AI Hears Your Health: Computer Audition for Health Monitoring

Shahin Amiriparian, Björn Schuller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

Acoustic sounds produced by the human body reflect changes in our mental, physiological, and pathological states. A deep analysis of such audio that are of complex nature can give insight about imminent or existing health issues. For automatic processing and understanding of such data, sophisticated machine learning approaches are needed that can extract or learn robust features. In this paper, we introduce a set of machine learning toolkits both for supervised feature extraction and unsupervised representation learning from audio health data. We analyse the application of deep neural networks (DNNs), including end-to-end learning, recurrent autoencoders, and transfer learning for speech and body-acoustics health monitoring and provide state-of-the-art results for each area. As show-case examples, we pick three well-benchmarked examples for body-acoustics and speech, each, from the popular annual Interspeech Computational Paralinguistics Challenge (ComParE). In particular, the speech-based health tasks are COVID-19 speech analysis, recognition of upper respiratory tract infections, and continuous sleepiness recognition. The body-acoustics health tasks are COVID-19 cough analysis, speech breath monitoring, heartbeat abnormality recognition, and snore sound classification. The results for all tasks demonstrate the suitability of deep computer audition approaches for health monitoring and automatic audio-based early diagnosis of health issues.

Original languageEnglish
Title of host publicationICT for Health, Accessibility and Wellbeing - 1st International Conference, IHAW 2021, Revised Selected Papers
EditorsEdwige Pissaloux, George Angelos Papadopoulos, Achilleas Achilleos, Ramiro Velázquez
PublisherSpringer Science and Business Media Deutschland GmbH
Pages227-233
Number of pages7
ISBN (Print)9783030942083
DOIs
StatePublished - 2021
Externally publishedYes
Event1st International Conference on ICT for Health, Accessibility and Wellbeing, IHAW 2021 - Larnaca, Cyprus
Duration: 8 Nov 20219 Nov 2021

Publication series

NameCommunications in Computer and Information Science
Volume1538 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference1st International Conference on ICT for Health, Accessibility and Wellbeing, IHAW 2021
Country/TerritoryCyprus
CityLarnaca
Period8/11/219/11/21

Keywords

  • Computer audition
  • Digital health
  • Health monitoring

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