ArticleJMIR human factors2026
Postural Education in School-Aged Populations: Development and Usability Evaluation of a Mobile Biofeedback App (EduBack).
Article in JMIR human factors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
Background: Postural education is crucial during childhood and adolescence, yet traditional approaches often lack engaging tools that promote awareness and behavioral change. Wearable technologies and real-time biofeedback systems offer new opportunities to support postural learning through immediate, embodied feedback. However, most existing systems focus on clinical rehabilitation, with few designed specifically for educational use. Objective: This study aimed to design, develop, and evaluate the usability and technical performance of EduBack, a mobile app that delivers real-time lumbar posture biofeedback through inertial sensors, with a specific focus on educational settings such as schools and physical education environments. Methods: EduBack was developed using Kotlin (JetBrains) for Android OS (Google; version 8.0 and above) and integrates with 2 inertial measurement units via Bluetooth (2.4 GHz). The app provides visual biofeedback through a dynamic interface showing a virtual spine, corrective messages, and a color-coded alignment bar. The usability evaluation involved 24 undergraduate students (mean age 21.4, SD 1.8 y) who used the app in a controlled session. Participants completed the system usability scale and open-ended qualitative feedback questions. Technical performance data were collected from system logs, latency measurements, and received signal strength indicator values to assess connection stability and sensor-to-app communication. Results: The average system usability scale score was 83.5 (SD 8.7), indicating excellent usability. Participants reported the interface to be intuitive, the biofeedback visualization clear, and the posture information easy to interpret. Qualitative responses highlighted the app's potential to support postural awareness and motor learning, especially in school-aged populations. From a technical perspective, the system demonstrated robust performance: mean data transfer latency was approximately 120 milliseconds, with less than 1% packet loss across sessions. Received signal strength indicator values consistently remained within the optimal signal range, confirming stable Bluetooth connectivity. All session data were successfully stored and exported without errors. The real-time posture tracking displayed on the app closely matched raw sensor data, ensuring fidelity in feedback. Conclusions: EduBack is a usable and technically stable mobile app designed to support postural education through wearable sensors and real-time biofeedback. Its user-friendly interface and reliable data transmission make it well-suited for use in schools and educational programs targeting postural health. The app fills a gap in the mobile health field by offering a preventive, educational tool rather than a clinical one. Future research should explore its application in younger populations, integration into physical education curricula, and long-term effects on postural behavior and motor skill acquisition.
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