の温度分布を測定する．サーマルアレイセンサは室内の状況を温度分布として取得可能である．姿勢推定は時系列の姿勢遷移図とある領域の温度の合計値を用いて行う．実験では，高齢者介護施設の個室を想定した部屋で温度分布の測定を行った．推定結果より，本システムは姿勢の推定に成功したことを確認した．
  • Tsukuda Koki, Egawa Tadahito, Taniguchi Kazuhiko, Hata Yutaka
    Transactions of the Institute of Systems, Control and Information Engineers, 27(2) 42-48, 2014  
    This paper describes fuzzy average difference imaging for ultrasonic nondestructive testing. In our experiment, we employ a piece of wind turbine blade as a specimen. The specimen has holes on back side as artificial damages. We acquire ultrasonic waveforms from scanning lines on surface of the specimen using an ultrasonic single probe. We make cross-section images of the specimen by correcting the each scanning line wave data. We set scanning lines so that specimen constructions under the lines are same each other. Therefore the images show same construction of inside of the specimen, we can enhance the damage echoes by using average difference imaging. To extract the damage echoes from the images, we applied damage extraction method aided by fuzzy logic and average difference imaging. As the results, we found the line image with all damage portions, and we estimated depth of damage surface with high accuracy. Therefore fuzzy average difference imaging showed effectiveness for extracting difference potions on similar images.
  • Kuki Masato, Nakajima Hiroshi, Tsuchiya Naoki, Tanaka Junichi, Hata Yutaka
    Transactions of the Institute of Systems, Control and Information Engineers, 27(4) 149-159, 2014  
    This paper proposes human movement trajectory (HMT) extraction system and a state of people estimation system by thermopile array sensors. In our systems, sensors are attached at the ceiling and acquire thermal distribution, which are two-dimensional temperatures. The system distinguishes humans, object and others by fuzzy inference based on human characteristics, such as body temperature and movement. Each human is classied by the connected-component labeling. In the HMT extraction system, it extracts HMT as label centroids trajectory. In the state of people estimation system, it distinguishes adjoining people based on shape of human distribution in label image and estimates the number of human as the number of labels. In the HMT extraction experiment, we employed an adult and he performed 15 movements. As the results, the system successfully extracted HMTs with 78[%] accuracy and positional error was 21.5[cm]. In the state estimation experiment, we employed 4 adults and they performed 4 movements. As the results, the system successfully estimated the number of humans with 52[%] accuracy.
  • Syoji Kobashi, Ryosuke Nakano, Kei Kuramoto, Yuki Wakata, Kumiko Ando, Reiichi Ishikura, Tomomoto Ishikawa, Shozo Hirota, Yutaka Hata, Naotake Kamiura
    2014 International Conference on Informatics, Electronics and Vision, ICIEV 2014, 2014  Peer-reviewed
  • Hideki Hata, Seturo Imawaki, Kei Kuramoto, Syoji Kobashi, Yutaka Hata
    Advances in Intelligent Systems and Computing, 268 65-75, 2014  Peer-reviewed
  • Koki Tsukuda, Tomomoto Ishikawa, Seturo Imawaki, Yutaka Hata
    Advances in Intelligent Systems and Computing, 268 125-136, 2014  Peer-reviewed
  • Kento Morita, Syoji Kabashi, Kei Kuramoto, Yuki Wakata, Kumiko Ando, Reiichi Ishikura, Tomomoto Ishikawa, Shozo Hirota, Yutaka Hata
    2014 International Conference on Informatics, Electronics and Vision, ICIEV 2014, 2014  Peer-reviewed
  • Masato Kuki, Hiroshi Nakajima, Naoki Tsuchiya, Junichi Tanaka, Yutaka Hata
    Advances in Intelligent Systems and Computing, 268 35-49, 2014  Peer-reviewed
  • Sho Kikuchi, Yusho Kaku, Kei Kuramoto, Syoji Kobashi, Yutaka Hata
    Advances in Intelligent Systems and Computing, 268 77-84, 2014  Peer-reviewed
  • Yusuke Taniguchi, Hiroshi Nakajima, Naoki Tsuchiya, Junichi Tanaka, Fumiji Aita, Yutaka Hata
    Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 2014-January(January) 3930-3935, 2014  Peer-reviewed
  • Naomi Yagi, Tomomoto Ishikawa, Setsurou Imawaki, Yutaka Hata
    Advances in Intelligent Systems and Computing, 268 137-146, 2014  Peer-reviewed
  • Shoji Higuchi, Yutaka Hata
    Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 2014-January(January) 3952-3957, 2014  Peer-reviewed
  • Tatsuhiro Fujimoto, Hiroshi Nakajima, Naoki Tsuchiya, Yutaka Hata
    Advances in Intelligent Systems and Computing, 268 95-108, 2014  Peer-reviewed
  • Takahiro Takeda, Hiroshi Nakajima, Naoki Tsuchiya, Yutaka Hata
    Advances in Intelligent Systems and Computing, 268 109-124, 2014  Peer-reviewed
  • Tetsuya Fujisawa, Tadahito Egawa, Kazuhiko Taniguchi, Syoji Kobashi, Yutaka Hata
    Advances in Intelligent Systems and Computing, 268 51-64, 2014  Peer-reviewed
  • YAGI Naomi, ISHIKAWA Tomomoto, HATA Yutaka
    知能と情報, 26(3) 728‐735 (J‐STAGE), 2014  
  • Yoshitada Sakai, Akira Hashiramoto, Yoshiko Kawasaki, Takaichi Okano, Takahiro Takeda, Naomi Yagi, Yutaka Hata
    ARTHRITIS AND RHEUMATISM, 65 S895-S895, Oct, 2013  
  • Haruhisa Hayashi, Yutaka Hata, Isao Ohta
    IPSJ SIG Technical Reports, 2013(9) 1-5, Sep 20, 2013  
    In April 2013, the University of Hyogo was transformed into the municipal university corporation. Therefore, the business-use systems for financial, traveling-expenses, personal affairs and salary, which was using the prefectual system by exclusive-use PCs, s introduced newly. Furthermore, the cost of such a change would be considerable, we have discussed the burden sharing with the Hyogo prefecture. In this paper, we explain the design and introduction of new systems.
  • Takahiro Takeda, Kei Kuramoto, Syoji Kobashi, Yutaka Hata
    International Journal of Intelligent Computing in Medical Sciences and Image Processing, 5(2) 147-160, Sep, 2013  Peer-reviewed
  • Syoji Kobashi, Kei Kuramoto, Yuki Wakata, Kumiko Ando, Reiichi Ishikura, Tomomoto Ishikawa, Shozo Hirota, Yutaka Hata
    International Journal of Intelligent Computing in Medical Sciences and Image Processing, 5(2) 115-124, Sep, 2013  Peer-reviewed
  • Yutaka Hata
    International Journal of Intelligent Computing in Medical Sciences and Image Processing, 5(1) 1-2, Jul, 2013  Peer-reviewed

Books and Other Publications

 3

Presentations

 14
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Teaching Experience

 7
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Professional Memberships

 4

Works

 7
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Research Projects

 16
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