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Technology and Dementia Preconference.

Franco Javier Ferrante1,2,3, Gonzalo Nicolás Pérez1,2,3, Joaquín Ponferrada2

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The Toolkit to Examine Lifelike Language (TELL) 2.0 offers advanced speech biomarker analysis for dementia detection. New features improve data collection and analysis, enhancing early diagnosis and accessibility for diverse populations.

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Area of Science:

  • Neurolinguistics and Computational Linguistics
  • Biomedical Engineering and Health Informatics
  • Artificial Intelligence in Healthcare

Background:

  • The Toolkit to Examine Lifelike Language (TELL) is a web application developed for collecting voice samples and extracting speech biomarkers for dementia detection.
  • The initial version of TELL successfully supported clinical evaluations globally, including in under-resourced regions.
  • TELL 2.0 has been developed to enhance the capabilities of the original toolkit, introducing advanced features for data handling and analysis.

Purpose of the Study:

  • To introduce TELL 2.0, an upgraded version of the Toolkit to Examine Lifelike Language, with enhanced features for dementia-related speech biomarker analysis.
  • To expand data collection methods, improve data processing and analysis, and refine visualization tools for dementia evaluation.
  • To increase the accessibility and clinical utility of speech biomarkers in dementia diagnosis.

Main Methods:

  • TELL 2.0 incorporates significant backend and frontend improvements, supporting videocall-based and offline data collection with lossless audio and local transcription.
  • A comprehensive audio standardization pipeline, including amplitude normalization, noise reduction, and channel harmonization, has been implemented.
  • New interpretable metrics for lexical retrieval, motor speech, semantic memory, and self-referential language have been integrated, alongside machine learning-based predictions for dementia profiles.

Main Results:

  • Consistent audio and transcription quality were demonstrated across all data collection modes.
  • The newly integrated metrics accurately distinguish individuals with specific neurological disorders from healthy controls, achieving 85-93% accuracy.
  • The updated visualization interface provides clinicians with actionable insights, aligning metrics with established neuropsychological frameworks.

Conclusions:

  • TELL 2.0 significantly enhances the accessibility and impact of speech biomarkers for dementia evaluation, building upon the success of its predecessor.
  • The toolkit represents a practical, scalable, and cost-effective solution for dementia assessment, driven by research and technological advancements.
  • The continuous development of TELL aims to translate cutting-edge research into widely applicable clinical tools for early dementia detection.