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基于條件經(jīng)驗(yàn)?zāi)J椒纸夂痛⑿蠧NN的腦電信號(hào)識(shí)別

唐賢倫 李偉 馬偉昌 孔德松 馬藝瑋

唐賢倫, 李偉, 馬偉昌, 孔德松, 馬藝瑋. 基于條件經(jīng)驗(yàn)?zāi)J椒纸夂痛⑿蠧NN的腦電信號(hào)識(shí)別[J]. 電子與信息學(xué)報(bào), 2020, 42(4): 1041-1048. doi: 10.11999/JEIT190124
引用本文: 唐賢倫, 李偉, 馬偉昌, 孔德松, 馬藝瑋. 基于條件經(jīng)驗(yàn)?zāi)J椒纸夂痛⑿蠧NN的腦電信號(hào)識(shí)別[J]. 電子與信息學(xué)報(bào), 2020, 42(4): 1041-1048. doi: 10.11999/JEIT190124
Xianlun TANG, Wei LI, Weichang MA, Desong KONG, Yiwei MA. Conditional Empirical Mode Decomposition and Serial Parallel CNN for ElectroEncephaloGram Signal Recognition[J]. Journal of Electronics & Information Technology, 2020, 42(4): 1041-1048. doi: 10.11999/JEIT190124
Citation: Xianlun TANG, Wei LI, Weichang MA, Desong KONG, Yiwei MA. Conditional Empirical Mode Decomposition and Serial Parallel CNN for ElectroEncephaloGram Signal Recognition[J]. Journal of Electronics & Information Technology, 2020, 42(4): 1041-1048. doi: 10.11999/JEIT190124

基于條件經(jīng)驗(yàn)?zāi)J椒纸夂痛⑿蠧NN的腦電信號(hào)識(shí)別

doi: 10.11999/JEIT190124
基金項(xiàng)目: 國(guó)家自然科學(xué)基金(61673079, 61703068),重慶市基礎(chǔ)研究與前沿探索項(xiàng)目(cstc2018jcyjAX0160)
詳細(xì)信息
    作者簡(jiǎn)介:

    唐賢倫:男,1977年生,教授,博士,研究方向?yàn)橹悄芟到y(tǒng)與機(jī)器人,模式識(shí)別理論與應(yīng)用

    李偉:男,1996年生,碩士生,研究方向?yàn)樯疃葘W(xué)習(xí)、腦電信號(hào)識(shí)別

    馬偉昌:男,1995年生,碩士生,研究方向?yàn)闄C(jī)器人控制

    孔德松:男,1993年生,碩士生,研究方向?yàn)樯疃葘W(xué)習(xí)

    馬藝瑋:女,1980年生,副教授,博士,研究方向?yàn)橹悄苄畔⑻幚?/p>

    通訊作者:

    李偉 cqyddxliwei@foxmail.com

  • 中圖分類號(hào): TP391.4

Conditional Empirical Mode Decomposition and Serial Parallel CNN for ElectroEncephaloGram Signal Recognition

Funds: The National Natural Science Foundation of China (61673079, 61703068), The Basic Research and Frontier Exploration Project of Chongqing (cstc2018jcyjAX0160)
  • 摘要:

