Voice data as a biomarker for disease
audEERING launches online platform for AI-based analysis of disease symptoms based on voice
audEERING
AI SoundLab is designed as a platform for researchers and end users to collect personal health information and audio data through a user-friendly interface. The platform and the voice data are used to research the expression of various disease patterns in the human voice based on validated and standardized voice tests. The aim is to detect so-called biomarkers (measurable and objectively assessable indicators of the presence or severity of a disease state) for various disease patterns, especially in the neurodegenerative and psychological fields, by analyzing the voice samples provided via AI SoundLab. In addition, it should also be possible to analyze the long-term development and change of various disease processes and interventions during therapy.
Based on AI SoundLab, applications will be enabled that allow non-invasive, efficient and fast screening as well as support for diagnostics. Exemplary for this are the markers that audEERING determined for COVID-19 in the first Corona Wave 2020. In recent years, audEERING has also already been able to identify indicators in the voice for neurodegenerative disorders (such as Parkinson's disease) and mental illnesses (such as depression).
Currently, audEERING is conducting data collection in clinical studies with national and international institutes and universities. Various voice biomarkers associated with neurodegenerative and mental diseases are being investigated and validated, based on motor, cognitive, physical characteristics as well as psychological states.
audEERING's goal is to use AI SoundLab to sustainably improve individual health and significantly advance digital health solutions. The easy-to-use, permanently available tool for screening, supportive diagnosis, efficient individualized monitoring and thus significantly improved therapy lays the foundation for this. Healthcare professionals should be able to use the data enriched by AI technology for faster diagnosis and to reorganize, evaluate and expand therapy concepts.
For Dagmar Schuller, CEO of audEERING, this confirms the company's vision to take applied voice research to a new level: "Already in 2020, our work on detecting COVID-19 disease using voice analysis has gained worldwide recognition. This gave rise to the idea of AI SoundLab, an efficient, standardized platform for voice biomarkers that can be used to research them for diverse diseases. Our mission is that soon patient:s, entrepreneurs:s and researchers:s will be able to use AI SoundLab to promote mental and physical health and take necessary preventive measures."
The AI technology is already being used by several companies in the pharmaceutical and research sectors, for example, to better assess and promote people's mental health. One of the partners is Safetytech Accelerator. In collaboration with HiLo Maritime Risk Management, the company is researching the mental health of seafarers. Using technology to collect and analyze data, it aims to better identify performance issues and dangerous situations caused by a stressed crew. Investing in prevention and mental health support for employees can lead to fewer accidents, repatriations, and correspondingly fewer claims. AI SoundLab is already currently in use here on a shipping route.
Maurizio Pilu, Managing Director at Safetytech Accelerator says, "In our extensive discussions with the maritime industry and welfare organizations, we have found that the ability to reliably and continuously determine crew wellbeing is often cited as key to improving wellbeing. We believe audio analytics like audEERING's AI Soundlab can play a big role."
Note: This article has been translated using a computer system without human intervention. LUMITOS offers these automatic translations to present a wider range of current news. Since this article has been translated with automatic translation, it is possible that it contains errors in vocabulary, syntax or grammar. The original article in German can be found here.
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