發(fā)布時間：2018-03-25 07:06

  本文選題：多傳感器數(shù)據(jù)融合　切入點：人體步態(tài)分析　出處：《大連理工大學》2016年博士論文

【摘要】：人的步行過程包含著豐富的運動學、動力學和生理學信息,對這些信息進行特征提取和模式分析就可以獲得人體步態(tài)的描述。通過科學的手段測量人的步態(tài)具有重要的現(xiàn)實意義,比如可以用于臨床醫(yī)學中的康復評定、下肢輔具設計和下肢機器人的開發(fā)等。本文提出了基于自行開發(fā)的可穿戴步態(tài)分析系統(tǒng)的步態(tài)分析方法。該系統(tǒng)可以采集下肢運動過程中的速度和方向變化信息。通過多層次的傳感器數(shù)據(jù)融合算法進行姿態(tài)解算,步行時相劃分以及誤差校正,可以精確地計算各項步態(tài)參數(shù)。本文在總結(jié)國內(nèi)外已有研究內(nèi)容的基礎上提出和解決了以下問題：如何減少姿態(tài)解算誤差,增加步態(tài)時相檢測精度；如何全面地評價雙足對稱性、步態(tài)穩(wěn)定性；如何消除傳感器綁定位置誤差以及多個傳感器的對準誤差；以及零速度更新算法的適用性問題。主要研究內(nèi)容如下：1.本研究使用微機電傳感器并結(jié)合人體傳感器網(wǎng)絡研制了可穿戴步態(tài)分析平臺,在傳感器的靈敏度標定,非正交誤差補償以及粗大誤差篩除等方面做了相關(guān)的研究。多數(shù)研究者忽視了傳感器綁定位置對步態(tài)分析的影響,本文提出了一種基于軸線對準(Boresighting)的傳感器初始對準方法,可以很好地消除初始綁定誤差對于參數(shù)估算的影響,也可以用于下肢運動分析的多傳感器初始對準。2.研究了基于擴展卡爾曼數(shù)字濾波器的融合算法減少系統(tǒng)噪聲和傳感器偏差對步態(tài)測量的影響；在站立期使用零速度更新算法校正速度和位置積分誤差；針對傳感器數(shù)據(jù)波動導致的步態(tài)時相誤檢測的問題,使用多閾值方法進行約束,提高步態(tài)時相檢測精度,為精確計算各項步態(tài)參數(shù)奠定基礎。3.目前大多數(shù)的步態(tài)分析研究缺少對于雙足運動協(xié)同性的分析。本文對于放置在雙側(cè)足部的兩個傳感器模塊進行傳感器數(shù)據(jù)融合,研究了人體步行過程中雙足的協(xié)調(diào)與交替運動規(guī)律。并創(chuàng)新性地使用動態(tài)時間規(guī)整(Dynamic time warping)算法融合雙足數(shù)據(jù),對于雙足步態(tài)對稱性、步態(tài)穩(wěn)定性與一致性提供了一種新的評價方法。4.關(guān)于在步態(tài)分析領(lǐng)域廣泛使用的零速度更新算法(ZUPT)的適用性問題,本文提出了一種擴展零速度更新算法(E-ZUPT),將三個傳感器模塊分別放置在單側(cè)下肢的不同部位,使用迪納維特-哈坦伯格法建立下肢運動學模型,建立約束,在檢測到完全站立相之后融合下肢運動信號,通過求解歐拉-拉格朗日方程來解決位置誤差最小化問題,從而使零速度更新算法的適用范圍擴展到足部之外的其他下肢部位。
[Abstract]:The human walking process contains a wealth of kinematics, dynamics, and physiological information. The description of human gait can be obtained by feature extraction and pattern analysis of this information. It is of great practical significance to measure human gait by scientific means, for example, it can be used for rehabilitation evaluation in clinical medicine. The design of lower extremity accessory and the development of lower limb robot, etc. In this paper, a gait analysis method based on self-developed wearable gait analysis system is proposed. The system can collect the information of velocity and direction change during the movement of lower extremity. Through multi-level sensor data fusion algorithm for attitude resolution, Walking phase division and error correction can accurately calculate the gait parameters. In this paper, the following problems are put forward and solved: how to reduce the error of attitude resolution, based on the summarization of existing research contents at home and abroad. How to improve the accuracy of gait phase detection, how to evaluate the biped symmetry and gait stability, how to eliminate the sensor binding position error and the alignment error of multiple sensors; The main contents of this study are as follows: 1.The wearable gait analysis platform is developed by using micro electromechanical sensor and human body sensor network, and the sensitivity of sensor is calibrated. Many researchers have neglected the influence of sensor binding position on gait analysis. In this paper, an initial alignment method based on axis alignment is proposed. The effect of initial binding error on parameter estimation is well eliminated. The fusion algorithm based on extended Kalman filter (EKF) is used to reduce the influence of system noise and sensor deviation on gait measurement. In the standing period, the zero-velocity updating algorithm is used to correct the velocity and position integral error, and to solve the problem of gait phase error detection caused by the fluctuation of sensor data, the multi-threshold method is used to restrain the gait phase detection accuracy, so as to improve the gait phase detection accuracy. In order to calculate the gait parameters accurately. 3. Most of the gait analysis research lacks the analysis of bipedal motion cooperation. In this paper, two sensor modules placed in the bilateral foot are fused to the sensor data. In this paper, we study the law of coordination and alternating motion of two feet during human walking, and creatively use dynamic time warping algorithm to fuse biped data for biped gait symmetry. A new evaluation method for gait stability and consistency is provided. (4) on the applicability of Zero-Velocity updating algorithm (ZUPT), which is widely used in gait analysis, In this paper, an extended zero-velocity updating algorithm, E-ZUPTT, is proposed. The three sensor modules are placed in different parts of the lower extremity on one side, and the kinematics model of the lower extremity is established by using the Dinawitt-Hartenberg method, and the constraints are established. After detecting the fully standing phase, the lower limb motion signal is fused, and the position error minimization problem is solved by solving the Euler-Lagrangian equation, so that the applicable range of the zero velocity updating algorithm is extended to other lower extremity parts outside the foot.
【學位授予單位】：大連理工大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：TP202;TP212
，

本文編號：1662045