Journal of the Korea Convergence Society (한국융합학회논문지)

Korea Convergence Society (한국융합학회)
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A Study on the Acoustic Analysis Method of the External Ear Canal Using DICOM Images

DICOM 영상을 이용한 외이도 음향해석 방법에 관한 연구

  • Received : 2018.12.12
  • Accepted : 2019.03.20
  • Published : 2019.03.28
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Abstract

This study simulated external ear canal modeling with different external ear canal lengths, vertical flexion angles, and inner/outer diameter ratios using digital imaging and communications in medicine(DICOM) of the head temporal region and measured the acoustic sensitivity. The experiment was performed by increasing the audible frequency for humans by 200 Hz and expressing the frequency constantly transmitted at 1 Pa as the eardrum acoustic volume and presented the measurements by linear and quadratic curve regression analysis. The results showed that the longer the external ear canal length and the higher the ratio of the outer/inner diameter, the faster the acoustic response at lower frequencies. The acoustic sensitivity correlation of the meta-model using regression analysis showed a 77% influence by the external ear canal length and 5% by the external/internal diameter ratio, while the vertical flexion angle did not show a significant relationship. This showed that auditory acoustic sensitivity of humans is a factor that reacts faster at a low frequency when the external ear canal length is longer and when the difference between the outer and inner diameter is higher.

머리 측두부 디지털 영상 및 통신 표준 영상을 이용한 외이도 길이, 상하 굴곡각도, 내 외경 비율에 따른 음향민감도를 외이도 모델링으로 시뮬레이션하고 측정하였다. 실험은 인간 가청주파수 기준으로 200Hz씩 증가하면서 1 파스칼의 압력으로 일정하게 전달된 주파수를 고막 음향크기로 나타내어 그 측정값들을 선형과 이차곡선 회귀분석으로 나타내었다. 그 결과 외이도 길이는 길수록, 외 내경 둘레의 비율은 높을수록 낮은 주파수에서 빠른 음향적 반응을 나타내었다. 회귀분석을 이용한 메타모델의 음향민감도 상관관계는 외이도 길이가 77%, 외 내경 비율 5%의 영향으로 나타났지만 상하 굴곡각도는 특별한 관계를 나타내지 못하였다. 이로써 인간의 청각음향 민감도는 외이도 길이가 길수록, 외 내경 둘레의 비율 차이가 높을수록 낮은 주파수에서 빠르게 반응하는 인자임을 알 수 있었다.

Keywords

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Fig. 1. The external ear canal extraction process using DICOM volume data of the head temporal region

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Fig. 2. Experimental modeling reflecting the shape characteristics of external ear canal (length, angle, inner and outer diameters)

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Fig. 3. The simulation process by increasing the frequency by 200Hz at a pressure of 1 Pa

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Fig. 4. Graph simulating the acoustic size for each frequency by modeling each external ear canal

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Fig. 5. The 1st peak response frequency graph classified by length, angle, and inner/outer diameter of the external ear canal

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Fig. 6. The regression cover graph for linear correlation and quadratic correlation

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Fig. 7. The simulation result graph through meta-model

Table 1. Measurements of the shape characteristics including external ear canal length, angle, and the circumference of the inner/outer diameters

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Table 2. Acoustic sound measured at the eardrum

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