Publication

@inproceedings{published_papers/40226624,

title = {Cooperative Local Distributed Machine Learning Considering Communication Latency and Power Consumption},

author = {Shota Ono and Taku Yamazaki and Takumi Miyoshi and Yuuki Nishiyama and Kaoru Sezaki},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {2023 IEEE 20th Annual Consumer Communications & Networking Conference (IEEE CCNC 2023)},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{published_papers/40226623,

title = {Enabling Block Transmission on Backoff-based Opportunistic Routing},

author = {Eri Hosonuma and Yuuki Nishiyama and Kaoru Sezaki and Takumi Miyoshi and Taku Yamazaki},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {2023 IEEE 20th Annual Consumer Communications & Networking Conference (IEEE CCNC 2023)},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ubicomp2022_han,

title = {A Micro-mobility Sensing System to Portray Riding Styles},

author = {Zengyi Han and Yuuki Nishiyama and Kaoru Sezaki},

year  = {2022},

date = {2022-09-12},

urldate = {2022-09-12},

booktitle = {Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers},

pages = {19–20},

publisher = {Association for Computing Machinery},

address = {USA and UK},

series = {UbiComp '22},

abstract = {Riding style concerns the way a micro-mobility rider chooses to ride, and it plays a significant role in traffic safety. Portraying a rider’s

riding style is a useful way to guide them towards safer riding behaviors, and offer fine-grained information for insurance companies

and bike-sharing companies to provide better services. To this end, we propose a micro-mobility sensing system to portray riding

styles. Utilizing helmet-mounted and bicycle handle-mounted inertial sensors, our sensing system is able to monitor the micro-mobility

movement status, detect the maneuver behaviors, and the safety check condition of riders. With 10 participants’ experimental data,

we present the feasibility of detecting maneuver behavior and recording the data that characterize the rider’s riding style with our

sensing system, and therefore make it a viable addition to the micro-mobility.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3557915.3560969,

title = {A Plug-in Memory Network for Trip Purpose Classification},

author = {Suxing Lyu and Tianyang Han and Yuuki Nishiyama and Kaoru Sezaki and Takahiko Kusakabe},

url = {https://doi.org/10.1145/3557915.3560969},

doi = {10.1145/3557915.3560969},

isbn = {9781450395298},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {Proceedings of the 30th International Conference on Advances in Geographic Information Systems},

publisher = {Association for Computing Machinery},

address = {Seattle, Washington},

series = {SIGSPATIAL '22},

abstract = {Trip purpose plays a critical role in reflecting human mobility behavior. However, it is relatively difficult to determine. With the rapid growth of urban mobility and big mobile data, utilizing these data for trip purpose classification has been a long-term objective to enhance travel demand and behavior models used in urban planning. Although studies on this topic have been extensively conducted, most past research preferred relying on traveler attributes or long-term travel histories to achieve accurate results. These data could be privacy sensitive and often do not satisfy real-world scenarios. This study addresses the problem of classifying trip purpose by only space activity information to avoid privacy conflict. 1) External memories are collected from factorized components based on the non-negative Tucker decomposition scheme. 2) These memories are extended by the cross-attention mechanism to achieve feature augmentation. 3) Subsequently, a novel concept called "latent mode alignment" is proposed. By leveraging the linear characteristics of external memories, geographic contextual latent modes are represented and matched with travel activities; this procedure is called älignment." 4) The gate mechanism controls the eventual outputs for update. The proposed plug-in memory network (PMN), combined with baseline models, effectively outperforms the original settings. Moreover, combination models are validated with strong tolerance through missing data tests, which are common and problematic in real-world scenarios. The proposed PMN is a plug-and-play design that is easy to combine with newly developed classification models, and other memory collection methods can be expected.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ubicomp2022_shimojo,

title = {A Preliminary Study for Detecting Visual Search Behaviors During Street Walking Using Earable Device},

author = {Kazuki Shimojo and Zengyi Han and Yuuki Nishiyama and Kaoru Sezaki},

year  = {2022},

date = {2022-09-12},

urldate = {2022-09-12},

booktitle = {Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2022 ACM International Symposium on Wearable Computers},

pages = {19–20},

publisher = {Association for Computing Machinery},

address = {USA and UK},

series = {UbiComp '22},

abstract = {Map applications on smartphones are powerful navigation tools for walking among places to visit for the first time and are used widely. On the other hand, checking the application tend to cause trouble on the road such as collisions with people, cars, and objects. To prevent the troubles, we need to detect the walker’s context regarding visual search behaviors and provide appropriate navigation information for the walker. In this paper, we propose a method to detect a walker’s context regarding visual search behaviors by using motion sensors on an earable device. We collected and investigated motion and gaze data from an earable device and gaze tracker respectively during street walking from five participants. Based on the investigation, we create a machine learning model for detecting looking around, smartphone, or normal during walking 

and stopping conditions. Our evaluations show that our models can detect more than 95% of walking and stopping conditions, and 71% of three details conditions during walking, respectively},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ubi75_zhuang,

title = {A preliminary study for monitoring hygiene behaviors by using multiple sensors on a wrist},

author = {Haoyu Zhuang and Liqiang Xu and Yuuki Nishiyama and Kaoru Sezaki},

url = {http://id.nii.ac.jp/1001/00219769/

https://www.mcl.iis.u-tokyo.ac.jp/wp-content/uploads/2022/12/IPSJ-UBI22075027.pdf},

issn = {2188-8698},

year  = {2022},

date = {2022-08-29},

urldate = {2022-08-29},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2022-UBI-75},

number = {27},

pages = {1--7},

abstract = {Under the epidemic of COVID-19, it is important to automatically detect epidemic protective behaviors without a user's intention. Existing studies utilized only sensor data from IMU for detecting epidemic protection behaviors. However, the performance of the classification for similar behaviors could be unsatisfactory due to the single data dimension. It is well known that washing hands and hand sterilization are essential personal hygiene behaviors. In this paper, we use multiple sensor data from an off-the-shelf smartwatch and smartphone for detecting these three behaviors. Our performance evaluation indicated that our proposed method has improved accuracy for classifying the target epidemic protective behaviors over previous methods. Furthermore, for applying our method in reality, we developed a prototype for detecting these behaviors on a wearable device, which allows us to utilize our method widely in health habits monitoring.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{smartcomp2022_kasahara,

title = {Detecting Childcare Activities Using an Off-the-shelf Smartwatch},

author = {Yuki Kasahara and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://smartcomp.aalto.fi/assets/WIP-posters/poster_1570812161.pdf},

doi = {10.1109/SMARTCOMP55677.2022.00038},

isbn = {978-1-6654-8152-6},

year  = {2022},

date = {2022-06-20},

urldate = {2022-06-01},

booktitle = {2022 IEEE International Conference on Smart Computing (SMARTCOMP)},

pages = {159-161},

publisher = {IEEE},

address = {Espoo, Finland},

abstract = {The childcare environment has significantly changed, owing to accelerating women's social advancement and the increasing number of nuclear families. Improving and supporting childcare have become major challenges in current society. Automatically recording and subsequently observing childcare activities can be used for various purposes to support childcare. However, methods to detect childcare activities using off-the-shelf devices have not yet been proposed. This study develops a method to detect childcare activities that parents perform for their babies using an off-the-shelf wearable device. We define nine childcare activities and develop corresponding detection models based on motion-sensor data from a smartwatch. Our evaluation in a laboratory setting resulted in classification performances of 71% (F1: 0.66).},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{healthcom2022_ono,

title = {Detecting Face-Mask Wearing Status Using Motion Sensors in Commercially Available Smartwatches},

author = {Shota Ono and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://healthcom2022.ieee-healthcom.org/},

year  = {2022},

date = {2022-10-17},

urldate = {2022-10-17},

booktitle = {2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom) },

publisher = {IEEE},

address = {Genoa, Italy},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{percom2022_dong,

title = {DoubleCheck: Detecting Single-Hand Cycling with Inertial Measurement Unit of Smartphone},

author = {Xuefu Dong and Zengyi Han and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://youtu.be/AW5B-cPdeFI

https://www.percom.org/},

doi = {10.1109/PerComWorkshops53856.2022.9767429},

year  = {2022},

date = {2022-03-21},

urldate = {2022-03-21},

booktitle = {IEEE International Conference on Pervasive Computing and Communications (PerCom)},

publisher = {IEEE},

address = {Pisa, Italy},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{smc2022_dong,

title = {DoubleCheck: Single-Handed Cycling Detection with a Smartphone},

author = {Xuefu Dong and Zengyi Han and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://ieeesmc2022.org/},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)},

pages = {xx-xx},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-031-05431-0_23,

title = {Enhancing Self-Protection: What Influences Human’s Epidemic Prevention Behavior during the COVID-19 Pandemic},

author = {Liqiang Xu and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://doi.org/10.1007/978-3-031-05431-0_23},

doi = {10.1007/978-3-031-05431-0_23},

isbn = {978-3-031-05430-3},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {Distributed, Ambient and Pervasive Interactions. Smart Living, Learning, Well-Being and Health, Art and Creativity: 10th International Conference, DAPI 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Virtual Event, June 26 – July 1, 2022, Proceedings, Part II},

pages = {336–351},

publisher = {Springer-Verlag},

address = {Berlin, Heidelberg},

abstract = {Under the circumstance of the rapid spread of the COVID-19 pandemic, enhancing human’s awareness of self-protection is one practical method to slow down the epidemic. In this study, we utilize mobile sensing to track human activity and guide human’s epidemic prevention behavior by gamified feedback techniques by our developed application. Virtually, human’s self-protection awareness is affected by many factors and the measures to enhance people’s self-protection behavior against the epidemic COVID-19 has always been an unresolved issue. In order to search for factors that influence human’s self-protection behavior, we analyzed the relationships between various human activities and the percentage complete of human’s self-protection behavior and we have extracted some more general conclusions from the results. Based on our data analysis results, we also made some proposals to enhance self-protection behavior. Meanwhile, our study illustrates the effectiveness of the method that analyzes human self-protection behavior through mobile sensing. Our study also validates the effectiveness of persuasive technology on human’s self-protection behavior against the COVID-19 pandemic and therefore we advocate enhancing human’s self-protection awareness through external intervention and guidance by smart device.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ieice2022_zhuang,

title = {Face-Touch Detection with Smartwatch by CNN: An Experimental Lab Study},

author = {荘昊昱 and 韓増易 and 西山勇毅 and 瀬崎薫},

year  = {2022},

date = {2022-06-30},

urldate = {2022-06-30},

booktitle = {電子情報通信学会ソサイエティ大会},

address = {オンライン},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3498361.3538782,

title = {Head Dynamics Enabled Riding Maneuver Prediction},

author = {Zengyi Han and Xuefu Dong and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://doi.org/10.1145/3498361.3538782},

doi = {10.1145/3498361.3538782},

isbn = {9781450391856},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services},

pages = {557–558},

publisher = {Association for Computing Machinery},

address = {Portland, Oregon},

series = {MobiSys '22},

abstract = {While micro-mobility brings convenience to the modern city, they also cause various social problems such as traffic accidents, casualties, and huge economic losses. Wearing protective equipment has become the primary recommendation for safe riding, but passive protection cannot prevent accidents from happening after all. Thus, timely predicting the rider's maneuver is essential for more active protection and buying more time to avoid potential accidents from happening. In this poster, we explore the feasibility of using riders' head dynamics to predict their riding maneuvers. Through ten participants' preliminary study, we observed that not only do riders' head movements appear ahead of their maneuvers but also head movement patterns are distinct with different maneuver intentions. We then construct a deep learning network using Long Short Term Memory, achieving 89% of accuracy on maneuver prediction.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ieice2022_hosonuma,

