The 6-Minute Walk Test (6MWT) is widely used in assessing the functional exercise capacity of individuals with chronic respiratory and pulmonary disorders. The primary measurement of this test is the 6-minute walk distance (6MWD), which is the total distance walked by the patients on a flat, hard surface within 6 min. When the patients walk forth and back on the walkway with a fixed length, the body rotates to complete a turn and continues to the next lap, resulting in changes in rotation angles. Hence, rotation detection based on the data obtained from the smartphone-embedded sensors is a suitable method to calculate 6MWD. This paper presents an Android mobile application that utilizes accelerometer and magnetometer sensors to compute the azimuth signal for rotation detection and 6MWD measurement. The rotation detection algorithm is developed based on calculation of the azimuth change before and after rotation, and the threshold values for rotation detection are determined based on the analysis of the azimuth graph obtained from data collection of 17 cardiovascular disease patients. Validation results show that this solution achieves the average accuracy of 92.46% and 92.44% for rotation detection and 6MWD measurement, respectively, while a user performing 6MWT using this mobile app and placing the handphone on the waist using waistband. This mobile app solution would be useful for the public community to facilitate home rehabilitation by enabling self-monitoring of fitness recovery after certain disease onset in an indoor home environment.