A Framework for Testing the Reliability and Validity of a Novel Non-Invasive Digital Biomarker Instrument Using Statistical Techniques: A Case Study with Lyfas
Keywords:Mobile health; mHealth; Biofeedback instrument; Heart Rate; Lyfas; Polar H10 HR sensor; Bland-Altman test; Q-Q plot; Pearson’s correlations; Linear regressions; 6Minutes Walk Test; Reliability test; Validity test.
Background: This paper demonstrates a framework for testing of efficacy (reliability and validity) of a novel instrument against a gold-standard instrument. Lyfas is a novel, non-wearable, non-invasive, and economic optical biomarker instrument that runs on android smartphones. By capturing the Pulse Rate (PR) and Pulse Rate Variability (PRV) from the index finger capillary using photoplethysmography, it measures the Cardiovascular Autonomic Modulation (CvAM). The Polar H10 sensor is a gold-standard electrical biofeedback instrument that comes with a wearable chest belt and is a relatively costly device. It captures the Heart Rate (HR) and Heart Rate Variability (HRV) that surrogates Cardiac Autonomic Modulation (CAM). Objective: To showcase the statistical framework in mining the efficacy of Lyfas as a biofeedback instrument by comparing it with that of the Polar H10 instrument following a ‘6Minute Walk Test’. Method: Using Lyfas and Polar H10 HR sensor, PR and HR were captured from 567 subjects(n=567, 312 healthy adult males, and 255 females, respectively). The data was checked for the (a) internal consistency (Cronbach’s alpha), (b) its distribution (Q-Q plots), (c) descriptive statistics (box plots), (d) Root Mean Square difference between the HR and PR, (e) reliability (Bland-Altman Reliability Test), and (f) correlations using (i) Pearson’s inter-class correlations (r), and (ii) Linear regressions (R2). Results: The efficacy of Lyfas as a biofeedback instrument has finally been computed by averaging the mean scores of BART (93.53%), ‘r’ (86.96%), and R2 (87.58%) for the sample and found to be 87.27%. Conclusion: Lyfas can also be used as a biofeedback instrument.
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Copyright (c) 2022 Subhagata Chattopadhyay, Rupam Das
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