title = {LPWAによる屋内混雑度推定に向けた基礎検討},

author = {細沼恵里 and 三好匠 and 山崎託 and 西山勇毅 and 瀬崎薫 },

year  = {2022},

date = {2022-06-30},

urldate = {2022-06-30},

booktitle = {電子情報通信学会ソサイエティ大会},

address = {オンライン},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mobicovid22_nishiyama,

title = {MOCHA: Mobile Check-in Application for University Campuses Beyond COVID-19},

author = {Yuuki Nishiyama and Hiroaki Murakami and Ryoto Suzuki and Kazusato Oko and Issey Sukeda and Kaoru Sezaki and Yoshihiro Kawahara},

doi = {10.1145/3492866.3557736},

isbn = {978-1-4503-9165-8/22/10},

year  = {2022},

date = {2022-10-18},

urldate = {2022-10-18},

booktitle = {The Twenty-third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing},

volume = {MobiHoc '22},

publisher = {ACM},

address = {Seoul, Republic of Korea},

abstract = {Users and operators of shared spaces must ensure safety in such areas to prevent the spread of COVID-19. Although each organization has operated a variety of safety-related systems, including contact tracing, congestion monitoring, and check-in services, it is unclear what elements, such as privacy protection level, benefits, and permission procedures, have promoted the usage of these systems. In this study, we created MOCHA, a platform for sharing and tracking room-level locations. This platform automatically detects visited places by scanning Bluetooth beacons in each room using smartphones and shares location data according to predefined user settings. The collected data is used for room-level contact tracing, congestion monitoring, and reservation services. According to >6,500 users' usage data for a year in a university, outlining the advantages of utilizing the app encouraged people to install the app, and reinforced connections in small private groups are encouraged to use the app continuously.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sensys2022_xu,

title = {Poster abstract: Convolutional Compressed Sensing for Smartphone Acceleration Data Compression},

author = {Liqiang Xu and Yuuki Nishiyama and Masamichi Shimosaka and Kota Tsubouchi and Kaoru Sezaki},

year  = {2022},

date = {2022-11-06},

urldate = {2022-11-06},

booktitle = {Proceedings of the 20th Conference on Embedded Networked Sensor Systems, Boston, USA},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

series = {SenSys '22},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sensys2022_sukeda,

title = {Poster abstract: Recursive Queueing Estimation Using Smartphone-based Acoustic Ranging},

author = {Issey Sukeda and Hiroaki Murakami and Yuuki Nishiyama and Hiroaki Murakami and Yoshihiro Kawahara},

year  = {2022},

date = {2022-11-06},

urldate = {2022-11-06},

booktitle = {Proceedings of the 20th Conference on Embedded Networked Sensor Systems, Boston, USA},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

series = {SenSys '22},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sensys2022_suzuki,

title = {Poster abstract: Room Scale Localization Improvement Utilizing Stay Time Characteristics of Each Room},

author = {Ryoto Suzuki and Yuuki Nishiyama and Hiroaki Murakami and Yoshihiro Kawahara and Kaoru Sezaki},

year  = {2022},

date = {2022-11-06},

urldate = {2022-11-06},

booktitle = {Proceedings of the 20th Conference on Embedded Networked Sensor Systems, Boston, USA},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

series = {SenSys '22},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sensys2022_ishioka,

title = {Poster abstract: UV index estimation leveraging GNSS sensors on smartphones},

author = {Riku Ishioka and Yuuki Nishiyama and Kota Tsubouchi and Kaoru Sezaki},

year  = {2022},

date = {2022-11-06},

urldate = {2022-11-06},

booktitle = {Proceedings of the 20th Conference on Embedded Networked Sensor Systems, Boston, USA},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

series = {SenSys '22},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{smartcomp2022_komatsu,

title = {Toward Measuring Conversation Duration Using a Wristwatch-type Wearable Device},

author = {Yuki Komatsu and Kazuki Shimojo and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://smartcomp.aalto.fi/assets/WIP-posters/1570807018-poster.pdf

https://www.youtube.com/watch?v=Ai72_ikjsQI},

doi = {10.1109/SMARTCOMP55677.2022.00035},

isbn = {978-1-6654-8152-6},

year  = {2022},

date = {2022-06-24},

urldate = {2022-06-24},

booktitle = {2022 IEEE International Conference on Smart Computing (SMARTCOMP)},

pages = {150-152},

publisher = {IEEE},

address = {Espoo, Finland},

abstract = {The frequency and duration of social contact, represented by conversation, is positively correlated with our physical and mental health. Therefore, a method that automatically measures social contact can provide insight into people's health conditions and risks. Even though off-the-shelf wristwatch-type wearable devices are widely used in our daily lives and have rich computational resources, they have not been used as a social-contact monitoring tool in everyday conditions. In this study, we propose a system, called Ohanashi, for continuously monitoring conversational events as a means of social contact in daily life, by edge processing on an off-the-shelf smartwatch. To monitor the conversational event, we developed an audio classification model and implemented it as a smartwatch application, which can classify conversation and noise from an audio stream. Our performance evaluation shows that the classification model can classify conversation and noise with more than 86% accuracy in both silent and noisy environments, and the system can monitor conversation events for more than 15 hours on a smartwatch.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ieice2022_hzy,

title = {Using Turning Data for Micro-Mobility Rider Identification},

author = {韓増易 and 西山勇毅 and 瀬崎薫},

year  = {2022},

date = {2022-06-30},

urldate = {2022-06-30},

booktitle = {電子情報通信学会ソサイエティ大会},

address = {オンライン},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ubi74_shimojo,

title = {イアラブルデバイスを用いた街歩き時におけるユーザの道迷い状態の検知},

author = {下条和暉 and 西山勇毅 and 瀬崎薫},

url = {http://id.nii.ac.jp/1001/00218074/},

issn = {2188-8698},

year  = {2022},

date = {2022-06-06},

urldate = {2022-06-06},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2022-UBI-74},

number = {3},

pages = {1 - 6},

abstract = {街歩きにおいて，ユーザの迷い状態を検知できれば効率的で安全な道案内が実現出来る．イアラブルデバイスは，耳に装着するウェアラブルデバイスであり，搭載された行動認知機構や音声インターフェスによってユーザの状態を把握することが出来る．イアラブルデバイスを活用することえユーザの街中における道迷い状態を検知し，音声案内が可能になると考えられるが，その手法についてはまだ明らかになっていない．そこで本研究では，イアラブルデバイスに搭載されているモーションセンサから収集したデータを用いることで，ユーザの道迷い状態を検知する手法を提案する．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ubi73_ono,

title = {ウェアラブルデバイスのマイクを用いたマスク装着状態の検知に向けて},

author = {小野翔多 and 西山勇毅 and 瀬崎薫},

year  = {2022},

date = {2022-03-01},

urldate = {2022-03-01},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2022-UBI-73},

pages = {1 - 8},

abstract = {感染症予防において，マスクの装着は飛沫による感染症への感染リスクを低下させる有効な手段の一つである．日常生活中におけるマスク装着の有無やその種類を自動的に検出できれば，感染リスクの判定やJust-in-Timeでの注意喚起，行動記録など様々な応用サービスが実現可能になる．しかし，映像処理や専用機器を用いずに，日常生活中において自動的にマスクの装着状態を検知する手法はまだ提案されていない．本研究では，市販のスマートウォッチの内蔵マイクのみを用いてマスクの装着状態を検出する．マスク装着時の音声特性調査とマスク装着状態判定モデルの評価実験から，マスク装着時・未装着時の音声データと機械学習を用いてマスク装着状態を検知できる可能性が示唆された．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{jchi2022_kasahara,

title = {ウェアラブルデバイスを用いた子育てコンテキストの検知に向けて},

author = {笠原有貴 and 西山勇毅 and 瀬崎薫},

url = {http://www.sighci.jp/events/sig/196},

year  = {2022},

date = {2022-01-11},

urldate = {2022-01-11},

booktitle = {研究報告ヒューマンコンピュータインタラクション研究会（CHI）},

publisher = {情報処理学会},

address = {石垣島},

abstract = {女性の社会進出や核家族化，産後うつ問題など，子育て環境は大きく変化しており，子育ての効率

化や子育て支援は社会的に大きな課題となっている．本研究では，近年普及傾向にあるウェアラブルデバイスを用いて，ミルクやオムツ替え，お散歩など「親」が「乳幼児」に行う子育て行動の検知技術の開発を行う．子育て中のモーションデータを腕時計型のウェアラブルデバイスに搭載されたモーションセンサを用いて収集し，収集データと機械学習を用いて子育てコンテキストの検知モデルを構築する．本稿では，9種類の子育てコンテキストを定義し，子育てコンテキストの検知モデルの構築とその精度評価を行なった．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ipsjbit-onob,

title = {スマートウォッチを用いたマスク装着の促進手法},

author = {小野翔多 and 西山勇毅 and 瀬崎薫},

url = {http://www.sig-bti.jp/event/kickoffinfo.html

http://www.sig-bti.jp/event/img/Proceedings%20of%20%20IPSJBTI%20Kickoff%20Symposium.pdf},

year  = {2022},

date = {2022-04-16},

urldate = {2022-04-16},

booktitle = {情報処理学会 IoT行動変容学研究グループ キックオフシンポジウム},

pages = {56--57},

abstract = {新型コロナウイルス感染症が世界的に蔓延しており，感染拡大を予防するために，マスクの装着などの飛沫感染のリスクを下げる行動が求められている [1]．感染リスクを低下させるためには、常時マスクを装着することが望ましいが，無意識のうちにマスク非装着のまま行動してしまうことがしばしば発生する．マスク装着を効果的に促すためには，個々人のマスク装着状態を自動検知し，その状態に応じてユーザに行動変容を促すことが求められる．しかし，これまでのところ，マスク装着状態を市販の端末のみを用いて常時検出する手法はまだ提案されていない．本稿では，スマートウォッチに搭載されている複数のセンサを用いてマスク装着状態を自動検知し，マスク非装着のユーザに通知することで，マスク装着の行動を促進させる手法を提案する．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{weko_222066_1,

title = {スマートフォンのGNSSセンサを用いたUVインデックス推定},

author = {石岡陸 and 坪内孝太 and 西山勇毅 and 瀬崎薫},

url = {http://id.nii.ac.jp/1001/00221996/},

issn = {2188-8698},

year  = {2022},

date = {2022-11-01},

urldate = {2022-11-01},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2022-UBI-76},

number = {20},

pages = {1 - 7},

publisher = {情報処理学会},

abstract = {個人の紫外線被曝量モニタリングは，個々人が最適な量の紫外線を浴びることを目的に，盛んに研究されてきた．先行研究では，スマートフォンのカメラや光センサ，ウェアラブルUVセンサを用いた UV 量の推定が提案されてきた．我々は，スマートフォンの GNSS センサを活用した世界初の UV インデックス推定手法を提案する．カメラや光センサを継続的に露出させなければならないような手法と比較して，GNSS を用いた方法は，普段のようにスマートフォンを身につけるだけで推定を可能にするという原理的な利点がある．GNSS による推定の第一歩として，1 つの地域の 3 ヶ所において GNSS データを収集し，OpenUV というAPI をベースラインとして用い，提案手法の有効性を検証した．提案手法は，平均絶対誤差（MAE）0.1523 を達成し，ベースラインを圧倒的に上回った．本研究によって実際のデータに対して提案システムの有効性が証明されたことは，人々が容易に日々の UV 被曝量を把握できるような未来への大きな一歩となることが期待される．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ieice2022,

title = {スマートフォンを用いたベビーカーのコンテキスト検知に向けた一検討},

author = {西山勇毅 and 瀬崎薫},

url = {https://www.ieice-taikai.jp/2022general/jpn/index.html},

year  = {2022},

date = {2022-03-01},

urldate = {2022-03-01},

booktitle = {電子情報通信学会総合大会（オンライン）},

publisher = {電子情報通信学会},

abstract = {ベビーカーは，子供がいる家庭の約70%が所有し，週に一回以上利用する家庭は73.8%であると報告されるなど，保有率・利用率ともに高い．ベビーカーは乳幼児を運搬するため，安全性と快適性が高く求められるが，街中・施設内において安全・快適な走行・滞在可能なルートや場所，時間を手軽に知ることは難しい．これらの情報を検知することで，様々な応用アプリケーションを実現できる．そこで本稿では，スマートフォンを用いたベビーカー移動時の急停止や段差との衝突，路面状態といったベビーカー移動に関するコンテキスト検知の可能性を調査し，その結果を報告する．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ipsj2022_ushijima,

