Графічний метод оцінки ефективності реабілітації слухового органу

Анастасія В. Паренюк; Дмитро В. Паренюк; Катерина Л. Руденька

doi:10.20535/2523-4455.mea.340703

Vol. 30 · Issue 3 · 2025 Dec 18, 2025 Acoustical devices and systems

Graphical Method of Effectively Estimation of Hearing Organ Rehabilitation

АП

Анастасія В. Паренюк Corresponding Національний технічний університет України «Київський політехнічний інститут імені Ігоря Сікорського» Ukraine

ДП

Дмитро В. Паренюк Національний технічний університет України «Київський політехнічний інститут імені Ігоря Сікорського» Ukraine

КР

Катерина Л. Руденька ДУ “Інститут отоларингології ім. проф. О.С.Коломійченка НАМН України” Ukraine

Pages340703.1-340703.10 PublishedDec 18, 2025

PDF (Ukrainian)

VOL 30 · ISS 3 · 2025 View issue

Abstract

Purpose. The purpose of this study is to analyze the usage ability and effectiveness of a new graphical method of estimation of presence of a difference between healthy and non-healthy hearing organ of a biological object during rehabilitation from the influence of an ototoxic influence. Said method is designed to provide higher analysis speed and possibility of its application of all medical personnel. Material & Methods. During data preparation 41 experiment was conducted. A total of 3936 measurements was made, 96 for every experiment. Each measurement was conducted on one ear of a guinea pig via implementation of a distortion product otoacoustic emission. Out of said 41 experiment 40 were conducted upon test groups with different medicament influence and 1 was done as a referential to normal state of a hearing organ. In each experiment measurements were distributed between 6 frequency bands (2 kHz, 4 kHz, 6 kHz, 8 kHz, 10 kHz, 12 kHz) – 16 measurements per each. Then mean value and standard error in each band for each experiment were calculated. Obtained values were used in a presented method to find differences between them. Later statistical analysis was implemented to check method for reliability. In statistical analysis normality of distribution of results in groups was calculated and depending on it parametric or nonparametric difference test were applied. Reliability of said methods was also tested via implementation of Sokolov’s criterion. Results. Implementation of proposed method showed that for each frequency band results were divided into two large groups – normal (containing experiment 1) and deviating. Differences between two groups are next – normal group has higher mean values, lower standard errors in experiments in it and results are less scattered on a grid. Reliability of a proposed method was tested in three different tests – presence of statistically meaningful differences between mean values of experiments in normal and deviating group, presence of a statistically meaningful differences between measurements in experiment 1 and experiments in deviating group and its correlation with results of usage of a Sokolov’s criterion. Tests confirmed the reliability of proposed method and had shown that it even has advantages over already used methods – be it higher susceptibility or simplicity of its implementation. Conclusion: testing of a new method had shown that it’s reliable due to the results of conducted test series for every frequency band. Apart from easiness of implementation and increase of speed of analysis of results proposed method also has higher sensitivity that some already existing methods of analysis test results of state of a hearing organ in biological object.

Keywords

#otoacoustic emission #distortion product #biological object #objective audiology #machine learning

