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1 A Smartphone Application for Improving Gait Hirotaka Kashihara, 1 Hiroki Shimizu, 1 Takefumi Miyoshi, 1 Tsutomu Yoshinaga 1 and Hidetsugu Irie 1 Although walking is a daily natural action, it might cause many body issues by bad habits of the action unconsciously. Such issues are preventable by consideration good gait. To help this, an application is implemented, which analyzes gait by acceleration sensors embedded in smart phones. The application alarms when bad gait is detected to make user conscious of own gait Graduate School of Information Systems, The University of Electro-Communications ) 9) 3 2. ( 1 ) ( 2 ) 1 c 2011 Information Processing Society of Japan

2 ( 3 ) 1 3) 2 Nooijen 1) ) 9) ) ) Fujiki 2) 10) 2 7) c 2011 Information Processing Society of Japan

3 情報処理学会研究報告 図2 スマートフォンの装着位置 方法 図 3 スマートフォンを装着した際の各軸の方向 x 軸:進行方向 y 軸:上下方向 z 軸:左右方向 も分析が可能ではないかと考えた よって 4.2 節では スマートフォンに内蔵された加速度 図1 センサで 何をどの程度分析することができるかを検証する スマートフォンの装着位置別の波形 4.2 検 ンピュータで分析しなければならない つまり 健常者が日常で用いるには手間がかかりす 証 スマートフォンを用いて歩行分析を行う際 以下のことを検証する必要がある ぎる そこで我々は 外出時の必需品であるスマートフォンに着目した スマートフォンに ( 1 ) 装着部位 は 3 軸の加速度センサがデフォルトで内蔵されている また比較的高性能な CPU や 結 ( 2 ) 評価する軸 果を表示しやすい大きな画面を有していることから 端末のみで演算 結果の表示が可能で ( 3 ) 評価する項目 ある さらにアプリケーションはインターネット経由で入手可能であるため ユーザーは手 また 本稿での検証 実験には Xperia arc を用いた スペックを表 1 に示す 軽に使いやすい 以上の理由から スマートフォンで歩行分析が可能であれば 健常者が日 1 装着部位 常の歩行を意識させる最適なツールとなりうる 通常 加速度センサは膝や足首に装着することが多い しかしスマートフォンをそれらの 一方でスマートフォンで歩行分析を行おうとする場合 歩行動作を測定するのは 内蔵さ 部位に装着することは実用的ではない 実用的で手軽に用いることができるのは 手で持 れた加速度センサのみであり 複数の部位に加速度センサを装着することは不可能である つ ズボンのポケットに入れる またはケースなどにより腰のベルトに装着する方法である このことから 多くの項目を精密に測定することは不可能であると考えられる しかし 今 手で持った場合は 腕の振りによる影響が大きすぎると判断した そこで ズボンの右前ポ 回は健常者向けの実用的な改善ツールを目指しており バイオメカニクス的研究やリハビリ ケットに入れた場合と 腰の右前方に装着した場合の各軸の時系列データを図 1 に示した テーションを目的としていない よって分析項目を絞り込むことで 単一の加速度センサで ズボンの前ポケットに入れた場合の波形は y z 軸においてパルスに左右差が顕著にあ 3 c 2011 Information Processing Society of Japan

4 y 1 y z Xperia arc OS Android 2.3 RAM 512 MB ROM 1 GB CPU MSM8255 1GHz x y z x 2 y 3) y c 2011 Information Processing Society of Japan

5 6 6 y 7 6 y 3 (a) (b) (c) a 5 6 b 6 a 8 c b b b Xperia arc y 9.8[m/s 2 ] c 2011 Information Processing Society of Japan

6 8 b 9 c 3) 7 6 b 3) y y 9.8[m/s 2 ] y y -1 y c 2011 Information Processing Society of Japan

7 -1 y y =-50 A B 8 2 C 13 5 D 8 4 E =-30 A 9 0 B 5 2 C 10 2 D 5 0 E ) Nienke terhoeve Carla FJNooijen and EdelleC Field-Fote. Gait quality is improved by locomotor training in individuals with sci regardless of training approach. Journal of NeuroEngineering and Rehabilitation, ) IoannisPavlidis YuichiFujiki, PanagiotisTsiamyrtzis. Making sense of accelerometer measurements in pervasive physical activity applications. CHI 2009 Student Research Competition, ).., ).., ).. html. 6),,,.., ),,.. C, ),,,. 3. USN, ).., c 2011 Information Processing Society of Japan

8 10),,.., c 2011 Information Processing Society of Japan

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