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Deep breathing in your hands: designing and assessing a DTx mobile app
Harim Jeong1,2, Joo Hun Yoo2,3, Michelle Goh1
1Department of Interaction Science, SungKyunKwan University, Seoul, South Korea.
Frontiers in Digital Health
|February 13, 2024
Summary
This study optimized deep breathing exercises in digital therapeutics (DTx) using gamified design and machine learning. The intervention group showed significant stress reduction and improved user engagement, highlighting DTx potential in mental healthcare.
Area of Science:
- Digital Therapeutics
- Mental Healthcare
- Mobile Health
Background:
- Digital Therapeutics (DTx) offer accessible solutions in mental healthcare.
- Deep breathing is a key technique for mental health management.
- Optimizing DTx for deep breathing requires innovative design and engagement strategies.
Purpose of the Study:
- To optimize deep breathing exercises within mobile Digital Therapeutics (DTx) platforms.
- To develop a gamified and affordance-driven design for intuitive breath control.
- To enhance user engagement through personalized machine learning-driven biofeedback visualization.
Main Methods:
- A gamified and affordance-driven DTx mobile platform was developed.
- Mel Frequency Cepstral Coefficient (MFCC)-driven machine learning was used for personalized biofeedback.
- 70 participants were divided into control and intervention groups, evaluating Heart Rate Variability (HRV) and user experience.
Main Results:
- The intervention group demonstrated significant stabilization of the Standard Deviation of the NN Interval (SDNN) in HRV, indicating stress alleviation.
- Users in the intervention group reported a 22% increase in perceived enjoyment and a 10.69% increase in positive attitudes.
- The DTx solution showed superior effectiveness and user experience compared to existing methods despite technical challenges.
Conclusions:
- The developed DTx solution effectively reduces stress and enhances mental well-being through optimized deep breathing exercises.
- Gamified design and MFCC-based personalized biofeedback significantly improve user engagement and positive attitudes toward DTx.
- User-centric machine learning techniques show strong potential for advancing mobile mental healthcare solutions.
Keywords:
Human–Computer Interaction (HCI)digital therapeutics (DTx)gamification designmachine learning feedbackmobile health interventionsuser engagementMore Related Videos
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