Voice Analysis and Digital Biomarkers: Detecting Diseases Through Speech

The healthcare industry is evolving dynamically, driven by the introduction of digital healthcare technologies. Modern tools, such as medical wearables, smart devices, and digital biomarkers enable clinicians to understand the underlying endotypes, and disease phenotypes for personalized treatment planning. Beyond disease diagnosis, digital biomarkers also help in understanding drug responses and associated risks to modify the treatment plan. This unique voice analysis approach helps to meet unmet medical needs at an early stage, facilitating the treatment of chronic and rare diseases.

Nevertheless, biomarkers are at the forefront of the upcoming digital revolution in healthcare and biomedical research. To date, several digital biomarkers have been developed, such as cognitive, physiological, and vocal. Among these, voice-based digital biomarkers represent a novel frontier. This voice analysis based digital biomarkers help to analyze subtle changes in a patient’s voice for comprehensive health assessment. As a cornerstone of innovation, voice analysis is opening new possibilities for healthcare professionals to use speech as a tool for diagnosis, screening, prevention, and monitoring of disease conditions.

Voice Analysis as a Digital Biomarker: The Science Behind Innovation

Verbal speech can be used for predictive analytics and improved healthcare insights. A recent study on voice as a digital biomarker has demonstrated that more than 6,000 different voice features can be analyzed from speech recordings. It is important to highlight here that the human voice has several features, such as jitter, fundamental frequency, harmonics-to-noise ratio, prosodic elements (such as pause duration and speech rate), and shimmer. When a person is affected by a disease, these voice features undergo alterations. Digital sensors can process these voice features to identify disease-specific patterns, acting as early indicators of health conditions.

Clinical Advantages of Voice Analysis and Digital Biomarkers

The ongoing revolution in digital biomarkers, specifically voice analysis biomarkers is offering several clinical advantages that are listed below:

• Non-Invasive Approach

Voice biomarkers are completely non-invasive and require only a recording device or a smartphone. Unlike traditional biomarkers, where clinicians require blood or tissue samples for disease identification, voice based biomarkers leverage AI algorithms and medical devices to understand changes in the linguistic patterns for identifying diseases. This non-invasive approach makes this technology more approachable to patients and improves diagnosis adherence for disease management.

• Cost Effective and Remote Monitoring Capabilities

Voice analysis is relatively cheaper as compared to traditional diagnostic procedures. In addition, these biomarkers have remote monitoring capabilities which help clinicians access the health data of patients continuously without clinical visits. Remote monitoring enhances patient outcomes and reduces the requirement for frequent hospital visits. Moreover, voice analysis biomarkers can leverage biosensors that are integrated with smartphone devices for virtual assistance.

• Voice Biomarkers for Early Disease Detection

Voice biomarkers are emerging as a potential tool that can help in detecting subtle changes in the speech. Notably, when an individual experience any disease, their speech pattern alters, which is a primary indicator of disease. The ability to detect early disease symptoms before they actually become apparent makes it a valuable tool in preventive screening, disease monitoring, and treatment planning. Moreover, voice biomarkers also help in screening multiple conditions simultaneously from a single voice recording, ensuring minimal time for comprehensive health analysis.

Current Applications of Voice Analysis as a Digital Biomarker

Digital biomarkers have offered enormous opportunities for utilizing speech patterns to diagnose and monitor a broad range of medical conditions. However, the primary application of voice as a digital biomarker includes neurological conditions.

Neurological Conditions Detection: Clinical Studies Show Successful Future

It is important to highlight here that several studies have been conducted where voice biomarkers have shown successful outcomes in detecting neurological conditions, such as Parkinson’s disease. During these clinical studies, researchers found that speech impairment is highly prevalent in patients with Parkinson’s disease, affecting around 90% of the diagnosed individuals. Therefore, the speech alteration is taken as the first motor sign that indicates a person may have Parkinson’s disease. Notably, the machine learning models, and digital biomarkers help in analyzing vowel sounds to predict disease progression so that healthcare professionals can provide patients with optimal treatment to manage their disease conditions.

