Publication

@inproceedings{mobisys2022_han,

title = {Poster: Head Dynamics Enabled Riding Maneuver Prediction},

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

url = {https://www.sigmobile.org/mobisys/2022/},

year  = {2022},

date = {2022-06-27},

urldate = {2022-06-27},

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

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 = {Activity Recognition, Mobile sensing, Wearable sensing},

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},

year  = {2022},

date = {2022-06-01},

urldate = {2022-06-01},

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

publisher = {IEEE Computer Society},

address = {Espoo, Finland},

keywords = {Activity Recognition, Childcare Activity, Wearable sensing},

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 = {Activity Recognition, behavior change, Wearable sensing},

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 = {Activity Recognition, context-awareness, Mobile sensing},

pubstate = {published},

tppubtype = {inproceedings}

}