Hearing the Future: Artificial Intelligence in Hearing Aids

Over a decade ago, the mere mention of “AI” or artificial intelligence conjured images of futuristic robots wreaking havoc, or at least that’s what was portrayed in the media . Fast forward to 2024, AI has transitioned from science fiction to an essential component of daily life.

The ubiquity of AI is evident in various electronic devices, from digital assistants to autonomous vehicles, and even in the field of healthcare. AI is revolutionizing healthcare, streamlining processes and improving patient care through its ability to perform tasks that traditionally required human intervention.

As health and fitness monitoring tools gain popularity, individuals can now share real-time health data with healthcare providers, enabling proactive monitoring and timely intervention. Moreover, AI solutions, including big data analytics and machine learning algorithms, are aiding clinicians in decision-making processes and disease detection, from COVID-19 to tuberculosis.

• What is AI?
• Hearing Aid Evolution and AI
• Machine Learning and AI
• Deep Neural Networks (DNNs)
• AI Applications in Hearing Aids
• Hearing Aids with AI
• Benefits of AI in Hearing Aids
• Limitations of AI in Hearing Aids

What is Artificial Intelligence (AI)?

At its core, AI empowers computers to mimic human intelligence and problem-solving abilities. This interdisciplinary field encompasses machine learning and deep learning, allowing computers to learn from data and make increasingly accurate predictions over time.

Despite its perceived complexity, AI has permeated everyday life through virtual assistants like Siri and Google Assistant, which utilize AI algorithms to understand and respond to user queries.

The advent of ChatGPT represents a significant milestone in AI evolution, particularly in natural language processing (NLP). Unlike previous AI breakthroughs in computer vision, ChatGPT’s ability to synthesize human language marks a pivotal moment, demonstrating AI’s potential to comprehend and generate diverse data types beyond just text.

“We have seen AI technologies proliferate in terms of integrations into other existing technologies… It is an important trend to think through generally, but also as audiologists and as hearing healthcare clinicians and researchers. It’s going to change the way in which we interface with patients and provide our services.”

–De Wet Swanepeol, PhD, Audiology Professor and Researcher

Hearing Aid Evolution and AI

In recent years, hearing aids have undergone a remarkable transformation, evolving from simple amplification devices to multifunctional tools equipped with cutting-edge technology. At the forefront of this evolution is the integration of artificial intelligence (AI), which has revolutionized the capabilities of modern hearing aids.

By combining acoustic and biometric sensors with advanced signal processing and AI algorithms, today’s hearing aids offer a range of innovative features beyond just improving speech intelligibility. These AI-powered devices can now monitor physical activity, detect falls, assess social engagement, and even serve as intelligent virtual assistants, all while enhancing sound clarity in various listening environments.

The integration of AI technology into hearing aids represents a significant advancement in personalized hearing loss treatment. It has enabled the development of devices that provide unparalleled levels of customization and performance, tailored to the unique needs of each individual user.

One of the leading players in this field is Starkey, a prominent hearing aid manufacturer that has been incorporating acoustic, inertial, and biometric sensors directly into their devices since 2018. These sensors, coupled with sophisticated AI algorithms, allow Starkey hearing aids to optimize speech intelligibility in noisy environments, track physical activity, detect falls, and assess social engagement levels.

While the technology behind AI hearing aids may seem complex, it can be simplified into three core components:

1. AI
2. Machine Learning
3. Deep Learning

These concepts are closely related and form the backbone of the intelligent algorithms that drive modern hearing aid functionality.

Machine Learning and Artificial Intelligence

Machine learning and artificial intelligence (AI) are closely related concepts, but they are not the same thing. While AI encompasses machine learning, it extends beyond it to include various other aspects of computer intelligence. At the heart of AI lies machine learning, a type of software that empowers electronic devices to analyze data and identify patterns autonomously.

Unlike traditional programming, where devices are explicitly instructed on what to do, machine learning enables devices to generate their own rules (algorithms), allowing them to continuously adapt and improve their performance.

Machine learning involves training computers to recognize patterns in data and make decisions based on this information, often with the aim of predicting outcomes for unseen input data. Just as online platforms like Amazon use machine learning to recommend products based on users’ browsing history and preferences, AI hearing aids leverage similar algorithms to adjust settings according to individual preferences.

Machine learning plays a crucial role in integrating AI into hearing aid technology, and several machine learning techniques are already being utilized in hearing aids available on the market.

While machine learning holds immense potential to revolutionize hearing aids, it is important to recognize its current limitations. Despite advancements, machine learning systems are still constrained compared to human-level intelligence. These systems rely on data generated by humans, and while they can learn and adapt within specific domains, they cannot match the comprehensive understanding and problem-solving capabilities of human intelligence.

Therefore, while machine learning may significantly enhance hearing aid technology, clinicians will continue to play a vital role in addressing new challenges and refining adjustments to meet individual needs.

Deep Neural Networks (DNNs)

Deep Neural Networks (DNNs) represent a more sophisticated form of computer learning algorithms designed to emulate the functioning of the human brain. DNNs have the ability to process information and recognize patterns at a remarkable speed, often surpassing human capabilities in certain tasks.

