Smartphone-Based Point-of-Care Urinalysis Vivoo App: A Validation Study

Authors : Balım Bengisu Caf, Gizem Çebi, Haluk Çelik, Aliasghar Noroozi, Ali Atasever, Miray Tayfun

Pages : 60-73

Doi:10.38001/ijlsb.1371191

View : 64 | Download : 159

Publication Date : 2024-04-15

Article Type : Research Paper

Abstract :Point-of-care (POC) analysis has emerged as a pivotal approach in providing rapid and convenient medical diagnostics. Smartphone-based solutions further augment the accessibility and ease of POC, enabling efficient on-the-go analysis. The integration of smartphone technology with POC has paved the way for innovative applications such as the Vivoo App, which empowers users to monitor various health parameters conveniently. Our study validated the accuracy and reliability of the smartphone-based POC urinalysis Vivoo mobile application. A comparative approach was followed wherein artificial urine samples were analyzed using both the Vivoo and traditional laboratory methods. A diverse range of health parameters were assessed. A total of 2618 strips were used over the course of this study to evalate the accuracy of Vivoo. The test strips results appeared to match exactly the expected measurement results. In addition, when the ±1 color block acceptance criterion was applied, 2608 of 2618 measurements of the tested strips were found to have met the expected measurement results completely. Based on the results, the 95% confidence interval for the exact match agreement proportion of Vivoo is 87.55% ± 1.27% and 99.62% ± 0.24%. As a wellness product, this study thus concludes that the Vivoo is appropriate in terms of both device reliability and performance. The app\'s ability to provide accurate and timely health results offers promising opportunities to improve individual health management.
Keywords : Hasta başı tanı, İdrar analizi, Yapay zeka, Sağlık, Sağlık Hizmeti