以嵌入式系統及Android為平台之無線自動聽性腦幹響應(AABR)量測系統

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林聖凱(Sheng-Kai Lin) 查詢紙本館藏

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電機工程學系

論文名稱

以嵌入式系統及Android為平台之無線自動聽性腦幹響應(AABR)量測系統
(Wireless-Automated Auditory Brainstem Response (AABR) Measurement System Bases on the Android and the Embedded System)

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摘要(中)

新生兒聽力篩檢於幼兒後天發展占重要地位，三歲內為幼兒語言學習黃金時期，聽損越早被診斷，就能盡早進行聽力相關手術、聽力及構音訓練，降低聽損對幼兒造成日後負面影響。國民健康署於2012年推動並補助新生兒聽力篩檢，採用自動聽性腦幹響應(Automated auditory brainstem responses, AABR)檢測。然而儀器昂貴、功能簡單、需電腦操作且空間受限、部分儀器介面也無顯示腦幹波形。
　　為降低成本與改善問題，本研究結合嵌入式系統與智慧型手機兩平台，搭配硬體與藍芽模組，開發無線AABR量測系統。使用者能以手機控制系統對人耳產生刺激音，再以電極片截取腦幹電位響應，並傳送至手機進行分析與顯示。本系統使用卡爾曼濾波器與指數權重平均演算法處理訊號，同時自動判斷第五波，並於手機即時顯示波形。
　　為了評估本系統偽陽性與再現性，本研究有6位年齡23至25歲男性個案(4位聽力正常；2位先天聽損)參與兩實驗。實驗一由本系統於聽力室對每位個案進行3次檢測，4位正常個案皆於系統辨識出第五波並顯示為”Pass”，2位聽損個案則為”Refer”，結果顯示此系統偽陽性為0，由於3次之檢測結果接近，因此具良好再現性。另外有2位個案於電磁波隔離室檢測，結果與聽力室無顯著差異；為了驗證本系統再現性，實驗二以市售儀器檢測並與本系統比較，發現兩者皆可比對出第五波，而市售儀器測得之反應時間較本系統長，但兩者於高音量刺激測得反應時間皆少於低音量。本研究開發之無線AABR量測系統能以手機無線操作，也可自動辨識第五波，於實驗檢測結果證實本系統可用性。

摘要(英)

Infants hearing screening is one of the most significant issues for the new born babies in their developments. It was the most important for the children to learn to speak before the age of 3 years old. Infants with congenital hearing-impaired should be diagnosed earlier. To reduce the negative influences for the developments of these children, it was suggested to carry out the hearing surgeries as earlier as possible. These children were also suggested to receive more trainings for hearing and articulation when they were growing. In 2012, Ministry of Health and Welfare (MHW) in Taiwan promoted the policy of the infants hearing screening with the technique of automated auditory brainstem responses (AABR). However, the instruments of AABR were expensive but with simple function, and designed to be operated with computers as the user interface, all these problems were caused to be inconvenient for each users. Furthermore, the function of displaying the patterns of the brainstem responses was not included with most instruments
To improve these disadvantages of these commercial instruments, a wireless-AABR measurement system was developed with the embedded system and the smart phone. Users could control this system to produce the stimuli with the smart phone. The evoked brainstem responses were measured from the scalp and transmitted to the smart phone through the Bluetooth module. The algorithms of Kalman filter and exponential weighted average (EWA) were used to process these signals in real-time. The wave V of the brainstem response would be identified automatically and displayed on the smart phone.
To evaluate the false positive and the reproducibility of our system, 6 male subjects (Age: 23-25; 4 subjects: Normal hearing, NH; 2 subjects: Congenital hearing-impaired, CHI) were tested in two experiments. In the first experiment, all subjects were tested with our system in the hearing exam room by 3 times. The wave V was identified with “Pass” from the results of the system on 4 normal subjects. In contract, the results showed “Refer” on another 2 subjects with hearing-impaired. The result of the false positive tested was 0, and the reproducibility was good for our system. There was no difference between the results measured in the hearing exam room and the electromagnetic pulses isolated room (EMP isolated room). To validate the accuracy of our system, we compared our system to the commercial system in the second experiment. The wave V of 5 subjects (4 NH, 1 CHI) were both identified from these two systems. However, the latencies measured from these two systems were both shorter in the higher volume of the stimuli. Although the relative latencies measured from the commercial system were longer than those of our system, our results showed that the wireless-AABR measurement system was plausible for hearing screening.

