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Journal publications

Integrating Modelling into the Ecosystem of CI

Computational Modelling for Improved Global Cochlear Implant Care

This perspective discusses how computer-based models could improve cochlear implant (CI) care, particularly in low- and middle-income countries where access to hearing services is limited. Cochlear implants can restore hearing, but they require long-term follow-up, skilled programming, and treatment of complications — resources that are often unavailable in remote or low-resource settings. The author explains how computational models can simulate how implants interact with the hearing system, predict fitting settings, and help diagnose issues without the patient being physically present. By creating personalised "digital twins" of a CI recipient's cochlea using scans and clinical data, clinicians could adjust implant settings, monitor changes over time, and better plan treatment. With proper validation and data collection, these models could make CI care more accurate, efficient, and accessible worldwide.

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CBCT Accuracy in Facial Canal Measurements

This study looked at whether 3D X-ray scans called cone-beam computed tomography (CBCT) can accurately measure parts of the facial canal. The facial canal is a tiny tunnel in the skull that protects the facial nerve. This is important because cochlear implants, used to treat hearing loss, can sometimes accidentally stimulate the facial nerve, causing pain or twitching. We scanned donated human heads and then dissected the same areas to compare results. We found that the CBCT scans consistently measured the canal slightly smaller than its actual size. Still, the differences were small and the scans were very reliable and consistent between different observers. This means CBCT can be a useful, non-invasive tool for doctors to study the facial canal before surgery. However, for computer models and surgical planning, these slight underestimations should be corrected to avoid complications. The research supports safer, more accurate planning for cochlear implant procedures using advanced imaging.

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Cochlear Implant as an Imaging Tool

This study explores whether cochlear implants can also be used to image the inner ear. Normally, it's very hard to get a clear look inside the cochlea, the spiral-shaped part of the ear where hearing happens. We tested a technique called Electrical Impedance Tomography (EIT), which creates images by measuring how electricity flows through tissue. By using the existing electrodes in cochlear implants, we simulated how this could work. The study showed that EIT can reliably locate the central part of the cochlea (the modiolus) with high accuracy, even in noisy conditions. This method could complement current medical scans and provide more personalised data for hearing treatment. The results are promising and suggest cochlear implants might one day help researchers and doctors see inside the ear safely, cheaply, and without extra equipment.

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Novel Facial Nerve Dissection Technique

This study presents a detailed and practical method for dissecting and exposing the facial nerve inside the skull, specifically within a small bony tunnel called the facial canal. The facial nerve controls facial expressions and passes close to critical ear structures, making it vulnerable during surgeries like cochlear implants. Damage to this nerve can cause permanent facial paralysis. While imaging scans are commonly used to study it, few hands-on studies using real human tissue exist. We developed a dissection technique using standard lab tools to safely expose the full length of the nerve in donated cadaver heads. This approach not only allows for accurate measurements and observations but also provides a clearer three-dimensional understanding of the nerve’s path. The technique is valuable for improving surgical safety, furthering research on conditions like Bell’s palsy and designing better computer models for research about complications in cochlear implant users. Importantly, it can be performed in most anatomy labs.

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Understanding the Inner Ear to Improve Cochlear Implants

This study focuses on creating accurate 3D models of the inner ear (cochlea) to help improve the performance of cochlear implants for people with hearing loss. Because current medical scans often can't show fine details inside the cochlea, we developed a method to predict these hidden structures using data from high-resolution images of dissected inner ears. By identifying key anatomical landmarks, we created mathematical equations that estimate the shape and position of critical inner structures. These predictions were shown to be more accurate than previous techniques, especially in difficult-to-see areas of the cochlea. Importantly, the study found that a structure called the spiral lamina plays the biggest role in how electrical signals from implants reach the hearing nerve. This work allows for more personalised implant models, even when only low-quality scans are available, which could lead to better hearing outcomes for cochlear implant recipients.

