Using ML for Voice-based Biomarkers

Drew Morris | Jan 5th, 2024
Using ML for Voice-based Biomarkers

We collaborated with a pioneering digital health company specializing in voice-based biomarkers and assays. Our mission was to devise intricate design strategies for online assessments that culminate in comprehensive reports for laboratories and healthcare providers, marking a significant advancement in the field of life sciences.

Project Overview

This client was looking to develop an intuitive user-interface for online surveys to collect voice and video samples that could be processed in a microservice architecture. Their goal was to address the complex needs of their life science customers. As a trusted technology partner, we were instrumental in architecting and implementing a solution that streamlined sample collection and facilitated advanced data analysis.


  • Interactive Survey Interface: Leveraged React to craft a custom interface for survey collection, incorporating WebRTC for high-quality voice and video capture.
  • Scalable Processing Architecture: Established a microservice architecture using NodeJS and Python within Kubernetes, ensuring efficient management and processing of voice samples.
  • Dynamic Data Streaming: Implemented Kafka for real-time voice sample streaming into a data pipeline, enabling comprehensive feature extraction and analysis across numerous processing jobs.
  • Advanced ML Feature Classification: Utilized Python’s ML and AI libraries to accurately classify features derived from the voice samples, tapping into the vast potential of machine learning.
  • Assessment Report Redesign: Undertook a significant redesign of the assessment reports provided to life science labs and healthcare providers, enhancing readability, accessibility, and the presentation of complex data insights.

SurveyLex's Website

A screenshot of NeuroLex's core product, SurveyLex.

Impact and Outcomes

The project’s success was marked by several key achievements:

  • Revenue Growth: Facilitated a 10X increase in revenue, demonstrating the platform’s efficacy and market impact.
  • Survey Collection Efficiency: Significantly improved the survey response rate, amassing thousands of submissions and enriching the analytical dataset.
  • Facilitated Acquisition: Supported the client through a seamless acquisition process by Sonde Health, heralding a new era for their technology.

Moving Forward

This collaboration highlights the transformative power of AI and machine learning in digital health, especially in analyzing voice-based biomarkers. Looking ahead, the foundation set by this project not only advances life science research but also opens avenues for further innovation in healthcare diagnostics and personalized treatment approaches.

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