We've said it before: Rejuve.AI is not just a company or a platform. It's a movement. Because kickstarting an entire movement is how we can decentralize longevity for everyone.
At the heart of this movement is our vibrant, exponentially growing Rejuve community. Coming from all walks of life and every corner of the globe, our community members constantly inspire us with the pivotal discussions they initiate across our social platforms.
As most of these discussions are too intriguing to keep to ourselves, we’re thrilled to announce that we’ll be using our blog to shed further light on the fascinating topics our community members bring up.
Now, it all kicks off with a question we spotted on our Telegram group a few weeks back: "Is there actually a solution to tinnitus? If not, can AI find a solution for this in the future?"
Admittedly, our gears start turning every time applications of AI in healthcare come up. So, let’s not wait any longer and dive straight into this captivating discussion and whether AI can transform tinnitus care!
What Is Tinnitus?
Tinnitus, in medical terms, refers to the perception of sounds when there are no external sources; sounds that are unheard by others. While often described as a persistent ringing in the ears, the experience of tinnitus varies — it can manifest as anything from whistles to roars, occurring in one ear or both [1].
The impact of tinnitus on an individual's life can be profound, ranging from mild annoyance to severe disruption, influencing overall well-being. The spectrum of effects includes disturbances such as insomnia, anxiety, and other psychological and physiological chronic conditions [1].
Interestingly, reports of tinnitus being a bothersome phenomenon trace back to ancient Egypt [2]. However, the prevalence of tinnitus has endured through time, with over 740 million adults estimated to be currently grappling with this condition [3].
What Are the Causes of Tinnitus?
Tinnitus, it's important to note, isn't a disease but a symptom that serves as a signal of underlying conditions.
The causes of this auditory phantom are diverse and multifaceted. Age-related hearing loss often brings with it the unwelcome companion of tinnitus, as does frequent exposure to loud noises. Ear infections and certain medications, too, can trigger this condition as a side effect [4].
The general mechanism behind tinnitus traces back to the delicate hair cells within the inner ear. These cells, sensitive to sound waves, initiate electrical signals that our brain interprets as sound. When these cells are damaged, this process is disrupted, which can lead to tinnitus.
Interestingly, the brain itself then plays a crucial role in tinnitus. It’s believed that when the auditory input is compromised due to damage in the ear, the brain attempts to fill in the gaps. This can result in increased activity in certain areas of the brain, creating the illusion of sound. So, while tinnitus might seem to originate in the ear, it’s actually a product of the brain’s compensatory mechanisms [4].
Tinnitus and Aging
Although it can strike at any age, the incidence of tinnitus increases in older adults, with 21% of this population reporting symptoms [5].
This is often due to the wear and tear of the aforementioned hair cells in the ear over time, leading to age-related hearing loss. This is especially true for those frequently exposed to loud noises. Moreover, the incidence of chronic diseases like hypertension and diabetes, which are common in older adults, is also associated with tinnitus [5].
In the past, tinnitus was often viewed as an incurable condition. But recent advancements in research have brought about new treatments, offering a ray of hope for those struggling with this condition.
Enter: AI!
As we've previously covered, AI has been taking over healthcare bit by bit, delivering massive savings and innovative solutions. The trajectory for AI in tinnitus care mirrors this trend, promising breakthroughs in both diagnosis and treatment. Let's dig deeper below!
AI in Diagnosis of Tinnitus
One of the trickiest parts about tinnitus care is that diagnosis has historically relied on patients' description of their symptoms. Despite advanced research, there are no specific biomarkers to track tinnitus [6]. Usually, patients are diagnosed through a questionnaire such as the Tinnitus Handicap Inventory [7].
As this is a subjective measure of an elusive condition, some tinnitus patients report issues of their friends and family not understanding and essentially wondering if it's "all just in their head." [8]
AI's entrance into tinnitus diagnosis, particularly through imaging tests, marks a significant shift. At the Bionics Institute, researchers deployed an algorithm using functional near-infrared spectroscopy (fNIRS), a non-invasive neuroimaging technique. In a study involving 25 individuals with chronic tinnitus, fNIRS measured brain activity in response to auditory stimuli.
The AI showcased impressive accuracy, identifying tinnitus presence with 78% precision and distinguishing between mild and severe forms with 87% accuracy. This breakthrough offers a more objective approach to tinnitus diagnosis, potentially reshaping how we understand and treat this intricate condition [9].
AI in Treatment of Tinnitus
It took us some stage-setting. But now, we're ready to address the first part of our community member's question on whether a "solution" for tinnitus exists. Unfortunately, there's currently no definitive cure.
However, the landscape is rich with diverse treatment options, encompassing sound therapy, cognitive behavioral therapy, pharmacological interventions, and even herbal remedies. Navigating this array of options can be challenging for tinnitus patients seeking the right treatment [10].
Here, AI steps in with remarkable applications. The EU-funded UNITI Project, for instance, leverages predictive machine learning models to tailor treatment approaches based on specific patient parameters. Analyzing data from various sources, including clinical, genetic, and audiological data, the project personalizes and optimizes tinnitus treatment strategies [11].
As for the second part of the question that sparked this discussion, yes, AI itself could potentially offer a solution to tinnitus.
Specific AI-driven treatment options have emerged, like Tinnibot, acting as virtual companions in tinnitus management. Tinnibot utilizes AI to deliver personalized therapies, mimicking interactions with skilled professionals. Offering cognitive behavioral therapy and mindfulness exercises, Tinnibot strives to make tinnitus treatment more accessible, effective, and cost-friendly [12].
