Development and Validation of Cloud-based Heart Rate Variability Monitor.

Abstract

Context: This article introduces a new cloud-based point-of-care system to monitor heart rate variability (HRV).

Aims: Medical investigations carried out at dispensaries or hospitals impose substantial physiological and psychological stress (white coat effect), disrupting cardiovascular homeostasis, which can be taken care by point-of-care cloud computing system to facilitate secure patient monitoring.

Settings and design: The device employs MAX30102 sensor to collect peripheral pulse signal using photoplethysmography technique. The non-invasive design ensures patient compliance while delivering critical insights into Autonomic Nervous System activity. Preliminary validations indicate the system's potential to enhance clinical outcomes by supporting timely, data-driven therapeutic adjustments based on HRV metrics.

Subjects and methods: This article explores the system's development, functionality, and reliability. System designed is validated with peripheral pulse analyzer (PPA), a research product of electronics division, Bhabha Atomic Research Centre.

Statistical analysis used: The output of developed HRV monitor (HRVM) is compared using Pearson's correlation and Mann-Whitney U-test with output of PPA. Peak positions and spectrum values are validated using Pearson's correlation, mean error, standard deviation (SD) of error, and range of error. HRV parameters such as total power, mean, peak amplitude, and power in very low frequency, low frequency, and high frequency bands are validated using Mann-Whitney U-test.

Results: Pearson's correlation for spectrum values has been found to be more than 0.97 in all the subjects. Mean error, SD of error, and range of error are found to be in acceptable range.

Conclusions: Statistical results validate the new HRVM system against PPA for use in cloud computing and point-of-care testing.