title = {タクシー車両を用いたマイクロモビリティ再配置},

author = {牛島秀暢 and 西山勇毅 and 瀬崎薫},

url = {https://www.ipsj.or.jp/event/taikai/84/index.html},

year  = {2022},

date = {2022-03-05},

urldate = {2022-03-05},

booktitle = {情報処理学会 第84回全国大会（愛媛大学）},

publisher = {情報処理学会 },

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ieice2022_ono,

title = {無線マルチホップ連合学習へ向けた実装実験},

author = {小野翔多 and 三好匠 and 山崎託 and 西山勇毅 and 瀬崎薫},

year  = {2022},

date = {2022-06-30},

urldate = {2022-06-30},

booktitle = {電子情報通信学会ソサイエティ大会},

address = {オンライン},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ono_icm2022,

title = {移動体通信併用型MANETにおける端末密度を用いた中継領域制御},

author = {小野翔多 and 山崎託 and 三好匠 and 西山勇毅 and 瀬崎薫},

year  = {2022},

date = {2022-03-01},

urldate = {2022-03-01},

booktitle = {情報通信マネジメント研究会 (ICM)},

publisher = {電子情報通信学会},

abstract = {Mobile ad-hoc network（MANET）は，端末間の通信のみで自律分散的にネットワークを構築できる．しかし，通信ネットワーク構築時に制御メッセージを全方位にフラッディングするため，通信資源を過剰に消費する. 位置情報を収集できる端末が通信ネットワーク構築に参加する環境では，端末の位置情報を組み合わせることで，より効率的なフラッディングが可能になると考えられる．本稿では，端末の位置情報に基づいて仮想通信領域を作成し，その領域内の端末にのみフラッディングすることで，経路探索を効率化する手法を提案する．シミュレーションによる評価の結果，提案手法は仮想通信領域を柔軟に作成し，過剰な通信資源消費の抑制と通信遅延の削減を実現できることが分かった．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ipsj2022_komatsu,

title = {腕時計型ウェアラブルデバイスを用いた会話時間計測手法の構築に向けて},

author = {小松勇輝 and 下条和暉 and 西山勇毅 and 瀬崎薫},

url = {https://www.ipsj.or.jp/event/taikai/84/index.html},

year  = {2022},

date = {2022-03-05},

urldate = {2022-03-05},

booktitle = {情報処理学会 第84回全国大会（愛媛大学）},

publisher = {情報処理学会},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{duc_vtc2021b,

title = {A Run-time Dynamic Computation Offloading Strategy in Vehicular Edge Computing},

author = {Hong Duc Nguyen and Shunsuke Aoki and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://events.vtsociety.org/vtc2021-fall/},

doi = {10.1109/VTC2021-Fall52928.2021.9625245},

isbn = {2577-2465},

year  = {2021},

date = {2021-09-27},

urldate = {2021-09-27},

booktitle = {2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)},

pages = {1-7},

publisher = {IEEE},

address = {Online},

abstract = {In vehicular edge computing (VEC), offloading the tasks to the nearby resource-rich edge servers helps each vehicle enhance computational capabilities and improve in-vehicle applications' performance. However, the concentration of travel at specific spaces and times poses significant challenges on the load-balancing and scheduling of computation tasks at the edge servers. This paper studies a low-complexity dynamic online offloading strategy that efficiently reduces task delay and computing resource consumption in the multi-user, multiserver vehicular edge computing scenarios. Our design addresses issues of computation task placement and execution order of the tasks on each server. We use a realistic approach that vehicles generate tasks over time, and the set of the tasks is unknown in advance so that the offloading decisions are made in runtime. Extensive simulations are conducted on a real mobility trace of Luxembourg city, and the results show that the proposed algorithm effectively improves the offloading utility of the system.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ieice2021_duc,

title = {An Online Task Offloading Strategy in Vehicular Edge Computing},

author = {Hong Duc Nguyen and Shunsuke Aoki and Yuuki Nishiyama and Kaoru Sezaki},

url = {http://www.ieice-taikai.jp/2021society/jpn/

https://www.ieice.org/~icm/jpn/award/sub/awardees.html},

year  = {2021},

date = {2021-09-14},

urldate = {2021-09-14},

booktitle = {IEICE Society Conference 2021},

publisher = {IEICE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{itsc2021_ntf,

title = {An Unsupervised Learning-based Approach for User Mobility Analysis of E-Scooter Sharing Systems},

author = {Hidenaga Ushijima and Shunsuke Aoki and Peng Helinyi and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://2021.ieee-itsc.org/},

doi = {10.1109/ITSC48978.2021.9564616},

isbn = {978-1-7281-9141-6},

year  = {2021},

date = {2021-10-25},

urldate = {2021-10-25},

booktitle = {2021 IEEE International Intelligent Transportation Systems Conference (ITSC)},

pages = {1425-1430},

publisher = {IEEE},

abstract = {Human mobility analysis is a key method for understanding urban dynamics and mobility optimization. Novel last-mile mobility, called micromo-bilities, that includes shared bicycles, electric bicycles (e-bikes), and electric scooters are seeing rapid widespread acceptance in major cities. Compared with existing mobility data such as cars, buses, and trains, the majority trip distance of micromobilities is short, typically less than a few miles. The riders use them for commuting, sightseeing, shopping, and/or fun. By using the mobility data of micromobilities, we can observe more fine-grained human mobility in urban areas than existing data sources. In this paper, we present an unsupervised learning-based technique to analyze human mobility in urban areas and to study user clusters for such micromobility services. In our approach, we cluster user mobility patterns by using non-negative tensor factorization (NTF) from area-based trip data (which only included locations of origin and destination). Our approach was applied to micromobility data collected from Chicago and Washington, D.C., and we observed characteristic patterns.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3460418.3479294,

title = {Detecting Single-Hand Riding with Integrated Accelerometer and Gyroscope of Smartphone},

author = {Xuefu Dong and Zengyi Han and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://doi.org/10.1145/3460418.3479294},

doi = {10.1145/3460418.3479294},

isbn = {9781450384612},

year  = {2021},

date = {2021-09-21},

urldate = {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 = {19–20},

publisher = {Association for Computing Machinery},

address = {Virtual, USA},

series = {UbiComp '21},

abstract = {Single-hand cycling poses a safety threat with the decrement of riders’ response 

capacity. Recognizing risky behavior by prevalently used smartphones could lead to 

enhanced riding safety. In this work, we propose a single-hand cycling recognition 

method based on motion data acquired from the three-axis accelerometer and gyroscope 

integrated into a handlebar-installed smartphone. We conducted a 4-person experiment. 

The data result demonstrates that motion data of double-hand cycling clearly distinguishes 

from that of single-hand, revealing the chance to materialize a robust detection tool 

in smartphones to enable safer biking. For future work, we prepare to redesign the 

experiment under more sophisticated circumstances with an improved platform, thus 

scaling this sensing method for real-life usage.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{igessc2021_peng,

title = {Estimation of Greenhouse Gas Emission Reduction from Shared Micromobility System},

author = {Helinyi Peng and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://youtu.be/vbt622kXNuU},

doi = {10.1109/IGESSC53124.2021.9618701},

issn = {2640-0138},

year  = {2021},

date = {2021-11-01},

urldate = {2021-11-01},

booktitle = {2021 IEEE Green Energy and Smart Systems Conference (IGESSC)},

pages = {1-6},

publisher = {IEEE},

address = {Long Beach, CA, USA},

abstract = {Shared micromobility is widely recognized as an environmentally friendly travel mode and a critical component of transportation decarbonization. However, quantitatively assessing its environmental impact using real-world trip data is an unresolved and challenging subject. In this research, we proposed a system combining machine learning algorithms and the Monte Carlo simulation to address this issue. First, several machine learning algorithms (Random Forest, XGBoost, and LightGBM) were utilized to identify citizens’ travel mode choice preferences and then estimate the substituted travel mode of each micromobility trip. Second, to ensure the reliability of the final environmental impact assessment, the Monte Carlo simulations were used to simulate the substituted mode of each trip. Then the environmental impacts were calculated based on the life cycle greenhouse gas emissions. Instead of estimating a specific number, we obtained a probabilistic outcome for environmental impacts by using the Monte Carlo simulation, which considers the uncertainty. According to the studies, the shared bike service and the shared e-scooter service have positive environmental impacts. However, these effects are limited compared to the transportation sector’s total emissions. The most compelling reason is that shared micromobility comprises a minuscule part of total urban travel.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@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 = {2021-09-21},

urldate = {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 = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3460418.3479282,

title = {HeadSense: A Head Movement Detecting System for Micro-Mobility Riders},

author = {Zengyi Han and Xuefu Dong and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://doi.org/10.1145/3460418.3479282},

doi = {10.1145/3460418.3479282},

isbn = {9781450384612},

year  = {2021},

date = {2021-09-21},

urldate = {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 = {26–27},

publisher = {Association for Computing Machinery},

address = {Virtual, USA},

series = {UbiComp '21},

abstract = {Head movement for traffic visual searching, is one of the important factors in traffic 

safety. In this paper, we present the design, implementation, and preliminary evaluation 

of the HeadSense, a helmet device that detects the head movement of micro-mobility 

rider. HeadSense is capable of generating data streams using the embedded 9-axis inertial 

measurement unit (IMU) sensor. After the process of segmentation and classification 

algorithm, HeadSense can automatically detect an individual’s head movement sequence 

and visual search episodes, across the rider’s entire riding journey. Experiments 

with 5 participants show that our system achieves 94.7% for per-second level detection 

and 80.59% F1-score for per-episode level detection.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ieee_itsc_mimosense,

title = {MiMoSense: An Open Crowdsensing Platform for Micro-Mobility},

author = {Zengyi Han and Hong Duc Nguyen and Shunsuke Aoki and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://2021.ieee-itsc.org/},

doi = {10.1109/ITSC48978.2021.9564524},

year  = {2021},

date = {2021-09-19},

urldate = {2021-09-19},

booktitle = {2021 IEEE International Conference on Intelligent Transportation (ITSC)},

pages = {1-6},

publisher = {IEEE},

abstract = {The use of micro-mobility (e.g., bicycle and scooter) and their data for urban sensing and rider assessment is becoming increasingly popular in research. However, different research topics require different sensor setups; no general data collecting tools for the micro-mobility makes the researcher who wishes to collect data has to build their own collecting system from scratch. To this end, we present MiMoSense, an open crowdsensing platform for micro-mobility. MiMoSense consists of two components: (1) MiMoSense server, which is set up on the cloud, and used to manage sensing studies and the collected data for research and sharing. (2) MiMoSense client, uses micro-mobility carrying various sensors and IoT devices to collect multiple kinds of data during traveling. As a reusable open-source software, MiMoSense shifts the researcher's focus from software development to sensing data analysis; it can help researchers quickly develop an extensible platform for collecting micro-mobility's raw sensing data and inferring traveling context. We have evaluated MiMoSense's battery consumption, message latency and discuss its use.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{edgedl2021-uv,

title = {Towards Estimating UV Exposure Using GPS Signal Strength from a Carrying Smartphone},

author = {Soichiro Higuma and Kosuke Hatai and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://www.smart-comp.info/},

