Article(id=1227591033182159663, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1227591023870800760, articleNumber=null, orderNo=null, doi=10.16385/j.cnki.issn.1004-4523.202401060, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1705852800000, receivedDateStr=2024-01-22, revisedDate=1710086400000, revisedDateStr=2024-03-11, acceptedDate=null, acceptedDateStr=null, onlineDate=1770610109848, onlineDateStr=2026-02-09, pubDate=1754755200000, pubDateStr=2025-08-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1770610109848, onlineIssueDateStr=2026-02-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1770610109848, creator=13701087609, updateTime=1770610109848, updator=13701087609, issue=Issue{id=1227591023870800760, tenantId=1146029695717560320, journalId=1225147924628267009, year='2025', volume='38', issue='8', pageStart='1645', pageEnd='1934', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1770610107611, creator=13701087609, updateTime=1770610373804, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1227592140348388157, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1227591023870800760, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1227592140348388158, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1227591023870800760, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1677, endPage=1687, ext={EN=ArticleExt(id=1227591034595640125, articleId=1227591033182159663, tenantId=1146029695717560320, journalId=1225147924628267009, language=EN, title=Loudness model for round window stimulation based on human ear physiology, columnId=null, journalTitle=Journal of Vibration Engineering, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Since current loudness models are unable to predict loudness under round window stimulation,a loudness model for round window stimulation is proposed in this paper. The loudness model consists of a peripheral auditory model and a data processing back-end. The peripheral auditory model that is able to calculate basilar membrane velocities under free-field acoustic stimulation and round window stimulation and the back-end that transforms basilar membrane velocities into loudness are constructed. The reliability of the peripheral auditory model is verified by comparing the model-predicted results with the experimental data on the outer ear transfer function,middle ear transfer function and stapes velocities under acoustic stimulation,round window stimulation transfer function,frequency selectivity and frequency response of the basilar membrane,and basilar membrane displacement. The reliability of the loudness model is verified by comparing the model-predicted results with the experimental data on equal-loudness contours,bandwidth noise loudness,loudness level of tone with frequency masking,and threshold for complex tones. The results indicate that the loudness model accurately calculates basilar membrane velocities under acoustic stimulation and round window stimulation,and is able to predict the loudness of pure tone,complex tones,and bandwidth noise under acoustic stimulation and round window stimulation.

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针对目前的响度模型无法用于预测圆窗激振下响度的问题,提出了一个适用于圆窗激振的人耳生理响度模型。该响度模型由听觉外周模型和数据处理后端组成。建立了能够计算自由场声激励和圆窗激振下基底膜振速的听觉外周模型以及将基底膜振速转变为听觉中枢所感受到的响度的数据处理后端;将听觉外周模型计算结果与已有文献中外耳传递函数、声激励下中耳传递函数和镫骨振速、圆窗激振传递函数、内耳基底膜选频特性、频响特性和位移的试验数据进行对比,验证了听觉外周模型的可靠性;将响度模型计算结果与等响曲线、带宽噪声响度、频域掩蔽下纯音响度级和复音阈值已有文献中的试验数据进行对比,验证了响度模型的可靠性。研究结果表明,该人耳生理响度模型较为准确地计算出了声激励和圆窗激振下基底膜振速,并能够用于计算声激励和圆窗激振下纯音、复音和带宽噪声的响度。

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刘后广(1982—),男,博士,教授。E-mail:
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刘兆海(1998—),男,博士研究生。 E-mail:

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刘兆海(1998—),男,博士研究生。 E-mail:

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刘兆海(1998—),男,博士研究生。 E-mail:

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articleId=1227591033182159663, language=CN, label=图17, caption=不同纯音的数量构成复音的阈值, figureFileSmall=osekpnVi+i7+AqU/em1ldw==, figureFileBig=JBe/gKcSJDX6XMWwJBqLNA==, tableContent=null), ArticleFig(id=1227653587304641405, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1227591033182159663, language=EN, label=Tab. 1, caption=

Parameters of the middle ear dynamics model

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质量/kg刚度/(N·m-1阻尼/(N·s·m-1
mM = 2.5×10-5kE = 30cE = 0.1
mI = 2.7×10-5kAML = 800cAML = 0.0432
mS = 1.78×10-6kIMJ = 1×106cIMJ = 3.6
mCF =7.15×10-5kPIL = 400cPIL = 0.02
kISJ = 4000cISJ = 0.1
kAL = 1400cAL = 0.3
kRW = 1.9cVA = 2.2
cCA = 77
cRW = 0.0015
), ArticleFig(id=1227653587422081923, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1227591033182159663, language=CN, label=表1, caption=