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A Transdisciplinary Approach to Cochlear Implants

This book chapter highlights the importance of customising cochlear implant (CI) care for each individual by using a team-based, transdisciplinary approach. Since everyone’s hearing loss and ear anatomy is different, a one-size-fits-all solution doesn’t work well for CIs. We argue that combining expertise from engineering, audiology, medicine, and even data science leads to better results for CI recipients. Modern tools like computer modelling and imaging can help tailor implants and their settings to each person's unique anatomy and hearing needs. By considering the user's full experience, including how they hear, think, and communicate, this approach aims to improve outcomes and quality of life for CI users. The chapter calls for close collaboration across disciplines and healthcare systems to make this personalised care widely available.

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  • Human-Baron R and Hanekom T, "Unpacking the terminology used in human cochlear dimension methodologies", Translational Research in Anatomy, Volume 35, 2024, 100290, ISSN 2214-854X, https://doi.org/10.1016/j.tria.2024.100290.
  • Mntungwa N, Human-Baron R and Hanekom T, "Morphology of the internal auditory canal: Deriving parameters from computer tomography scans.", Ear, Nose and Throat Journal, First Published August 13, 2022. [doi:10.1177/01455613221116196]
  • Roux J and Hanekom JJ, "Effect of stimulation parameters on sequential current-steered stimuli in cochlear implants", Journal of the Acoustical Society of America, Vol 152 (1), pp 609-623. July 2022. [doi:10.1121/10.0012763]
  • Van der Westhuizen J, Hanekom T and Hanekom JJ, "Apical Reference Stimulation: A Possible Solution to Facial Nerve Stimulation", Ear and Hearing, Vol 43 (4), pp 1189-1197, Jul-Aug 2022. [doi:10.1097/AUD.0000000000001170]
  • Badenhorst W, Hanekom T, Gross L & Hanekom JJ, "Facial nerve stimulation in a post-meningitic cochlear implant user: using computational modelling as a tool to probe mechanisms and progression of complications on a case-by-case basis", Cochlear Implants International, Vol 22(2), pp. 68 – 79, 2021. [doi: 10.1080/14670100.2020.1824431]
  • Martinus, L. and Hanekom, J.J., "Robotic hearing in noise", Proceedings of the 2017 IEEE Africon Conference Cape Town, South Africa, 18-20 Sept 2017. [doi: 10.1109/AFRCON.2017.8095688]
  • Badenhorst, W, Hanekom, T and Hanekom, JJ, "Development of a voltage-dependent current noise algorithm for conductance-based stochastic modelling of auditory nerve fibres", Biological Cybernetics, vol. 110, no. 6, (online 29 August 2016), pp. 403-416, 2016. [doi: 10.1007/s00422-016-0694-6].
  • Oosthuizen D.J.J. and Hanekom J.J., "Information transmission analysis for continuous speech features", Speech Communication, 82, 53-66, 2016. [DOI: 10.1016/j.specom.2016.06.003]
  • Hanekom T and Hanekom JJ, "Three-dimensional models of cochlear implants: a review of their development and how they could support management and maintenance of cochlear implant performance", invited review article in Network: Computation in Neural Systems, vol 27, 67-106, 2016. [DOI: 10.3109/0954898X.2016.1171411].
  • Malherbe T.K., Hanekom, T. and Hanekom, J.J., “Constructing a three-dimensional electrical model of a living cochlear implant user’s cochlea”, International Journal of Numerical Methods in Biomedical Engineering, vol. 32, no. 7, July 2016 (Online 2 Dec 2015) , article e02751 (23p) [DOI: 10.1002/cnm.2751]