doi = {10.1109/SMARTCOMP52413.2021.00063},

isbn = {2693-8340},

year  = {2021},

date = {2021-08-23},

urldate = {2021-08-23},

booktitle = {2021 IEEE International Conference on Smart Computing (SMARTCOMP)},

pages = {299-304},

publisher = {IEEE},

address = {Irvine, Orange County, California, USA (Virtual Workshop)},

abstract = {Owing to lifestyle changes, urbanization, and the COVID-19 pandemic, many people spend more time indoors and tend to receive less direct sunlight than before. Although excessive or inadequate ultraviolet (UV) exposure can be harmful to our physical and mental health, moderate UV exposure is essential for vitamin D (VD) production in the body. In this study, we estimate the UV exposure using an off-the-shelf smartphone, and explore the relationship between the UV values and GPS signal strength (C/N0). The results demonstrate that a strong correlation (R 2 = 0.73) between the UV values and carrier to noise density (C/N0) even if the smartphone and UV sensor are moved. Therefore, it is possible to estimate the UV exposure to some extent from a person's location, even while carrying a smartphone.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{taxi_co2_20201,

title = {Towards Infectious Disease Risk Assessment in Taxis using Environmental Sensors},

author = {Hidenaga Ushijima and Shota Ono and Yuuki Nishiyama and Kaoru Sezaki},

editor = {Norbert Streitz and Shiníchi Konomi},

url = {http://2021.hci.international/},

doi = {10.1007/978-3-030-77015-0_13},

isbn = {978-3-030-77015-0},

year  = {2021},

date = {2021-07-07},

urldate = {2021-07-07},

booktitle = {Distributed, Ambient and Pervasive Interactions},

volume = {12782},

pages = {178--188},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {The spread of Coronavirus disease of 2019 (COVID-19) has reaffirmed the importance of ventilation in enclosed public spaces. Studies on air quality in public spaces such as classrooms, hospitals, and trains have been conducted in the past. However, the interior of a taxi, where an extremely small space is shared with an unspecified number of people, has not been sufficiently studied. This is a unique environment where ventilation is important. This study compared ventilation meth-ods focusing on the CO2 concentration in the cabin, and evaluated the frequency of ventilation in an actual taxi using sensing technology},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{nokey,

title = {イヤラブルデバイスを用いた身体感覚記録・利活用システムの構築に向けて},

author = {西山勇毅 and 瀬崎薫},

url = {http://id.nii.ac.jp/1001/00213861/

https://www.yuukinishiyama.com/wp-content/uploads/2021/12/IPSJ-UBI21072012_.pdf},

isbn = {2188-8698},

year  = {2021},

date = {2021-11-23},

urldate = {2021-11-23},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2021-UBI-72},

number = {12},

pages = {1 - 8},

abstract = {スポーツや楽器の演奏，自動車の運転など，効率的に新しい運動スキルを習得し，さらに向上させることは，人々の生活をより豊かにする．運動学習は，主観的な運動感覚と実際の動作とのズレを反復練習により埋める作業であるが，客観的な運動情報に比べ，主観的な情報を低負荷に記録し，それらを活用する環境は整っていない．そこで本研究では，運動学習時における主観的な運動情報を容易に収集・利活用可能なシステムを設計・実装し，評価した．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sss_kasahara,

title = {スマートウォッチを用いた子育て行動の推定に向けた一検討},

author = {笠原有貴 and 西山勇毅 and 瀬崎薫},

url = {http://rcl.it.aoyama.ac.jp/member/sice-sss/20210913_program.html},

year  = {2021},

date = {2021-09-13},

booktitle = {計測自動制御学会 計測部門スマートセンシングシステム部会},

publisher = {計測自動制御学会},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{csis2021_shimojo,

title = {常時装着型イアラブルデバイスにおける割り込み可能タイミングの検討},

author = {下条和暉 and 西山勇毅 and 瀬崎薫},

url = {https://www.csis.u-tokyo.ac.jp/blog/research/csis-days-2021-program/

https://www.csis.u-tokyo.ac.jp/wp-content/uploads/2021/12/days21all.pdf},

year  = {2021},

date = {2021-09-10},

urldate = {2021-09-10},

booktitle = {CSIS DAYS 2021},

pages = {40},

publisher = {東京大学空間情報科学研究センター},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ubi71_chen,

title = {感染症予防行動を促進させるインセンティブモデルに関する一検討},

author = {陳美怡 and 幡井皓介 and 西山勇毅 and 瀬崎薫},

url = {http://id.nii.ac.jp/1001/00212342/

https://www.yuukinishiyama.com/wp-content/uploads/2021/12/IPSJ-UBI21071003.pdf},

issn = {2188-8698},

year  = {2021},

date = {2021-08-26},

urldate = {2021-08-26},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2021-UBI-71},

number = {3},

pages = {1--7},

publisher = {情報処理学会},

abstract = {現在，新型コロナウイルス感染症（COVID-19）の感染が拡大しており，人々の生命と健康を大きく脅かしている．政府は地方自治体，保健機関は，「手洗い」や「マスクの着用」 「行動記録」「外出自粛」などの感染症予防策を人々に積極的に取り続けることを推奨している.本研究では，ユーザの感染症予防行動の促進を日標とし，既存の行動記録アプリ（SelfGuard）を拡張し，感染症予防行動に対する最適なインセンティブモデルの導入を検討する.具体的には，スマートフォンとウェアラブルデバイスに搭載されたセンサを利用してユーザの感染症予防行動を認識し，行動に応じてインセンティブとして換金可能なポイントを付与する.固定・加算・減算モデルという三種類のインセンティブモデルにおいて人の行動に与える影響の違いを調査する.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{fit2021_selfguard,

title = {感染症予防行動を促進させるインセンティブモデルの構築に向けて},

author = {陳美怡 and 幡井皓介 and 西山勇毅 and 瀬崎薫},

url = {https://www.ipsj.or.jp/event/fit/fit2021/},

year  = {2021},

date = {2021-08-25},

urldate = {2021-08-25},

booktitle = {第20回情報科学技術フォーラム（FIT2021）},

publisher = {情報処理学会},

address = {オンライン},

abstract = {現在、新型コロナウイルス感染症（COVID-19）の感染が拡大しており，人々の生命と健康を大きく脅かしている．2021年4月18日時点で，COVID-19による全世界の累計死亡者数が300万人を超えたことが報告された[1]．市や政府は，感染症の感染拡大を防ぐために，自己隔離，ロックダウン，行動制限などの対策を実施している．また政府や保健機関は，人々が手洗い・マスクの着用・行動記録・外出自粛などの感染症予防策を積極的に取り続けることを推奨している．西山らの研究では，行動記録アプリ（SelfGuard）を開発し，半自動的にユーザの滞在情報・行動履歴を記録することで，感染症予防行動の促進を実現している[2]．本研究では，ユーザの感染症予防行動の促進を目標として，既存アプリ（SelfGuard）を拡張し，感染症予防行動に対する最適なインセンティブモデルの導入を検討する．具体的には，スマートフォンとウェアラブルデバイスに搭載されたセンサを利用してユーザの感染症予防行動を認識し，行動に応じてインセンティブとして換金可能なポイントを付与する．定額・加算・減算モデルという三種類のインセンティブモデルにおいて人の行動に与える影響の違いを評価する},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{nokey,

title = {移動体通信併用形MANETにおける経路要求送信回数に基づく経路構築手法},

author = {小野翔多 and 山崎託 and 三好匠 and 西山勇毅 and 瀬崎薫},

year  = {2021},

date = {2021-09-14},

booktitle = {2021 電子情報通信学会ソサイエティ大会},

address = {オンライン},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ubi71_suzuki,

title = {部屋毎の滞在時間特性を考慮した頑健な滞在場所推定手法},

author = {鈴木凌斗 and 村上弘晃 and 西山勇毅 and 川原圭博 and 瀬崎薫},

url = {http://id.nii.ac.jp/1001/00212335/

https://www.yuukinishiyama.com/wp-content/uploads/2021/12/IPSJ-UBI21071022.pdf},

year  = {2021},

date = {2021-09-01},

urldate = {2021-09-01},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2021-UBI-71},

pages = {1--7},

publisher = {情報処理学会},

abstract = {屋内での滞在情報を正確に把握することで，混雑度の推定や集客情報，人流の把握など，様々なサービスを提供できる．BluetoothビーコンやWiFiの信号強度を用いた滞在場所推定手法では，低コストに滞在推定システムを導入できる．しかしながら，受信信号強度の不安定さや隣接した部屋から漏れる信号などが原因となり，単純な信号強度のみを用いた判定では，受信環境によっては滞在場所の誤判定が頻繁に発生する．本稿では，部屋ごとの滞在時間特性の違いを考慮に入れることにより誤判定を抑制する手法を提案する．提案手法では，部屋ごとの滞在時間の分布をワイブル分布にフィッティングし，生存時間解析を適用することによりユーザの状態を推定する．信号強度の強弱のみに基づく既存手法との比較のため，正解ラベル付きのデータを収集し評価実験を行った．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{csis2021_koike,

title = {集約型都市におけるライドシェアサービス導入効果のシミュレーション},

author = {小池優太郎 and 西山勇毅 and 瀬崎薫},

url = {https://www.csis.u-tokyo.ac.jp/blog/research/csis-days-2021-program/

https://www.csis.u-tokyo.ac.jp/wp-content/uploads/2021/12/days21all.pdf},

year  = {2021},

date = {2021-09-10},

urldate = {2021-09-10},

booktitle = {CSIS DAYS 2021},

pages = {33},

publisher = {東京大学空間情報科学研究センター},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{weko_208650_1,

title = {BLEビーコンを用いた屋内位置推定システムの設計と実装},

author = {山下陸 and 西山勇毅 and 小松寛弥 and 川原圭博},

url = {http://id.nii.ac.jp/1001/00208548/ 

https://mocha.t.u-tokyo.ac.jp/},

isbn = {2188-8698},

year  = {2020},

date = {2020-12-01},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2020-UBI-68},

number = {8},

pages = {1--7},

publisher = {情報処理学会},

abstract = {現在，我々は大学キャンパスでの COVID-19 感染対策，そして，ポストコロナ時代における望ましい位置情報インフラの構築を目指している．ユーザーのプライバシーに配慮し，講義で活用する教室や図書館等の 181 のスペースに 200 の Bluetooth ビーコンを設置した．ビーコンが発する ID をスマートフォンで検知し，ユーザの部屋への入退室を判定する．ユーザの位置情報はサーバーサイドに集約された後，ユーザの同意に基づいたルールで，ニーズに応じた位置情報の開示が可能になっている．設置したビーコンをもとにキャンパス内で位置情報の取得予備実験を行ったところ，室内を隔てる壁の材質によっては電波の減衰率が大きく異なることや，大学の施設管理データベースの登録情報が実態を反映していないことなどが明るみになった．本稿では，MOCHA と名付けた本システムの設計と実装，システムアーキテクチャや利用規約を制定する際のポイントについて共有する． 