關鍵字(中)

★ 聽性腦幹響應量測
★ 自動聽性腦幹響應量測
★ 新生兒聽力篩檢
★ 嵌入式系統
★ 智慧型手機
★ 藍芽
★ 卡爾曼濾波器
★ 指數權重平均

關鍵字(英)

★ Auditory brainstem responses (ABR)
★ Automated auditory brainstem responses (AABR)
★ Automatic auditory brainstem responses (AABR)
★ Infants hearing screening
★ Embedded system
★ Smart phone
★ Bluetooth
★ Kalman filter
★ Exponential weighted average

論文目次

摘要……………………………………………………………...……...IV
Abstract…………………………………………………….....………. VI
誌謝……………………………………………..…………….…..…. VIII
圖目錄……………………………………………………………........XII
表目錄……………………………………………………………...….XV
第一章緒論…………………………………..………………………1
1.1 前言…………………………………………………………….1
1.2 研究動機…………………………………………………...…..5
1.3 文獻回顧…………………………………………………….…9
1.3.1 c-ABR、tb-ABR與ASSR比較…………………...…9
1.3.2 ABR功能性探討………………………………….…11
1.3.3 ABR臨床研究………………………………….……11
1.3.4 訊號擷取……………………………………..………12
1.3.5 訊號品質改善…………………………………….….13
1.3.6 客觀波形判斷與結果分析…………………..………13
1.4 論文架構……………………………………………………...16
第二章聽性腦幹響應………………………………………………17
2.1 起源與原理…………………………………………………...17
2.2 刺激音與ABR之關係……………………………………….22
2.3 受測者與ABR之關係……………………….………………24
2.4 基本檢測流程………………………………...………………25
2.5 自動聽性腦幹響應(AABR)與新生兒聽力篩檢………….…26
第三章無線AABR量測系統設計………………...………………27
3.1 系統架構……………………………………………………..27
3.2 韌體…………………………………………………………..29
3.2.1 脈衝寬度調變………………………………………..30
3.2.2 類比數位轉換器……………………………………..31
3.2.3 通用非同步收發傳輸器……………………………..32
3.2.4 運作方式……………………………………………..33
3.3 硬體…………………………………………………………..34
3.3.1 分壓電路……………………………………………..35
3.3.2 1階高通濾波器……………………………………...35
3.3.3 前級放大電路………………………………………..36
3.3.4 4階帶通濾波器……………………………...………38
3.3.5 後級放大電路………………………………..………39
3.3.6 保護電路…………………………………..…………40
3.4 軟體…………………………………………………………..40
3.4.1 Android作業系統主程式與手機介面……………...41
3.4.2 演算法………………………………………………..42
3.5 藍芽模組……………………………………………………..50
第四章系統呈現與測試結果分析…………………………………51
4.1 系統外觀……………………………………………………..51
4.2 實驗設計……………………………………………………..54
4.3 檢測結果……………………………………………………..57
4.3.1 實驗一………………………..………………………57
4.3.2 實驗二………………………………………..………64
第五章結論與展望…………………………………………………68
5.1 結論…………………………………………………………..68
5.2 展望…………………………………………………………..69
參考文獻………………………………………………………………..70
附錄A…………………………………………………………………..74
附錄B…………………………………………………………………..82

參考文獻

Ahadi, M., Pourbakht, A., Jafari, A. H., and Jalaie, S. (2014). “Effects of Stimulus presentation mode and subcortical laterality in speech-evoked auditory brainstem responses”, Int. J. Audiol., vol. 53, pp. 243-249.