  • Malherbe T.K., Hanekom, T. and Hanekom, J.J., “The effect of the resistive properties of bone on neural excitation and electric fields in cochlear implant models”, Hearing Research, 327, 2015, 126-135. [DOI: 10.1016/j.heares.2015.06.003].
  • Oosthuizen, D.J.J., Hanekom J.J., "Fuzzy information transmission analysis for continuous speech features", Journal of the Acoustical Society of America, 137(4), 2015, 1983 - 1994.
  • Venter P.J., Hanekom J.J., "Is there a fundamental 300 Hz limit to pulse rate discrimination in cochlear implants?", Journal of the Association for Research in Otololaryngology (JARO), 15(4), 849-866, 2014. DOI: 10.1007/s10162-014-0468-6
  • Van Zyl, M. and Hanekom, J.J., "Perception of vowels and prosody by cochlear implant recipients in noise", Journal of Communication Disorders, 46, 2013, 449-464.
  • Labuschagne, I.B., Hanekom, J.J., "Preparation of stimuli for timbre perception studies", Journal of the Acoustical Society of America, 134 (3), 2013, pp 2256-2267.
  • Van Zyl, M. and Hanekom, J.J., "When '"okay" is not okay: acoustic characteristics of single-word prosody conveying reluctance", Journal of the Acoustical Society of America Express Letters, online 6 Dec 2012, vol 133 no 1 (Jan 2013), EL13 – EL19.
  • Malherbe, T.K., Hanekom, T. and Hanekom, J.J., "Can subject-specific electrically evoked auditory brainstem response data be predicted from a model?", Medical Engineering and Physics, online September 2012. Vol 35, 2013, pp. 926-936.
  • Swanepoel, R, Oosthuizen, D.J.J. and Hanekom, J.J., "The relative importance of spectral cues for vowel recognition in severe noise", Journal of the Acoustical Society of America, vol 132(4), pp. 2652-2662, 2012.
  • Van Zyl, M, Hanekom J.J.,"Perception of a prosodic pattern in background noise", Journal of Hearing Science, vol. 1 (2), Oct 2011, pp. 54-56.
  • Strydom, T. and Hanekom, J.J., " An analysis of the effects of electrical field interaction in cochlear implant listeners using an acoustic model", Journal of the Acoustical Society of America, vol. 129 (4), April 2011, pp. 2213 – 2226. DOI: 10.1121/1.3518761.
  • Strydom, T. and Hanekom, J.J., The performance of different synthesis signals in acoustic models of cochlear implants", Journal of the Acoustical Society of America, vol. 129 (2), Feb 2011, pp. 920-933. DOI: 10.1121/1.3518760.
  • Theunissen, M., Swanepoel, D., Hanekom, J.J., "The development of an Afrikaans test of sentence recognition thresholds in noise", International Journal of Audiology, published online Nov 2010, doi:10.3109/14992027.2010.532511; Vol. 50 no. 2, pp. 77-85, 2011.
  • Smit, J.E., Hanekom, T., Van Wieringen, A., Wouters, J. and Hanekom, J.J., "Threshold predictions of different pulse shapes using a human auditory nerve fibre model containing persistent sodium and slow potassium currents", Hearing Research, vol 269, pp 12-22, 2010. DOI:10.1016/j.heares.2010.08.004.
  • Venter, P.J. and Hanekom, J.J., "Automatic Detection of African Elephant (Loxodonta Africana) Infrasonic Vocalizations from Recordings", Biosystems Engineering, Vol 106, April 2010, pp. 286-294. DOI:10.1016/j.biosystemseng.2010.04.001.
  • Smit JE, Hanekom T & Hanekom JJ, "Modelled temperature-dependent excitability behaviour of a generalised human peripheral sensory nerve fibre", Biological Cybernetics, vol 101, pp 115-130, 2009. DOI 10.1007/s00422-009-0324-7.
  • Theunissen M, Swanepoel D, Hanekom JJ, "Sentence recognition in noise: variables in compilation and interpretation of tests", International Journal of Audiology, vol 48, pp 743-757, 2009.  [Note: This article was chosen as one of the outstanding articles for The Hearing Journal’s Best of Audiology Literature of 2009]
