It’s staggering to consider the degree to which technology has progressed, even within the past several decades. Hearing aids, for instance, went from clunky, unwieldy boxes clamped to the side of one’s head to sleek, modern hardware equipped with everything from Bluetooth functionality to companion apps. And hearing aids aren’t the only hearing assistance technology to have grown more advanced.
Cochlear implants, too, have improved significantly and are now advanced enough to be beneficial to individuals with asymmetrical hearing loss. Moreover, because the majority of a cochlear implant’s components are housed externally, they can be upgraded with relative ease. Even people who received an implant many years ago can enjoy their benefits to the fullest.
Unsurprisingly, the evolution of hearing assistance tech has had a significant impact on audiology. For one, patients no longer need to visit an audiologist to readjust their device regularly. Instead, they can do so through a smartphone app, tweaking and modifying the settings to their own unique auditory needs.
These apps are capable of doing more than modifying settings, as well. They can be used to make and receive phone calls, convert speech to text, translate languages in real-time, and even connect to other devices via Bluetooth. This technology can also be used to eliminate microphone feedback, improve signal-to-noise ratios, and even locate a misplaced hearing aid via GPS.
More advanced models take that a step further, wrapping in artificial intelligence to automatically respond to certain noises and activate user-defined presets based on context. There’s even the potential for them to transmit usage data directly back to the audiologist’s practice. In addition to saving time on follow-up appointments, this can potentially help an audiologist identify underlying issues they may otherwise have missed.
As noted by a research brief published by the National Center for Biotechnology Information, artificial intelligence and machine learning have the potential to shape audiology in other ways, as well. Through neural networks and advanced algorithms, for instance, AI can assist in the diagnosis of genetic conditions such as Ménière’s disease. Such technology also has significant potential applications in telemedicine and patient acquisition.
Imagine, if you will, an audiologist who can diagnose a patient without them ever having to set foot in the audiologist’s clinic. Imagine if doctor’s offices were able to instantly and affordably perform pre-screening tests for hearing loss and direct their patients accordingly. Imagine an audiologist leveraging AI assistants to help them serve more patients than would otherwise be possible, thereby addressing the looming talent shortage in the sector.
These may sound like lines taken directly from the realm of science fiction. But each one is completely within our reach with the technology that is currently available. And each one is likely to start seeing use within the next several years.
Audiology research has led to some incredible innovations. But if what we’ve seen in recent years is any indication, we’ve barely scratched the surface. The best, as they say, is yet to come.