中耳动力学模型参数

, figureFileSmall=null, figureFileBig=null, tableContent=
质量/kg刚度/(N·m-1阻尼/(N·s·m-1
mM = 2.5×10-5kE = 30cE = 0.1
mI = 2.7×10-5kAML = 800cAML = 0.0432
mS = 1.78×10-6kIMJ = 1×106cIMJ = 3.6
mCF =7.15×10-5kPIL = 400cPIL = 0.02
kISJ = 4000cISJ = 0.1
kAL = 1400cAL = 0.3
kRW = 1.9cVA = 2.2
cCA = 77
cRW = 0.0015
), ArticleFig(id=1227653587535328137, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1227591033182159663, language=EN, label=Tab. 2, caption=

Parameters of the inner ear model

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参数取值
耳蜗横截面积AC / m21.45×10-6-1.1×10-8i
基底膜宽度WBi / mm0.31+0.002i
基底膜质量mBi / kg4.11×10-13×e0.04523i
基底膜刚度kBi / (N‧m-1)1.012×e-0.09803i
基底膜阻尼cBi / (N‧s‧m-1)1.587×10-8×e0.02245i
基底膜纵向刚度kLi / (N‧m-1)1.012×10-4×e-0.09803i
基底膜纵向阻尼cLi / (N‧s‧m-1)1.587×10-12×e0.02245i
外毛细胞刚度kOHCi / (N‧m-1)1×106×e0.0563i
外毛细胞阻尼cOHCi / (N‧s‧m-1)7.745×10-4×e0.0107i
网状板质量mRi / kg2.712×10-13×e0.04523i
网状板刚度kRi / (N‧m-1)0.2023×e-0.09803i
网状板阻尼cRi / (N‧s‧m-1)1.167×10-7×e-0.02673i
盖膜质量mTi / kg3.78×10-10×e0.0175i
盖膜刚度kTi / (N‧m-1)0.21×e-0.077i
盖膜阻尼cTi / (N‧s‧m-1)4.455×10-6×e-0.02975i
鼓阶接地电阻RTL / Ω1.3714×106
蜗管接地电阻RML4.8×106
外毛细胞顶部电阻Ra2.5×108
外毛细胞基部电阻Rb3.75×107
外毛细胞顶部电容Ca / F1.4583×10-13
外毛细胞基部电容Cb / F5.17×10-12+7.07×10-14i
静息电位差VEP-VOHC / V0.15-3.5×10-4i
网状板倾角θ / rad1.134-3.491×10-3i
压电耦合系数ε / (N‧V-1)-0.008-2.8×10-5i
纤毛束电导率G1 / (S‧m-2)4.17×106×e-0.1683i
), ArticleFig(id=1227653587677934481, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1227591033182159663, language=CN, label=表2, caption=

内耳模型参数

, figureFileSmall=null, figureFileBig=null, tableContent=
参数取值
耳蜗横截面积AC / m21.45×10-6-1.1×10-8i
基底膜宽度WBi / mm0.31+0.002i
基底膜质量mBi / kg4.11×10-13×e0.04523i
基底膜刚度kBi / (N‧m-1)1.012×e-0.09803i
基底膜阻尼cBi / (N‧s‧m-1)1.587×10-8×e0.02245i
基底膜纵向刚度kLi / (N‧m-1)1.012×10-4×e-0.09803i
基底膜纵向阻尼cLi / (N‧s‧m-1)1.587×10-12×e0.02245i
外毛细胞刚度kOHCi / (N‧m-1)1×106×e0.0563i
外毛细胞阻尼cOHCi / (N‧s‧m-1)7.745×10-4×e0.0107i
网状板质量mRi / kg2.712×10-13×e0.04523i
网状板刚度kRi / (N‧m-1)0.2023×e-0.09803i
网状板阻尼cRi / (N‧s‧m-1)1.167×10-7×e-0.02673i
盖膜质量mTi / kg3.78×10-10×e0.0175i
盖膜刚度kTi / (N‧m-1)0.21×e-0.077i
盖膜阻尼cTi / (N‧s‧m-1)4.455×10-6×e-0.02975i
鼓阶接地电阻RTL / Ω1.3714×106
蜗管接地电阻RML4.8×106
外毛细胞顶部电阻Ra2.5×108
外毛细胞基部电阻Rb3.75×107
外毛细胞顶部电容Ca / F1.4583×10-13
外毛细胞基部电容Cb / F5.17×10-12+7.07×10-14i
静息电位差VEP-VOHC / V0.15-3.5×10-4i
网状板倾角θ / rad1.134-3.491×10-3i
压电耦合系数ε / (N‧V-1)-0.008-2.8×10-5i
纤毛束电导率G1 / (S‧m-2)4.17×106×e-0.1683i
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适用于圆窗激振的人耳生理响度模型研究
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刘兆海 1 , 郭维维 2, 3, 4 , 贺志恒 1 , 陈伟 2, 3, 4 , 饶柱石 5 , 刘后广 1
振动工程学报 | 2025,38(8): 1677-1687
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振动工程学报 | 2025, 38(8): 1677-1687
适用于圆窗激振的人耳生理响度模型研究
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刘兆海1 , 郭维维2, 3, 4, 贺志恒1, 陈伟2, 3, 4, 饶柱石5, 刘后广1
作者信息
  • 1.中国矿业大学机电工程学院,江苏 徐州 221116
  • 2.中国人民解放军总医院耳鼻咽喉头颈部外科医学部,北京 100853
  • 3.听觉与平衡觉全国重点实验室,北京 100853
  • 4.国家耳鼻咽喉疾病临床医学研究中心,北京 100853
  • 5.上海交通大学机械系统与振动全国重点实验室,上海 200240
  • 刘兆海(1998—),男,博士研究生。 E-mail:

