Ogawa, Ami

写真a

Affiliation

Faculty of Science and Technology, Department of System Design Engineering (Yagami)

Position

Assistant Professor/Senior Assistant Professor

External Links

Career 【 Display / hide

  • 2017.04
    -
    2019.03

    Japan Society for the Promotion of Science, 特別研究員 (DC2)

  • 2019.04
    -
    Present

    Keio University, 助教

  • 2022.04
    -
    Present

    Keio University, Assistant Professor

Academic Background 【 Display / hide

  • 2010.04
    -
    2014.03

    Keio University, Faculty of Science and Technology, Department of System Design Engineering

  • 2014.04
    -
    2016.03

    Keio University, Graduate School of Science and Technology, 前期博士課程

  • 2016.04
    -
    2019.03

    Keio University, Graduate School of Science and Technology, 後期博士課程

 

Research Areas 【 Display / hide

  • Humanities & Social Sciences / Family and consumer sciences, and culture and living

  • Social Infrastructure (Civil Engineering, Architecture, Disaster Prevention) / Architectural environment and building equipment

  • Social Infrastructure (Civil Engineering, Architecture, Disaster Prevention) / Architectural planning and city planning

 

Papers 【 Display / hide

  • Modeling and utilizing habits using process mining for building spatial design systems

    Haraguchi N., Ogawa A.

    Materials Research Proceedings (Materials Research Proceedings)  27   103 - 110 2023

    ISSN  24743941

     View Summary

    Residents need to change their habitual behaviors following living space changes, such as moving or remodeling, and that may occur mental stress. This stress is a major problem, especially for the elderly, who are less able to cope with changes in their environment. To reduce this stress, a system that reflects the living information of the original houses in new houses, where habits can be retained in the new environments is needed. Many studies have been conducted to quantify life information as a habitual model using data mining and pattern recognition methods. “Process Mining” is a theory developed to visualize and improve processes in the business field and applied to lifestyle information, and it is possible to create a habit model. In recent years, several studies on habit models using process mining have been reported. However, there are no studies in which these process mining-based habit models have been adopted to design architectural spaces such as living spaces. Therefore, the purpose of this study is to investigate the relationship between habit and architectural space by utilizing a process mining-based habit model. Specifically, we propose the automatic extraction and visualization of habit behaviors through process mining and the use of habit models. The data acquisition experiment was conducted in an experimental smart home. This smart home is a mobile trailer house built by a multi-company project and is equipped with many sensors that can automatically acquire many daily living data. Subjects were recruited randomly and lived alone in this smart home for one week. An input matrix was created from the acquired data set and process mining was adapted to create habit models. In this study, two habit models were created: (1) a habit model based on behavioral information and (2) a habit model based on location information. Each input matrix consisted of (1) 16 types of behavior record data manually entered by the subject and (2) ground reaction force data in the house divided into 7 areas. We investigated the relationship between habitual behaviors and spatial conditions by integrating these two models.

  • Evaluation of a practical automatic damage assessment system using a single accelerometer for wooden frame houses

    Furukawa Y., Horita K., Mita A., Ogawa A.

    Materials Research Proceedings (Materials Research Proceedings)  27   143 - 149 2023

    ISSN  24743941

     View Summary

    In recent years, Structural Health Monitoring (SHM) has been attracting more attention as a method to determine the existence of the damage and its extent. The typical SHM system employs many sensors to assess the damage quantitatively and qualitatively. However, such a system is not appropriate for wooden houses as it is very costly despite the strong demand. Therefore, developing a low-cost SHM system for wooden houses is necessary. We have been working on algorithms that automatically determine the degree of damage from the maximum inter-story drift angle and natural frequencies using two accelerometers and evaluate the accuracy of the results by applying them to full-scale shake table experimental data.[1] Then, we evolved the system to use only a single accelerometer. In this advanced method, we estimate the first natural frequency without being annoyed by the fundamental frequency of ground motion, which often deteriorates frequency estimation accuracy. In this paper, we demonstrate the applicability of the SHM system using only one sensor in practical scenarios. Firstly, we examined the proposed method using only one accelerometer through the simulation approach. Secondly, we test the system's applicability utilizing a series of large-scale shake table test data. Finally, we examine this method's validity and economic feasibility, contributing to cost reduction and simplification of the algorithm for practical use.

  • Effects of architectural space design on predicting turning in daily life

    Matsunami Y., Motoyama R., Miyaguchi M., Kondou M., Ogawa A.

