應用高階模糊派翠網路與智慧型手機於跌倒預測之研究

Fall Risk Prediction System on a Smartphone Using High-Level

陳韋誠(Wei-Cheng Chen)

指導教授 ： 沈榮麟

國立臺北大學/電機資訊學院/資訊工程學系/碩士(2015年)

摘要

日漸衰退的身體使老人的生活中充滿了各種未知的危險，跌倒對老人來說就是一個致命的危機。本文致力於利用智慧型手機上的三軸加速度感測器來開發一款跌倒預測的APP軟體。透過本系統紀錄使用者的步態資料，再將資料換算成穩定度與平衡度，最後利用高階模糊派翠網路分析使用者狀態。並於使用者跌倒前的搖晃狀態時發出警報，使旁人能夠注意並幫忙，以預防跌倒事件的發生。本研究於90次實驗終成功預測62次，預測的準確度為7成。本研究希望透過跌倒預測來提供老人與義肢使用者更高的生活品質，並減少跌倒事件的發生。

關鍵字

高階模糊派翠網路 ； 跌倒預測

並列摘要

Elderly life is full of hazards. The fall is one of the problems for elderly people. In this thesis, we intend to develop a fall risk prediction system on a smartphone which has an accelerometer. First, the system will record the user’s gait data sets and analyze the stability and the symmetry from the data sets. This thesis uses a high-level fuzzy Petri net (HLFPN) to identify human actions including normal action, exercising and fall. In total, there are 90 times of trials, and 62 times of successful prediction done by the system. We intend to decrease the probability to fall down for elderly people and the people who use the prostheses, and provide a safer environment for them.

並列關鍵字

High-Level Fuzzy Petri Net ； Fall Prediction

參考文獻

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