Smartphone Movement Sensors for Remote Monitoring of Respiratory Rate: Observational Study (Preprint)

Abstract

Mobile health (mHealth) offers notable potential clinical and economic benefits to patients and healthcare systems alike. Although respiratory rate (RR) is of great clinical significance, existing remote technologies to measure RR suffer from limitations, such as cost, accessibility and reliability. Using smartphone movement sensors to measure RR may offer a potential solution to these shortcomings.

The aim of this study was to conduct a comprehensive and ecologically valid assessment of a novel mHealth smartphone application designed to measure RR using movement sensors.

Study 1 offered a preliminary evaluation, in which RR measurements from 15 participants generated via the mHealth app were compared to simultaneous measurements from a reference device cleared by the US Food and Drug Administration (FDA). Participants’ ability to successfully operate the app was also determined. Finally, a novel reference method, that would allow accuracy of the mHealth app to be investigated ‘in the wild’, was assessed for validity against the FDA-cleared reference. In Study 2, 165 participants of balanced demographics remotely downloaded the mHealth app and measured their RR. Measures from the mHealth app were compared to the novel reference that was assessed in Study 1. Usability was quantified based on the proportion of participants that were able to successfully use the app to measure their RR and standardised usability scales.

Outcomes from Study 1 supported further assessment of the mHealth app, including as assessed by the novel reference. The mHealth app, when compared to the FDA-cleared and novel references, respectively, showed a mean absolute error (MAE) of 1.65 (standard deviation (SD) = 1.49) and 1.14 (1.44), relative MAE of 12.2 (9.23) and 9.5 (18.70) and bias of 0.81 (limits of agreement (LoA) = -3.27-4.89) and 0.08 (-3.68-3.51). Pearson Product Moment Correlation (PPMC) coefficients were 0.700 and 0.885. 93% of participants could successfully operate the device on their first use and standardised usability scores were above industry averages.

The accuracy and usability of the mHealth app demonstrated in this research hold promise for the use of mHealth solutions employing smartphone movement sensors to remotely monitor RR. Considering methodological limitations, further research should be undertaken to more holistically validate the benefits that this technology may offer patients and healthcare systems.