Feasibility of Using a Single Heart Rate-Based Measure for Real-time Feedback in a Voluntary Deep Breathing App for Children: Data Collection and Algorithm Development.

Abstract

Background: Deep diaphragmatic breathing, also called belly breathing, is a popular behavioral intervention that helps children cope with anxiety, stress, and their experience of pain. Combining physiological monitoring with accessible mobile technology can motivate children to comply with this intervention through biofeedback and gaming. These innovative technologies have the potential to improve patient experience and compliance with strategies that reduce anxiety, change the experience of pain, and enhance self-regulation during distressing medical procedures.

Objective: The aim of this paper was to describe a simple biofeedback method for quantifying breathing compliance in a mobile smartphone app.

Methods: A smartphone app was developed that combined pulse oximetry with an animated protocol for paced deep breathing. We collected photoplethysmogram data during spontaneous and subsequently paced deep breathing in children. Two measures, synchronized respiratory sinus arrhythmia (RSA_sync) and the corresponding relative synchronized inspiration/expiration heart rate ratio (HR-I:E_sync), were extracted from the photoplethysmogram.

Results: Data collected from 80 children aged 5-17 years showed a positive RSA_sync effect in all participants during paced deep breathing, with a median (IQR; range) HR-I:E_sync ratio of 1.26 (1.16-1.35; 1.01-1.60) during paced deep breathing compared to 0.98 (0.96-1.02; 0.82-1.18) during spontaneous breathing (median difference 0.25, 95% CI 0.23-0.30; P<.001). The measured HR-I:E_sync values appeared to be independent of age.

Conclusions: An HR-I:E_sync level of 1.1 was identified as an age-independent threshold for programming the breathing pattern for optimal compliance in biofeedback.