Breathing as an Input Modality in a Gameful Breathing Training App (Breeze 2): Development and Evaluation Study

Abstract

Background Slow-paced breathing training can have positive effects on physiological and psychological well-being. Unfortunately, use statistics indicate that adherence to breathing training apps is low. Recent work suggests that gameful breathing training may help overcome this challenge. Objective This study aimed to introduce and evaluate the gameful breathing training app Breeze 2 and its novel real-time breathing detection algorithm that enables the interactive components of the app. Methods We developed the breathing detection algorithm by using deep transfer learning to detect inhalation, exhalation, and nonbreathing sounds (including silence). An additional heuristic prolongs detected exhalations to stabilize the algorithm’s predictions. We evaluated Breeze 2 with 30 participants (women: n=14, 47%; age: mean 29.77, SD 7.33 years). Participants performed breathing training with Breeze 2 in 2 sessions with and without headphones. They answered questions regarding user engagement (User Engagement Scale Short Form [UES-SF]), perceived effectiveness (PE), perceived relaxation effectiveness, and perceived breathing detection accuracy. We used Wilcoxon signed-rank tests to compare the UES-SF, PE, and perceived relaxation effectiveness scores with neutral scores. Furthermore, we correlated perceived breathing detection accuracy with actual multi-class balanced accuracy to determine whether participants could perceive the actual breathing detection performance. We also conducted a repeated-measure ANOVA to investigate breathing detection differences in balanced accuracy with and without the heuristic and when classifying data captured from headphones and smartphone microphones. The analysis controlled for potential between-subject effects of the participants’ sex. Results Our results show scores that were significantly higher than neutral scores for the UES-SF (W=459; P<.001), PE (W=465; P<.001), and perceived relaxation effectiveness (W=358; P<.001). Perceived breathing detection accuracy correlated significantly with the actual multi-class balanced accuracy (r=0.51; P<.001). Furthermore, we found that the heuristic significantly improved the breathing detection balanced accuracy (F1,25=6.23; P=.02) and that detection performed better on data captured from smartphone microphones than than on data from headphones (F1,25=17.61; P<.001). We did not observe any significant between-subject effects of sex. Breathing detection without the heuristic reached a multi-class balanced accuracy of 74% on the collected audio recordings. Conclusions Most participants (28/30, 93%) perceived Breeze 2 as engaging and effective. Furthermore, breathing detection worked well for most participants, as indicated by the perceived detection accuracy and actual detection accuracy. In future work, we aim to use the collected breathing sounds to improve breathing detection with regard to its stability and performance. We also plan to use Breeze 2 as an intervention tool in various studies targeting the prevention and management of noncommunicable diseases.

Development of “LvL UP 1.0”: a smartphone-based, conversational agent-delivered holistic lifestyle intervention for the prevention of non-communicable diseases and common mental disorders

“…In addition, the transdiagnostic CBT approach supports the use of journaling and breathing exercises. Breeze is a gamified slow-paced breathing training ( 136 – 138 ). Users are instructed to inhale and exhale at set ratios, and the inhalations and exhalations are detected by the smartphone's microphone.…”

Deep breathing in your hands: designing and assessing a DTx mobile app

“…One innovative strategy that’s gaining traction is the incorporation of gamification into deep breathing interventions. By gamifying deep breathing exercises, these interventions aim not only to harness the therapeutic advantages of controlled respiration but also to elevate user commitment, thereby improving the overall effectiveness of the intervention ( 15 , 16 ).…”

Engagement With a Relaxation and Mindfulness Mobile App Among People With Cancer: Exploratory Analysis of Use Data and Self-Reports From a Randomized Controlled Trial

“…The app offers 7 different types of relaxation exercises recommended as evidence-based interventions to reduce distress in people with cancer [35,36,46,47]. The relaxation exercises include guided audio recordings of a short meditation (5 minutes), walking meditation (5 minutes), mindfulness meditation (15 minutes), guided imagery (15 minutes), progressive muscle relaxation (15 minutes), body scan (40 minutes), and slow-paced breathing training with visual guidance through gameful visualizations (2-5 minutes; Breeze 2 [48]). The audio files are available in male and female voices with and without background music.…”