We are currently working to build the desirable location infrastructure on university campus to combat COVID-19 and also in the post-corona era. In consideration of the user privacy, we have installed 200 Bluetooth beacons in 181 spaces, including the libraries and the classrooms used for the lectures. The IDs emitted by the beacons are detected by a smartphone to determine the user's entering and exiting the room. After the user's location information is collected on the server side, rules based on the user's consent enable the location information to be disclosed according to their needs. A preliminary experiment of the location information acquisition in the campus using the beacons revealed that the attenuation rate of radio waves differs greatly depending on the material of the wall, and the information registered in the facility management database of the university does not reflect the reality. In this paper, we share the design and implementation of our system, named MOCHA, and the key points for establishing the system architecture and terms of use.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{higuma2020_ubi66,

title = {GPS 信号受信状態を用いた紫外線量推定手法の検討},

author = {日隈壮一郎 and 西山勇毅 and 瀬崎薫},

url = {http://id.nii.ac.jp/1001/00204523/},

issn = {2188-8698},

year  = {2020},

date = {2020-05-18},

booktitle = {研究報告ユビキタスコンピューティングシステム (UBI)},

journal = {研究報告ユビキタスコンピューティングシステム (UBI)},

volume = {2020-UBI-66},

number = {5},

pages = {1--7},

publisher = {情報処理学会},

abstract = {近年の都市構造の変容と急激なライフスタイルの変化に伴い，人間が屋内で過ごす時間は長時間化し，逆に屋外で直射日光を浴びる時間は年々短くなっている．過度な紫外線の被曝は皮膚癌やシワ，シミの発生可能性を高めるが，一方で適度な紫外線被曝は体内でのビタミン D の生成に必要不可欠である．また，基本的に野菜に含まれていないビタミン D の不足は，カルシウム不足や低カルシウム血症，骨の軟化やうつ病などに繋がる危険性があり，長期的な健康管理において，紫外線被曝量の管理は重要である．しかしながら，紫外線センサを常に携帯することはユーザの負担が大きく，長期的な利用には日常的に計測または推定可能な手法が必要である．そこで本研究では，スマートフォンに搭載された GPS モジュールを用いて，GPS 信号の受信状態から紫外線量を推定する手法の検討を行う．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Nishiyama2020_LOIS,

title = {In-the-Wild実験におけるiOS用モバイルセンシングフレームワークの性能評価},

author = {西山勇毅 and 佐々木航 and 栄元優作 and 本木悠介 and 大越匡 and 中澤仁 and 瀬崎薫},

url = {https://www.ieice.org/ken/index/ieice-techrep-119-477.html},

issn = {0913-5685},

year  = {2020},

date = {2020-03-11},

urldate = {2020-03-11},

booktitle = {電子情報通信学会技術研究報告: 信学技報},

volume = {119},

number = {477},

pages = {127-132},

publisher = {電子情報通信学会},

address = {大濱信泉記念館（石垣島）},

organization = {ライフインテリジェンスとオフィス情報システム(LOIS)},

abstract = {ユーザの携帯端末より収集したセンサデータを用いて，人や集団・空間の状態を理解するモバイルセンシングは，情報科学だけでなく社会科学や公衆衛生など様々な分野で利用されている．モバイルセンシングを容易に実現するツールは多数提案されており，それらは研究室内実験など「コントール環境」での性能評価は行われている．しかし，実際の被験者にシステムを配布し実験を行う「In-the-Wild環境」における性能評価は行われていない．特にAndroidに比べiOSは制約が多く，制約を無視した設定はデータ収集率の低下を招くため，適切な設定を明らかにする必要がある． 

そこで本研究では，iOS用モバイルセンシングフレームワーク（it AWARE-iOS）を用いて，1週間のIn-the-Wild環境実験を10人の被験者を対象に行い，その際のit AWARE-iOSのデータ収集性能及びバッテリ消費を評価した．その結果，最も収集率が高い可能性のある設定（ESM＋SPN）では，ユーザがit AWARE-iOSを強制終了しない限り95%以上のデータを収集可能であり，平均11.39時間の起動が可能であることが明らかになった．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-030-50344-4_17,

title = {iOS Crowd-Sensing Won't Hurt a Bit!: AWARE Framework and Sustainable Study Guideline for iOS Platform},

author = {Yuuki Nishiyama and Denzil Ferreira and Yusaku Eigen and Wataru Sasaki and Tadashi Okoshi and Jin Nakazawa and Anind K Dey and Kaoru Sezaki},

editor = {Norbert Streitz and Shiníchi Konomi},

url = {https://www.yuukinishiyama.com/2020/07/25/hcii2020/

https://www.yuukinishiyama.com/wp-content/uploads/2020/07/AWARE-iOS_HCII2020_preprint.pdf

https://github.com/tetujin/AWAREFramework-iOS},

doi = {10.1007/978-3-030-50344-4_17},

isbn = {978-3-030-50344-4},

year  = {2020},

date = {2020-07-10},

urldate = {2020-07-10},

booktitle = {Distributed, Ambient and Pervasive Interactions},

volume = {12203},

pages = {223--243},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {The latest smartphones have advanced sensors that allow us to recognize human and environmental contexts. They operate primarily on Android and iOS, and can be used as sensing platforms for research in various fields owing to their ubiquity in society. Mobile sensing frameworks help to manage these sensors easily. However, Android and iOS are constructed following different policies, requiring developers and researchers to consider framework differences during research planning, application development, and data collection phases to ensure sustainable data collection. In particular, iOS imposes strict regulations on background data collection and application distribution. In this study, we design, implement, and evaluate a mobile sensing framework for iOS, namely AWARE-iOS, which is an iOS version of the AWARE Framework. Our performance evaluations and case studies measured over a duration of 288 h on four types of devices, show the risks of continuous data collection in the background and explore optimal practical sensor settings for improved data collection. Based on these results, we develop guidelines for sustainable data collection on iOS.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Chenwei2020_LOIS,

title = {Mobile Sensing of Pedestrian Mobility and its Assessment},

author = {Chenwei Song and Masaki Ito and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://www.ieice.org/ken/paper/20200312h1vo/eng/},

isbn = {0913-5685},

year  = {2020},

date = {2020-03-04},

booktitle = {IEICE Tech. Rep.},

volume = {119},

number = {477},

pages = {121--126},

publisher = {IEICE Technical Committee},

organization = {Life Intelligence and Office Information Systems (LOIS)},

abstract = {We propose a client-server system that provides crowd detection and mobility information. Our proposed system has the advantages of low cost and location flexibility without pre-deployed, as long as there is a sufficient number of users involved. We conducted several experiments in real environments to determine the feasibility, accuracy and applicable environment of the system. The result shows that the system can effectively capture the flow of people in the experimental area. In some cases, under the same environment, it can obtain almost the same mobility tracking information from fewer participating users than the GPS method.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ushijima2020_its,

title = {Non-Negative Tensor Factrization を用いたドックレス型マイクロモビリティの利用形態分類手法の検討},

author = {牛島秀暢 and 青木俊介 and 西山勇毅 and 瀬崎薫},

url = {http://id.nii.ac.jp/1001/00204626/

https://www.mcl.iis.u-tokyo.ac.jp/wp-content/uploads/2020/08/ITS81.pdf},

issn = {2188-8965},

year  = {2020},

date = {2020-05-21},

booktitle = {研究報告高度交通システムとスマートコミュニティ（ITS）},

journal = {研究報告モバイルコンピューティングとパーベイシブシステム (MBL)},

volume = {2020-ITS-81},

number = {1},

pages = {1--8},

publisher = {情報処理学会},

abstract = {交通やインフラ，スマートフォンなどから得られる様々なデータを統合的に利活用し，都市計画の継続的な改善に役立てるという都市コンピューティングが注目されている．都市コンピューティングは少子高齢化と過疎化が進行する日本においても公共インフラを有効活用し都市を維持するためにも有効である．限られた公共インフラを活用するためには人々の移動目的を推定し，交通リソースを最適化する必要があるが，既存の IC カードなどの交通データでは推定粒度に限界があった．こうした状況の中，特定の返却場所を持たないドックレス型のマイクロモビリティが急速に普及している．ドックレス型マイクロモビリティは平均移動距離が 500m 程度と短く，直接目的地に向かうため，より詳細な移動行動が検出可能である．本研究では，マイクロモビリティが都市空間で離散的に分布する点に着目した．そして，細かく単発的な移動行動を大域的に分析することで潜在的な移動パターンがあることを，Non-Negative Tensor Factrization と呼ばれる教師なし学習を用いることで明らかにした．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sensys2020_selfguard,

title = {SelfGuard: Semi-Automated Activity Tracking for Enhancing Self-Protection against the COVID-19 Pandemic},

author = {Yuuki Nishiyama and Takuro Yonezawa and Kaoru Sezaki},

url = {http://sensys.acm.org/2020/

https://youtu.be/KYmvCHl_U7g},

doi = {10.1145/3384419.3430592},

isbn = {9781450375900},

year  = {2020},

date = {2020-11-16},

urldate = {2020-11-16},

booktitle = {Proceedings of the 18th Conference on Embedded Networked Sensor Systems, Virtual Event, Japan},

number = {2},

pages = {780–781},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

series = {SenSys '20},

abstract = {Contagious diseases like COVID-19 spread periodically and threaten our lives. Self-protection, such as washing hands, wearing a mask, and staying home, are simple and practical solutions to safeguard against these diseases. Most governments and health departments recommend that people maintain self-protection. Although continuous self-protection effectively prevents the spread of infection, only the intent to self-protect is unsustainable in the long term. In this study, we design, develop, and deploy an application to track users' daily activities semi-automatically and enhance self-protection behavior using mobile sensing and gamified feedback techniques. Currently, more than 324 people have installed the app via AppStore, and 52 users have shared their activity data to our research group.},

key = {self-tracking, mobile sensing, GPS, COVID-19},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3410530.3414434,

title = {Towards Estimating UV Light Intensity Using GPS Signal Strength},

author = {Soichiro Higuma and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://doi.org/10.1145/3410530.3414434},

doi = {10.1145/3410530.3414434},

isbn = {9781450380768},

year  = {2020},

date = {2020-09-13},

urldate = {2020-09-13},

booktitle = {Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers},

pages = {684–687},

publisher = {Association for Computing Machinery},

address = {Virtual Event, Mexico},

series = {UbiComp-ISWC '20},

abstract = {Due to recent urbanization and changing lifestyles, many people have been spending more time indoors. Hence, they tend to receive less direct sunlight than ever before. Although excessive/inadequate UV exposure can be harmful to human health leading to illnesses such as skin cancer, spots, or depression, moderate UV exposure is necessary for vitamin D production in the body. Therefore, estimating UV exposure with a commonly used device is useful for maintaining a healthy lifestyle from excessive/inadequate UV exposure in our daily life. In this study, we aim to estimate UV exposure, and to this end, we used the GPS signal strength (C/No) collected from an off-the-shelf smartphone for exploring the relationship between UV values and C/No. We conducted an experiment and measured UV values and C/No from 10 places in two different situations. From the results, we observed a significant correlation (R2 more than 0.87) between UV values and C/No when all the data were divided by the sun/shade condition. This result supports the fact that UV values potentially can be inferred from C/No to some degree if the sun/shade condition can be detected.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3410530.3414369,

title = {Using IOS for Inconspicuous Data Collection: A Real-World Assessment},

author = {Yuuki Nishiyama and Denzil Ferreira and Wataru Sasaki and Tadashi Okoshi and Jin Nakazawa and Anind K Dey and Kaoru Sezaki},

url = {https://doi.org/10.1145/3410530.3414369

https://www.yuukinishiyama.com/wp-content/uploads/2020/09/AWARE_HASCA2020_UbiComp2020.pdf},

doi = {10.1145/3410530.3414369},

isbn = {9781450380768},

year  = {2020},

date = {2020-09-12},

urldate = {2020-09-12},

booktitle = {Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers},

pages = {261–266},

publisher = {Association for Computing Machinery},

address = {Virtual Event, Mexico},

series = {UbiComp-ISWC '20},

abstract = {Mobile Crowd Sensing (MCS) is a method for collecting multiple sensor data from distributed mobile devices for understanding social and behavioral phenomena. The method requires collecting the sensor data 24/7, ideally inconspicuously to minimize bias. Although several MCS tools for collecting the sensor data from an off-the-shelf smartphone are proposed and evaluated under controlled conditions as a benchmark, the performance in a practical sensing study condition is scarce, especially on iOS. In this paper, we assess the data collection quality of AWARE iOS, installed on off-the-shelf iOS smartphones with 9 participants for a week. Our analysis shows that more than 97% of sensor data, provided by hardware sensors (i.e., accelerometer, location, and pedometer sensor), is successfully collected in real-world conditions, unless a user explicitly quits our data collection application.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{kamimura2020_2020Soc,