通讯作者:

刘后广(1982—),男,博士,教授。E-mail:
Loudness model for round window stimulation based on human ear physiology
Zhaohai LIU1 , Weiwei GUO2, 3, 4, Zhiheng HE1, Wei CHEN2, 3, 4, Zhushi RAO5, Houguang LIU1
Affiliations
  • 1.School of Mechanical and Electrical Engineering,China University of Mining and Technology,Xuzhou 221116,China
  • 2.Department of Otolaryngology Head and Neck Surgery,Chinese PLA General Hospital,Beijing 100853,China
  • 3.State Key Laboratory of Hearing and Balance Science,Beijing 100853,China
  • 4.National Clinical Research Center for Otolaryngologic Diseases,Beijing 100853,China
  • 5.State Key Laboratory of Mechanical System and Vibration,Shanghai Jiao Tong University,Shanghai 200240,China
出版时间: 2025-08-10 doi: 10.16385/j.cnki.issn.1004-4523.202401060
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针对目前的响度模型无法用于预测圆窗激振下响度的问题,提出了一个适用于圆窗激振的人耳生理响度模型。该响度模型由听觉外周模型和数据处理后端组成。建立了能够计算自由场声激励和圆窗激振下基底膜振速的听觉外周模型以及将基底膜振速转变为听觉中枢所感受到的响度的数据处理后端;将听觉外周模型计算结果与已有文献中外耳传递函数、声激励下中耳传递函数和镫骨振速、圆窗激振传递函数、内耳基底膜选频特性、频响特性和位移的试验数据进行对比,验证了听觉外周模型的可靠性;将响度模型计算结果与等响曲线、带宽噪声响度、频域掩蔽下纯音响度级和复音阈值已有文献中的试验数据进行对比,验证了响度模型的可靠性。研究结果表明,该人耳生理响度模型较为准确地计算出了声激励和圆窗激振下基底膜振速,并能够用于计算声激励和圆窗激振下纯音、复音和带宽噪声的响度。

响度感知  /  圆窗激振  /  人工中耳  /  听觉外周  /  动力学建模  /  时域分析

Since current loudness models are unable to predict loudness under round window stimulation,a loudness model for round window stimulation is proposed in this paper. The loudness model consists of a peripheral auditory model and a data processing back-end. The peripheral auditory model that is able to calculate basilar membrane velocities under free-field acoustic stimulation and round window stimulation and the back-end that transforms basilar membrane velocities into loudness are constructed. The reliability of the peripheral auditory model is verified by comparing the model-predicted results with the experimental data on the outer ear transfer function,middle ear transfer function and stapes velocities under acoustic stimulation,round window stimulation transfer function,frequency selectivity and frequency response of the basilar membrane,and basilar membrane displacement. The reliability of the loudness model is verified by comparing the model-predicted results with the experimental data on equal-loudness contours,bandwidth noise loudness,loudness level of tone with frequency masking,and threshold for complex tones. The results indicate that the loudness model accurately calculates basilar membrane velocities under acoustic stimulation and round window stimulation,and is able to predict the loudness of pure tone,complex tones,and bandwidth noise under acoustic stimulation and round window stimulation.

