Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jejak digital: Jurnal Ilmiah Multidisiplin
Yovita Nindita Putri Pamungkas
Department of Physical Medicine and Rehabilitation, Faculty of Medicine, Universitas Indonesia
Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Measurement of Coughing Capacity and Peak Expiratory Flow Using Smartphone-Based Voice Tool: A New Screening Diagnostic Tool Anitta Florence Stans Paulus; Yovita Nindita Putri Pamungkas; Tashiani Candra
Jejak digital: Jurnal Ilmiah Multidisiplin Vol. 2 No. 3 (2026): MEI 2026
Publisher : INDO PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/48vddx32

Abstract

This study evaluates smartphone-based cough sound analysis as a non-invasive alternative to traditional flow meters for measuring Peak Cough Flow (PCF) and Peak Expiratory Flow (PEF). We compared Coughing Sound Intensity (CSI) measured via a Voice Tools (VT) application across three smartphones (iPhone, Samsung, Xiaomi) against a standard Sound Level Meter (SLM). In 62 healthy adults, significant positive correlations were found between PCF and CSI measured by both SLM (r = 0.372, p = 0.003) and the iPhone app (VTi) (ρ = 0.402, p = 0.001). PEF also significantly correlated with huffing sound intensity using SLM, VTi, and Samsung. Among the tested smartphones, VTi demonstrated the strongest predictive value for reduced PCF (60.78% sensitivity, 72.73% specificity) and PEF. While the SLM retained the highest overall sensitivity for predicting reduced PCF (87.5%), the iPhone application provided the most robust smartphone-based correlation. Conclusively, smartphone voice applications, particularly on iOS devices, offer a promising and accessible method to evaluate respiratory function parameters, correlating effectively with standard clinical measurement tools.
Co-Authors Anitta Florence Stans Paulus Tashiani Candra