Voice perturbations under the stress overload in young individuals: phenotyping and suboptimal health as predictors for cascading pathologies.

作者: A. Kunin , N. Sargheini , C. Birkenbihl , N. Moiseeva , Holger Fröhlich

DOI: 10.1007/S13167-020-00229-8

关键词:

摘要: Verbal communication is one of the most sophisticated human motor skills reflecting both-the mental and physical health an individual. Voice parameters quality changes are usually secondary towards functional and/or structural laryngological alterations under specific systemic processes, syndrome pathologies. These include but not restricted to dry mouth Sicca syndromes, body dehydration, hormonal linked pubertal, menopausal, andropausal status, respiratory disorders, gastrointestinal reflux, autoimmune diseases, endocrinologic underweight versus overweight obesity, diabetes mellitus. On other hand, it well-established that stress overload a significant risk factor cascading pathologies, including neurodegenerative psychiatric mellitus, cardiovascular disease, stroke, cancers. Our current study revealed voice perturbations as potentially useful biomarker identify individuals in suboptimal conditions who might be strongly predisposed associated Contextually, extended surveys applied population identify, for example, persons at high complications pandemic such COVID-19. Symptoms syndrome, disturbed microcirculation, altered sense regulation, shifted circadian rhythm, low BMI were positively with overload. Their interrelationships relevance pathologies presented article. Automated analysis recordings via artificial intelligence (AI) has potential derive digital biomarkers. Further, predictive machine learning models should developed allows detecting condition based on recordings, ideally automated manner using derived Follow-up stratification monitoring recommended disease-specific cell-free nucleic acids (ccfDNA, ctDNA, mtDNA, miRNA) combined metabolic patterns detected fluids. Application cost-effective targeted prevention within phase reversible damage individualised patient profiling.

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