But, AI’s potential in tinnitus care extends beyond being a solution to evaluating treatment outcomes as well. Deep learning, a powerful AI technique, enters the scene as researchers harness EEG data and questionnaire scores to predict treatment outcomes.
Trained on complex patterns in the EEG data, a deep learning model was developed to distinguish between responders and non-responders to sound-based therapy with impressive accuracy [13].
This groundbreaking approach highlights the potential of AI in foreseeing the effectiveness of tinnitus treatments, marking a significant stride toward more targeted and successful interventions.
And that’s it for our community discussion today! What topics would you like us to explore next? Join the conversation today through our official channels:
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References
[1] Han, B. I., Lee, H. W., Kim, T. Y., Lim, J. S., & Shin, K. S. (2009). Tinnitus: Characteristics, Causes, Mechanisms, and Treatments. Journal of Clinical Neurology, 5(1), 11. https://doi.org/10.3988/jcn.2009.5.1.11
[2] Dietrich, S. (2004). Earliest historic reference of ’tinnitus’ is controversial. The Journal of Laryngology & Otology, 118(7), 487–488. https://doi.org/10.1258/0022215041615182
[3] Jarach, C. M., Lugo, A., Scala, M., van den Brandt, P. A., Cederroth, C. R., Odone, A., Garavello, W., Schlee, W., Langguth, B., & Gallus, S. (2022). Global Prevalence and Incidence of Tinnitus: A Systematic Review and Meta-analysis. JAMA Neurology, 79(9), 888–900. https://doi.org/10.1001/jamaneurol.2022.2189
[4] Makar, S. K. (2021). Etiology and Pathophysiology of Tinnitus - A Systematic Review. The International Tinnitus Journal, 25(1). https://doi.org/10.5935/0946-5448.20210015
[5] Oosterloo, B. C., Croll, P. H., de Jong, R. J. B., Ikram, M. K., & Goedegebure, A. (2020). Prevalence of Tinnitus in an Aging Population and Its Relation to Age and Hearing Loss. Otolaryngology–Head and Neck Surgery, 019459982095729. https://doi.org/10.1177/0194599820957296
[6] Cederroth, C. R., Hong, M., Freydin, M. B., Edvall, N. K., Trpchevska, N., Jarach, C., Schlee, W., Schwenk, J. M., Lopez‐Escamez, J. A., Gallus, S., Canlon, B., Bulla, J., & Williams, F. (2023). Screening for Circulating Inflammatory Proteins Does Not Reveal Plasma Biomarkers of Constant Tinnitus. Journal of the Association for Research in Otolaryngology, 24(6), 593–606. https://doi.org/10.1007/s10162-023-00920-3
[7] Newman, C. W., Jacobson, G. P., & Spitzer, J. B. (1996). Development of the Tinnitus Handicap Inventory. Archives of Otolaryngology - Head and Neck Surgery, 122(2), 143–148. https://doi.org/10.1001/archotol.1996.01890140029007
[8] Hall, D. A., Fackrell, K., Li, A. B., Thavayogan, R., Smith, S., Kennedy, V., Tinoco, C., Rodrigues, E. D., Campelo, P., Martins, T. D., Lourenço, V. M., Ribeiro, D., & Haider, H. F. (2018). A narrative synthesis of research evidence for tinnitus-related complaints as reported by patients and their significant others. Health and Quality of Life Outcomes, 16(1). https://doi.org/10.1186/s12955-018-0888-9
[9] Shoushtarian, M., Alizadehsani, R., Khosravi, A., Acevedo, N., McKay, C. M., Nahavandi, S., & Fallon, J. B. (2020). Objective measurement of tinnitus using functional near-infrared spectroscopy and machine learning. PLOS ONE, 15(11), e0241695. https://doi.org/10.1371/journal.pone.0241695
[10] Vatsal Chhaya, Patel, D. S., Foram Shethia, Vinaya Manchaiah, & Kapil Khambholja. (2023). Current Therapeutic Trends for Tinnitus Cure and Control: A Scoping Review. Indian Journal of Otolaryngology and Head & Neck Surgery, 75(4), 4158–4166. https://doi.org/10.1007/s12070-023-03910-2
[11] Schoisswohl, S., Langguth, B., Schecklmann, M., Bernal-Robledano, A., Boecking, B., Cederroth, C. R., Chalanouli, D., Cima, R., Denys, S., Dettling-Papargyris, J., Escalera-Balsera, A., Espinosa-Sanchez, J. M., Gallego-Martinez, A., Giannopoulou, E., Hidalgo-Lopez, L., Hummel, M., Kikidis, D., Koller, M., Lopez-Escamez, J. A., & Marcrum, S. C. (2021). Unification of Treatments and Interventions for Tinnitus Patients (UNITI): a study protocol for a multi-center randomized clinical trial. Trials, 22(1). https://doi.org/10.1186/s13063-021-05835-z
[12] Bardy, F., Jacquemin, L., Wong, C. L., Maslin, M. R., & Purdy, S. C. (2024). Delivery of internet-based cognitive behavioral therapy combined with human-delivered telepsychology in tinnitus sufferers through a chatbot-based mobile app. Frontiers in Audiology and Otology, 1, 1302215. https://doi.org/10.3389/fauot.2023.1302215
[13] Doborjeh, M., Liu, X., Doborjeh, Z., Shen, Y., Searchfield, G., Sanders, P., Wang, G. Y., Sumich, A., & Yan, W. Q. (2023). Prediction of Tinnitus Treatment Outcomes Based on EEG Sensors and TFI Score Using Deep Learning. Sensors, 23(2), 902. https://doi.org/10.3390/s23020902