Voice-based digital biomarkers present an exciting opportunity for the healthcare industry, offering a novel, non-invasive method to monitor health through voice analysis. They help in early detection and continuous tracking of various health conditions, such as Parkinson's and Alzheimer's diseases.
However, despite the huge potential they offer, some challenges can hamper their successful adoption in clinical practice and wider commercialization. Here are some of these challenges:
Technical aspects
Voice-based technology needs clear, noise-free speech recordings to work well. Simple speech is easier to analyze but less informative than natural speech. Detecting changes in voice, like slurring, and turning these into accurate algorithms can be a challenge, which medical devices consulting services can help overcome.
Dearth of data samples
Voice biomarker technology requires large, diverse datasets to train AI models that generalize across populations. However, there is a lack of high-quality collections of voice samples linked to clinical data or disease information, as using voice as a medical marker is still a new area of research.
Privacy concerns
Another challenge in the adoption of these medical devices is patients’ wariness to share their voice samples. This is because laws view voice as personal data that can be used to identify someone. However, voice samples taken from controlled speech tasks, like holding a sound, might not be covered under these strict privacy laws. With business and technology consulting services, organizations can ensure secure data practices and navigate the complex regulatory landscape.
Confounding variables
Many factors can interfere with speech analysis, so they need to be accounted for in the algorithm. For instance, when developing a speech-based biomarker for Parkinson’s disease, the algorithm considers possible confounding factors, such as the patient’s age, dialect or common comorbidities, like depression.
Clinical relevance
Unlike other biomarkers, vocal biomarkers don’t yet have proven methods to link speech features with specific diseases. While there are some ways to measure voice in certain conditions, such as Parkinson’s, where measurements include jitter, shimmer, pitch and noise levels, these cases are still rare.
Adopting voice-based digital biomarkers is not without its hurdles, but the future definitely looks promising. To overcome these challenges and bring this important medical analysis approach to patients faster, collaboration with experts in technology consulting is crucial for businesses.
Comments
0 comment