    Materials Research Proceedings (Materials Research Proceedings)  27   127 - 134 2023

    ISSN  24743941

     View Summary

    In recent years, the diversification of lifestyles and the increase in the number of elderly single-person households have increased the need to introduce robots and sensors into living spaces to control living spaces appropriately for individuals. To realize these goals, it is necessary to predict people’s non-steady motions which is one of the challenges in introducing robots into living spaces. In response, we have conducted research on motion prediction systems using robots and sensors. These studies will contribute to the realization of safe and comfortable architectural spaces by introducing robots into living spaces and collaborating with various space controls such as automatic doors and lighting. In this study, we focused on turning related to walking, which is the most basic motion in activities of daily living. As turning is a non-steady motion greatly affected by aging and disease, it is difficult to predict while is highly useful as a health indicator. Previous studies have suggested that architectural space design can influence the prediction of turning, but the actual effects are not clear because these studies were conducted only under highly constrained conditions in a laboratory environment. Thus, existing systems for predicting turning have not been validated in daily living environments due to issues such as instructions of motions to participants, limitations of natural motions because of contact sensors, and validation in experimental environments that are specially prepared to ensure reproducibility. Therefore, the purpose of this study was to introduce our sensing systems into actual living spaces and to validate our turning prediction system using acquired data on participants’ natural motion. In addition, the influence of architectural space design on predicting turning was clarified by conducting an experiment at a T-junction with an open space and a crossroad with poor visibility. In this study, an office space was selected as the experimental field as a living space to verify the feasibility of our turning prediction system.

  • Augmented architectural space system for the creation of casual connections with people

    Suetomi Y., Ogawa A.

    Materials Research Proceedings (Materials Research Proceedings)  27   183 - 190 2023

    ISSN  24743941

     View Summary

    In recent years, the increasing social isolation has become a major problem in Japan because of the growing trend toward nuclear families. In addition, further social isolation is concerned caused by a decrease on face-to-face communication opportunities due to the outbreak of the COVID-19 infection. Therefore, it is necessary to create connections among people. On the other hand, opportunities for people to communicate online have increased rapidly. However, various information obtained the face-to-face is missing online, which degrades the quality of communication and causes physical and mental fatigue to users. To solve these problems, this study aims to minimize the gap that exists between online and the face-to-face, and to propose an Augmented Architectural Space that creates casual connections between people within their living space. By comparing the results of impression evaluation experiments using questionnaires for the face-to-face environment, the video conferencing system environment, and the proposed system environment, we demonstrate the usefulness of the proposed Augmented Architectural Space system for creating casual connections between people.

  • Identification of Early Knee Osteoarthritis Based on Knee Joint Trajectory during Stair Climbing

    A Ogawa, H Iijima, M Takahashi

    International Journal of Environmental Research and Public Health 19 (22), 15023 (International Journal of Environmental Research and Public Health)  19 ( 22 )  2022.11

    ISSN  16617827

     View Summary

    Patients with knee osteoarthritis show low stair climbing ability, but a diagnosis of stair performance time is not enough to identify the early stages of knee osteoarthritis. Therefore, we developed an indicator named range of the knee joint trajectory (RKJT) as a kinematic parameter to express more detailed characteristics than stair performance time. To achieve this, we used our developed “IR-Locomotion”, a markerless measurement system that can track the knee joint trajectory when climbing stairs. This study aimed to test whether the RKJT effectively identifies patients with early knee osteoarthritis even after controlling stair performance time. Forty-seven adults with moderate to severe knee pain (mean age 59.2 years; 68.1% women) underwent the radiographic examination (Kellgren and Lawrence grade) of both knees and a stair climbing test on 11 stairs. The RKJT during the stair climbing test was calculated by “IR-Locomotion”. A generalized linear mixed model was used to evaluate the discriminative capability of RKJT on early knee osteoarthritis (i.e., Kellgren and Lawrence grade of 1). As expected, patients with early knee osteoarthritis showed larger RKJT than non-radiographic controls (95% confidence interval: 1.007, 1.076). Notably, this finding was consistent even after adjusting stair performance time.

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Papers, etc., Registered in KOARA 【 Display / hide

Research Projects of Competitive Funds, etc. 【 Display / hide

  • 人・居住環境間の力学的インタラクションのモデル化による空間の歩行支援性能評価

    2022.04
    -
    2025.03

    Grants-in-Aid for Scientific Research, Grant-in-Aid for Early-Career Scientists, No Setting

     View Summary

    個人の身体機能に適した居住環境整備は、加齢や疾患などにより身体に障害を持つ人の生活動作の自立を促し、介護負担の軽減に貢献する。本研究では、居住環境が持つ人への動作支援性能の定量評価手法を提案し、居住環境整備プロセスを体系化することで個人の身体機能に適切な居住環境整備の実現を目指す。歩行動作を対象とし、家具や建具のもつ「寄り掛かれる」「把握できる」などの記号的な属性情報を数値的に扱うための人・居住環境間の力学的インタラクションモデルの提案と、空間の歩行支援性能評価を目的とする。この研究を居住環境整備に活用することで、必要十分な歩行支援による生活の自立に寄与し、健康寿命延伸に貢献する。

  • Elucidation of Effects of Environmental and Physical Factors on Activities of Daily Living in the Living Space Using "Monitoring Infill"

