Self-diagnosis of diseases is highly desired and very popular nowadays. This kind of diagnosis will not only permit early disease detection but will also provide access to appropriate treatment promptly. Further to that, due to the frequent increment of diseases nowadays, it becomes impossible for doctors to recall all symptoms and medical conditions for all kind of diseases. This research innovates a new diagnosis algorithm that could be incorporated with web-based tool to provide an efficient online system that corroborate diagnosis using several wearable sensors output. The system incorporates several defined medical conditions. A medical condition is composed of a set of vital signs with abnormal value ranges. The proposed system was experimented on various scenarios and a software simulator has been developed for evaluating and performance testing. Since the algorithm uses an access to the database in order to get real-time vital signs and to check the medical conditions, the calculation of time change depends on the server load. However, during all the tests that were conducted, we observed that the performance of calculating the health Indicator is faster by 10% to 48% than the sequential search method.