Respiratory Rate Measurement Using Mobile Applications in Healthcare Settings: A Scoping Review

TL;DR

This review examines mobile apps that measure respiratory rate by tapping breaths, finding them generally usable but with mixed accuracy.

Contribution

The study maps existing evidence on tap-per-breath apps in healthcare settings and identifies gaps in accuracy and generalizability.

Findings

Most apps showed high usability and efficiency in healthcare settings.

Median-based apps were more accurate in measuring respiratory rate.

Evidence gaps remain in adult and pre-hospital use and robust reference standards.

Abstract

Respiratory rate (RR) is a strong indicator of clinical trajectory and forms the basis of patient care and assessment. However, clinicians often face barriers to easily obtaining a RR without inefficient methods or costly technology. To remedy this, several phone applications have emerged where clinicians can tap out each breath to calculate a RR. We aimed to map the available evidence for tap‐per‐breath applications used in healthcare settings. We searched for articles using multiple databases, including primary research articles that evaluated tap‐per‐breath apps in healthcare settings. 14 articles were selected for this review, mostly cross‐sectional and hospital based. Most applications reported high usability and efficiency, although results of accuracy were mixed across the included literature. Median‐based apps were more often an accurate measure of RR, however more research is required. Articles were commonly limited in generalisability due to poorly defined reference standards, small sample sizes, or using retrospective video recordings for patient assessment. Studies showed favourable usability and efficiency across the literature, with median‐based apps demonstrating greater consistency and accuracy of RR measurements. Though the scope of this review and limited evidence restrict any far‐reaching clinical implications until further evidence emerges.

Tap‐per‐breath mobile applications estimate RR from breath‐breath intervals on a mobile phone. This scoping review maps 14 primary studies across clinical settings. Usability and efficiency were consistently favourable; accuracy was mixed overall, with median‐based algorithms more often meeting clinically acceptable agreement. Evidence gaps include adult and pre‐hospital use and studies with robust simultaneous reference standards.

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