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The risk of falling in elderly persons with neurodegenerative disease as Parkinson’s disease is generally assessed by clinical tests such as the Timed Up and Go test, the Tinetti test, the oneleg standing test, and others. Most of these tests are performed in a clinical environment, which could lead to spending time and money. Current studies have therefore shown that some clinical tests could be also made at home by using wearable devices based on inertial sensors. However, the experimental protocol used is not often straightforward and does not taken into account the environment conditions such as the type of soil. In addition, the clinical scores or gait abnormalities detection should be interpreted by a physiotherapist or by a house doctor. In this paper, we propose an automatic version of the one-leg standing (OLS) test for risk of falling assessment by using a smartphone and an instrumented insole over four types of ground. The instrumented insole and our application running on Android can be used at home as a diagnostic aid tool for analyzing the performance of elderly people in OLS test. Our work suggests that there is an inverse relationship between the OLS scores from the smartphone and the risk of falling. The score level can be used as a motivation in order to improve the physical condition of elderly.