ArticleJournal of medical physics
Development and Validation of Cloud-based Heart Rate Variability Monitor.
Article in Journal of medical physics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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