title = {スマートフォンセンサを用いた気分情報を基にした都市空間評価手法に向けて},

author = {神村潤 and 西山勇毅 and 瀬崎薫},

url = {http://www.ieice-taikai.jp/2020society/jpn/},

year  = {2020},

date = {2020-03-17},

booktitle = {電子情報通信学会 電子情報通信学会総合大会},

address = {広島大学東広島キャンパス},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eigen2020_ubi65,

title = {モバイルコンピューティングによるエモーショナル・イーティングの検知},

author = {栄元優作 and 佐々木航 and 西山勇毅 and 大越匡 and 中澤仁},

url = {http://id.nii.ac.jp/1001/00203697/},

issn = {2188-8698},

year  = {2020},

date = {2020-01-01},

booktitle = {研究報告ユビキタスコンピューティングシステム (UBI)},

volume = {2020},

number = {39},

pages = {1--8},

publisher = {情報処理学会},

abstract = {ストレスや感情の変化に左右された食行動はエモーショナル・イーティングと呼ばれる．エモーショナル・イーティングが発生する原因として，ストレスや生活習慣の乱れによる自律神経やホルモンバランスの乱れがあげられる．したがって，自律神経の活性度やホルモン分泌量を継続して観察・分析することで，エモーショナル・イーティングの発生を予期することが可能である．しかし，それらの計測には特殊な生体センサが必要であり，また長時間の使用は負担が大きい．本研究では，ユーザが日常的に利用しており，かつ利用者の行動パターンの特徴が表れるスマートフォンのセンサ情報と機械学習を組み合わせることで，エモーショナルイーティングの検知に取り組む．そして，スマートフォンのセンサデータと食生活データを収集する SEED システムを構築し，収集データからエモーショナル・イーティングを検知する機械学習モデルを作成した．本システムを用いて 60 人の被験者から 28 日間のデータを収集したところ，87.5% の精度でエモーショナル・イーティングを検知することに成功した．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mbl_co2,

title = {環境センサを用いたタクシー車室内における感染症リスク評価に関する一検討},

author = {牛島秀暢 and 西山勇毅 and 小野翔多 and 瀬崎薫},

url = {http://id.nii.ac.jp/1001/00207760/

https://mbl.ipsj.or.jp/excellent/2020/

https://www.yuukinishiyama.com/wp-content/uploads/2021/12/IPSJ-MBL20097010.pdf},

issn = {2188-8817},

year  = {2020},

date = {2020-11-17},

urldate = {2020-11-17},

booktitle = {研究報告モバイルコンピューティングと新社会システム研究会（MBL）},

volume = {2020-MBL-97},

number = {10},

pages = {1--6},

publisher = {情報処理学会},

address = {オンライン},

abstract = {COVID-19の感染拡大により，公共空間や飲食業などの対面サービスにおいて，持続的かつ安全で低コストな感染症への対策が求められている．これまでは，密閉，密集，密接の三密と呼ばれる状態が感染リスクがあるとされ，換気の徹底などが推奨されてきたが，その効果を定量的に計測する事は極めて困難である．本研究では，タクシーという密閉空間の状態を複数の環境センサを用いて計測し，感染症リスクを定量的に分析する．},

keywords = {},

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 = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3338286.3340133,

title = {Challenges of Parkinson’s Disease: User Experiences with STOP},

author = {Elina Kuosmanen and Valerii Kan and Julio Vega and Aku Visuri and Yuuki Nishiyama and Anind K Dey and Simon Harper and Denzil Ferreira},

url = {https://doi.org/10.1145/3338286.3340133},

doi = {10.1145/3338286.3340133},

isbn = {9781450368254},

year  = {2019},

date = {2019-01-01},

booktitle = {Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services},

publisher = {Association for Computing Machinery},

address = {Taipei, Taiwan},

series = {MobileHCI ’19},

abstract = {Parkinson's disease (PD) is the second most common neurodegenerative disorder, impacting an estimated seven to ten million people worldwide. Measuring the symptoms and progress of the disease, and medication effectiveness is currently performed using subjective measures and visual estimation. We developed and evaluated a mobile application, STOP for tracking hand's motor symptoms, and a medication journal for recording medication intake. We followed 13 PD patients from two countries for a 1-month long real-world deployment. We found that PD patients are willing to use digital tools, such as STOP, to track their medication intake and symptoms, and are also willing to share such data with their caregivers and medical personnel to improve their own care.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3356995.3364541,

title = {Using Mobile Sensing Technology for Capturing People Mobility Information},

author = {Chenwei Song and Masaki Ito and Yuuki Nishiyama and Kaoru Sezaki},

url = {https://doi.org/10.1145/3356995.3364541},

doi = {10.1145/3356995.3364541},

isbn = {9781450369640},

year  = {2019},

date = {2019-01-01},

booktitle = {Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Prediction of Human Mobility},

pages = {33–40},

publisher = {Association for Computing Machinery},

address = {Chicago, IL, USA},

series = {PredictGIS’19},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{tadashi2019_ubi,

title = {人の限定合理性を超越した行動変容支援に向けた情報プラッ トフォームの設計},

author = {大越匡 and 西山勇毅 and 佐々木航 and 栄元優作 and 中澤仁},

url = {http://id.nii.ac.jp/1001/00200838/},

issn = {2188-8698},

year  = {2019},

date = {2019-12-03},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2019-UBI-64},

number = {8},

pages = {1--6},

publisher = {情報処理学会},

series = {UBI64},

abstract = {ユビキタスコンピューティングシステムとして，例えば睡眠，食事，運動，学びといった人の多くの行動における行動変容を支援するための研究が数多くなされてきた一方，現状の取り組みは，人間が合理的であろうとするが種々の能力の限界によって限られた合理性しかもてない「限定合理性」(bounded rationality）を超えて人間を支援できていない．本研究では，この限定合理性を超越する情報技術の実現を目指し，その概念を整理し，解決手法における方針と情報アーキテクチャへの要件を明らかにする．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{isokawa2018,

title = {Fish Species Annotation System for Environmental Detection by Marine Life as a Sensor},

author = {Naohiro Isokawa and Wataru Sasaki and Yuuki Nishiyama and Tadashi Okoshi and Jin Nakazawa},

url = {http://hcioutdoors.net/wp-content/uploads/2018/03/Isokawa-fish-species-annotation.pdf},

year  = {2018},

date = {2018-04-21},

booktitle = { HCI Outdoors: A CHI 2018 Workshop on Understanding Human-Computer Interaction in the Outdoor, Canada, Montreal},

abstract = {The ocean was born on the earth 4.6 billion years ago. Life

was born in the ocean, further evolved creatures created

oxygen in the ocean, and that oxygen also changed the atmospheric composition of the Earth. From ancient times life

has received many benefits from the ocean. Even in recent

years, fluctuations in the marine environment are drawing

attention as one of the major environmental problems. Because there is a possibility that it will have a big influence

on human society and ecosystem. Therefore, in the field

of oceanography, research to detect and predict changes

in the marine environment in various ways is actively conducted. We aim to detect changes in the marine environment from the behavior of marine organisms (mainly fish).

In this paper, we implemented a system for annotation of

fish species which is an important module for our research.

This system aims to collect accurate data on fish species by

targeting professional oceanographers. For motivation for

annotation work, the system provides analytical results and

generation models as rewards for work. We also conducted

a questionnaire survey of 14 professors, researchers, and

students specializing in oceanography for annotation system.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3267305.3267584,

title = {Meal Photo SNS with Mutual Healthiness Evaluation for Improving Users’ Eating Habits},

author = {Yusaku Eigen and Yuuki Nishiyama and Takuro Yonezawa and Tadashi Okoshi and Jin Nakazawa},

url = {https://doi.org/10.1145/3267305.3267584},

doi = {10.1145/3267305.3267584},

isbn = {9781450359665},

year  = {2018},

date = {2018-01-01},

booktitle = {Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers},

pages = {339–342},

publisher = {Association for Computing Machinery},

address = {Singapore, Singapore},

series = {UbiComp ’18},

abstract = {We propose a Meal Photo SNS (called HealthyStadium) for improving users' eating habits by mutually assessing each others' health. This application's method is to evaluates pictures of meals leads to the realization of sustainable journaling. In addition, we implement competitive awareness that motivates the users to improve their eating habits by allowing users to share their healthiness ranking amongst the users. Through our study, we confirmed that our system enables users to motivate for improving eating habits. Also we found the number of records is increased by our system.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3282894.3289737,

title = {Mobile-Based Monitoring of Parkinson’s Disease},

author = {Elina Kuosmanen and Valerii Kan and Aku Visuri and Julio Vega and Yuuki Nishiyama and Anind K Dey and Simon Harper and Denzil Ferreira},

url = {https://doi.org/10.1145/3282894.3289737},

doi = {10.1145/3282894.3289737},

isbn = {9781450365949},

year  = {2018},

date = {2018-01-01},

booktitle = {Proceedings of the 17th International Conference on Mobile and Ubiquitous Multimedia},

pages = {441–448},

publisher = {Association for Computing Machinery},

address = {Cairo, Egypt},

series = {MUM 2018},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3236112.3236154,

title = {Senbay: A Platform for Instantly Capturing, Integrating, and Restreaming of Synchronized Multiple Sensor-Data Stream},

author = {Yuuki Nishiyama and Anind K Dey and Denzil Ferreira and Takuro Yonezawa and Jin Nakazawa},

url = {https://github.com/tetujin/SenbayKit

http://www.senbay.info/

https://youtu.be/lfUzxinGl24

https://www.yuukinishiyama.com/wp-content/uploads/2020/08/Senbay-MobileHCI2018-demo_preprint.pdf},

doi = {10.1145/3236112.3236154},

isbn = {9781450359412},

year  = {2018},

date = {2018-01-01},

booktitle = {Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct},

pages = {291},

publisher = {Association for Computing Machinery},

address = {Barcelona, Spain},

series = {MobileHCI ’18},

abstract = {The spread of smartphones allows us to freely capture video and diverse hardware sensors' data (e.g., accel erometer, gyroscope). While recording such data is relatively simple, it is often challenging to share and restream this data to other people and applications. Such capability is very valuable for a range of applications such as a context-aware prototyping/developing platform, an integrated data recording and analysis tool, and a sensor-data based video editing system. To enable such complex operations, we propose Senbay, a platform for instant sensing, integrating, and restreaming multiple-sensor data streams. The platform embeds collected sensor data into a video frame using an animated two-dimensional barcode via real-time video processing. The video-embedded sensor data, dubbed Senbay Video, can be easily restreamed to other people and reused by data rich, context-aware applications.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{weko_183088_1,

title = {HealthFight: 多数決を用いた食習慣改善ソーシャルメディア},

author = {栄元優作 and 江頭和輝 and 河野慎 and 西山勇毅 and 大越匡 and 米澤拓郎 and 高汐一紀 and 中澤仁},

url = {http://id.nii.ac.jp/1001/00183000/},

doi = {2188-8698},

year  = {2017},

date = {2017-01-01},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2017-UBI-55},

number = {16},

pages = {1--7},

publisher = {情報処理学会},

institution = {慶應義塾大学環境情報学部, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学環境情報学部, 慶應義塾大学環境情報学部},

abstract = {近年，食習慣の悪化による肥満が社会問題となり，継続的な食習慣の改善手法が求められている．継続して日々の習慣を変えるには動機の維持向上が重要であり，ユーザの同期を持続させる手法として，ゲームのメカニズムを用いたゲーミフィケーション手法が提案されている．ゲーミフィケーション手法の 1 つである 「競争手法」 は，歩数などのユーザの行動量を可視化し，他者との優劣を意識させることで，動機の維持向上を促す．しかし食事分野では，食事指標として知られるカロリー値の正確な算出が難しく，計算には労力がかかるため，競争の適用が困難である．本研究では本問題を解決するために，ユーザ間で食事の健康度合いを競わせるシステム 「HealthFight」 を構築し有効性を評価する．本システムは食事画像を共有するソーシャルメディアであり，投稿した食事画像の 「ヘルシーさ」 をユーザ間で競わせる．競争相手は食事ごとに更新されるため，ユーザは食事ごとに違った楽しさを感じられ，継続した利用が見込める．本システムによる食習慣の変化を評価するため，7 人の被験者に対して 20 日間の実験を行った．その結果，他者の評価を気にしやすい被験者の食生活は，健康的になる傾向が見られた．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{weko_178211_1,