  • Smit, J.E., Hanekom, T. and Hanekom, J.J., "Estimation of stimulus attenuation in cochlear implants", Journal of Neuroscience Methods, vol 180, pp. 363-373, 2009. DOI: 10.1016/j.jneumeth.2009.03.024.
  • Smit, J.E., Hanekom, T. and Hanekom, J.J., " Modelled temperature-dependent excitability behaviour of a single Ranvier node for a human peripheral sensory nerve fibre", Biological Cybernetics, Volume 100, Issue 1, pp 49-58, 2009. DOI: 10.1007/s00422-008-0280-7.
  • Pretorius, L.L., Hanekom, J.J., " Free field frequency discrimination abilities of cochlear implant users", Hearing Research, vol 244, pp 77-84, July 2008.
  • Smit, J.E., Hanekom, T., Hanekom, J.J., "Predicting human auditory action potential characteristics through adaptation of the Hodgkin-Huxley equations", South African Journal of Science, vol. 104, pp. 284-292, July/August 2008.
  • Jönsson, A.E.R., Hanekom, T., Hanekom, J.J., "Initial results from a model of ephaptic excitation in the electrically excited peripheral auditory nervous system", Hearing Research, vol 237, no 1-2, pp 49-56, 2008.
  • Pretorius L.L. , Hanekom J.J., Van Wieringen A, and Wouters J, " 'n Analitiese tegniek om die foneem-herkenningsvermoë van Suid-Afrikaanse kogleêre inplantinggebruikers te bepaal" (An analytical method to determine phoneme intelligibility of South African cochlear implant users), Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie, vol. 25 no. 4, Dec 2006, pp. 195-208.
  • Pretorius L.L. and Hanekom J.J., "An accurate method for determining the conspicuity area associated with visual targets ", Human Factors, vol. 48 no. 4, Dec 2006, pp. 774-784.
  • Hanekom T. and Hanekom J.J. "The influence of electrode geometry and configuration on intracochlear electrical stimulation", Transactions of the SAIEE, vol. 95 no. 4, Dec 2004, pp. 270-278.
  • Hanekom, J.J. & Krüger, J.J., "A model of frequency discrimination with optimal processing of auditory nerve spike intervals", Hearing Research, Vol 151 no 1-2, Jan 2001, pp 188-204.
  • Hanekom J.J., "What do cochlear implants teach us about the encoding of frequency in the auditory system?", South African Journal of Communication Disorders, vol. 47, 2000, pp. 49-56.
  • Hanekom T. and Hanekom J.J., "Die bydrae van basiese navorsing in kliniese toepassings met verwysing na kogleêre inplantings" (The contribution of basic research in clinical applications with reference to cochlear implants), South African Journal of Communication Disorders, vol. 47, 2000, pp. 41-47.
  • Hanekom, J.J., "A model of frequency coding in the central auditory nervous system", South African Journal of Communication Disorders, Vol 46, 1999, pp. 81-89.
  • Hanekom, T., Hanekom, J.J., Marais, P., "Actively deposited ceramic layers as insulation on thin implantable electrode conductors", South African Journal of Science, vol. 94, 1998, pp. 310-311.
  • Hanekom, T., Hanekom, J.J., "On the design of implantable electrodes for electrical nerve stimulation", South African Journal of Science, vol. 94, 1998, pp. 307-310.
  • Hanekom, J.J. and Shannon, R.V., "Gap detection as a measure of electrode interaction in cochlear implants", Journal of the Acoustical Society of America, vol 104 no 4, October 1998, pp 2372-2384.
  • Muntingh L., Hanekom J.J. & Steinmann C.M.L., "A model for the mechanical events during contraction of an isolated myocyte", South African Journal of Science, Vol. 93, June 1997, pp. 292-295.
  • Hanekom J.J. & Shannon R.V., "Place pitch discrimination and speech recognition in cochlear implant users", SA Journal of Communication Disorders, Vol 43, 1996, pp 27-40.