Abstract

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Chronic conditions are the main causes of morbidity and mortality worldwide. Heart failure (HF) has a prevalence between 0.5% and 2% in the western population and the number is destined to increase from 25% in 2012 to 46% in 2030. Older adults affected by HF have difficulties to recognize signs and symptoms of the disease, bringing to a reduction of life expectancy. The voice is a complex coordination mechanism between systems and subsystems (i.e. glottis, lung, nose,..). Changes in voice parameters, measuring by algorisms of artificial intelligence, could be useful markers of HF exacerbation. To date, no prior studies have investigated the changing of voice parameters in HF patients and the relationships between voice parameter changes and the clinical course of HF. Aims Explore voice parameter differences between HF patients and healthy subjects; to investigate the relationships between voice parameter changes and the clinical course of the disease. Methods Observational study. Patients with HF and healthy subjects between 60 to 80 y/o will be enrolled in inpatient and outpatient settings. Patients and healthy participants will record voices by microphones and smartphones. Voice data will be analyzed with algorithms of artificial intelligence. Results This study will identify differences in voice parameters between HF patients and healthy participants, and the associations between the voice parameters and the clinical changes of HF patients. Conclusion Monitoring of voice parameters allows to clinicians to early identify, via voice changes, signs and symptoms of HF exacerbations, and to monitor patients at home.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.