HEAR4Health: a blueprint for making computer audition a staple of modern healthcare
Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalents that are adequately equipped to tackle contemporary challenges. This has led to a wave of applications that utilise A...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-09-01
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| Series: | Frontiers in Digital Health |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2023.1196079/full |
| _version_ | 1797688065490157568 |
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| author | Andreas Triantafyllopoulos Alexander Kathan Alice Baird Lukas Christ Alexander Gebhard Maurice Gerczuk Vincent Karas Tobias Hübner Xin Jing Shuo Liu Adria Mallol-Ragolta Adria Mallol-Ragolta Manuel Milling Sandra Ottl Anastasia Semertzidou Srividya Tirunellai Rajamani Tianhao Yan Zijiang Yang Judith Dineley Shahin Amiriparian Katrin D. Bartl-Pokorny Katrin D. Bartl-Pokorny Anton Batliner Florian B. Pokorny Florian B. Pokorny Florian B. Pokorny Björn W. Schuller Björn W. Schuller Björn W. Schuller |
| author_facet | Andreas Triantafyllopoulos Alexander Kathan Alice Baird Lukas Christ Alexander Gebhard Maurice Gerczuk Vincent Karas Tobias Hübner Xin Jing Shuo Liu Adria Mallol-Ragolta Adria Mallol-Ragolta Manuel Milling Sandra Ottl Anastasia Semertzidou Srividya Tirunellai Rajamani Tianhao Yan Zijiang Yang Judith Dineley Shahin Amiriparian Katrin D. Bartl-Pokorny Katrin D. Bartl-Pokorny Anton Batliner Florian B. Pokorny Florian B. Pokorny Florian B. Pokorny Björn W. Schuller Björn W. Schuller Björn W. Schuller |
| author_sort | Andreas Triantafyllopoulos |
| collection | DOAJ |
| description | Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalents that are adequately equipped to tackle contemporary challenges. This has led to a wave of applications that utilise AI technologies; first and foremost in the fields of medical imaging, but also in the use of wearables and other intelligent sensors. In comparison, computer audition can be seen to be lagging behind, at least in terms of commercial interest. Yet, audition has long been a staple assistant for medical practitioners, with the stethoscope being the quintessential sign of doctors around the world. Transforming this traditional technology with the use of AI entails a set of unique challenges. We categorise the advances needed in four key pillars: Hear, corresponding to the cornerstone technologies needed to analyse auditory signals in real-life conditions; Earlier, for the advances needed in computational and data efficiency; Attentively, for accounting to individual differences and handling the longitudinal nature of medical data; and, finally, Responsibly, for ensuring compliance to the ethical standards accorded to the field of medicine. Thus, we provide an overview and perspective of HEAR4Health: the sketch of a modern, ubiquitous sensing system that can bring computer audition on par with other AI technologies in the strive for improved healthcare systems. |
| first_indexed | 2024-03-12T01:26:04Z |
| format | Article |
| id | doaj.art-37ec478a52a04d60a259dc435e111374 |
| institution | Directory Open Access Journal |
| issn | 2673-253X |
| language | English |
| last_indexed | 2024-03-12T01:26:04Z |
| publishDate | 2023-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Digital Health |
| spelling | doaj.art-37ec478a52a04d60a259dc435e1113742023-09-12T17:55:23ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2023-09-01510.3389/fdgth.2023.11960791196079HEAR4Health: a blueprint for making computer audition a staple of modern healthcareAndreas Triantafyllopoulos0Alexander Kathan1Alice Baird2Lukas Christ3Alexander Gebhard4Maurice Gerczuk5Vincent Karas6Tobias Hübner7Xin Jing8Shuo Liu9Adria Mallol-Ragolta10Adria Mallol-Ragolta11Manuel Milling12Sandra Ottl13Anastasia Semertzidou14Srividya Tirunellai Rajamani15Tianhao Yan16Zijiang Yang17Judith Dineley18Shahin Amiriparian19Katrin D. Bartl-Pokorny20Katrin D. Bartl-Pokorny21Anton Batliner22Florian B. Pokorny23Florian B. Pokorny24Florian B. Pokorny25Björn W. Schuller26Björn W. Schuller27Björn W. Schuller28EIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyCentre for Interdisciplinary Health Research, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyDivision of Phoniatrics, Medical University of Graz, Graz, AustriaEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyDivision of Phoniatrics, Medical University of Graz, Graz, AustriaCentre for Interdisciplinary Health Research, University of Augsburg, Augsburg, GermanyEIHW – Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, GermanyCentre for Interdisciplinary Health Research, University of Augsburg, Augsburg, GermanyGLAM – Group on Language, Audio, & Music, Imperial College London, London, United KingdomRecent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalents that are adequately equipped to tackle contemporary challenges. This has led to a wave of applications that utilise AI technologies; first and foremost in the fields of medical imaging, but also in the use of wearables and other intelligent sensors. In comparison, computer audition can be seen to be lagging behind, at least in terms of commercial interest. Yet, audition has long been a staple assistant for medical practitioners, with the stethoscope being the quintessential sign of doctors around the world. Transforming this traditional technology with the use of AI entails a set of unique challenges. We categorise the advances needed in four key pillars: Hear, corresponding to the cornerstone technologies needed to analyse auditory signals in real-life conditions; Earlier, for the advances needed in computational and data efficiency; Attentively, for accounting to individual differences and handling the longitudinal nature of medical data; and, finally, Responsibly, for ensuring compliance to the ethical standards accorded to the field of medicine. Thus, we provide an overview and perspective of HEAR4Health: the sketch of a modern, ubiquitous sensing system that can bring computer audition on par with other AI technologies in the strive for improved healthcare systems.https://www.frontiersin.org/articles/10.3389/fdgth.2023.1196079/fullcomputer auditiondigital healthdigital medicinespeech and language disordersauscultation |
| spellingShingle | Andreas Triantafyllopoulos Alexander Kathan Alice Baird Lukas Christ Alexander Gebhard Maurice Gerczuk Vincent Karas Tobias Hübner Xin Jing Shuo Liu Adria Mallol-Ragolta Adria Mallol-Ragolta Manuel Milling Sandra Ottl Anastasia Semertzidou Srividya Tirunellai Rajamani Tianhao Yan Zijiang Yang Judith Dineley Shahin Amiriparian Katrin D. Bartl-Pokorny Katrin D. Bartl-Pokorny Anton Batliner Florian B. Pokorny Florian B. Pokorny Florian B. Pokorny Björn W. Schuller Björn W. Schuller Björn W. Schuller HEAR4Health: a blueprint for making computer audition a staple of modern healthcare Frontiers in Digital Health computer audition digital health digital medicine speech and language disorders auscultation |
| title | HEAR4Health: a blueprint for making computer audition a staple of modern healthcare |
| title_full | HEAR4Health: a blueprint for making computer audition a staple of modern healthcare |
| title_fullStr | HEAR4Health: a blueprint for making computer audition a staple of modern healthcare |
| title_full_unstemmed | HEAR4Health: a blueprint for making computer audition a staple of modern healthcare |
| title_short | HEAR4Health: a blueprint for making computer audition a staple of modern healthcare |
| title_sort | hear4health a blueprint for making computer audition a staple of modern healthcare |
| topic | computer audition digital health digital medicine speech and language disorders auscultation |
| url | https://www.frontiersin.org/articles/10.3389/fdgth.2023.1196079/full |
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