In the realm of hearing aids, DNN technology aims to replicate the auditory processing of the human brain, allowing users to experience sound in a manner akin to natural hearing.

By mimicking the brain’s response to sound, DNN-enabled hearing aids offer several benefits, including improved sound quality, enhanced signal-to-noise ratio (SNR), better comprehension of speech, and enhanced recall. These devices leverage advanced sound processing and noise reduction algorithms powered by DNNs to recognize and amplify specific voices, providing users with a more personalized and immersive listening experience.

Much like how platforms such as Facebook utilize DNNs to automatically recognize faces in photos, AI hearing aids leverage this technology to identify and prioritize familiar voices, ensuring a clearer and more intelligible auditory experience for users.

AI Applications in Hearing Aids

Real-life hearing presents challenges for individuals with hearing loss, as auditory environments constantly change in context and circumstance. Modern hearing aids have evolved to easily detect the user’s auditory environment, necessitating reliable automation to approximate an ideal setting most of the time. Here are some of the applications of AI in hearing aids:

Auditory Intention

Hearing aid personalization, commonly known as fitting and fine-tuning, is carried out using predefined prescription rules followed by several fine-tuning attempts. However, hearing aid personalization can be complicated due to individual differences influenced by unique auditory scenarios, varying auditory intentions, and the numerous parameters available in modern hearing aids. To bridge this gap, machine learning access through smartphones can automatically adapt advanced hearing aid settings based on the end-user’s preferences and intentions.

Sound Processing Optimization

AI algorithms can analyze and adapt to different sound environments in real-time, adjusting settings such as amplification, noise reduction, and directional focus to optimize speech clarity and overall sound quality for the wearer.

Personalized Hearing Profiles

Machine learning algorithms create personalized hearing profiles based on the wearer’s preferences, listening habits, and unique hearing characteristics. These profiles allow hearing aids to adapt and optimize performance according to the wearer’s specific needs and preferences.

Feedback Management

AI algorithms can effectively detect and suppress feedback signals, providing a more comfortable listening experience for the wearer by accurately identifying feedback signals.

Natural Sound Processing

AI technology replicates the way the human brain processes sound, leading to more natural and lifelike sound perception for hearing aid users. Advanced machine learning algorithms analyze incoming sound signals and adjust processing parameters to preserve speech clarity while maintaining natural sound quality.

Automatic Environment Detection

AI hearing aids use sophisticated algorithms to continuously analyze surrounding sounds, automatically adjusting settings to optimize sound quality for the listening environment. These hearing aids can classify different listening environments, such as quiet settings or noisy restaurants, and adjust settings accordingly, ensuring a consistently enhanced auditory experience for the wearer.

Automatic Mode Switching Based on Location

Some AI hearing aids can create customized listening modes assigned to specific locations, automatically activating when the wearer arrives. This feature ensures optimal auditory experiences tailored to the wearer’s frequently visited places.

Health and Wellness Monitoring

Some AI hearing aids include built-in health monitoring capabilities, allowing wearers to track daily activity levels, heart rate, and step count. This data can be shared with healthcare providers for comprehensive health monitoring.

Fall Detection and Alerts

Advanced AI hearing devices incorporate fall detection technology, utilizing built-in sensors to identify sudden changes in movement or orientation that may indicate a fall. These devices can automatically alert designated contacts in the event of a fall, providing timely assistance when needed.

Adaptive Learning

AI algorithms continuously learn from user interactions and feedback to improve performance and enhance user satisfaction. By analyzing usage patterns and preferences, machine learning models refine recommendations and adjustments to better meet the wearer’s needs over time.

Voice Recognition and Prioritization

AI-powered hearing aids can identify and prioritize specific voices, enhancing their clarity even in noisy environments. These devices automatically refocus on the source of the sound, providing a more natural and personalized listening experience for the wearer.

Real-Time Language Translation

State-of-the-art AI hearing aid apps offer real-time language translation, instantly translating languages into the wearer’s dialect and playing it directly to their hearing aids, breaking down language barriers.

Virtual Assistant Integration

Some AI hearing aids are compatible with virtual assistant apps, allowing wearers to adjust settings, set reminders, ask questions, and perform other tasks using voice commands.

Google® Labs and AI

Google® Labs has made significant strides in enhancing hearing aids for individuals with hearing loss. They have developed technology capable of distinguishing between different vocal formants, allowing for the identification of specific speakers. For example, this technology can differentiate between a person addressing the wearer and someone merely speaking to them, providing valuable context for individuals with hearing loss.

Hearing Aids with AI

Leading global hearing aid manufacturers are integrating AI into their products to enrich the user experience. Here’s a closer look at how some of these manufacturers are incorporating smarter AI and machine-learning capabilities into their hearing aids:

Starkey: Livio, Evolv & Genesis AI Hearing Aids

• Starkey was one of the first companies to incorporate AI into hearing aids, aiming to enhance the user experience.
• Their automatic sound manager system employs machine learning to adapt to various environments.
• The Genesis AI line of hearing aids, equipped with the Neuro Processor, analyzes over 80 million sound scenarios per hour, making nearly two billion adjustments daily.
• Edge Mode introduces advanced edge AI computing, enabling users to control hearing aid settings in challenging environments without relying on external connectivity.
• Features like Intellivoice Deep Neural Networks and a Table Microphone Accessory enhance speech clarity and reduce background noise.