loudness perception  /  round window stimulation  /  active middle ear implant  /  auditory periphery  /  dynamics modeling  /  time-domain analysis
刘兆海, 郭维维, 贺志恒, 陈伟, 饶柱石, 刘后广. 适用于圆窗激振的人耳生理响度模型研究. 振动工程学报, 2025 , 38 (8) : 1677 -1687 . DOI: 10.16385/j.cnki.issn.1004-4523.202401060
Zhaohai LIU, Weiwei GUO, Zhiheng HE, Wei CHEN, Zhushi RAO, Houguang LIU. Loudness model for round window stimulation based on human ear physiology[J]. Journal of Vibration Engineering, 2025 , 38 (8) : 1677 -1687 . DOI: 10.16385/j.cnki.issn.1004-4523.202401060
据世界卫生组织的报告,约有4.3亿人患有致残性听力损伤[1]。大多数感音神经性听力损伤患者采用助听器进行听力补偿。但是助听器存在声音失真、声反馈、中耳衰减和高频增益低等问题[2]。传统的通过作动器机械激振听骨链来补偿听力损伤的人工中耳虽然克服了这些问题,但是无法应用于伴有听骨链腐蚀等传导性听力损伤的混合性听力损伤患者[3]。COLLETTI等[4]在临床上探索了一种避开听骨链的方法——圆窗激振。这种方法绕开损伤的听骨链,直接激振耳蜗圆窗膜进行听力补偿,并取得良好的术后效果[5]。然而,圆窗激振人工中耳在验配过程中出现初始验配误差大、后期微调困难等问题[6]。这是由于至今没有开发针对圆窗激振的验配算法,临床上借用助听器验配算法完成验配[7]
响度是声品质的一个重要参数[8-9],其能较好地评估听力补偿效果。BYRNE等[10]和MOORE等[11-12]助听器典型验配算法的开发均是基于MOORE等[13-14]建立的响度模型。然而,MOORE等[13-16]建立的响度模型采用滤波器拟合声激励下中耳的传递函数,并未基于真实人耳的生理结构,不能用于圆窗激振。因此,为开发圆窗激振的验配算法,有必要建立能够预测圆窗激振的响度模型。
由于目前响度的国际标准均基于自由场声激励[17-18],因此,本文首先建立了一个可以计算自由场声激励和圆窗激振下基底膜振速的听觉外周模型。然后,根据声激励下基底膜振速和响度的国际标准,建立了一个可以根据基底膜振速计算出对应响度的数据处理后端。最后,通过与试验数据对比,验证了本文听觉外周模型、数据处理后端和响度模型的可靠性。
在声音从正前方自由场传递到耳膜的过程中,外耳起着收集和共振的作用。为了对该过程进行模拟,采用600阶的数字滤波器建立了外耳模型:
PE(n)=k=0600a(k)PFree(n-k); n=0,1,2,
式中,PE为耳膜处的声压;PFree为自由场声源处的声压;a为滤波器的增益参数;n为声音信号采样点的时间索引;k为滤波器的阶数。
此外,由于人耳感知的声压范围数量级很大,通常采用声压级(SPL)描述声压,如下式所示:
SPL=20×lg(PP0)
式中,SPL的单位为dB;P为所要描述的声压;P0为基准声压,P0 = 2×10-5 Pa[19]
为了对中耳部分进行动力学建模,将锤骨、砧骨、镫骨和耳蜗液简化为质量,其他人耳组织被简化为刚度和阻尼[20],如图1所示。锤骨(mM)、砧骨(mI)和镫骨(mS)分别通过与锤骨前韧带(kAML,cAML)、砧骨后韧带(kPILcPIL)和镫骨底环状韧带(kALcAL)连接而悬挂在鼓室中。声激励下,声压作用在耳膜(kEcE)上,引起锤骨振动。然后,振动依次通过砧锤关节(kIMJcIMJ)、砧骨、砧镫关节(kISJcISJ)和镫骨传递到耳蜗液(mCF)。
此外,为了模拟圆窗激振,在模型中考虑了前庭导水管(cVA)和耳蜗导水管(cCA[21]。圆窗激振下,作动器振动直接通过圆窗膜(kRWcRW)传递到耳蜗液(mCF),引起耳蜗隔膜两侧压差。由于中耳阻抗相对于前庭导水管阻抗较大,圆窗激振下前庭导水管处耳蜗液溢出,降低了前庭阶压强,进一步增大了耳蜗隔膜两侧压差[22]
经上述简化,中耳在声激励和圆窗激振下的动力学方程为:
{mMx¨M+k11xM+k12xI+c11x˙M+c12x˙I=PEAEmIx¨I+k21xM+k22xI+k23xS+c21x˙M+c22x˙I+c23x˙S=0mSx¨S+k32xI+k33xS+c32x˙I+c33x˙S+c34x˙CF=0mCFx¨CF+k44xCF+c43x˙S+c44x˙CF=PRWARW
