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Speech-Based BMI Classification Method by Abbs Alazhari is a document available to read on EtoBox.

This study proposes a novel method for classifying body mass index (BMI) using speech signals, aiming to facilitate remote healthcare applications. The research involved 1830 subjects and achieved classification accuracy ranging from 60.4% to 73.8% based on age and gender-specific groups. The findings suggest that speech features can effectively predict BMI status, potentially aiding in automatic BMI diagnosis in telemedicine settings.

Author

Abbs Alazhari

Language

EN