Similarly, several researchers have conducted studies where voice analysis in detecting early-stage dementia, cognitive impairment, and Alzheimer’s disease. These research studies have shown promising results in detecting these conditions with higher accuracy by analyzing changes in linguistic features, such as word-finding difficulties, semantic fluency, and syntactic complexity.

Respiratory Disease Detection:

Voice biomarkers have also demonstrated significant potential in detecting respiratory infections. Several studies have been published that show the potential of AI models in detecting COVID-19 by using voice recordings with higher accuracy. These technologies help analyze changes in the vocal records and the upper respiratory tract that occur during respiratory infections. Moreover, studies have also shown that voice based biomarkers help in diagnosing COVID-19 by using cough sound pattern analysis.

Cardiovascular Conditions: Exploring Voice Based Digital Biomarkers for Heart Failure Monitoring

The current research scenario is focusing on exploring the use of voice biomarkers across cardiovascular conditions, such as heart failure monitoring. Notably, the AHF-voice study is identifying how voice changes can help in recognizing heart failure decompensation, and pulmonary congestion. The early results of the study indicate that voice analysis can help in the real-time monitoring of cardiovascular conditions in patients through smartphone-based applications.

Voice Biomarker: What the US Food and Drug Administration Says About Emerging Technology?

Although, voice-based digital biomarkers have a promising future in early disease diagnosis, the USFDA hasn’t approved any voice biomarker yet. The concept of using voice patterns for disease diagnosis is still at an early stage and several researchers are currently showing promising outcomes. Based on the ongoing studies, the USFDA is providing breakthrough designation to the emerging vocal biomarkers.

Recently, Speech Vital-ALS has received breakthrough designation from the USFDA, recognizing the immense potential of this platform to offer more effective monitoring and management of diseases. Jeremy Moore, director of Aural Analytics said that Speech Vitals-ALS is developed to understand early deterioration in speech patterns, such as speaking rate, and articulatory precision, which can serve as vocal biomarkers. These vocal biomarkers help in the early detection of ALS symptoms by using speech samples from patients through smartphone apps. The company is presently working on securing regulatory approval for its software under the de novo clearance pathway for medical devices. This designation has been provided to the medical devices that have no similar devices on the market.

Future Potential of Voice-Based Biomarkers

The innovation of voice-based biomarkers indicates a promising future for early stage disease detection, progression, and monitoring. Beyond neurological conditions, researchers are currently exploring voice-based biomarkers for pediatric applications, which further indicates a promising future for this technology. Some other future scenarios are listed below:

• Voice Biomarkers for Pediatric Developmental Applications

Currently, the researchers are exploring clinical applications of voice-based biomarkers for pediatric health, specifically autism diagnosis and ADHD. It is worth mentioning that the early detection capabilities can help to improve primary care and long-term treatment outcomes for pediatric patients. Moreover, the integration of machine learning algorithms with voice biomarkers helps to detect depression and anxiety symptoms from children’s speech patterns.

• Next-Generation AI Models for Smart Hospitals

The future approach is further focusing on the implementation of next-generation AI models with multimodal voice recognition devices and software, such as Siri, and Alexa for passive health monitoring. This multimodal approach further helps in enhancing healthcare assessment in real-time.

• Cloud Connectivity and 5G Networks

Researchers are also aiming for the implementation of cloud connectivity so healthcare personnel can process data in real-time. In addition, the future focus will be on 5G networks to improve high-quality audio transmission and real-time data analysis.

Conclusion

Voice based biomarkers have immense potential to identify diseases at an early stage, allowing healthcare providers to tailor treatment. However, the technology is currently in the initial stages and soon it will become democratize in the healthcare industry with the USFDA approval. In the future, human voice will become more robust tool for understanding and maintaining health conditions with a whole new approach.

Contributor Name

Name: Gunjan Bedi

Author Bio Data: Gunjan Bedi is a seasoned medical content writer with diverse writing experience spanning more than 5 years of experience. My medical science background, including master’s in medical microbiology and bachelor’s in biotechnology has provided me with a solid mindset to understand latest research, innovation, and technology upgradation in healthcare industry. Throughout my professional journey, I have had the privilege of writing piece of medical contents and continue to unwind more opportunities in future.