式中,AEARW分别为耳膜和圆窗膜的面积,分别为59.4 mm2[2]和2.1 mm2[2]PRW为圆窗激振下圆窗膜处压强;xMxIxSxCF分别为锤骨、砧骨、镫骨和耳蜗液的位移。其他系数如下式所示:
k11=kE+kAML+kIMJ,k12=k21=-kIMJ,c11=cE+cAML+cIMJ,c12=c21=-cIMJ,k22=kIMJ+kPIL+kISJ,k23=k32=-kISJ,c22=cIMJ+cPIL+cISJ,c23=c32=-cISJ,k33=kISJ+kAL,c33=cISJ+cAL+cVA,c34=c43=-cVA,k44=kRW,c44=cVA+cWA+cCAcRW/(cCA+cRW)
式中,cWA为耳蜗液摩擦阻尼。式(4)中参数的值参考自文献[223-24],具体如表1所示。
为了对内耳部分进行模拟,采用一维流体耦合假设计算声激励和圆窗激振引起的耳蜗隔膜两侧压差分布[25-26],如图2所示。根据一维流体耦合假设,耳蜗液中行波的传递和压差的分布可以表示为:
2px2-2ρHw¨=0
式中,p为耳蜗液中的压差;w¨为耳蜗液中径向加速度;ρ为耳蜗液的密度;H为前庭阶和鼓阶的有效高度,H2AC/(8WB),其中,AC为耳蜗的横截面积,WB为基底膜的宽度。对方程(5)使用有限差分近似可以分别得到基部、中部和蜗孔处耳蜗压差分布:
{p2-p1Δ-2ρw¨1=2ρw¨CFpi-1-2pi+pi+1Δ2-2ρw¨iH=0pn=0
式中,Δ为每个耳蜗片段的长度;w¨1为第1个耳蜗片段的径向加速度;w¨CF为耳蜗液轴向加速度。式(6)的矩阵形式为:
Lp-w¨=q
其中,矩阵Lpw¨q具体如下式所示:
L=H2ρΔ2[-ΔHΔH01-2101-2100-2ρΔ2H],p=[p1p2pn-1pn],w¨=[w¨1w¨2w¨n-1w¨n],q=[x¨CF000]
其中,w¨与基底膜加速度z¨成正比。因此向量p可以表示为:
p=L-1(q+Bz¨),w¨=Bz¨
式中,B为耳蜗液加速度与基底膜的耦合系数矩阵。
最终,耳蜗液流体耦合产生的压力差向量Fd为:
Fd=ABMp
式中,ABM为基底膜片段面积的矩阵。
耳蜗隔膜两侧的压差引起柯蒂氏器的振动。为了计算不同位置柯蒂氏器的运动状态,将其划分为100个片段[27]。相邻片段直接通过基底膜的纵向刚度kLi和阻尼cLi耦合。每个片段中基底膜(kBicBi)与盖膜(kTicTi)均与骨蜗管壁耦合。基底膜(mBi)因两侧耳蜗液压差产生振动后,振动经外毛细胞(kOHCicOHCi)传递至网状板(mRi)。网状板的振动经由纤毛束(kHBicHBi)传递至盖膜(mTi)。盖膜的剪切位移引起纤毛束的偏转,进一步引起外毛细胞的电致运动。外毛细胞的电致运动产生主动激励力FOHCi进一步放大基底膜的运动,如图3所示。
基于上述对耳蜗柯蒂氏器振动的分析,可以得到柯蒂氏器的动力学方程为:
{mB1z¨B1+k11zB1+k12zR1+k14zB2+c11z˙B1+c12z˙R1+c14z˙B2=Fd1+FOHC1          mBiz¨Bi+k(3i-2)(3i-5)zB(i-1)+k(3i-2)(3i-2)zBi+k(3i-2)(3i-1)zRi+k(3i-2)(3i+1)zB(i+1)+c(3i-2)(3i-5)z˙B(i-1)+c(3i-2)(3i-2)z˙Bi+c(3i-2)(3i-1)z˙Ri+c(3i-2)(3i+1)z˙B(i+1)=Fdi+FOHCimR1z¨Ri+k(3i-1)(3i-2)zBi+k(3i-1)(3i-1)zRi+k(3i-1)(3i)zTi+c(3i-1)(3i-2)z˙Bi+c(3i-1)(3i-1)z˙Ri+c(3i-1)(3i)z˙Ti=-FOHCimTiz¨Ti+k(3i)(3i-1)zRi+k(3i)(3i)zTi+c(3i)(3i-1)z˙Ri+c(3i)(3i)z˙Ti=0          mBnz¨Bn+k(3n-2)(3n-5)zB(n-1)+k(3n-2)(3n-2)zBn+k(3n-2)(3n-1)zRn+c(3n-2)(3n-5)z˙B(n-1)+c(3n-2)(3n-2)z˙Bn+c(3n-2)(3n-1)z˙Ri=Fdn+FOHCn          
式中,zBizRizTi分别为第i个耳蜗片段中基底膜、网状板和盖膜的位移;Fdi为第i个耳蜗片段基底膜两侧压强差产生的压力。参数kijcij具体值由下式计算得出:
