Publication

@inproceedings{10.1145/3460418.3479283,

title = {Experience Sampling Tool for Repetitive Skills Training in Sports Using Voice User Interface},

author = {Yuuki Nishiyama and Kaoru Sezaki},

url = {https://doi.org/10.1145/3460418.3479283},

doi = {10.1145/3460418.3479283},

isbn = {9781450384612},

year  = {2021},

date = {2021-01-01},

booktitle = {Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers},

pages = {54–55},

publisher = {Association for Computing Machinery},

address = {Virtual, USA},

series = {UbiComp '21},

abstract = {Repetitive skills training (RST) is a commonly used method for improving skills. 

Although wearable devices and existing context-aware technologies allow us to easily 

detect objective data during RST, subjective data have not been collected effectively, 

even though both objective and subjective data are important for RST. In this paper, 

we propose and implement a prototype system, called MiQ, to collect subjective data 

with minimum workload during RST for sports. MiQ allows us to record subjective data 

hands-free via a voice user interface (VUI). We also discuss the future scope of the 

proposed prototype system.},

keywords = {context-awareness, Experience Sampling, Voice User Interface, Wearable Devices},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3307334.3328719,

title = {Capturing Subjective Time as Context and It’s Applications (Poster)},

author = {Takuro Yonezawa and Yuuki Nishiyama and Kei Hiroi and Nobuo Kawaguchi},

url = {https://doi.org/10.1145/3307334.3328719},

doi = {10.1145/3307334.3328719},

isbn = {9781450366618},

year  = {2019},

date = {2019-01-01},

booktitle = {Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services},

pages = {647–648},

publisher = {Association for Computing Machinery},

address = {Seoul, Republic of Korea},

series = {MobiSys ’19},

abstract = {We propose an integrated framework for sensing, recognizing and utilizing of subjective time as context. Various studies on experimental psychology have showed several factors which affects subjective time. Those factors should be partially captured by ubiquitous sensors such as smartphones and wearable devices, therefore, we tackle to create common and individual model for subjective time based on the sensor data. We report our first prototype implementation for the framework based on AWARE framework with adding experience sampling method for subjective time recognition. In addition, we discuss potential applications which leveraging advantages of subjective time as context.},

keywords = {context-awareness, experience sampling method, subjective time},

pubstate = {published},

tppubtype = {inproceedings}

}