Boston, J. R. (1989). “Automated Interpretation of Brainstem Auditory Evoked Potentials: A Prototype System”, IEEE Trans Inf Technol Biomed, vol. 36, pp. 528-532.

Baldwin, M., and Watkin, P. (2013). “Predicting the Degree of Hearing Loss Using Click Auditory Brainstem Response in Babies Referred From Newborn Hearing Screening”, Ear & Hearing, vol. 34, pp. 361-369.

Berninger, E., Olofsson, Å., and Leijon, A. (2014). “Analysis of Click-Evoked Auditory Brainstem Responses Using Time Domain Cross-Correlations Between Interleaved Responses”, Ear & Hearing, vol. 35, pp. 318-329.

Delgado, R. E., and Özdamar, Ö. (1994). “Automated Auditory Brainstem Response Interpretation”, IEEE Eng. Med. Biol., vol. 13, pp. 227-237.

Delgado, R. E., and Özdamar, Ö. (2004). “Deconvolution of evoked responses obtained at high stimulus rates”, J. Acoust. Soc. Am., vol. 115, pp. 1242-1251.

Davey, R., McCullagh, P., Lightbody, G., and McAllister, G. (2007). “Auditory brainstem response classification: A hybrid model using time and frequency features”, Artif. Intell. Med., vol. 40, pp. 1-14.

Dzulkarnain, A. A. A., Zam, T. Z. H. T. Z., Azed, Z., Zuri, M. I. R., and Sulaiman, N. (2014). “Effects of Electrode Position in Tone-Burst-Evoked Auditory Brainstem Responses (ABR) in Human”, Middle East J. Sci. Res., vol. 21, pp. 1180-1187.

Gentiletti-Faenze, G. G., Yaiiez-Suarez, O., Cornejo-Cruz, J. M. (2003). “Evaluation of Automatic Identification Algorithms for Auditory Brainstem Response used in Universal Hearing Loss Screening”, The 25th Annual lntenational Conference of the IEEE EMBS, pp. 2857-2860.

First years, 2014, Peripheral Auditory System
http://firstyears.org/anatomy/ear.htm

Georgiadis, S. D., Ranta-aho, P. O., Tarvainen, M. P., and Karjalainen, P. A. (2005). “Single-Trial Dynamical Estimation of Event- Related Potentials: A Kalman Filter-Based Approach”, IEEE Trans. Biomed. Eng., vol. 52, pp. 1397-1406.

Georgiadis, S. D., Ranta-aho, P. O., Tarvainen, M. P., and Karjalainen, P. A. (2006). “A Subspace Method for Dynamical Estimation of Evoked Potentials”, Comput. Intell. Neurosci., vol. 2007, pp. 1-11.

Hall, J. W., III. (1992). “Handbook of auditory evoked Responses,” Boston: Allyn and Bacon., The United States of America.

Hang, A. X., Roush, P. A., Teagle, H. F. B., Zdanski, C., Pillsbury, H. C.,
Adunka, O. F., and Buchman, C. A. (2014). “Is “No Response” on Diagnostic Auditory Brainstem Response Testing an Indication for Cochlear Implantation in Children?”, Ear & Hearing, vol. 36, pp. 3-16.

Jewett, D. L. (1970). “Volume-conducted potentials in response to auditory stimuli as detected by averaging in the cat”, Electroenceph. clin. Neurophysiol., vol. 28, pp. 609-618.

Jewett, D. L., and Williston, J. S. (1971). “Auditory-evoked far fields averaged from the scalp of humans”, Brain, vol. 94, pp. 681-696.

Kalman, R. E. (1960). “A New Approach to Linear Filtering and Prediction Problems”, Transactions of the ASME - Journal of Basic Engineering, vol. 82, pp. 35-45.

