研究者詳細 - 井上　創造

講演 - 井上　創造

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看護および介護における行動センシングとビッグデータ分析について

CPS／IoTにおけるセンシングソリューション技術分科会 2017年10月 publications/431

人工知能研究の基盤となる機械学習技術とIoT医療応用

日本心血管脳卒中学会学術集会 2017年06月 publications/400

IoTの世の中へのインパクト

日本糖尿病学会年次学術集会 2017年05月 publications/395

Mobile Activity Recognition and Smart Lifecare

Asian Workshop on Smart Sensor Systems 2017年03月 publications/399

地域イノベーションエコシステム井上チーム

地域イノベーションとエコシステム形成　第一回ワークショップ 2017年03月 publications/401

行動認識とヘルスケア応用

筑波大学情報システム特別講義D（ビッグデータ基盤技術） 2017年01月 publications/397

人工知能の社会実装に向けて

自動制御連合講演会講演論文集 2017年01月

Recognizing Unknown Activities Using Semantic Word Vectors and Twitter Timestamps

International Symposium on Applied Engineering and Sciences (SAES2016) 2016年12月 publications/389

Deep Recurrent Neural Network for Human Activity Recognition

International Symposium on Applied Engineering and Sciences (SAES2016) 2016年12月 publications/390

Nursing Activity Recognition and Future Prediction in Hospitals

International Symposium on Applied Engineering and Sciences (SAES2016) 2016年12月 publications/393

Text Mining for Nursing Care Service Improvement

International Symposium on Applied Engineering and Sciences (SAES2016) 2016年12月 publications/392

Robust Methods for Sensor-based Activity Recognition

International Symposium on Applied Engineering and Sciences (SAES2016) 2016年12月 publications/391

(Invited) Activity Recognition and Future Prediction in Hospitals

First International Workshop on Smart Sensing Systems (IWSSS’16) 2016年11月 publications/382

(Invited) Activity Recognition and Future Prediction in Hospitals

First International Workshop on Smart Sensing Systems (IWSSS’16) 2016年11月

開催期間： 2016年11月28日発表言語：英語講演種別：特別講演開催地：Hiroshima

In this paper, we firstly introduce our work [9] where we proposed for recognizing whole day activities using prior knowledge, and applied the method for real nursing sensor dataset we have col- lected. Then, we introduce the method for predicting near future of nurses by integrating nurse activity data, location data, and medical records, based on our work[10]. For both works, we independently collected real and open nursing datasets with 2 weeks of accelerom- eters and training labels from 22 nurses for the former work, and nurse activity, location, medical payment, and nursing needs data from 35 nurses and 96 patients for 40 days for the latter work.

Towards Smarter Life Care Using Sensing and Big Data Analytics

Kobe University Core-Team Workshop on Cyber-Physical System for Smarter World (CPS-SW 2016) 2016年03月 publications/349

モバイル行動認識の研究動向

電子情報通信学会総合大会企画セッション（都市と市民のためのCPS（サイバーフィジカルシステム）の姿を描く） 2016年03月 publications/337

介護サービス向上のためのテキスト分析とセンシング実験について

人間行動センシングミーティング2015 2016年01月 publications/338

Understanding Nursing Activities with Long-term Mobile Activity Recognition with Big Dataset

The 47th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (SSS) 2015年12月 publications/323

Understanding Nursing Activities with Long-term Mobile Activity Recognition with Big Dataset

The 47th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (SSS) 2015年12月

開催期間： 2015年12月05日発表言語：英語講演種別：特別講演開催地：Hawaii, USA

In this paper, we introduce a real nursing sensor dataset which includes labeled dataset for supervised machine learning and the big data combined with patient medical records and sensors attempted for 2 years, and also describe a method for recognizing activities for a whole day utilizing prior knowledge about the activity segments in a day and utilizing importance sampling and Bayesian estimation, based on our paper at UbiComp2015. Moreover, we demonstrate data mining by applying our method to the bigger data with additional hospital data. Our method of recognizing a whole day activities outperformed the traditional method without using the prior knowledge. Moreover, the method significantly reduces the duration errors of activity segments. We also demonstrate a data mining applying our method to bigger data in a hospital, and show several results about the correlations with nurse profiles and patients’ status.

(Keynote) Pervasive Sensing and Healthcare Applications

IIAE International Conference on Intelligent Systems and Image Processing 2015年09月

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