Publications by authors named "Tadashi Okoshi"

Article Synopsis
  • The research focuses on estimating the mood states of web users to provide personalized services through a model that uses search-query data, supplemented by mobile sensor data to improve accuracy.
  • A nationwide mood score was developed to analyze and visualize the mood trends of over 11 million users, revealing patterns related to the COVID-19 pandemic and significant news events.
  • The study also discovered specific types of advertisements that correlated with distinct mood trends among users who engaged with them.
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Background: Obese pregnant women are known to experience poorer pregnancy outcomes and are at higher risk of postnatal arteriosclerosis. Hence, weight control during and after pregnancy is important for reducing these risks. The objective of our planned randomized controlled trial is to evaluate whether the rate of change in body weight in obese women before pregnancy to 12 months postpartum would be lower with the use of an intervention consisting of Internet of Things (IoT) devices and mobile applications during pregnancy to 1 year postpartum compared to a non-intervention group.

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Recent technological trends in mobile/wearable devices and sensors have been enabling an increasing number of people to collect and store their "lifelog" easily in their daily lives. Beyond exercise behavior change of individual users, our research focus is on the behavior change of teams, based on lifelogging technologies and lifelog sharing. In this paper, we propose and evaluate six different types of lifelog sharing models among team members for their exercise promotion, leveraging the concepts of "competition" and "collaboration.

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