title = {Likeyboard: ライフログデータ共有簡易化のためのスマートフォンキーボードインタフェース},

author = {石川伶 and 佐々木航 and 西山勇毅 and 大越匡 and 米澤拓郎 and 中澤仁 and 高汐一紀 and 徳田英幸},

url = {http://id.nii.ac.jp/1001/00178123/},

isbn = {2188-8698},

year  = {2017},

date = {2017-03-02},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {	2017-UBI-53},

number = {12},

pages = {1--6},

publisher = {情報処理学会},

institution = {慶應義塾大学環境情報学部, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学環境情報学部, 慶應義塾大学環境情報学部, 慶應義塾大学環境情報学部, 慶應義塾大学環境情報学部, 慶應義塾大学環境情報学部},

abstract = {	近年，食事や睡眠，運動量などを記録するライフログに対する関心が高まってきている．スマートフォンやウェアラブルデバイスなど，様々なライフログデータを検知可能なデバイスの普及し，様々なライフログデータが蓄積されている．しかし，蓄積されたライフログデータは，ライフログアプリケーションやウェブ API を通して個人の活動の振り返りには利用されているが，共有を行うユーザは少ない．ライフログデータの共有は更なるライフログデータ蓄積のモチベーションを向上や，新たなコミュケーションの創出，行動変容の促進にも繋がる．そこで本研究では，ライフログデータ共有の簡易化を目的とした，“Likeyboard” を提案する．“Likeyboard” は，スマートフォンのキーボードインタフェースを用いて 「ライフログデータの選択」 「日時の選択」 「出力形式の選択」 のみで，スマートフォン上でのライフログデータの共有を可能とする．大学生 12 人を被験者として，既存のライフログデータアプリとのインタフェースの比較実験を行った．その結果本システムが既存アプリよりライフログデータの共有が簡易化されたいう評価結果を得た．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3081333.3089324,

title = {Poster: Extensive Evaluation of Emotional Contagion on Smiling Selfies over Social Network},

author = {Wataru Sasaki and Mikio Obuchi and Kazuki Egashira and Naohiro Isokawa and Yuki Furukawa and Yuuki Nishiyama and Tadashi Okoshi and Jin Nakazawa},

url = {https://doi.org/10.1145/3081333.3089324},

doi = {10.1145/3081333.3089324},

isbn = {9781450349284},

year  = {2017},

date = {2017-01-01},

booktitle = {Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services},

pages = {180},

publisher = {Association for Computing Machinery},

address = {Niagara Falls, New York, USA},

series = {MobiSys ’17},

abstract = {We propose "SmileWave", the first selfie social networking service to reveal the existence of emotional cognation through smiling selfies on the social network. We conducted multiple rounds of in-the-wild user studies with 86 cumulative total users for total duration of 5 weeks. Throughout the entire study, we confirmed the occurrence of smile-based emotional contagion over social network, not only in the momentary duration but in longer term period.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{40021159040,

title = {SpoTrip : 観光客リピータ化促進のための隠れスポット情報提供システムの評価},

author = {片山晋 and 礒川直大 and 小渕幹夫 and 西山勇毅 and 大越匡 and 米澤拓郎 and 中澤仁 and 高汐一紀 and 徳田英幸},

url = {https://ci.nii.ac.jp/naid/40021159040/},

issn = {0913-5685},

year  = {2017},

date = {2017-03-01},

urldate = {2017-03-01},

booktitle = {電子情報通信学会技術研究報告 = IEICE technical report : 信学技報},

volume = {116},

number = {508},

pages = {157-164},

publisher = {電子情報通信学会},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{weko_178225_1,

title = {TalkingNemoPad : Aquarium Fish Talks Its Mind for Breeding Support through Your iPad},

author = {礒川直大 and 西山勇毅 and 大越匡 and 中澤仁 and 高汐一紀 and 徳田英幸},

url = {http://id.nii.ac.jp/1001/00178137/},

isbn = {2188-8698},

year  = {2017},

date = {2017-03-01},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2017-UBI-53},

number = {26},

pages = {1--8},

publisher = {情報処理学会},

institution = {慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学環境情報学部, 慶應義塾大学環境情報学部, 慶應義塾大学環境情報学部},

abstract = {	ペットとしての生き物を飼育する際には，飼い主がペットの状態を正しく理解できず，ペットの体調管理は難しくなっている．世界中で最も飼育されているペットである観賞魚においては特に飼い主とペットとのコミュニケーションがより困難であるため，犬や猫などと比較してもそのような状況に陥りやすい．そのため，飼い主と観賞魚とのインタラクションを促進し，観賞魚飼育に役立てる研究が行われているが，それらのシステムは特定の水槽においてのみ動作しているため，一般的な飼育者が用いることは難しく，また様々な種類の観賞魚に関するデータを一律に収集することができない．本稿では，広く普及したデバイス上で動作する飼い主と観賞魚のインタラクションシステム “TalkingNemoPad” を提案する．TalkingNemoPad には，ユーザのタブレット上で動作し，観賞魚を飼育する人の多くが導入 ・ 実用可能という特徴がある．また，これにより様々な観賞魚飼育環境から広くデータを収集することが可能となる．本稿では，TalkingNemoPad が一般的な観賞魚飼育環境下でに使用可能であることを示すために，環境の異なる複数の水槽を用い，本システムの適用可能な観賞魚の飼育環境について評価する．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{40020758536,

title = {MyFactor : ライフログを用いたユーザの内面状態に関する因子分析},

author = {小渕幹夫 and 古川侑紀 and 西山勇毅 and 大越匡 and 米澤拓郎 and 高汐一紀 and 中澤仁 and 徳田英幸},

url = {https://ci.nii.ac.jp/naid/40020758536/},

issn = {0913-5685},

year  = {2016},

date = {2016-02-01},

booktitle = {電子情報通信学会技術研究報告},

journal = {電子情報通信学会技術研究報告 = IEICE technical report : 信学技報},

volume = {115},

number = {467},

pages = {39-44},

publisher = {電子情報通信学会},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{40020759069,

title = {MyTime : タイムマネジメントの促進を目的としたアプリケーション使用時間自動記録システムの提案},

author = {小出粋玄 and 西山勇毅 and 大越匡 and 米澤拓郎 and 高汐一紀 and 中澤仁 and 徳田英幸},

url = {https://ci.nii.ac.jp/naid/40020759069/},

issn = {0913-5685},

year  = {2016},

date = {2016-02-01},

booktitle = {電子情報通信学会技術研究報告 = IEICE technical report : 信学技報},

volume = {115},

number = {467},

pages = {177-182},

publisher = {電子情報通信学会},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{weko_160676_1,

title = {NiSleep: ゲーミフィケーションを適用可能な睡眠評価},

author = {江頭和輝 and 古川侑紀 and 西山勇毅 and 大越匡 and 米澤拓郎 and 中澤仁 and 高汐一紀 and 徳田英幸},

url = {http://id.nii.ac.jp/1001/00160642/},

year  = {2016},

date = {2016-05-01},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2016-UBI-50},

number = {2},

pages = {1--6},

publisher = {情報処理学会},

institution = {慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学大学院政策・メディア研究科, 慶應義塾大学環境情報学部, 慶應義塾大学環境情報学部, 慶應義塾大学環境情報学部},

abstract = {人気ゲームでよく使われるゲームデザインの技術を現実の問題解決に用いることをゲーミフィケーションと呼ぶ．しかし睡眠に関しては，必ずしも睡眠時間が長いほど良い睡眠であるとは限らない特徴を持つため，既存のゲーミフィケーションを適用することが難しい．本研究ではゲーミフィケーションを適用可能な睡眠評価方式 「NiSleep」 を提案する．社会的な活動時間帯と生物時計の不一致によって生ずる不調を社会的ジェットラグと呼ぶ．そして，NiSleep 指数は社会的ジェットラグが解消される睡眠であるかを 「睡眠時間」 「睡眠中央時刻」 「睡眠効率」 を 100 点法で評価し，それらから最終的な評価点を算出する．NiSleep 指数を用いた睡眠評価を行う NiSleep アプリケーションを構築し，被験者 10 人に対して 28 日間にわたるユーザ環境上での実証評価実験を行った．睡眠評価指数の精度と使用者の睡眠行動の変化について検証した．その結果，提案した睡眠評価指数は社会的ジェットラグの特徴を再現 (r=-.440) した．},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{7460714,

title = {Poster Abstract: SmileWave - Sensing and Analysis of Smile-Based Emotional Contagion over Social Network},

author = {Wataru Sasaki and Yuki Furukawa and Yuuki Nishiyama and Tadashi Okoshi and Jin Nakazawa and Hideyuki Tokuda},

doi = {10.1109/IPSN.2016.7460714},

isbn = {978-1-5090-0802-5},

year  = {2016},

date = {2016-04-28},

booktitle = {2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)},

pages = {1-2},

publisher = {IEEE},

address = {Vienna, Austria},

abstract = {This paper proposes ''SmileWave", a system for revealing smile-based emotional contagion, propagation effect of the similar emotion through smiley facial expression, on the social network where users interact each other through web-based user interface rather than in-person interaction. SmileWave is a picture-based networking service and detects the change of smile degree when the user looks at posted smile images of others. Our extensive user study with 50 participants for 30 days confirmed the emotional contagion effect on SmileWave. Users' smile degree improved by 27% when the user looked at posted smile images. The result also proved that there is a stronger effect on smile-based emotional contagion when the examinee and the person in the image are in close relationship.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/2938559.2938603,

title = {Poster: NiSleep: Gamification-Friendly Quantitative Evaluation Methodology of Sleep Quality},

author = {Kazuki Egashira and Yuki Furukawa and Yuuki Nishiyama and Tadashi Okoshi and Jin Nakazawa and Hideyuki Tokuda},

url = {https://doi.org/10.1145/2938559.2938603},

doi = {10.1145/2938559.2938603},

isbn = {9781450344166},

year  = {2016},

date = {2016-01-01},

booktitle = {Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Companion},

pages = {132},

publisher = {Association for Computing Machinery},

address = {Singapore, Singapore},

series = {MobiSys ’16 Companion},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{7061042,

title = {A robot control system for video streaming services by using dynamic encoded QR codes},

author = {Masaki Ogawa and Takuro Yonezawa and Yuuki Nishiyama and Jin Nakazawa and Hideyuki Tokuda},

doi = {10.1109/ICMU.2015.7061042},

isbn = {978-4-9076-2612-9},

year  = {2015},

date = {2015-03-16},

booktitle = {2015 Eighth International Conference on Mobile Computing and Ubiquitous Networking (ICMU)},

pages = {86-87},

publisher = {IEEE},

address = {Hakodate, Japan},

abstract = {We propose a novel robot control system by transmitting robot control information on existing video streaming services as dynamic encoded two-dimentional visual code. We implemented sensor data transmitting system by using dynamic encoded two-dimentional visual code which called SENSe-TREAM [1] and we built the robot controlling system by using SENSeTREAM architecture. This paper shows the architecture of robot controlling system and future vision of telepresence and human-robot interaction.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{aqua_mapping,

title = {Aqua Mapping: 水槽を介した観賞魚とのインタラクションシステム},

author = {礒川直大 and 西山勇毅 and 大越匡 and 米澤拓郎 and 中澤仁 and 高汐一紀 and 徳田英幸},

url = {http://id.nii.ac.jp/1001/00141672/},

isbn = {2188-8698},

year  = {2015},

date = {2015-05-01},

booktitle = {研究報告ユビキタスコンピューティングシステム（UBI）},

volume = {2015-UBI-46},

number = {5},

pages = {1 - 8},

organization = {情報処理学会},

abstract = {魚を飼い，その水槽を鑑賞することは，我々の生活に潤いと落ち着きを与えてくれる．観賞魚を飼育する上で水槽内の環境や魚の体調管理が重要となるが，観賞魚は自分の状態を飼い主に伝えることができないため，飼い主が魚の状態に基づきインタラクティブに飼育することは難しい．本研究では，観賞魚の位置情報をもとに水槽背面のディスプレイに観賞魚の状態を表示することで，飼い主に水槽内の環境や観賞魚の体調などの情報を伝えるシステム “Aqua Mapping” を提案する．本システムにより水槽を介した観賞魚とユーザのインタラクティブな飼育環境を提供する．