k11=kL1+kB1+kOHC1+kL2,k12=-kOHC1,k14=-kL2,c11=cL1+cB1+cOHC1+cL2,c12=-cOHC1,c14=-cL2,k(3i-2)(3i-5)=-kLi,k(3i-2)(3i-2)=kLi+kBi+kOHCi+kL(i+1),k(3i-2)(3i+1)=-kL(i+1),c(3i-2)(3i-5)=-cLi,c(3i-2)(3i-2)=cLi+cBi+cOHCi+cL(i+1),c(3i-2)(3i+1)=-cL(i+1),k(3i-2)(3i-1)=-kOHCi,k(3i-1)(3i-1)=kOHCi+kHBi,c(3i-2)(3i-1)=-cOHCi,c(3i-1)(3i-1)=cOHCi+cHBi,k(3i-1)(3i)=-kHBi,k(3i)(3i)=kHBi+kTi,c(3i-1)(3i)=-cHBi,c(3i)(3i)=cHBi+cTi,k(3n-2)(3n-5)=-kLn,k(3n-2)(3n-2)=kLn+kBn+kOHCn,k(3n-2)(3n-1)=-kOHCn,c(3n-2)(3n-5)=-cLn,c(3n-2)(3n-2)=cLn+cBn+cOHCn,c(3n-2)(3n-1)=-cOHCn,kij=kji,cij=cji
上述方程中参数的值参考自文献[27-32],具体如表2所示。
外毛细胞的电致运动进一步放大了耳蜗响应[32]。为更准确地模拟耳蜗响应,建立了外毛细胞模型以计算其产生的主动激励力,如图4所示,图中φSM为蜗管处电位。在该模型中,纤毛束的偏转和外毛细胞的收缩引起外毛细胞的电致运动,从而产生主动激励力。纤毛束的偏转位移uHB和外毛细胞的收缩位移uOHC为:
{uHB=zRcosθuOHC=(zR-zB)sinθ
式中,zRzB分别为网状板和基底膜的位移。
纤毛束偏转和外毛细胞收缩分别引起的转导电流和压电电流为:
{IS1=(VEP-VOHC)G1uHBIS2=-j2πfεuOHC
式中,VEPVOHC分别为蜗管和外毛细胞的静息电位;f 为特征频率;ε为压电耦合系数;G1为纤毛束电导率;j为虚数单位。
然后,求出外毛细胞内电位φOHC和细胞外电位φST
φOHC=IS1-αβIS21Za+α/βZb,φST=φOHCZb+IS2β
式中,参数αβZaZb分别为:
α=1RTL+RML/RTLZa,β=1RTL+1Zb,Za=1(1/Ra)+jωCa,Zb=1(1/Rb)+jωCb
式中,RMLRTL分别为蜗管和鼓阶的接地电阻;RaRb分别为外毛细胞顶部和基部的电阻;CaCb分别为外毛细胞顶部和基部的电容;ω为每个耳蜗片段的特征角频率。
最终,由外毛细胞内、外电位差产生的主动激励力FOHC[32]
FOHC=ε(φOHC-φST)
为了将上述听觉外周模型计算出的基底膜振速转化为听觉中枢感知到的响度,构建了一个数据处理后端。首先,该后端对耳蜗每个片段上的基底膜振速进行求绝对值和时间积分[33]
Ei,0=0,Ei,t=(1-e-1τfs)|vi,t|+e-1τfsEi,t-1
式中,Eit为第i个基底膜片段在时间t上的初始兴奋;vit为第i个基底膜片段在时间t上的振速;采样频率fs = 200 kHz;时间常数τ = 15 ms。然后,该后端将100个耳蜗片段的响应划分为23个兴奋段。根据1/3倍频程,特征频率为88.4 ~11313.7 Hz的耳蜗片段被划分为21个兴奋段,特征频率小于88.4 Hz和大于11313.7 Hz的耳蜗片段分别作为一个兴奋段。第x个兴奋段上的兴奋Ex可以计算为:
Ex=max(1Mm=1MEm,t)
式中,M为第x个兴奋段包含的耳蜗片段数。接下来,第x个兴奋段上的特征响度Lx可以计算为:
Lx=(CxEx+Ax)αx-Axαx
式中,CxαxAx均为第x个兴奋段上计算特征响度的常数。国际标准ISO 226:2023[18]的等响曲线中相同声压级、不同频率激励下人耳感知到的响度级不同,这表明每个兴奋段的兴奋转化为响度所占的权重不同。为拟合这种正常人耳响度感知特性,参数CxαxAx的值在每个兴奋段中不同。为了准确地确定23个兴奋段中参数CxαxAx的值,采用了自适应粒子群优化算法对上述参数进行寻优。上述参数的调整目标为本文响度模型的等响曲线与ISO 226:2023[18]中的等响曲线吻合。
确定上述参数之后,激励产生的初始响度LI可以根据下式由23个兴奋段的特征响度求和得出:
LI=x=123Lx
根据函数S,初始响度可以转化为响度级LLevel,如图5所示。最后,根据函数P,响度级可以转化为响度L,如图6所示。
由于数据处理后端中参数的调整目标为国际标准ISO 226:2023[18]中的响度数据,因此,本文所构建的正常听力响度模型适用范围与ISO 226:2023[18]一致,能够模拟18岁至25岁正常听力者的声音感知响度。
为验证听觉外周模型可靠性,分别对组成听觉外周模型的外耳模型、中耳模型和内耳模型的传声特性进行验证。
为了验证外耳模型的可靠性,将模型计算结果与标准ANSI S3.4—2007[17]中外耳传递函数(耳膜处声压与自由场正面射入声压的比值)进行了对比。如图7所示,计算结果与标准十分吻合。该结果表明外耳模型能够准确地模拟外耳的传声特性。