    2020.04
    -
    2022.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Early-Career Scientists , Principal investigator

     View Summary

    本研究では、運動器疾患罹患者もしくは予備軍を主な対象とし、動作計測システム、環境設置型の環境センサおよび時計型のウェアラブルセンサから構成される見守りインフィルを住宅内に導入することで、日常生活中の動作計測と動的な環境情報および身体情報の取得を長期にわたり実施する。医師による定期的な診断結果より得られる真の身体機能レベルを用いて、環境要因および身体要因の変動と、取得される動作パラメタの変化からそれらの要因が動作に与える影響を定量化する。これにより将来的に定期的な医師による診断を受けずに、見守りインフィルのみから真の身体機能レベルを推定することが期待される。

  • 運動器疾患の発症危険性評価のための精神状態を考慮した歩行t軸推移モデルの構築

    2017.04
    -
    2019.03

    Keio University, Grants-in-Aid for Scientific Research, Grant-in-Aid for JSPS Fellows, No Setting

     View Summary

    本研究は住宅内に導入可能な歩行情報取得システムを構築し、これを用いて居住者の運動器疾患の発症危険性検知が可能な歩行t軸(時間軸)推移モデルを構築することを目的とした。提案システムの居住空間への導入可能性の検証、および運動器疾患の早期診断に役立つ指標の開発を達成した。提案システムはRGB-Dセンサ搭載ロボットを用いて対象者の下肢関節座標および角度を推定する。ロボットが対象者から一定距離を保つことで、距離の制限のないデータ取得が可能である。階段歩行では、センサを階段下と階段上に設置し同システムを適用する。搭載センサで取得した対象者の後ろ姿の深度データ(距離データ)を用いて歩行情報を推定する。
    提案システムの精度を直線歩行と階段歩行において検証したところ、従来手法よりも高精度で推定が可能であった。居住空間内での試用実験では、方向転換時など片足が死角に入る場合を除いて歩行情報推定が概ね可能であった。被験者が歩行した全経路のうちデータ取得可能であった区間は平均54 %であったことから、日常的にシステムを運用させた場合に従来の歩行テストと比較して十分なサンプル数が得られると考察される。
    運動器疾患として特に高齢者に罹患者の多い変形性膝関節症(膝OA)を取り上げ、地域在住高齢者を対象とした計測会において提案システムによる階段歩行計測を実施した。取得データから膝関節の空間上の軌跡を用いた独自のパラメタを算出したところ、膝関節部のレントゲン画像を用いた理学療法士による膝OAの5段階診断結果と相関が認められ、膝OAリスク評価指標の新たな提案と位置付けられた。
    膝OAは膝関節の変形と疼痛が徐々に進行するため、自覚症状が出る頃には既に介入が手遅れと言われる。本研究では提案システムを用いた膝OAの早期発見の可能性を示唆した。提案システムの活用により運動器疾患の早期発見による健康寿命の延伸が期待される。
    平成30年度が最終年度であるため、記入しない。
    平成30年度が最終年度であるため、記入しない。

Awards 【 Display / hide

  • 日本機械学女性未来賞

    2019.03, 一般社団法人日本機械学会

  • 2017年度日本建築学会大会(中国)学術講演会 環境工学部門 若手優秀発表賞

    2017.11, 日本建築学会

  • 2016年度日本建築学会大会(九州)学術講演会 情報システム技術部門 若手優秀発表賞

    2016.09, 日本建築学会

  • 義塾賞

    2014.03, 慶應義塾大学

  • 日本機械学会畠山賞

    2014.03, 一般社団法人日本機械学会

 

Courses Taught 【 Display / hide

  • SPECIAL LECTURE ON SPACE AND ENVIRONMENT DESIGN ENGINEERING 1

    2023

  • SPATIAL AND STRUCTURAL MECHANICS

    2023

  • SPACE DESIGN OVERSEAS FIELD STUDY

    2023

  • SEMINAR IN SYSTEM DESIGN ENGINEERING

    2023

  • PRINCIPLES OF HEALTH MANAGEMENT

    2023

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Memberships in Academic Societies 【 Display / hide

  • 日本生体医工学会, 

    2019.04
    -
    Present
  • 計測自動制御学会, 

    2019.04
    -
    Present
  • 日本機械学会, 

    2018.10
    -
    Present
  • 日本建築学会, 

    2014.04
    -
    Present

Committee Experiences 【 Display / hide

  • 2020.09
    -
    2021.03

    関東支部 第27期総会・講演会実行委員会, 日本機械学会

  • 2019.07
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    2019.09

    LIFE2019 実行委員会, 日本機械学会

  • 2019.04
    -
    Present

    サスティナブル情報デザイン小委員会, 日本建築学会

  • 2019.04
    -
    Present

    システム・情報部門 コンピューテーショナル・インテリジェンス部会, 計測自動制御学会