基於下肢之使用者狀態判別與預防跌落策略研發

Abstract

近年來，人口老化的問題日益嚴重，照顧銀髮族的生活起居成為一個重要的課題。隨著醫療科技的進步，各式各樣的行動輔具機器人之發展越趨成熟，本實驗室也開發行動輔具i-go以應對銀髮族生活不便的困擾。在本論文中，我們透過分析使用者的下肢角度與重心來判別使用者狀態(坐姿、站立、行走與危險)，並且因應使用者的狀態，提出預防跌落的控制策略，針對坐姿到站立的轉換，應施與煞車力，令輔具支撐使用者時不會滑動造成危險；對於站姿與行走，藉由下肢角度與使用者軀幹長度計算重心，分析使用者習慣可得一穩定區間，行動輔具系統於使用期間持續更新穩定區間來輔合使用者目前狀態，提供合適的輔助力，讓使用者重心保持於穩定區間內預防跌落。此基於下肢角度之使用者狀態判別與預防跌落策略經實驗驗證，確實有其一定的功效，未來希望能夠幫助正在復健且行走和保持平穩能力較差的銀髮族，提供一個完善且安全的智慧型行動輔具系統。

Recently, the problem of aging population becomes more serious. How to take good care of the elderly is an important issue around the world. Along with the progress of the medical and robot technology, several robot walking helpers have been developed. It motivates us to develop a robot walking helper, named i-go, in our laboratory for assisting the lives of the elderly. In the thesis, we propose estimating the human state by analyzing the angles of the lower limbs and the center of gravity(COG) of human body, and develop the corresponding assistive strategies. From sitting to standing, we should give maximum brake force to make i-go a firm support that can prevent the user from falling. During standing and walking, we calculate the COG of the user by the angles of lower body and length of each limb. We then collect and analyze COG data of stable standing and walking for establishing the stable region. i-Go will continuously renew the stable region to fit the user’s current condition and give proper assistive brake force to keep the user’s COG within the stable region for preventing the user from falling. The proposed fall prevention strategy based on human state has been verified via the experiment. In the near future, we expect i-Go can assist the elderly in real environments.