为了验证中耳模型的可靠性,将模型计算结果与中耳传递函数(声激励下耳蜗压差与耳膜处声压的比值)和圆窗激振传递函数(圆窗激振下耳蜗压差与圆窗膜处的压强的比值)的文献数据进行对比。
图8所示,耳膜处94 dB SPL声激励下本文模型的中耳传递函数与文献[34]中颞骨试验数据十分吻合。该结果表明本文模型能够准确地模拟声激励下中耳的传声特性。
图9所示,将圆窗膜处50 μN圆窗激振下本文模型的中耳传递函数与文献[34]中MED-EL公司的振动声桥中电磁悬浮质量作动器激励下的颞骨试验数据进行了对比。模型计算结果在小于300 Hz时略低于文献中的试验数据,在大于300 Hz 时与文献中的试验数据较为吻合。该结果表明本文模型能够较好地模拟圆窗激振下人耳的传声特性。
此外,由于内耳模型验证的需要,还对耳膜处94 dB SPL声激励下本文模型的镫骨振速进行了验证。如图10所示,模型计算结果在文献[35]统计的颞骨试验数据范围之内,且趋势与文献中的试验数据一致。
为了验证内耳模型的可靠性,将模型计算结果与基底膜选频特性、频响特性和位移的文献中试验数据进行了对比。
图11所示,内耳模型计算结果与文献[36]中颞骨试验数据十分吻合。该结果表明该内耳模型准确地模拟了基底膜的选频特性。
图12所示,本文模型距镫骨12 mm处基底膜振速的频响曲线与文献[37-38]的颞骨试验数据较为一致。该结果表明内耳模型较好地模拟了中耳到内耳的传声特性和基底膜的频响特性。
图13所示,将被动和主动内耳模型的计算结果分别与文献[39]中死亡和存活耳蜗的基底膜位移试验数据进行对比。模型计算结果与文献中的试验数据十分吻合。该结果表明本文听觉外周模型准确地模拟了不同声压级激励下基底膜的位移,并且外毛细胞模型较好地模拟了耳蜗放大作用。
综上所述,本文听觉外周模型能够较好模拟人耳各种传声特性,模型的可靠性得到了较为全面的验证。
本文响度模型数据处理后端中参数的调整目标为国际标准ISO 226:2023[18]中等响曲线,该曲线是基于18岁至25岁正常听力受试者测听获得。优化后本文响度模型的等响曲线如图14所示,可见模型计算结果与ISO 226:2023[18]中等响曲线较为吻合。该结果表明本文响度模型能够较为准确地计算不同声压级、不同激励频率下正常人耳感知到的响度级。
参照文献[40]中不同带宽的噪声与对比噪声进行等响度匹配的试验,验证本文响度模型计算带宽噪声响度的能力。如图15所示,将模型计算结果与文献[40]中22名正常听力受试者的试验数据进行了对比。对于30 dB SPL 3500 Hz带宽噪声,模型计算结果略大于文献中的试验数据。对于30 dB SPL、小于1100 Hz带宽噪声以及50 dB和80 dB SPL、不同带宽噪声,模型计算结果与文献中的试验数据较为吻合。此外,在噪声带宽小于510 Hz时,随着带宽的增大,对比噪声的声压级变化很小;在噪声带宽大于510 Hz时,对比噪声的声压级随着带宽的增大而增大。该结果表明本文响度模型较为准确地计算了带宽噪声的响度,并模拟了临界带宽现象。
参照文献[41]中安静环境纯音和带宽噪声中纯音等响度匹配的试验,对本文响度模型计算频域掩蔽下纯音响度的能力进行了验证。如图16所示,模型计算结果与文献[41]中8名正常听力受试者的40 dB和60 dB SPL带宽噪声掩蔽下纯音响度级的试验数据十分吻合。该结果表明本文响度模型较为准确地计算了带宽噪声掩蔽下纯音的响度级,并模拟了频域掩蔽效应。
参照文献[42]中的试验,进一步对本文响度模型计算频域掩蔽引起的掩蔽阈值的能力进行了验证。如图17所示,将模型计算的复音中平均单个纯音的阈值与文献[42]中4名25岁至33岁并且有心理声学测试经验的正常听力受试者(三名男性和一名女性)的试验数据进行了对比。对于小于等于19个纯音组成的复音,模型计算结果与文献中的试验数据较为吻合。对于41个纯音组成的复音,模型计算结果小于文献中的试验数据。该结果表明本文响度模型能够对频域掩蔽引起的掩蔽阈值进行较为准确的计算。
综上所示,本文响度模型能较为准确地计算纯音、复音和带宽噪声的响度,并模拟临界带宽和领域掩蔽效应。本文响度模型和数据处理后端的可靠性得到了较为全面的验证。
STEVENS[43]最早基于响度概念建立了响度模型。STEVENS模型与ZWICKER等[44]提出的响度模型一起构成了国际标准ISO 532:1975[45]。然而,ISO 532:1975与基于ZWICKER模型重新修订的国际标准ISO 532-1:2017[46]均采用的是图表法,该方法存在响度预测值不连续等问题。
为此,MOORE等[13]提出了基于分析公式进行计算的响度模型。该响度模型采用滤波器模拟外耳和中耳传声特性,滤波器组模拟基底膜的选频特性,基于滤波器组计算出的兴奋拟合正常听力者的响度数据。后来,MOORE等[15-16]提出的双耳响度模型和时变响度模型分别被国际标准组织确定为标准ISO 532-2:2017[47]和ISO 532-3:2023[48]。MOORE等[14]的响度模型可以通过调整中耳传递函数模拟传导性听力损伤,以及通过调整等效矩形带宽兴奋模拟感音神经性听力损伤。然而,该响度模型是对主观感知响度数据的拟合,未考虑人耳生理结构。
