We are working on following projects
In recent years, the interest in life logs that record diet, sleep, exercise amount, etc. has increased, and an enormous amount of life log data has been accumulated. However, accumulated life log data is used for “feedback” of activities through life log applications and so on, but few users conduct “sharing”.Lifelog data sharing further improves motivation of accumulation of data, creation of new communication, behavior change by further life log. In this research, we propose “Likeyboard” for the purpose of simplifying life log data sharing. Likeyboard makes it possible to share life log data only “select life log data”, “select date and time”, and “select output format” using the keyboard interface of the smartphone.
Investigating Interruptibility at Activity Breakpoints using Smartphone Activity Recognition API
We propose a system for improving the answer rate to ESM inquiry to reduce the user’s mental burden by detecting breakpoints in user’s physical activity and pushing notifications in such timings. As a result, the answer rate was improved rather than delivering a notification immediately.
Interruptibility Map: Geographical Analysis of Users’ Interruptibility in Smart Cities
We propose the “Interruptibility Map”, a geographical tool for analyzing and visualizing the user’s local interruptibility status in the context of smart city research. Our map describes where citizens are expected to feel more or less interruptive against notifications produced by computing devices, which are known to have negative effects on work productivity, emotion, and psychological state.
We propose “SmileWave”, the first selfie social networking service for revealing smile selfie-based emotional contagion on the social network.
The key feature of SmileWave is detecting “smile degrees” inside user’s posting selfies and in reactive facial expressions when the user is viewing the posted photos from others.
Our multiple rounds of in-the-wild user studies with 86 cumulative total users for total duration of 5 weeks revealed several interesting phenomena in smile-based emotional contagion.
Throughout the entire study, we confirmed the occurrence of smile-based emotional contagion over the social network, based on the results that the users’ smile degree improved (15% to 27% on average) when the user looked at posted smile selfie photos.
The System of Detecting Transfer Activity Using Accelerometer (2012~)
Nowadays, various kinds of sensors are available due to expansion of the smartphones. Along with this, the research that records the action on a daily basis has become very popular. Distinction of transport is also a part of the studies. The major result from resent studies has been detected those trans- port by using the sensors such as GPS or a microphone or an acceleration sensor. However, since this is one of the biggest cause to encourage the consumption of the batteries, it is not practical to detect only with a smartphone. I suggested the system to detect transport adopting acceleration sensor.
It is known that the emotional state can be improved by making smile. However, we do not really get conscious about when we were smiling and how much we are smiling in our daily life. It has been also demonstrated that personal happiness is spread in a large social networks. Therefore, we propose a system “SmileSpreader”. SmileSpreader promote the user to make a smile , log this data as life-log and help us to evaluate that the advanced emotional state of the user is spread people around the user.