基於有限狀態機之智慧型手機跌倒偵測機制

A Fall Detection Mechanism for Smart Phones Based on Finite State Machine

蘇明雄(Ming-Hsiung Su)

指導教授 ： 謝尚琳

大同大學/電機資訊學院/資訊工程學系所/碩士(2012年)

摘要

老人化社會的來臨，年長者的照護相對的越來越重要，快速且正確的跌倒偵測可縮短年長者因跌倒後無法自主行動，而導致延遲送醫的時間，並即時接受治療，降低延遲送醫的二次傷害，因而提升照護的品質。本研究提出一個能快速與正確判定跌倒的偵測機制，利用Android智慧型手機中內建的三軸加速度計，將跌倒前後的三軸變化建構成有限狀態機，並開發成JAVA手機程式。當手機放置於上衣口袋、褲子前口袋與褲子後口袋時，透過本機制能有效準確地偵測出各類跌倒，包括前趴跌倒、後躺跌倒、右側跌倒與左側跌倒，而走路、坐下、蹲下、上樓梯和下樓梯的一般動作本機制則不會誤判為跌倒。本機制跌倒偵測的平均敏感度為97%，平均變異度為100%，證明本機制能有效並準確的偵測跌倒且不會誤判。

關鍵字

三軸加速度計 ； 智慧型手機 ； 有限狀態機 ； 跌倒偵測

並列摘要

With the approaching of an aging society, healthcare for the elderly has gradually gained its importance. Early and accurate detection of the older people’s accidental falls can significantly shorten the time to receive instant and proper treatment. This can also lessen the avoidable harm resulting from the delay of sending the patients to the hospital, and thus improve the quality of healthcare. The study proposes a fall detection mechanism which can quickly and accurately detect falls of any kind. By utilizing the built-in 3 axis-accelerometers in Android-based smartphones, a finite-state machine was constructed from the triaxial variations of pre-falls and post-falls. Such mechanism was later realized by an Android application. When the smartphone running the application is placed in 3 positions, namely pockets of the shirts, and front and back pockets of the pants, the mechanism can effectively detect real falls, including forward, backward, rightward, and leftward falls. On the other hand, non-fall activities such as walking, sitting down, squatting, and going upstairs or downstairs will not be mistakenly recognized as real falls. The average sensitivity of the presented detection mechanism is 97%, and the average specificity is 100%. These results prove the effectiveness of the presented mechanism.

並列關鍵字

smartphones ； finite-state machine ； fall detection

參考文獻

[16]溫瓊容、黎家銘、陳晶瑩，「老人跌倒的評估與預防」，臺灣家庭醫學研究，第4卷第3、4期，第118 -128頁，2006年。

[21]宏達國際電子股份有限公司，2011年9月28日，檢自：http://www.htc.com/tw/。

[3]龔聖祐，「運動訓練、環境改善及教育對跌倒老人生活品質的影響」，臺北醫學大學傷害防治學研究所碩士論文，2005年。

[4]T. Tamura, T. Yoshimura, M. Sekine, M. Uchida, and O. Tanaka, “A Wearable Airbag to Prevent Fall Injuries,” IEEE Transactions on Information Technology in Biomedicine, Vol. 13, Issue 6, pp. 910-914, 2009.

[5]Guangyi Shi, Cheung Shing Chan, Wen Jung Li, Kwok-Sui Leung, Yuexian Zou, and Yufeng Jin, “Mobile Human Airbag System for Fall Protection Using MEMS Sensors and Embedded SVM Classifier,” IEEE Sensors Journal, Vol. 9, No. 5, pp. 495-503, 2009.