References

F. S. Koumpa, C. T. Forde, and J. G. Manjaly, “Sudden irreversible hearing loss post COVID-19,” BMJ Case Reports CP, vol. 13, no. 11, 2020, doi: https://doi.org/10.1136/bcr-2020-238419 .
A. Gupta, P. Raj, A. Sood, and A. Raghavan, “Acoustic Trauma in Soldiers: Pure-Tone Audiometry versus Distortion Product Otoacoustic Emissions as a Tool for Early Detection,” Indian J. Otol., vol. 29, no. 1, 2023. doi: https://doi.org/10.4103/indianjotol.indianjotol_103_22
J. Seethapathy, P. Boominathan, A. K. Uppunda, and B. Ninan, “Distortion product otoacoustic emissions in very preterm infants: A longitudinal study,” Int. J. Pediatr. Otorhinolaryngol., vol. 146, p. 110745, 2021, doi: https://doi.org/10.1016/j.ijporl.2021.110745 .
J. E. Sorrel, C. Spankovich, C. E. Bishop, D. Su, K. Valle, and J. M. Schweinfurth, “Stroke risk in African Americans with subclinical auditory dysfuntion evidenced by Distortion Product Otoacoustic Emissions: the Jackson heart study,” Int. J. Audiol., vol. 59, no. 10, pp. 737–744, Oct. 2020, doi: https://doi.org/10.1080/14992027.2020.1745304 .
C. A. Brooks et al., “Distortion product otoacoustic mapping measured pre- and post-loud sound exposures,” Int. J. Audiol., pp. 1–10, Jun. 2021, doi: https://doi.org/10.1080/14992027.2021.1928303 .
R. Sisto et al., “Distortion product otoacoustic emission sensitivity to different solvents in a population of industrial painters,” Int. J. Audiol., vol. 59, no. 6, pp. 443–454, Jun. 2020, doi: https://doi.org/10.1080/14992027.2019.1710776 .
L. Leyssens et al., “The Ototoxic Potential of Cobalt From Metal-on-Metal Hip Implants: Objective Auditory and Vestibular Outcome.,” Ear Hear., vol. 41, no. 1, pp. 217–230, 2020, doi: https://doi.org/10.1097/AUD.0000000000000747 .
H. Van Der Biest, S. Keshishzadeh, H. Keppler, I. Dhooge, and S. Verhulst, “Platinum-induced ototoxicity : potential bio-markers of cochlear synaptopathy”, in XXVIII International Evoked Response Audiometry Study Group (IERASG) Biennial Symposium, Cologne, Germany, 2023. URL: http://hdl.handle.net/1854/LU-01HHC87Q0WV5554YG74BP5KRSS
T. Endo, J. Suzuki, R. Ikeda, and Y. Katori, “Sensorineural Hearing Loss due to Acute Carbon Monoxide Poisoning.,” J. Int. Adv. Otol., vol. 19, no. 5, pp. 435–439, Oct. 2023, doi: https://doi.org/10.5152/iao.2023.231117 .
N. Bello-Mohammed and M. G. Hasheem, “Clinical Applications of Otoacoustic Emission: A Review of the Indications in Aminu Kano Teaching Hospital Northern Nigerian,” Niger. J. Basic Clin. Sci., vol. 20, no. 2, 2023. doi: https://doi.org/10.4103/njbcs.njbcs_40_23
R. Mittal, K. McKenna, G. Keith, J. R. N. Lemos, J. Mittal, and K. Hirani, “A systematic review of the association of Type I diabetes with sensorineural hearing loss,” PLoS One, vol. 19, no. 2, p. e0298457, Feb. 2024. doi: https://doi.org/10.1371/journal.pone.0298457
S. Alagoz et al., “Effect of Using N95 and Surgical Masks on Otoacoustic Emission in Cochlear Outer Hair Cells,” Ear, Nose Throat J., vol. 103, no. 1, 2024, doi: https://doi.org/10.1177/01455613211034600 .
B. Öztürk, H. Kavruk, and A. Aykul, “Audiological findings in individuals diagnosed with COVID-19,” Am. J. Otolaryngol., vol. 43, no. 3, p. 103428, 2022, doi: https://doi.org/10.1016/j.amjoto.2022.103428 .
STMicroelectronics, “STM32F407VE.” [Online]. Available: https://www.st.com/en/microcontrollers-microprocessors/stm32f407ve.html
"Tsentr slukhovoyi reabilitatsiyi AVRORA", “Skryninhovyy audiometr OtoRead™.” ["AURORA Hearing Rehabilitation Center", “OtoRead™ Screening Audiometer.”] [Online]. Available: https://audiometers.biz/vsi-priladi/otoread
A. Şanlı, S. Aydın, and R. Öztürk, “Microscopic guide to the middle ear anatomy in guinea pigs”, The Turkish Journal of Ear Nose and Throat, vol. 19, no. 2, pp. 87–94, Jan. 2009. URL: https://iupress.istanbul.edu.tr/journal/tr-ent/article/microscopic-guide-to-the-middle-ear-anatomy-in-guinea-pigs?id=936434
R. B. A. Saremi, M. Dietz, G. Ashida, J. Kretzberg, and S. Verhulst, “A comparative study of seven human cochlear filter models,” J. Acoust. Soc. Am., vol. 140, no. 3, pp. 1618–1634, 2016, doi: https://doi.org/10.1121/1.4960486 .
