2019.03.28 (Thu)
「2019 IEEE 1st Global Conference on Life Sciences and Technologies」における、ヘルスケアIoTコンソーシアムとの共同提案オーガナイズドセッション 「Future of Healthcare IoT/ICT」にて、受賞者5名を選出、受賞者が発表を行いました。
本セッションはHITが演題を募集し、応募があった11件から5件を選抜、顕彰することによってヘルスケアIoTに資する若手研究者の育成を図る目的で実施いたしました。
受賞者および発表テーマは以下の通りです。
受賞者の皆さん、おめでとうございます。
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Future of Healthcare IoT/ICT
Co-organized by Healthcare IoT Consortium
Chairs: Yamamoto Yoshiharu (The University of Tokyo, Japan), Toru Nakamura (Osaka University, Japan)
An epidemiological sleep study based on a large-scale physical activity database
Li Li and Toru Nakamura (Osaka University, Japan)
A data-driven approach for reconstructing bifurcation diagrams of discrete dynamical systems
Hironori Ohigashi, Taishin Nomura and Toru Nakamura (Osaka University,Japan)
Fluctuation of stride time intervals during walking with smartphone
Shunpei Yano (Osaka University, Japan); Lauren Dimalanta (University of California at San Diego, USA); Yasuyuki Suzuki and Taishin Nomura (Osaka University, Japan)
Assimilating the intermittent control model into postural sway data using Bayesian inference
Akihiro Nakamura, Yasuyuki Suzuki, Kazuya Kondo and Taishin Nomura (Osaka University, Japan)
Relationship between saccadic intrusions and a bimodal aspect of inter-microsaccadic intervals
Makoto Ozawa and Taishin Nomura (Osaka University, Japan)
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山本義春先生、中村亨先生と受賞者の皆さん
イベント情報
＜2019 IEEE 1st Global Conference on Life Sciences and Technologies＞
http://www.ieee-lifetech.org/2019/index.html
| 開催日 | March 12-14, 2019 |
| 開催場所 | 1-4-2, Shinsenrihigashimachi, Toyonaka-city, Osaka, 560-0082 Japan TEL: +81-(0)6-6873-2010 http://www.senrilc.co.jp/ |
| 概要 |
「Future of Healthcare IoT/ICT」 Chair:Yoshiharu Yamamoto, JP (The University of Tokyo) Abstract: The recent development of IoT/ICT has enabled us to track our health conditions in daily life and provided a great impact on medical and healthcare fields. Wearable smart devices (wristbands, shirts, eye-glasses, etc.) can continuously measure personal health-related data such as heart rate, physical activity, or sleep qualities. Those IoT data are thought to have a great potential to diagnosis and an early detection of diseases. Therefore, the establishment of a new framework to utilize them, especially methods to extract useful information associated with diseases, have been focused. The proposed organized session will present the recent researches aiming at the evaluation of health-related risks or early detection of disease onset, based on novel signal processing, machine learning, or mathematical modeling approaches. |