Phonak: Paradise & Lumity Hearing Aids

• Phonak harnesses over 20 years of machine learning expertise to classify acoustic environments.
• Their AutoSense OS adapts to changing surroundings in real-time, with the latest Lumity hearing aids said to blend features from 200 different settings to ensure natural sound perception without manual intervention.

Oticon: Intent, Real, Own & More Hearing Aids

• Oticon integrates deep learning through embedded DNNs in their hearing aids, with its current Intent hearing aids powered by the new Sirius™, and Own, More and Real hearing aids powered by the Polaris™ platforms
• These advanced AI technologies optimize sound processing and enhance speech understanding for wearers.

WS Audiology: Widex MOMENT & SmartRIC and Signia AX & IX Hearing Aids

• WS Audiology leverages a decade of experience in AI development, integrating AI into their latest Widex Moment, SmartRIC and the Signia IX and AX hearing aids.
• Widex’s MySound 2.0, an AI based customization tool within the Widex app, guides users to a better sound through a series of A/B comparisons, allowing them to tailor the experience to their exact listening needs.
• The Signia Assistant, available in the Signia app, helps refine the user’s voice and the voices of others, creating a more natural auditory experience. The AI even learns from users’ preferences and usage patterns, optimizing settings for challenging listening environments.

Beyond the biggest names in prescription hearing aids, there are a growing number of over the counter (OTC) hearing aids that are also integrating AI into the way their devices function, and the list of both prescription and OTC devices utilizing AI is anticipated to only grow in number in the years ahead.

The Benefits of AI in Hearing Aids

Investing in AI for hearing aids may initially seem unnecessary, especially if your current hearing aids meet your needs. However, the benefits offered by AI technology make it a worthwhile consideration. Here are some advantages these advanced hearing aids can provide:

• Improved Speech Understanding: AI-enabled hearing aids significantly enhance speech intelligibility, particularly in noisy environments. Research from the Ohio State University indicates that users of AI hearing aids understand up to 84% of conversations in noisy settings, compared to just 29% without AI technology.
• Enhanced Sound Control: With AI, users can actively engage in conversations and social activities without feeling left out due to background noise. Whether in a bustling restaurant or a business meeting, AI-enabled hearing aids ensure users can fully participate and communicate with confidence.
• Noise Reduction: AI algorithms identify and filter out background noise, enabling users to focus on essential sounds with greater clarity. This feature enhances listening comfort, especially in challenging acoustic environments.
• Enhanced Quality of Life: AI hearing aids cater to individual preferences, allowing users to enjoy personalized listening experiences. Whether it’s enjoying favorite TV programs or relaxing in quiet surroundings, AI technology enhances overall auditory comfort and enjoyment.
• Health Tracking: Advanced AI hearing aids incorporate health-monitoring features, such as activity tracking and fall detection. These devices provide valuable insights into users’ well-being, allowing for timely intervention and support when needed.
• Automatic Calibration: AI streamlines the calibration process by automatically adjusting settings to suit individual user preferences. This ensures optimal sound quality without the need for manual intervention.
• Reduced Cognitive Load: AI technology mimics the brain’s natural processing of sound, alleviating the cognitive strain associated with hearing loss. By clarifying and interpreting sounds in real-time, AI-enabled hearing aids optimize auditory perception and reduce mental fatigue.
• Natural Conversation Experience: AI-driven voice recognition software enhances user-device interaction, making conversations with hearing aids more intuitive and seamless. This facilitates effortless communication and operation for users.

Limitations of AI in Hearing Aids

Despite its numerous benefits, AI technology in hearing aids has some limitations:

• Severe Hearing Loss: AI can enhance sound quality and reduce noise levels, but it may not fully compensate for severe hearing loss or underlying medical conditions.
• Permanent Damage: While AI can mitigate strain on the ears, it cannot prevent permanent hearing damage from prolonged exposure to loud noises or neglecting ear care.
• Professional Expertise: AI complements professional audiological care but cannot replace the expertise of audiologists in programming and customizing hearing aids for individual needs.

Ethical Considerations

As AI continues to advance in healthcare, ethical considerations become increasingly crucial. The World Health Organization (WHO) emphasizes principles such as autonomy, safety, transparency, and equity to ensure AI benefits public health responsibly and ethically.

Final thoughts

While AI has made remarkable strides in improving hearing aid performance, there are still limitations to address. Nevertheless, ongoing research and development hold promise for further innovations in the field. Integrating AI into hearing aid design offers users more options and control over their auditory experience, complementing professional audiological care. Looking ahead, machine learning and AI technologies will continue to evolve, providing enhanced functionalities and personalized solutions for individuals with hearing loss.

 

References:

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