W. Nae-Yuh, “Power and Sample Size: Considerations in Study Design.” Accessed: Dec. 13, 2025. [Online]. Available: https://ictr.johnshopkins.edu/wp-content/uploads/2014/07/Wang-Sample_Size_16July2014.pdf
D. K. Lee, J. In, and S. Lee, “Standard deviation and standard error of the mean,” Korean J. Anesthesiol., vol. 68, no. 3, pp. 220–223, Jun. 2015, doi: https://doi.org/10.4097/kjae.2015.68.3.220 .
D. G. Altman and J. M. Bland, “Parametric v non-parametric methods for data analysis,” BMJ, vol. 338, 2009, doi: https://doi.org/10.1136/bmj.a3167 .
P. Sedgwick, “A comparison of parametric and non-parametric statistical tests.,” BMJ, vol. 350, p. h2053, Apr. 2015, doi: https://doi.org/10.1136/bmj.h2053 .
D. Pareniuk, “Algorithm for determining the character of the distribution of values in a small-sized sample,” in XIX International Scientific Mykhailo Kravchuk Conference, dedicated to the 125th anniversary of Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, 2023, pp. 176–177.
F. Orcan, “Parametric or Non-parametric: Skewness to Test Normality for Mean Comparison TT - Parametric or Non-parametric: Skewness to Test Normality for Mean Comparison,” Int. J. Assess. Tools Educ., vol. 7, no. 2, pp. 255–265, 2020, doi: https://doi.org/10.21449/ijate.656077 .
L. Minitab, “Interpret all statistics and graphs for Power and Sample Size for 2-Sample t.” [Online]. Available: https://support.minitab.com/en-us/minitab/help-and-how-to/statistics/power-and-sample-size/how-to/hypothesis-tests/power-and-sample-size-for-2-sample-t/interpret-the-results/all-statistics-and-graphs/
Causeweb, “Power Comparisons of the Mann-Whitney U and Permutation Tests.” [Online]. Available: https://www.causeweb.org/usproc/sites/default/files/usclap/2016/Final Project.pdf
D. V. Pareniuk and S. A. Naida, “The Study of the Possibility of Usage of the Sokolov’s Criteria for Assessing the Results of Directed Influence on the Auditory System of a Biological Object,” Microsystems, Electron. Acoust., vol. 24, no. 3, pp. 72–78, Jun. 2019, doi: https://doi.org/10.20535/2523-4455.2019.24.3.169848 .
K. A. Fernandez et al., “What’s New in Ototoxicity Management?,” Perspect. ASHA Spec. Interes. Groups, vol. 9, no. 1, pp. 113–123, 2024, doi: https://doi.org/10.1044/2023_PERSP-23-00153 .
G. Zepidou and S. Dance, “Comparison of Pure Tone Audiometry and Otoacoustic Emission based Hearing Assessment for Classical Music Students,” in INTER-NOISE and NOISE-CON Congress and Conference Proceedings, Institute of Noise Control Engineering, 2023. doi: https://doi.org/10.3397/IN_2022_0348 .
Y. Ding, Y. Liu, D. Li, R. Hu, Z. Tian, and Q. Xie, “Correlation between pure tone audiometry at all frequencies and distortion product otoacoustic emission of patients with hidden hearing loss.,” Biotechnol. Genet. Eng. Rev., pp. 1–12, May 2023, doi: https://doi.org/10.1080/02648725.2023.2209408 .
S. P. Putri Manyakori, N. Purnami, and B. Utomo, “Hearing screening using distortion product otoacoustic emission(DPOAE) in high-risk employees of an Indonesian hospital”, European Journal of Molecular & Clinical Medicine, no. 5, pp. 752–755, Jan. 2020. URL: https://www.ejmcm.com/archives/volume-7/issue-5/8893
L. Petersen, W. J. Wilson, and H. Kathard, “Towards the preferred stimulus parameters for distortion product otoacoustic emissions in adults: A preliminary study.,” South African J. Commun. Disord. = Die Suid-Afrikaanse Tydskr. vir Kommun., vol. 65, no. 1, pp. e1–e10, Jul. 2018, doi: https://doi.org/10.4102/sajcd.v65i1.585 .
J. D. Lewis, “Model-based prediction of otoacoustic emission level, noise level, and signal-to-noise ratio during time-synchronous averaging,” J. Acoust. Soc. Am., vol. 154, no. 2, pp. 709–720, Aug. 2023, doi: https://doi.org/10.1121/10.0020568 .
A. Van Den Broucke, F. Drakopoulos, D. Baby, and S. Verhulst, “Otoacoustic emissions in a deep-neural-network model of cochlear mechanics,” AIP Conf. Proc., vol. 3062, no. 1, p. 30011, Feb. 2024, doi: https://doi.org/10.1063/5.0189629 .
Y. Liu, B. Jiang, H. Liu, Y. Zhao, F. Xiong, and Y. Zhou, “A Novel Earprint: Stimulus-Frequency Otoacoustic Emission for Biometric Recognition,” IEEE Trans. Inf. Forensics Secur., vol. 18, pp. 5484–5494, 2023, doi: 10.1109/TIFS.2023.3309101.