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Related Experiment Video

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Evaluating Voice-Assistant Commands for Dementia Detection.

Xiaohui Liang1, John A Batsis2, Youxiang Zhu1

  • 1Department of Computer Science, University of Massachusetts Boston, 100 Morrissey Blvd., Boston, MA 02125-3393 USA.

Computer Speech & Language
|November 12, 2021
PubMed
Summary

Voice commands from Amazon Alexa can help detect early cognitive decline in older adults. Machine learning models achieved up to 90% accuracy, identifying key features for assessing cognitive status.

Keywords:
Alzheimer’s DiseaseCognitive DeclineMachine LearningSpeech AnalysisVoice Assistant

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Area of Science:

  • Gerontology
  • Artificial Intelligence
  • Neurology

Background:

  • Early detection of Alzheimer's Disease and Related Dementias (ADRD) is crucial for timely interventions in older adults living alone.
  • Voice-Assistant Systems (VAS) offer a potential avenue for unobtrusive cognitive monitoring.

Purpose of the Study:

  • To investigate the utility of voice commands from a VAS (Amazon Alexa) for detecting cognitive decline in older adults.
  • To compare the performance of machine learning models in classifying cognitive status based on voice command features.

Main Methods:

  • Collected voice command data from 40 older adults (Healthy Control and Mild Cognitive Impairment).
  • Extracted 163 unique features from VAS usage.
  • Developed and compared machine learning models (neural networks, SVM, decision tree, random forest) for classification and regression.

Main Results:

  • Fusion features achieved 68% classification accuracy.
  • Decision Tree and Random Forest models with selected features reached 80-90% accuracy.
  • Features related to overall performance, music, calls, and Automatic Speech Recognition (ASR) were most impactful.

Conclusions:

  • Voice-Assistant Systems show promise for home-based cognitive assessments.
  • Specific voice command features can effectively infer cognitive status in older adults.
  • This approach could support early detection of cognitive decline.