Towards Predicting Polycystic Ovary Syndrome with a Novel Smartphone-based Biomedical Application Lyfas  

¹ Department of Research and Development (Digital Health), Acculi Labs Pvt. Ltd. Bangalore 560098, Karnataka India

^*Corresponding Author

Subhagata Chattopadhyay

Department of Research and Development (Digital Health) Acculi Labs Pvt. Ltd. Bangalore 560098, Karnataka

India

Email: subhagata.chattopadhyay2017@gmail.com  

Phone Number: +919972774547

Abstract

Background: Polycystic Ovary Syndrome (PCOS) adversely affects reproductive and metabolic health. It mandates early detection. Lyfas is a mHealth instrument, which is a personalized, fast, non-invasive, and pervasive smartphone-based application. It captures Heart rate variability and its biomarkers (HRVBs) by finger touch on the phone camera. HRVBs are a surrogate for cardiac autonomic modulation that occurs in PCOS.

Objective: Early prediction of PCOS by Lyfas HRVBs and its validation by gynecologists.

Methods and Material: A retrospective double-blind control trial has been conducted on a mixed population of PCOS (N=218) and healthy (N=153) participants. The cohort is further divided into a) ‘Forward miners or FM’ (N=210: PCOS 135, healthy 75), where Lyfas has been used to mine the ‘significant’ HRVBs of PCOS, and b) ‘Reverse mappers or RM’ (N=161), where Lyfas decisions, based on the ‘significant’ HRVBs are validated by a panel of gynecologists. 

Statistical analysis: Cronbach’s alpha, Descriptive statistics, Q-Q plots, Spearman’s correlation, and classification metric (recall, specificity, precision, accuracy, fscore, and Youden’s index), and Bland-Altman’s reliability test (BART).

Results: LF/HF and SD1/SD2 shows significant positive correlation (ρ = 0.60 and 0.45 and p-value = 0.009 and 0.02, respectively). Lyfas shows 82% recall, 84% specificity, 85% precision, 83% accuracy, 84% fscore, and 74% Youden’s index when compared to the diagnoses of gynecologists. BART shows Lyfas has a 2% of proportional bias, i.e., 98% reliable when compared to gynecologists’ prediction.

Conclusions: Lyfas HRVBs (LF/HF and SD1/SD2) can be assistive to gynecologists to predict the possibility of PCOS in the suspected population in 3-5 minutes.

Keywords: Lyfas; Polycystic Ovary Syndrome; Cardiovascular optical biomarkers; Heart rate variability

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