Background Ankle sprain is the most common sports-related injury, and approximately 80% of patients studied suffered recurrent sprains. These repeated ankle injuries could cause chronic ankle instability, a decrease in sports performance, and a decrease in postural control ability. At the present time, smartphones have become very popular and powerful devices, and smartphone applications (apps) that have been shown to have good validity have been designed to measure human body motion. However, the app focusing on ankle function assessment and rehabilitation is still not widely used and has very limited functions. The purpose of this study is to evaluate the feasibility of smartphone-based systems in the assessment of postural control ability for patients with chronic ankle instability. Methods Fifteen physically active adults (6 male, 9 female; aged = 23.4 ± 5.28 years; height = 167.13 ± 7.3 cm; weight = 62.06 ± 10.82 kg; BMI = 22.08 ± 2.57 kg/ m2) were recruited, and these participants had at least one leg that was evaluated as scoring lower than 27 points according to the Cumberland Ankle Instability Tool (CAIT). The smartphone used in the study was ASUS Zenfone 2, and an app developed using MIT App Inventor was used to record built-in accelerometer data during the assessment process. Subjects were asked to perform single leg stance for 20 s in eyes-open and eyes-closed conditions with each leg. The smartphone was fixed in an upright position on the middle of the shin, using an exercise armband, with the screen facing forward. The average of recorded acceleration data was used to represent the postural control performance, and higher values indicated more instability. Data were analyzed with a paired t-test with SPSS 17.0, and the statistical significance was set as alpha <0.05. Results A significant difference was found between CAIT scores from the healthier leg and injured leg (healthier leg 23.07 ± 3.80 vs. injured leg 18.27 ± 3.92, p < 0.001). Significant differences were also found between the scores for the healthier leg and injured leg during both eyes-open and eyes-closed conditions (eyes-open: healthier leg 0.051 ± 0.018 vs. injured leg 0.072 ± 0.034, p = 0.027; eyes-closed: healthier leg 0.100 ± 0.031 vs. injured leg 0.123 ± 0.038, p = 0.001, unit: m/s2). Significant differences were also found between eyes-open and eyes-closed conditions during both single leg standing with healthier leg and injured leg (healthier leg: eyes-open 0.051 ± 0.018 vs. eyes-closed 0.100 ± 0.031, p < 0.001; injured leg: eyes-open 0.072 ± 0.034 vs. eyes-closed 0.123 ± 0.038, p = 0.001, unit: m/s2). The results demonstrate that the smartphone software can be used to discriminate between the different performances of the healthier leg and injured leg, and also between eyes-open and eyes-closed conditions. Conclusion The smartphone may have the potential to be a convenient, easy-to-use, and feasible tool for the assessment of postural control ability on subjects with chronic ankle instability.