【摘要】：表面肌電信號是由人體肌肉活動所引起的一種生理電信號。當人體進行相同的動作時,其相關肌群處的表面肌電信號呈現(xiàn)出一種可重復的固有模式。因此,通過對表面肌電信號進行分析,可以獲得其中蘊含的與肌肉活動相關的特征。本課題是圍繞著構建基于表面肌電信號的實時控制系統(tǒng)這個目的逐步展開的,主要解決了表面肌電信號特征如何提取、控制命令如何獲取以及實時系統(tǒng)如何構建等問題。 首先,對實驗環(huán)境下采集到的表面肌電信號進行分析,利用短時傅立葉變換提取了左右肩膀和左右小腿處肌群的收縮狀態(tài)的特征作為控制命令,同時考慮了慣用手的個體差異以及心電干擾等因素對肌電特征的影響。所提出的基于左右肩膀和左右小腿處肌群的收縮狀態(tài)的控制命令提取方法準確率高,處理速率快,能夠較好地反映肌肉活動的狀態(tài)。 其次,結合實際的實驗條件,構建了一個生物電信號實時處理平臺。該平臺集成了數(shù)據(jù)采集,數(shù)據(jù)分析和控制命令提取等功能模塊,能夠適用于肌電等各類生物電信號的實時分析和控制。 最后,在肌電信號分析方法和實時平臺的研究基礎上,實現(xiàn)了基于表面肌電信號的光標實時控制系統(tǒng)。該系統(tǒng)操作簡單且容易上手,實時性能良好,控制命令轉(zhuǎn)換的準確率高。此外,分析了肌電信號與運動意圖的關聯(lián),對人體上肢肩、肘關節(jié)運動意圖判定開展了研究。通過對表面肌電信號進行分析,實現(xiàn)了人體上肢的實時運動意圖實時提取。能夠為輔助手臂裝置的運動控制提供新的控制模式,有應用價值。
[Abstract]:Surface electromyography (EMG) is a physiological signal caused by human muscle activity. When the human body performs the same action, the surface electromyography of the associated muscle group presents a repeatable and inherent pattern. Therefore, the features associated with muscle activity can be obtained by analyzing surface EMG signals. The purpose of this paper is to construct a real-time control system based on surface electromyography (EMG), which mainly solves the problems of how to extract the features of SEMG, how to obtain the control command and how to construct the real-time system. Firstly, the surface EMG signals collected in the experimental environment are analyzed, and the characteristics of the contraction state of the left and right shoulders and the left and right calves are extracted by using the short time Fourier transform (STFT) as the control command. At the same time, the influence of individual differences and ECG interference on EMG characteristics was considered. The proposed control command extraction method based on the contractile state of the left and right shoulders and the left and right calf muscles has high accuracy and fast processing rate, which can better reflect the state of muscle activity. Secondly, a real-time bioelectric signal processing platform is constructed. The platform integrates function modules such as data acquisition, data analysis and command extraction, and can be used for real-time analysis and control of bioelectric signals such as electromyography. Finally, based on the research of EMG signal analysis method and real-time platform, a real-time cursor control system based on surface EMG signal is implemented. The system is easy to operate and easy to use. It has good real-time performance and high control command conversion accuracy. In addition, the relationship between EMG signal and motion intention is analyzed, and the determination of motion intention of human upper limb, shoulder and elbow joint is studied. By analyzing the surface electromyography (EMG) signal, the real-time motion intention of human upper limb can be extracted in real time. It can provide a new control mode for the motion control of the auxiliary arm device and has application value.
【學位授予單位】：華東理工大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TN911.6;R318.0

【引證文獻】

相關碩士學位論文 前1條

1 王士允;基于表面肌電信號的膝關節(jié)康復機器人控制技術研究[D];南京理工大學;2013年

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本文編號：2291090