發(fā)布時間：2018-05-31 20:45

  本文選題：腦機接口 + 頻率和相位混合調(diào)制��； 參考：《南昌大學(xué)》2016年碩士論文

【摘要】：腦機接口是一座搭建于大腦和外部環(huán)境之間的橋梁,通過這座橋梁人可以不經(jīng)由外圍神經(jīng)肌肉而直接與外界進行通信。隨著對腦機接口技術(shù)需求人數(shù)的增加,腦神經(jīng)科學(xué)和工程技術(shù)的日漸成熟,越來越多的機構(gòu)和科學(xué)家致力于腦機接口的研究。在各類腦機接口中,基于穩(wěn)態(tài)視覺誘發(fā)電位的腦機接口和基于編碼調(diào)制的視覺誘發(fā)電位腦機接口被研究較多且性能較好,為了進一步提高這兩種腦機接口的性能,本文對穩(wěn)態(tài)視覺誘發(fā)電位腦機接口和編碼調(diào)制腦機接口進行深入的研究和探索。傳統(tǒng)的基于穩(wěn)態(tài)視覺誘發(fā)電位的腦機接口系統(tǒng)采用頻率編碼,每個刺激塊以不同頻率閃爍。由于穩(wěn)態(tài)視覺誘發(fā)電位響應(yīng)頻帶窄且某些受試者存在盲頻,因此呈現(xiàn)的目標數(shù)有限。為了解決這個問題,本文研究了頻率和相位混合調(diào)制的穩(wěn)態(tài)視覺誘發(fā)電位腦機接口,在這種調(diào)制方式下,同一頻率可以以不同相位調(diào)制多個目標,大大提高頻率利用率,增加刺激目標數(shù)。目標識別的方法是對腦電信號做各刺激頻率處的快速傅立葉變換,得到的各刺激頻率處的傅立葉系數(shù)投影至各目標的參考相位,最大投影值所對應(yīng)的目標即為識別目標。時間窗為2s時,受試者的平均目標識別準確率達到89.30%。在編碼調(diào)制腦機接口中,偽隨機碼的調(diào)制性能對識別準確率有很大的影響,為此本文研究了M序列、近完美序列、Golay互補序列三種偽隨機序列的調(diào)制性能,目標識別算法均采用模板匹配法。研究結(jié)果表明,時間窗為一個刺激周期時三種序列的目標識別率分別為89.71%、94.29%、93.20%。從自相關(guān)函數(shù)波形來看,與M序列相比,近完美序列、Golay互補序列的峰值更尖銳且整體旁瓣更低,因而這兩種序列的調(diào)制性能更佳。為了增加刺激目標數(shù)同時兼顧識別率和識別速度,本文提出不同編碼分組調(diào)制方法,并聯(lián)合多導(dǎo)聯(lián)腦電信號進行目標識別。在采用近完美序列和Golay互補序列調(diào)制兩組目標的多導(dǎo)聯(lián)系統(tǒng)中,平均識別率為92.34%。
[Abstract]:Brain-computer interface is a bridge between the brain and the external environment, through which people can communicate directly with the outside world without passing through the peripheral nerve muscles. With the increasing demand for brain-computer interface technology and the maturation of brain neuroscience and engineering technology, more and more institutions and scientists are devoting themselves to the research of brain-computer interface. Among all kinds of brain-computer interfaces, the brain-computer interface based on steady-state visual evoked potential and the brain-computer interface based on coded modulation have been studied more and better. In order to further improve the performance of these two kinds of BCI, In this paper, the steady-state visual evoked potential brain-computer interface and coded modulation brain-computer interface are deeply studied and explored. The traditional brain-computer interface system based on steady-state visual evoked potentials uses frequency coding, and each stimulus block flashes at different frequencies. Due to the narrow response band of steady-state visual evoked potential (VEP) and blind frequency in some subjects, the number of targets presented is limited. In order to solve this problem, the steady-state VVEP brain-computer interface of frequency and phase mixing modulation is studied in this paper. In this modulation mode, multiple targets can be modulated with different phases at the same frequency, and the frequency utilization ratio can be greatly improved. Increase the number of stimulus targets. The method of target recognition is to do the fast Fourier transform at every stimulation frequency of EEG signal, and the Fourier coefficients of each stimulus frequency are projected to the reference phase of each target. The target corresponding to the maximum projection value is the recognition target. When the time window is 2 s, the average target recognition accuracy is 89.30%. The modulation performance of pseudorandom codes has a great influence on the recognition accuracy in the coded modulation brain-computer interface. In this paper, the modulation performance of three pseudorandom sequences, M sequence, near perfect sequence and Golay complementary sequence, is studied in this paper. Template matching is used in all target recognition algorithms. The results show that when the time window is a stimulus cycle, the target recognition rate of the three sequences is 89.71 and 94.290.93.20, respectively. From the waveform of autocorrelation function, compared with M sequence, the near perfect sequence Golay complementary sequence has more sharp peak value and lower global sidelobe, so the modulation performance of these two sequences is better. In order to increase both the recognition rate and the recognition speed, different coded block modulation methods are proposed and multi-lead EEG signals are combined for target recognition. The average recognition rate is 92.34 in the multi-lead system which uses near-perfect sequence and Golay complementary sequence to modulate two groups of targets.
【學(xué)位授予單位】：南昌大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TN911.7;R49

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相關(guān)期刊論文 前2條

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本文編號：1961223