This study aims to testify to the feasibility of a self-developed mobile application (app) designed for patients to self-assess trigger muscles in Myofascial Pain Syndrome (MFPS). The app's results were compared with the professional medical diagnoses to evaluate the app's potential feasibility in a preliminary setting.
We developed a guided self-assess trigger muscles app using Android Studio (Android Studio Iguana, 2023.2.1 Patch 1), allowing users to select painful areas on a body map. The app then provides potential trigger muscle diagnoses based on the selected pain locations. Patients are recruited for preliminary testing. Each patient performed a self-assessment using the app, followed by a professional Traditional Chinese Medicine (TCM) physician diagnosis. To evaluate the app's diagnostic accuracy, we calculated a physician-based recall rate, defined as the ratio of correctly identified muscles by the app (numerator) to the total number of muscles diagnosed by the physician (denominator).
We assessed the app's performance using data from 10 MFPS patients across different body regions: shoulder/neck (n=3), lower back (n=5), upper limb (n=1), and lower limb (n=1). The overall physician-based recall rate was 70%, indicating the app's ability to correctly identify 70% of the muscles diagnosed by the TCM physician. Recall rates varied among different body regions: shoulder/neck (66.6%), lower back (80%), upper limb (0%), and lower limb (100%). Due to the limited sample size in specific anatomical regions, the recall rates for these areas should be interpreted with caution and considered preliminary. These preliminary findings suggest that the app's performance may vary depending on the affected area, providing insights for future refinements and targeted improvements.
The developed app shows potential for self-assessment of trigger muscles in MFPS. While differences exist compared to professional TCM diagnoses, the app provides a convenient preliminary screening tool that may aid in the early identification of trigger muscles in MFPS.
This app could become a useful auxiliary tool for MFPS patients, helping them conduct preliminary self-assessments before seeking medical attention. It has the potential to improve early identification rates of MFPS and may reduce delays in diagnosis and treatment. However, app diagnostic results should be used with professional medical advice to ensure accurate diagnosis and appropriate treatment.
Self-Assessment
Mobile Health Application