Kemp, D. T. (1978). “Stimulated acoustic emissions from within the human auditory system”, J. Acoust. Soc. Am., vol. 64, pp.1386-1391.
Kostorz, I., Kowalski, W. Ludwig, Z., and Zaja˛c, J. (2013). “Detection of waves of auditory brainstem responses using ipan99 algorithm”, J. Med. Inform. & Technol., vol. 22, pp. 219-226.

Rotert, G. L. (2004). “Comparing auditory steady state response and auditory brainstem response in normal hearing adults”, Program in Audiology and Communication Sciences.

Rance, G., Tomlin, D., and Rickards, F. W. (2006). “Comparison of Auditory Steady-State Responses and Tone-Burst Auditory Brainstem Responses in Normal Babies”, Ear & Hearing, vol. 27, pp. 751-762.

Robinette, M. S., and Glattke, T. J. (2007). Otoacoustic Emissions Clinical Applications Third ed., Thieme Medical Publishers, Inc., New York.

Ramli, A., Hasan, R. A., Rahman, N. I. A., Salleh S., and Harris, A. R. (2014). “High Resolution Auditory Brainstem Response System”, The 15th International Conference on Biomed. Eng.

Stach, B. A. (1988). Clinical Audiologic, Singular Publishing Group Inc., San Diego, London.

Stürzebecher, E., Cebulla, M., and Neumann, K. (2003). “Click-evoked ABR at high stimulus repetition rates for neonatal hearing screening”, Int. J. Audiol., vol. 42, pp. 59-70.

Swanepoel, D., and Ebrahim, S. (2009). “Auditory steady-state response and auditory brainstem response thresholds in children”, Eur Arch Otorhinolaryngol, vol. 266, pp. 213-219.

Skoe, E., and Kraus, N. (2010). “Auditory Brain Stem Response to Complex Sounds: A Tutorial”, Ear & Hearing, vol. 31, pp. 302-324.

Tian, J., Juhola, M., and Grönfors, T. (1997). “Latency estimation of auditory brainstem response by neural networks”, Artif. Intell. Med, vol. 10, pp. 115-128.

Valderrama, J. T., Torre, A., Alvarez, I., Segura, J. C., Thornton, A. R. D., Sainz, M., and Vargas, J. L. (2013). “A portable, modular, and low cost auditory brainstem response recording system including an algorithm for automatic identification of responses suitable for hearing screening”, IEEE PHT, Bangalore, India, pp. 180-183.

Valderrama, J. T., Torre, A., Alvarez, I., Segura, J. C., Thornton, A. R. D., Sainz, M., and Vargas, J. L. (2014). “Automatic quality assessment and peakidentification of auditory brainstem responseswith fitted parametric peaks”, Comput. Meth. Prog. Biomed., vol. 114, pp. 262-275.

Wesson, B. C., Dowell, R. C., Tomlint, D., Rance, G., and Ming, W. J. (2002). “The Auditory Steady-State Response: Comparisons with the Auditory Brainstem Response”, J Am Acad Audiol, vol. 13, pp. 173-187.

Zhang, R., McAllister, G., Scotney, B., and McClean, S. (2006). “Combining Wavelet Analysis and Bayesian Network for the Classification of Auditory Brainstem Response”, IEEE Trans. Inf. Technol. Biomed., vol. 10, pp. 458-467.

林鴻清, 2009, 新生兒聽力篩檢國內趨勢與臺灣現況
http://blog.yam.com/hclin59/article/22704889

國民健康署, 2014, 新生兒聽力篩檢,
http://www.hpa.gov.tw/BHPNet/Web/HealthTopic/Topic.aspx?id=201207040001

劉致中(2011). “以個人數位助理為平台之短暫誘發耳聲傳射檢測儀,” 碩士論文, 國立中央大學電機工程學系。

指導教授

吳炤民(Chao-Min Wu)

審核日期

2015-1-28

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