为研究主观感知响度与客观耳蜗响应之间的关系,PIEPER等[49]建立了考虑耳蜗生理结构的响度模型。该响度模型仍采用滤波器模拟声激励下振动通过耳膜、听骨链和卵圆窗进入耳蜗过程中的传递函数,未考虑中耳生理结构和耳蜗第三窗。圆窗激振下振动通过圆窗膜传递至耳蜗。两种激振方式的振动传递途径不同,传递函数不同。因此,PIEPER模型不能模拟圆窗激振。相对于PIEPER响度模型,本文响度模型进一步考虑了中耳生理结构和耳蜗第三窗,故能够用于计算圆窗激振响度。计算步骤如下:(1)将圆窗激振人工中耳作动器激振力输入至响度模型内中耳动力学模型的圆窗膜处,计算得到圆窗激振下的耳蜗液加速度;(2)将耳蜗液加速度代入内耳模型,计算得到圆窗激振下每个耳蜗片段上的基底膜振速;(3)将基底膜振速代入数据处理后端得到圆窗激振响度。
相较于上述响度模型,本文响度模型具有以下优点:(1)本文响度模型能够计算圆窗激振的响度;(2)本文响度模型考虑了中耳和内耳的生理结构,能够更真实地模拟听力损伤;(3)本文响度模型能够与人工中耳作动器的力学模型耦合,可以用于优化作动器的设计参数以及开发人工中耳的验配算法。
本文响度模型除了有上述优点以外,还存在一些将来工作中要逐渐解决的不足:(1)由于考虑了人耳生理结构,本文响度模型所需计算时间要长于MOORE响度模型;(2)本文响度模型是基于双耳所受激励相同假设建立的,不能准确计算双耳所受激励不同情况下的响度。这是由于双耳抑制作用,相同激励下双耳响度并不简单是标准ANSI S3.4—2007[17]中描述的单耳响度之和,MOORE等[15]的研究结果显示双耳响度为单耳响度的1.5倍。
本文提出了一个适用于圆窗激振的人耳生理响度模型。该响度模型由听觉外周模型和数据处理后端组成。通过将听觉外周模型计算结果与已有文献中的外耳传递函数、声激励下中耳传递函数和镫骨振速、圆窗激振传递函数、内耳基底膜选频特性、频响特性和位移等试验数据进行对比,证明了听觉外周模型能够较为准确地模拟出声激励和圆窗激振下基底膜振速。根据声激励下基底膜振速和等响曲线,构建了数据处理后端。通过与已有文献中的试验数据的对比,进一步验证了本文响度模型能够计算纯音响度、带宽噪声响度、频域掩蔽下纯音的响度级和复音的阈值,并模拟临界带宽和频域掩蔽等心理声学现象。由于听觉外周模型能够模拟圆窗激振下基底膜振速,并且响度的计算基于基底膜振速,因此本文响度模型能够计算圆窗激振的响度。此外,由于该响度模型基于人耳生理结构,因此还可以用于研究耳硬化症等传导性听力损伤和外毛细胞损伤情况等感音神经性听力损伤患者的响应感知。基于该响度模型和患者的听力损伤情况,可以开发个性化的圆窗激振式人工中耳的验配算法。
  • 国家自然科学基金资助项目(52275296)
  • 国家重点研发计划项目(2022YFC2402700)
  • 江苏高校优势学科建设工程资助项目(PAPD)
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2025年第38卷第8期
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doi: 10.16385/j.cnki.issn.1004-4523.202401060
  • 接收时间:2024-01-22
  • 首发时间:2026-02-09
  • 出版时间:2025-08-10
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  • 收稿日期:2024-01-22
  • 修回日期:2024-03-11
基金
国家自然科学基金资助项目(52275296)
国家重点研发计划项目(2022YFC2402700)
江苏高校优势学科建设工程资助项目(PAPD)
作者信息
    1.中国矿业大学机电工程学院,江苏 徐州 221116
    2.中国人民解放军总医院耳鼻咽喉头颈部外科医学部,北京 100853
    3.听觉与平衡觉全国重点实验室,北京 100853
    4.国家耳鼻咽喉疾病临床医学研究中心,北京 100853
    5.上海交通大学机械系统与振动全国重点实验室,上海 200240

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刘后广(1982—),男,博士,教授。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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