    針對(duì)運(yùn)動(dòng)想象腦電信號(hào)(EEG)的非線性、非平穩(wěn)特點(diǎn),該文提出一種結(jié)合條件經(jīng)驗(yàn)?zāi)J椒纸?CEMD)和串并行卷積神經(jīng)網(wǎng)絡(luò)(SPCNN)的腦電信號(hào)識(shí)別方法。在CEMD過程中,采用各階固有模式分量(IMF)與原始信號(hào)的相關(guān)性系數(shù)作為第1個(gè)IMF篩選條件,在此基礎(chǔ)上,提出各階IMF之間的相對(duì)能量占有率作為第2個(gè)IMF篩選條件。此外,為了考慮腦電信號(hào)各個(gè)通道之間的特征和突出每個(gè)通道內(nèi)的特征,該文提出SPCNN網(wǎng)絡(luò)模型對(duì)進(jìn)行CEMD過程后的腦電信號(hào)進(jìn)行分類。實(shí)驗(yàn)結(jié)果表明,在自行采集的腦電數(shù)據(jù)集上平均識(shí)別率達(dá)到94.58%。在公開數(shù)據(jù)集BCI competition IV 2b上平均識(shí)別率達(dá)到82.13%,比卷積神經(jīng)網(wǎng)絡(luò)提高了3.85%。最后,在自行設(shè)計(jì)的智能輪椅腦電控制平臺(tái)上進(jìn)行了輪椅前進(jìn)、左轉(zhuǎn)和右轉(zhuǎn)在線控制實(shí)驗(yàn),驗(yàn)證了該文算法對(duì)腦電信號(hào)識(shí)別的有效性。

  • 圖  1  串并行卷積神經(jīng)網(wǎng)絡(luò)結(jié)構(gòu)圖

    圖  2  Emotiv腦電采集儀

    圖  3  Emotiv腦電采集儀電極安放位置

    圖  4  單次腦電信號(hào)采集過程

    圖  5  設(shè)定不同的閾值$\alpha $時(shí)識(shí)別率情況

    圖  6  設(shè)定不同的閾值$\beta $時(shí)識(shí)別率情況

    圖  7  采用不同處理方法的識(shí)別準(zhǔn)確率對(duì)比

    圖  8  智能輪椅系統(tǒng)結(jié)構(gòu)圖

    表  1  不同算法對(duì)5受試者腦電信號(hào)的識(shí)別準(zhǔn)確率(%)

    算法CSPACSPDBNCNNSTFT-CNNSPCNN本文CEMD-SPCNN
    S0165.0077.5087.0886.2588.7590.4293.33
    S0281.6782.9287.5087.9289.1791.2594.17
    S0398.3397.0895.8395.8396.6797.0899.16
    S0476.2578.3383.3385.4285.4286.2589.58
    S0595.4296.2593.7591.6792.5094.1796.67
    均值83.3386.4189.5089.4290.5091.8394.58
    方差190.0191.8826.5118.6118.1816.6213.02
    下載: 導(dǎo)出CSV

    表  2  不同算法對(duì)BCI competition IV 2b數(shù)據(jù)集的識(shí)別準(zhǔn)確率(%)

    算法ChinGanCoyleCSPACSPDBNCNNSTFT-CNNSPCNN本文CEMD-SPCNN
    B0170.0071.0060.0066.5667.5066.5672.2275.0076.3980.56
    B0261.0061.0056.0057.8155.3162.5061.0361.7663.2464.71
    B0361.0057.0056.0061.2562.1960.0061.1162.5062.5064.58
    B0498.0097.0089.0094.0694.6996.8798.6598.6599.3299.32
    B0593.0086.0079.0080.6376.8882.1986.4887.1687.8488.51
    B0681.0081.0075.0075.0075.9477.5079.1780.5681.2583.33
    B0778.0081.0069.0072.5071.2576.5678.4777.0879.1781.25
    B0893.0092.0093.0089.3889.3888.7586.1886.1886.8490.13
    B0987.0089.0073.0085.6381.2585.9481.2582.6484.0386.81
    均值80.2279.4472.2275.8674.9377.4378.2879.0680.0682.13
    方差192.19190.03181.69158.75157.50155.85147.92138.63137.52129.78
    下載: 導(dǎo)出CSV

    表  3  各類操作在線識(shí)別準(zhǔn)確率(%)

    操作直行左轉(zhuǎn)右轉(zhuǎn)
    S01968486
    S02949082
    S03988892
    下載: 導(dǎo)出CSV
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  • 收稿日期:  2019-03-01
  • 修回日期:  2019-11-22
  • 網(wǎng)絡(luò)出版日期:  2019-12-14
  • 刊出日期:  2020-06-04

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