Honda, Yuka



Graduate School of Media and Governance (Shonan Fujisawa)


Project Associate Professor (Non-tenured)

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  • 健康医学者・博士(医学)。神奈川県横浜市生まれ。1997年、順天堂大学スポーツ健康科学部スポーツ科学科(所属ゼミ:生理学研究室)卒業後、株式会社タニタに入社。在職中の15年間、研究員として女性やアスリートの研究、体組成計や睡眠計のアルゴリズム開発、商品企画・開発などに携わる。また、在職中に、東京大学大学院医学系研究科母性看護学・助産学分野客員研究員として、8年間、妊娠・出産・産後の女性の身体についても深く研究。同社を2012年に退社後、丸の内朝大学講師などを務め、現在は、産科婦人科舘出張 佐藤病院の研究コーディネーター、順天堂大学医学部小児科での非常勤助手などを務める。本学での研究活動としては、 病院や様々な機関(大学、自治体等)、企業と連携した共同研究の他、子どものヘルスケアプラットフォーム開発、ウエルビーイン向上を目的としたフェムテック事業研究等を進める。戦略的創造研究推進事業(CREST)「限定合理性を超越する共生インタラクション基盤」の研究メンバーでもある。夢は「女性と子どもの健康力をあげて日本を元気にすること」。

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  • Doctor (Medicine), Juntendo University, Coursework, 2015.03

    Decreased serum anti-Müllerian hormone level is associated with vitamin D deficiency in healthy Japanese women


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  • COVIDGuardian: A Machine Learning approach for detecting the Three Cs

    Katsumata K., Honda Y., Okoshi T., Nakazawa J.

    ACM International Conference Proceeding Series (ACM International Conference Proceeding Series)     147 - 150 2022.11

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    On January 30, 2020, WHO officially declared the outbreak of COVID-19 a Public Health Emergency of International Concern. Japan announced the state of emergency and implemented safety protocols the "Three Cs", a warning guideline addressing to voluntarily avoid potentially COVID-19 hazardous situations such as confined and closed spaces, crowded places and close-contact settings that lead to occurrence of serious clusters. The primary goal of this research is to identify the factors which help to estimate whether the user is in the Three Cs. We propose COVIDGuardian, a system that detects the Three Cs based on data such as CO2, temperature, humidity, and wireless packet log. The results show that estimation of closed space had the highest accuracy followed by close-contact settings and crowded places. The ensemble Random Forest (RF) classifier demonstrates the highest accuracy and F score in detecting closed spaces and crowded spaces. The findings indicated that integrated loudness value, average CO2, average humidity, probe request log, and average RSSI are of critical importance. In addition, when the probe request logs were filtered at three RSSI cutoff points (1m, 3m, and 5m), 1m cut-off points had the highest accuracy and F Score among the Three C models.