	It relaxes us and enriches our daily lives to rear fish and appreciate an aquarium. In that case, the aquarium environment and the physical condition management of the fish become important. However, it's difficult that an owner rears aquarium fish interactively based on the state of the fish because fish can't tell the owner about its state. Thus, this study proposes the “Aqua Mapping” which informs an owner about the condition of an aquarium and fish by indicating fish state on the screen set behind the aquarium using the position information. This system can offer interactive rearing environment between an user and fish through an aquarium.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{40020557350,

title = {Senbay : 活動促進のためのスマートフォンを利用したセンサデータ統合型動画記録・共有・分析プラットフォーム},

author = {西山勇毅 and 米澤拓郎 and 中澤仁 and 徳田英幸},

url = {https://ci.nii.ac.jp/naid/40020557350/},

issn = {0913-5685},

year  = {2015},

date = {2015-07-01},

booktitle = {知的環境とセンサネットワーク研究会(ASN), 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報},

volume = {115},

number = {162},

pages = {49-54},

publisher = {電子情報通信学会},

address = {長野},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/2800835.2800847,

title = {Senbay: Smartphone-Based Activity Capturing and Sharing Using Sensor-Federated Video},

author = {Yuuki Nishiyama and Tadashi Okoshi and Yin Chen and Takuro Yonezawa and Jin Nakazawa and Hideyuki Tokuda},

url = {https://doi.org/10.1145/2800835.2800847},

doi = {10.1145/2800835.2800847},

isbn = {9781450335751},

year  = {2015},

date = {2015-01-01},

booktitle = {Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers},

pages = {21–24},

publisher = {Association for Computing Machinery},

address = {Osaka, Japan},

series = {UbiComp/ISWC’15 Adjunct},

abstract = {We present Senbay, a novel smartphone-based platform for capturing and sharing synchronously-recorded video/sensor data stream using animated two-dimensional barcode. In the ubicomp environment, mobile devices have enabled us to capture video and various types of sensor data easily. However, currently we do not have a framework to instantly integrate video and those sensor data on smartphones and share them easily with other users on the net. In this paper, we present Senbay, a platform to integrate video and sensor data stream into single video on smartphones. With Senbay, sensor data stream will be embedded into a video as animated QR code in real-time, thus users can share the "sensor-federated" video easily on the web, through lots of popular video sharing services. This paper introduces the architecture and evaluation of Senbay and discusses future vision of the sensor-federated video sharing platform along with several applications.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{110009895732,

title = {SmileSpot: 他人の笑顔画像の共有によるユーザの笑顔形成への影響評価},

author = {佐々木航 and 西山勇毅 and 大越匡 and 米澤拓郎 and 中澤仁 and 高汐一紀 and 徳田英幸},

url = {https://ci.nii.ac.jp/naid/110009895732/},

issn = {09196072},

year  = {2015},

date = {2015-05-01},

booktitle = {情報処理学会研究報告. UBI, [ユビキタスコンピューティングシステム]},

volume = {2015-UBI-46},

number = {9},

pages = {1-7},

publisher = {一般社団法人情報処理学会},

abstract = {「人は幸福であるが故に笑うのではなく,笑うが故に幸福である」 という言説にもある通り笑顔を形成することがユーザの幸福感につながると考えられ,これを支持する研究は多い.幸福感は周囲に伝達することが知られている.以上のことから,幸福な人からの笑顔情報によるユーザの笑顔形成への促進が,ユーザの幸福感を引き起こし,それによって幸福感が伝達していくと考えられる.そこで本研究では,他人の笑顔画像の共有によるユーザの笑顔形成への影響を評価する "SmileSpot" を実装した."SmileSpot" は個人のスマートフォン端末のディスプレイに他人の顔画像を映し出し,それを見た際のユーザの笑顔度を検知する.38 人の被験者を対象とした 15 日間の評価実験から他人の笑顔画像がユーザの笑顔形成を促進させることがわかった.それに加え,女性のほうが男性と比べて影響を受けやすく,また親密度が高い人の笑顔画像のほうが親密度の低い人の笑顔画像より影響を受けることがわかった.



As there is a famous statement, "We don't laugh because we're happy, we're happy because we laugh", we are considered that making users smile will make them happy. There are many research that support this idea. And also, "happiness" is known to transfer to surroundings. Therefore we thought that formating users'smile by smile of others who are happy will make users happy, and this process will transfer happiness to surroundings. Now, in this research, we create a system called "SmileSpot" to see the effect of smile which makes users also smile and lead them to happiness. "SmileSpot" works by showing pictures of people smiling on user's smartphone display, and observe how much users will laugh when they using this system. By an experiment which was done by observing 38 research participants over 15 days, result which proved the statement came up. "Others' smile will make users happy" is proved. In addition, we found that women are more susceptible to influence than men, and also smile-image of the community that users belong to is easier to effect the users than the smile-image which was taken from the community that users don't belong or care.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{7001876,

title = {Towards health exercise behavior change for teams using life-logging},

author = {Yuuki Nishiyama and Tadashi Okoshi and Takuro Yonezawa and Jin Nakazawa and Kazunori Takashio and Hideyuki Tokuda},

doi = {10.1109/HealthCom.2014.7001876},

isbn = {978-1-4799-6644-8},

year  = {2014},

date = {2014-10-01},

booktitle = {2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)},

pages = {397-403},

publisher = {IEEE},

address = {Natal, Brazil},

abstract = {Recent technological trends on mobile/wearable devices and sensors have been enabling increasing number of people to collect and store their “life-logs” easily in their daily lives. Beyond exercise behavior change of individual user, our research focus is on the behavior change of teams, based on life-logging technologies and information sharing. In this paper, we propose and evaluate six different types of information sharing model among team members for their exercise promotion, leveraging concepts of “competition” and “collaboration”. According to our experimental mobile web application for exercise promotion and extensive user study among 64 total users for three weeks, the model with “external competition” technique resulted the most effective performance for competitive teams such as sport teams.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{110009676752,

title = {加速度センサのみを用いた移動手段判定アルゴリズムの評価},

author = {古川侑紀 and 西山勇毅 and 大越匡 and 中澤仁 and 高汐一紀 and 徳田英幸},

url = {https://ci.nii.ac.jp/naid/110009676752/},

issn = {09196072},

year  = {2014},

date = {2014-03-01},

booktitle = {情報処理学会研究報告. MBL, [モバイルコンピューティングとユビキタス通信研究会研究報告]},

volume = {2014},

number = {43},

pages = {1-7},

publisher = {一般社団法人情報処理学会},

abstract = {近年のスマートフォンの普及により,様々なセンサを利用できるようになった.それに伴い,日常的な行動を記録する研究が盛んになっている.移動手段の判定もその一部である.既存の研究では加速度センサやマイク,GPS など複数のセンサを用いて移動手段を判定しているため,電池の消耗が激しくスマートフォンのみを用いて判定することは実用的ではない.本研究では加速度センサを用いて移動手段の判定を行うシステムの提案を行い,本システムに様々な機械学習の手法を適用することによって分類精度の評価を行う.また,本システムの省電力性を評価する.



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 transport 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 in this paper the system to detect transport adopting acceleration sensor and evaluated the detection accuracy by applying various kinds of method of machine learning. Moreover, I evaluated power saving of this system.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{2D-code-2014,

title = {動画二次元コードを用いたウェアラブルセンシングのための情報記録・配信手法},

author = {米澤拓郎 and 西山勇毅 and 小川正幹 and 中澤仁 and 徳田英幸},

url = {http://ahi-soc.info/pdf/19thAHI_proceedings.pdf},

year  = {2014},

date = {2014-12-01},

booktitle = {第19回人間情報学会},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{110009579737,

title = {チームの動機づけにおける個人の貢献度の可視化に関する一検討},

author = {西山勇毅 and 米澤拓郎 and 中澤仁 and 徳田英幸},

url = {https://ci.nii.ac.jp/naid/110009579737/},

issn = {09196072},

year  = {2013},

date = {2013-05-01},

booktitle = {情報処理学会研究報告. UBI, [ユビキタスコンピューティングシステム]},

volume = {2013-UBI-38},

number = {21},

pages = {1-8},

publisher = {一般社団法人情報処理学会},

abstract = {近年,個人の動機付けや行動改善のためのアプリケーションが普及してきた.今後,研究プロジェクトチームやスポーツチームなどの明確な目標を持ち,様々な立場の人間が所属するチームでの利用が考えられる.本研究では,個人の貢献度の可視化がチームの動機づけに与える影響の調査を行った.情報共有アプリケーションを実装し,ランダムに抽出したチームに対して,他人に個人の貢献度を見せた場合と見せない場合での比較実験を行い評価した.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{dalt_pervasive2012,

title = {DALT: Detection Algorithm of Throwing Form Changing to Prevent the Baseball Player ’s Throwing Related Injuries},

author = {Yuuki Nishiyama and Tomotaka Ito and Takuro Yonezawa and Jin Nakazawa and Kazunori Takashio and Hideyuki Tokuda},

url = {https://sites.google.com/site/ubihealth2012/workshop_program},

year  = {2012},

date = {2012-06-18},

booktitle = {UbiHealth: 6th International Workshop on Ubiquitous Health and Wellness (Part of Pervasive 2012 conference)},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{110008800304,

title = {野球選手の投球動作変化を用いた疲労度取得手法の提案 : 投球障害予防支援システム構築に向けて},

author = {西山勇毅 and 瀧本拓哉 and 米澤拓郎 and 中澤仁 and 高汐一紀 and 徳田英幸},

url = {https://ci.nii.ac.jp/naid/110008800304/},

issn = {09135685},

year  = {2011},

date = {2011-07-01},

booktitle = {電子情報通信学会技術研究報告. USN, ユビキタス・センサネットワーク : IEICE technical report},

volume = {111},

number = {134},

pages = {119-125},

publisher = {一般社団法人電子情報通信学会},

abstract = {野球では崩れた投球フォームでの投球や過度の練習などにより,投球障害(肩や肘への怪我)が多く発生する.特に野手は自分の練習量を意識せずに練習することが多く,主観による体調管理しか行われていない.既存研究では,スポーツ障害の防止,投球パフォーマンスの向上などを目的として,三次元モーションキャップチャーや動画解析などによる投球動作の分析が行われてきた.しかし,これらの研究は実際の練習での使用を想定していないため,場所の制限や解析の時間的コストなどの問題点がある.本研究では,野球選手の野手を対象に体に装着したウェアラブルなセンサを用いて客観的な投球疲労の取得手法を提案する.



Some baseball players have their shoulder and elbow injuries cause of the disorder of the throwing form and an overwork. Fielders especially practice without knowledge of their bodies and care for it. However it is difficult to recognize their throwing form and number of throws. This research has been supported player's performance by analysis of player's throwing using sanjigen-motion-capcher and douga-bunnseki for all time. But this research has problems with place and time. Because it doesn't assume actual practices. So we are researching for their new supports to improve their form and to take a break by using the radio small acceleration sensor which you can check your throwing form and number of throws easily.



収録刊行物},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}